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Disentangling molecular alterations from water-content changes in the aging human brain using quantitative MRI

Reporter: Dror Nir, PhD

 

Authors’ list: Shir Filo, Oshrat Shtangel, Noga Salamon, Adi Kol, Batsheva Weisinger, Sagiv Shifman & Aviv A. Mezer
Published in: Nature Communications volume 10, Article number: 3403 (2019)

Abstract

It is an open question whether aging-related changes throughout the brain are driven by a common factor or result from several distinct molecular mechanisms. Quantitative magnetic resonance imaging (qMRI) provides biophysical parametric measurements allowing for non-invasive mapping of the aging human brain. However, qMRI measurements change in response to both molecular composition and water content. Here, we present a tissue relaxivity approach that disentangles these two tissue components and decodes molecular information from the MRI signal. Our approach enables us to reveal the molecular composition of lipid samples and predict lipidomics measurements of the brain. It produces unique molecular signatures across the brain, which are correlated with specific gene-expression profiles. We uncover region-specific molecular changes associated with brain aging. These changes are independent from other MRI aging markers. Our approach opens the door to a quantitative characterization of the biological sources for aging, that until now was possible only post-mortem.

 

Introduction

The biology of the aging process is complex, and involves various physiological changes throughout cells and tissues1. One of the major changes is atrophy, which can be monitored by measuring macroscale brain volume reduction1,2. In some cases, atrophy can also be detected as localized microscale tissue loss reflected by increased water content3. This process is selective for specific brain regions and is thought to be correlated with cognitive decline in Alzheimer’s disease2,4,5. In addition to atrophy, there are molecular changes associated with the aging of both the normal and pathological brain5,6. Specifically, lipidome changes are observed with age, and are associated with several neurological diseases7,8,9,10,11.

It is an open question as to whether there are general principles that govern the aging process, or whether each system, tissue, or cell deteriorates with age for different reasons12,13. On one hand, the common-cause hypothesis proposes that different biological aging-related changes are the result of a single underlying factor14,15. This implies that various biomarkers of aging will be highly correlated16. On the other hand, the mosaic theory of aging suggests that there are several distinct aging mechanisms that have a heterogenous effect throughout the brain12,13. According to this latter view, combining different measurements of brain tissue is crucial in order to fully describe the state of the aging brain. To test these two competing hypotheses in the context of volumetric and molecular aging-related changes, it is essential to measure different biological aspects of brain tissue. Unfortunately, the molecular correlates of aging are not readily accessible by current in vivo imaging methods.

The main technique used for non-invasive mapping of the aging process in the human brain is magnetic resonance imaging (MRI)2,17,18,19. Advances in the field have led to the development of quantitative MRI (qMRI). This technique provides biophysical parametric measurements that are useful in the investigation and diagnosis of normal and abnormal aging20,21,22,23,24,25,26,27. qMRI parameters have been shown to be sensitive to the microenvironment of brain tissue and are therefore named in vivo histology28,29,30. Nevertheless, an important challenge in applying qMRI measurements is increasing their biological interpretability. It is common to assume that qMRI parameters are sensitive to the myelin fraction20,23,30,31,32,33, yet any brain tissue including myelin is a mixture of multiple lipids and proteins. Moreover, since water protons serve as the source of the MRI signal, the sensitivity of qMRI parameters to different molecular microenvironments may be confounded by their sensitivity to the water content of the tissue34,35. We hypothesized that the changes observed with aging in MRI measurements20,23,30,31,32,33,36 such as R1, R2, mean diffusivity (MD), and magnetization transfer saturation (MTsat)37, could be due to a combination of an increase in water content at the expense of tissue loss, and molecular alterations in the tissue.

Here, we present a qMRI analysis that separately addresses the contribution of changes in molecular composition and water content to brain aging. Disentangling these two factors goes beyond the widely accepted “myelin hypothesis” by increasing the biological specificity of qMRI measurements to the molecular composition of the brain. For this purpose, we generalize the concept of relaxivity, which is defined as the dependency of MR relaxation parameters on the concentration of a contrast agent38. Instead of a contrast agent, our approach exploits the qMRI measurement of the local non-water fraction39 to assess the relaxivity of the brain tissue itself. This approach allows us to decode the molecular composition from the MRI signal. In samples of known composition, our approach provides unique signatures for different brain lipids. In the live human brain, it produces unique molecular signatures for different brain regions. Moreover, these MRI signatures agree with post-mortem measurements of the brain lipid and macromolecular composition, as well as with specific gene-expression profiles. To further validate the sensitivity of the relaxivity signatures to molecular composition, we perform direct comparison of MRI and lipidomics on post-mortem brains. We exploit our approach for multidimensional characterization of aging-related changes that are associated with alterations in the molecular composition of the brain. Finally, we evaluate the spatial pattern of these changes throughout the brain, in order to compare the common-cause and the mosaic theories of aging in vivo.

 

Results

Different brain lipids have unique relaxivity signatures
The aging process in the brain is accompanied by changes in the chemophysical composition, as well as by regional alterations in water content. In order to examine the separate pattern of these changes, we developed a model system. This system was based on lipid samples comprising common brain lipids (phosphatidylcholine, sphingomyelin, phosphatidylserine, phosphatidylcholine-cholesterol, and phosphatidylinositol-phosphatidylcholine)7. Using the model system, we tested whether accounting for the effect of the water content on qMRI parameters provides sensitivity to fine molecular details such as the head groups that distinguish different membrane phospholipids. The non-water fraction of the lipid samples can be estimated by the qMRI measurement of lipid and macromolecular tissue volume (MTV, for full glossary of terms see Supplementary Table 1)39. By varying the concentration of the lipid samples, we could alter their MTV and then examine the effect of this manipulation on qMRI parameters. The parameters we estimated for the lipid samples were R1, R2, and MTsat. The potential ambiguity in the biological interpretation of qMRI parameters is demonstrated in Fig. 1a. On one hand, samples with similar lipid composition can present different R1 measurements (Fig. 1a, points 1 & 2). On the other hand, scanning samples with different lipid compositions may result in similar R1 measurements (Fig. 1a, points 2 & 3). This ambiguity stems from the confounding effect of the water content on the MR relaxation properties.

Screenshot 2019-08-01 at 14.36.20

We evaluated the dependency of different qMRI parameters on the non-water fraction estimated by MTV. This analysis revealed strong linear dependencies (median R2 = 0.74, Fig. 1a, b and Supplementary Fig. 1a, b). These linear MTV dependencies change as a function of the lipid composition, reflecting the inherent relaxivity of the different lipids. We could therefore use the MTV derivatives of qMRI parameters (dqMRIdMTV, i.e., the slope of the linear relationship between each qMRI parameter and MTV) as a measure that is sensitive to molecular composition. By accounting for the Multidimensional Dependency on MTV (“MDM”) of several qMRI parameters, a unique MRI relaxivity signature was revealed for each lipid (Fig. 1c). This implies that the water-related ambiguity demonstrated in the inset of Fig. 1a can be removed by measuring the MTV dependencies (Fig. 1c). Creating mixtures of several lipids provided supportive evidence for the generality of our framework. Figure 1d and Supplementary Fig. 1c show that the qMRI measurements of a mixture can be predicted by summing the MTV dependencies of pure lipids (for further details see Supplementary Note 1 and Supplementary Fig. 2). Furthermore, we used this biophysical model to predict the lipid composition of a mixture from its MDM measurements (Fig. 1e). This model provided a good estimation of the sphingomyelin (Spg) and phosphatidylserine (PS) content (R2 > 0.64) but failed to predict phosphatidylcholine (PtdCho) content (for further details see Supplementary Note 2). While lipids are considered to be a major source of the MRI signal in the brain 40,41,42,43,44,45, our approach can be applied to other compounds to reveal differences in the MRI signal between different proteins, sugars, and ions (Supplementary Fig. 1d). Hence, the relationships between qMRI parameters and MTV account for the effect of water on MRI measurements and could be of use in quantifying the biological and molecular contributions to the MRI signal of water protons.

The tissue relaxivity of the human brain is region-specific.
In order to target age-related changes in molecular composition, we applied the same approach for the human brain (Fig. 2a).

Screenshot 2019-08-01 at 14.41.35

We found that the linear dependency of qMRI parameters on MTV is not limited to in vitro samples and a similar relationship was also evident in the human brain (Fig. 2b and Supplementary Figs. 3–5). Importantly, different brain regions displayed a distinct dependency on MTV. Therefore, the relaxivity of brain tissue is region-specific. Figure 2b provides an example for the regional linear trends of R1 and MTsat in a single subject. Remarkably, while the thalamus and the pallidum presented relatively similar R1 dependencies on MTV, their MTsat dependencies were different (p < 0.001, two-sample t-test). Compared to these two brain regions, frontal white-matter demonstrated different dependencies on MTV (p < 0.001, two-sample t-test). A better separation between brain regions can therefore be achieved by combining the MTV dependencies of several qMRI parameters (MTsat, MD, R1 and R2). The MTV derivatives of qMRI parameters are consistent across subjects (Fig. 2c and Supplementary Fig. 6), with good agreement between hemispheres (Supplementary Fig. 5). Moreover, they provide a novel pattern of differentiation between brain regions, which is not captured by conventional qMRI methods (Supplementary Fig. 7). In our lipid sample experiments, the MDM approach revealed unique relaxivity signatures of different lipids (Fig. 1c). Therefore, we attribute the observed diversity in the MTV derivatives of qMRI parameters across brain regions to the intrinsic heterogeneity in the chemophysical microenvironment of these regions. The multidimensional dependency of various qMRI parameters on MTV can be represented by the space of MTV derivatives to reveal a unique chemophysical MDM signature for different brain regions (Fig. 2d, see explanatory scheme of the MDM method in Supplementary Fig. 8). Fig. 2 figure2 The MDM method provides region-specific signatures in the in vivo human brain. a Representative MTV, MTsat, and R1 maps. b Calculating the MDM signatures. The dependency of R1 (left) and MTsat (right) on MTV in three brain regions of a single subject. For each region, MTV values were pooled into bins (dots are the median of each bin; shaded area is the median absolute deviation), and a linear fit was calculated (colored lines). The slopes of the linear fit represent the MTV derivatives of R1 and MTsat and vary across brain regions. c The reliability of the MDM method across subjects. Variation in the MTV derivatives of R1 (left) and MTsat (right) in young subjects (N = 23). Different colors represent 14 brain regions (see legend). Edges of each box represent the 25th, and 75th percentiles, median is in black, and whiskers extends to extreme data points. Different brain regions show distinct MTV derivatives. d Unique MDM signatures for different brain regions (in different colors). Each axis is the MTV derivative (“MDM measurements”) of a different qMRI parameter (R1, MTsat, R2, and MD). The range of each axis is in the legend. Colored traces extend between the MDM measurements, shaded areas represent the variation across subjects (N = 23). An overlay of all MDM signatures is marked with dashed lines Full size image The in vivo MDM approach captures ex vivo molecular profiles To validate that the MDM signatures relate to the chemophysical composition of brain tissue, we compared them to a previous study that reported the phospholipid composition of the human brain7. First, we established the comparability between the in vivo MRI measurements and the reported post-mortem data. MTV measures the non-water fraction of the tissue, a quantity that is directly related to the total phospholipid content. Indeed, we found good agreement between the in vivo measurement of MTV and the total phospholipid content across brain regions (R2 = 0.95, Fig. 3a). Söderberg et al.7 identified a unique phospholipid composition for different brain regions along with diverse ratios of phospholipids to proteins and cholesterol. We compared this regional molecular variability to the regional variability in the MDM signatures. To capture the main axes of variation, we performed principal component analysis (PCA) on both the molecular composition of the different brain regions and on their MDM signatures. For each of these two analyses, the first principal component (PC) explained >45% of the variance. The regional projection on the first PC of ex vivo molecular composition was highly correlated (R2 = 0.84, Fig. 3b) with the regional projection on the first PC of in vivo MDM signatures. This confirms that brain regions with a similar molecular composition have similar MDM. Supplementary Fig. 9a provides the correlations of individual lipids with MDM. Importantly, neither MTV nor the first PC of standard qMRI parameters was as strongly correlated with the ex vivo molecular composition as the MDM (Supplementary Fig. 9b, c). We next used the MDM measurements as predictors for molecular properties of different brain regions. Following our content predictions for lipids samples (Fig. 1e), we constructed a weighted linear model for human data (for further details see Supplementary Note 3). To avoid over fitting, we reduced the number of fitted parameters by including only the MDM and the molecular features that accounted for most of the regional variability. The MTV derivatives of R1 and MTsat accounted for most of the variance in MDM. Thus, we used these parameters as inputs to the linear model, while adjusting their weights through cross validation. We tested the performance of this model in predicting the three molecular features that account for most of the variance in the ex vivo molecular composition. Remarkably, MRI-driven MDM measurements provided good predictions for the regional sphingomyelin composition (R2 = 0.56, p < 0.05 for the F-test, Fig. 3c) and the regional ratio of phospholipids to proteins (R2 = 0.56, p < 0.05 for the F-test, Fig. 3c).

Screenshot 2019-08-01 at 14.44.06
Last, we compared the cortical MDM signatures to a gene co-expression network based on a widespread survey of gene expression in the human brain46. Nineteen modules were derived from the gene network, each comprised of a group of genes that co-varies in space. Six out of the nineteen gene modules were significantly correlated with the first PC of MDM. Interestingly, the first PC of MDM across the cortex was correlated most strongly with the two gene modules associated with membranes and synapses (Fig. 4, for further details see Supplementary Note 4 and Supplementary Figs. 10 and 11).

Screenshot 2019-08-01 at 14.47.04

Post-mortem validation for the lipidomic sensitivity of MDM.
The aforementioned analyses demonstrate strong agreement between in vivo MDM measurements and ex vivo molecular composition based on a group-level comparison of two different datasets. Strikingly, we were able to replicate this result at the level of the single brain. To achieve this we performed MRI scans (R1, MTsat, R2, MD, and MTV mapping) followed by histology of two fresh post-mortem porcine brains (Fig. 5a, b). First, we validated the qMRI estimation of MTV using dehydration techniques. MTV values estimated using MRI were in agreement with the non-water fraction found histologically (adjusted R2 = 0.64, p < 0.001 for the F-test, Fig. 5c).

Screenshot 2019-08-01 at 14.50.12
Next, we estimated the lipid composition of different brain regions. Thin-layer chromatography (TLC) was employed to quantify seven neutral and polar lipids (Supplementary Table 2 and Supplementary Fig. 12a). In accordance with the analysis in Fig. 3, we performed PCA to capture the main axes of variation in lipidomics, standard qMRI parameters, and MDM. Figure 5d shows that MTV did not correlate with the molecular variability across the brain, estimated by the 1st PC of lipidomics. Likewise, the molecular variability did not agree with the 1st PC of standard qMRI parameters (Fig. 5e).

Last, we applied the MDM approach to the post-mortem porcine brain. Similar to the human brain, different porcine brain regions have unique MDM signatures (Fig. 5f, g and Supplementary Fig. 12b). Remarkably, we found that agreement between lipid composition and MRI measurements emerges at the level of the MDM signatures. The molecular variability across brain regions significantly correlated with the regional variability in the MDM signatures (adjusted R2 = 0.3, p < 0.01 for the F-test, Fig. 5h). Excluding from the linear regression five outlier brain regions where the histological lipidomics results were 1.5 standard deviations away from the center yielded an even stronger correlation between MDM signatures and lipid composition (adjusted R2 = 0.55, p < 0.001 for the F-test, Supplementary Fig. 12c). This post-mortem analysis validates that the MDM approach allows us to capture molecular information using MRI at the level of the individual brain.

Disentangling water and molecular aging-related changes.
After establishing the sensitivity of the MDM signatures to the molecular composition of the brain, we used them to evaluate the chemophysical changes of the aging process. To assess aging-related changes across the brain, we scanned younger and older subjects (18 older adults aged 67 ± 6 years and 23 younger adults aged 27 ± 2 years). First, we identified significant molecular aging-related changes in the MDM signatures of different brain regions (Figs. 6 and 7, right column; Supplementary Fig. 13). Next, we tested whether the changes in MRI measurements, observed with aging, result from a combination of changes in the molecular composition of the tissue and its water content. We found that although it is common to attribute age-related changes in R1 and MTsat to myelin28,30,36, these qMRI parameters combine several physiological aging aspects. For example, using R1 and MTsat we identified significant aging-related changes in the parietal cortex, the thalamus, the parietal white-matter and the temporal white-matter (Figs. 6 and 7, left column). However, the MDM approach revealed that these changes have different biological sources (Figs. 6 and 7, middle columns; see Supplementary Figs. 14–17 for more brain regions).

Screenshot 2019-08-01 at 14.51.53

Screenshot 2019-08-01 at 14.54.44

Screenshot 2019-08-01 at 14.56.06

In agreement with the mosaic hypothesis, we identified distinct aging patterns for different brain regions. For example, in the hippocampus we found a change in R2* values related to a higher iron concentration with age, along with significant reduction in the total hippocampal volume (Fig. 8a). This age-related shrinkage was not accompanied by lower MTV values, indicating conserved tissue density (Fig. 7b). In addition, there was no significant difference in the hippocampal MDM signature with age (Fig. 7b). Cortical gray-matter areas also exhibited similar trends of volume reduction without major loss in tissue density (Fig. 8a). Unlike the gray matter, in the white matter we did not find volume reduction or large iron accumulation with age (Fig. 8a). However, we did find microscale changes with age in tissue composition, as captured by the MDM signature (Figs. 6a and 7c, and Supplementary Fig. 13), accompanied by a significant density-related decline in MTV (Fig. 8a). These findings are consistent with previous histological studies49,50,51 (see Discussion), and provide the ability to monitor in vivo the different components of the aging mosaic.

Last, to test whether the different biological aging trajectories presented in Fig. 8a share a common cause, we evaluated the correlations between them (Fig. 8b). Importantly, the chemophysical trajectory did not correlate significantly with the iron or volume aging patterns. The spatial distribution of water-related changes was found to correlate with iron content alterations (R2 = 0.27) and chemophysical alterations (R2 = 0.25). However, the strongest correlation between aging-related changes was found in volume and iron content (R2 = 0.77). As shown previously, this correlation may be explained to some extent by a systematic bias in automated tissue classification23. Additional analysis revealed that the different dimensions of the MDM signature capture distinct patterns of aging-related changes (Supplementary Fig. 30). Hence, complementary information regarding the various chemophysical mechanisms underlying brain aging could be gained by combining them.

 

Discussion

Normal brain aging involves multiple changes, at both the microscale and macroscale level. MRI is the main tool for in vivo evaluation of such age-related changes in the human brain. Here, we propose to improve the interpretation of MRI findings by accounting for the fundamental effect of the water content on the imaging parameters. This approach allows for non-invasive mapping of the molecular composition in the aging human brain.

Our work is part of a major paradigm shift in the field of MRI toward in vivo histology30,36,52. The MDM approach contributes to this important change by providing a hypothesis-driven biophysical framework that was rigorously developed. We demonstrated the power of our framework, starting from simple pure lipid phantoms to more complicated lipid mixtures, and from there, to the full complexity of the brain. In the brain, we show both in vivo and post-mortem validations for the molecular sensitivity of the MDM signatures. Early observations relate different qMRI parameters to changes in the fraction of myelin20,23,30,31,32,33,36. The current approach enriches this view and provides better sensitivity to the molecular composition and fraction of myelin and other cellular tissues.

We developed a unique phantom system of lipid samples to validate our method. While the phantom system is clearly far from the complexity of brain tissue, its simplicity allowed us to verify the specificity of our method to the chemophysical environment. Remarkably, our approach revealed unique signatures for different lipids, and is therefore sensitive even to relatively subtle details that distinguish one lipid from another. We chose to validate our approach using membrane lipids based on previous experiments40,41,42,43,44,45. Nevertheless, we do acknowledge the fact that brain tissue comprises many other compounds beside lipids, such as proteins, sugars, and ions. As we have shown, these other compounds also exhibit unique dependency on MTV. The effect of such compounds, along with other factors such as microstructure, and multi-compartment organization28 is probably captured when we apply the MDM approach to the in vivo human brain. Therefore, the phantoms were made to examine the MRI sensitivity for the chemophysical environment, and the human brain data was used to measure the true biological effects in a complex in vivo environment.

Our relaxivity approach captures the molecular signatures of the tissue, but is limited in its abilities to describe the full complexity of the chemophysical environment of the human brain. For example, R1 and R2, which are used to generate the MDM signatures, are also sensitive to the iron content23,48,52. However, we found that most of our findings cannot be attributed to alterations in iron content as measured with R2* (for more details see Supplementary Note 5). While there is great importance in further isolating different molecular components, we argue that accounting for the major effect of water on qMRI parameters (for R2 distributions see Supplementary Fig. 5) is a crucial step towards more specific qMRI interpretation.

We provide evidence from lipids samples and post-mortem data for the sensitivity of the MDM signatures to the molecular environment (Figs. 1e, 3b, and 5h). The variability of MDM values between human brain regions also correlated with specific gene-expression profiles (Fig. 4). While the comparison of in vivo human brain measurements to previously published ex vivo findings is based on two different datasets, these measurements are highly stable across normal subjects and the intersubject variabilities are much smaller than the regional variability. The agreement between the modalities provides strong evidence for the ability of our method to capture molecular information.

Remarkably, we were able to demonstrate the sensitivity of MDM signatures to lipid composition using direct comparison on post-mortem porcine brains. Even though there are many challenges in scanning post-mortem tissue, segmenting it, and comparing it to anatomically relevant histological results, we were able to replicate our in vivo findings. We provide histological validation for the MRI estimation of MTV. Moreover, we find that while standard qMRI parameters and MTV do not explain the lipidomic variability across the brain, the MDM signatures are in agreement with histological results. Lipids constitute the majority of the brain’s dry weight and are known to be important for maintaining neural conduction and chemical balance53,54. The brain lipidome was shown to have a great deal of structural and functional diversity and was found to vary according to age, gender, brain region, and cell type55. Disruptions of the brain lipid metabolism have been linked to different disorders, including Alzheimer’s disease, Parkinson’s disease, depression, and anxiety7,8,11,54,55,56,57. Our results indicate that the MDM approach enhances the consistency between MRI-driven measurements and lipidomics, compared with standard qMRI parameters.

The simplicity of our model, which is based on a first-order approximation of qMRI dependencies, has great advantages in the modeling of complex environments. Importantly, we used lipids samples to show that the contributions of different mixture-components can be summed linearly (Fig. 1d). For contrast agents, the relaxivity is used to characterize the efficiency of different agents. Here, we treated the tissue itself, rather than a contrast material, as an agent to compute the relaxivity of the tissue. While relaxivity is usually calculated for R1 and R2, we extended this concept to other qMRI parameters. Our results showed that the tissue relaxivity changes as a function of the molecular composition. This suggests that the relaxivity of the tissue relates to the surface interaction between the water and the chemophysical environment. A theoretical formulation for the effect of the surface interaction on proton relaxation has been proposed before58,59. Specifically, a biophysical model for the linear relationship between R1 and R2 to the inverse of the water content (1/WC = 1/(1 – MTV)) was suggested by Fullerton et al.43. Interestingly, 1/WC varies almost linearly with MTV in the physiological range of MTV values. Applying our approach with 1/WC instead of MTV produces relatively similar results (Supplementary Fig. 28). However, using MTV as a measure of tissue relaxivity allowed us to generalize the linear model to multiple qMRI parameters, thus producing multidimensional MDM signatures.

We show that the MDM signatures allow for better understanding of the biological sources for the aging-related changes observe with MRI. Normal brain aging involves multiple changes, at both the microscale and macroscale levels. Measurements of macroscale brain volume have been widely used to characterize aging-associated atrophy. Our method of analysis can complement such findings and provide a deeper understanding of microscale processes co-occurring with atrophy. Moreover, it allows us to test whether these various microscale and macroscale processes are caused by a common factor or represent the aging mosaic. Notably, we discovered that different brain regions undergo different biological aging processes. Therefore, combining several measurements of brain tissue is crucial in order to fully describe the state of the aged brain. For example, the macroscale aging-related volume reduction in cortical gray areas was accompanied by conserved tissue density, as estimated by MTV, and region-specific chemophysical changes, as estimated by the MDM. In contrast, in white-matter areas both MDM and MTV changed with age. These microscale alterations were not accompanied by macroscale volume reduction. Our in vivo results were validated by previous histological studies, which reported that the cortex shrinks with age, while the neural density remains relatively constant49,50. In contrast, white matter was found to undergo significant loss of myelinated nerve fibers during aging51. In addition, we found that the shrinkage of the hippocampus with age is accompanied with conserved tissue density and chemophysical composition. This is in agreement with histological findings, which predict drastic changes in hippocampal tissue composition in neurological diseases such as Alzheimer, but not in normal aging49,50,60,61. In contrast, hippocampal macroscale volume reduction was observed in both normal and pathological aging2.

It should be noted that most of the human subjects recruited for this study were from the academic community. However, the different age groups were not matched for variables such as IQ and socioeconomic status. In addition, the sample size in our study was quite small. Therefore, the comparison we made between the two age groups may be affected by variables other than age. Our approach may benefit from validation based on larger quantitative MRI datasets27,62. Yet, we believe we have demonstrated the potential of our method to reveal molecular alterations in the brain. Moreover, the agreement of our findings with previous histological aging studies supports the association between the group differences we measured and brain aging. Our results suggest that the MDM approach may be very useful in differentiating the effects of normal aging from those of neurodegenerative diseases. There is also great potential for applications in other brain research fields besides aging. For example, our approach may be used to advance the study and diagnosis of brain cancer, in which the lipidomic environment undergoes considerable changes63,64,65.

To conclude, we have presented here a quantitative MRI approach that decodes the molecular composition of the aging brain. While common MRI measurements are primarily affected by the water content of the tissue, our method employed the tissue relaxivity to expose the sensitivity of MRI to the molecular microenvironment. We presented evidence from lipid samples, post-mortem porcine brains and in vivo human brains for the sensitivity of the tissue relaxivity to molecular composition. Results obtained by this method in vivo disentangled different biological processes occurring in the human brain during aging. We identified region-specific patterns of microscale aging-related changes that are associated with the molecular composition of the human brain. Moreover, we showed that, in agreement with the mosaic theory of aging, different biological age-related processes measured in vivo have unique spatial patterns throughout the brain. The ability to identify and localize different age-derived processes in vivo may further advance human brain research.

Methods

Phantom construction
The full protocol of lipids phantom preparation is described in Shtangel et al.66.

In short, we prepared liposomes from one of the following lipids: phosphatidylserine (PS), phosphatidylcholine (PtdCho), phosphatidylcholine-cholesterol (PtdCho-Chol), Phosphatidylinositol-phosphatidylcholine (PI-PtdCho), or sphingomyelin (Spg). These phantoms were designed to model biological membranes and were prepared from lipids by the hydration–dehydration dry film technique67. The lipids were dissolved over a hot plate and vortexed. Next, the solvent was removed to create a dry film by vacuum-rotational evaporation. The samples were then stirred on a hot plate at 65 °C for 2.5 h to allow the lipids to achieve their final conformation as liposomes. Liposomes were diluted with Dulbecco’s phosphate buffered saline (PBS), without calcium and magnesium (Biological Industries), to maintain physiological conditions in terms of osmolarity, ion concentrations and pH. To change the MTV of the liposome samples we varied the PBS to lipid volume ratios66. Samples were then transferred to the phantom box for scanning in a 4 mL squared polystyrene cuvettes glued to a polystyrene box, which was then filled with ~1% SeaKem Agarose (Ornat Biochemical) and ~0.0005 M Gd (Gadotetrate Melumine, (Dotarem, Guerbet)) dissolved in double distilled water (ddw). The purpose of the agar with Gd (Agar-Gd) was to stabilize the cuvettes, and to create a smooth area in the space surrounding the cuvettes that minimalized air–cuvette interfaces. In some of our experiments we used lipid mixtures composed of several lipids. We prepared nine mixtures containing different combinations of two out of three lipids (PtdChol, Spg and PS) in varying volume ratios (1:1,1:2,2:1). For each mixture, we prepared samples in which the ratio between the different lipid components remained constant while the water-to-lipid volume fraction varied.

For the bovine serum albumin (BSA) phantoms, samples were prepared by dissolving lyophilized BSA powder (Sigma Aldrich) in PBS. To change the MTV of these phantoms, we changed the BSA concentration. For the BSA + Iron phantoms, BSA was additionally mixed with a fixed concentration of 50 µg/mL ferrous sulfate heptahydrate (FeSO4*7H2O). Samples were prepared in their designated concentrations at room temperature. Prepared samples were allowed to sit overnight at 4 ℃ to ensure BSA had fully dissolved, without the need for significant agitation, which is known to cause protein cross-linking. Samples were then transferred to the phantom box for scanning.

For Glucose and Sucrose phantoms, different concentrations of D-( + )-Sucrose (Bio-Lab) and D-( + )-Glucose (Sigma) were dissolved in PBS at 40 ℃. Samples were allowed to reach room temperature before the scan.

MRI acquisition for phantoms

Data was collected on a 3 T Siemens MAGNETOM Skyra scanner equipped with a 32-channel head receive-only coil at the ELSC neuroimaging unit at the Hebrew University.

For quantitative R1 & MTV mapping, three-dimensional (3D) Spoiled gradient (SPGR) echo images were acquired with different flip angles (α = 4°, 8°, 16°, and 30°). The TE/TR was 3.91/18 ms. The scan resolution was 1.1 × 1.1 × 0.9 mm. The same sequence was repeated with a higher resolution of 0.6 × 0.6 × 0.5 mm. The TE/TR was 4.45/18 ms. For calibration, we acquired an additional spin-echo inversion recovery (SEIR) scan. This scan was done on a single slice, with adiabatic inversion pulse and inversion times of TI = 2000, 1200, 800, 400, and 50. The TE/TR was 73/2540 ms. The scan resolution was 1.2 mm isotropic.

For quantitative T2 mapping, images were acquired with a multi spin-echo sequence with 15 equally spaced spin echoes between 10.5 ms and 157.5 ms. The TR was 4.94 s. The scan resolution was 1.2 mm isotropic. For quantitative MTsat mapping, images were acquired with the FLASH Siemens WIP 805 sequence. The TR was 23 ms for all samples except PI:PtdCho for which the TR was 72 ms. Six echoes were equally spaced between 1.93 ms to 14.58 ms. The on-resonance flip angle was 6°, the MT flip angle was 220°, and the RF offset was 700. We used 1.1-mm in-plane resolution with a slice thickness of 0.9 mm. For samples of sucrose and glucose, MTsat mapping was done similar to the human subjects, based on 3D Spoiled gradient (SPGR) echo image with an additional MT pulse. The flip angle was 10°, the TE/TR was 3.91/28 ms. The scan resolution was 1 mm isotropic.

Estimation of qMRI parameters for phantoms

MTV and R1 estimations for the lipids samples were computed based on a the mrQ39 (https://github.com/mezera/mrQ) and Vista Lab (https://github.com/vistalab/vistasoft/wiki) software. The mrQ software was modified to suit the phantom system66. The modification utilizes the fact that the Agar-Gd filling the box around the samples is homogeneous and can, therefore, be assumed to have a constant T1 value. We used this gold standard T1 value generated from the SEIR scan to correct for the excite bias in the spoiled gradient echo scans. While the data was acquired in two different resolutions (see “MRI acquisition”), in our analysis we use the median R1 and MTV of each lipid sample and these are invariant to the resolution of acquisition (Supplementary Fig. 1e). Thus, we were able to use scans with different resolutions without damaging our results. T2 maps were computed by implementing the echo‐modulation curve (EMC) algorithm68.

For quantitative MTsat mapping see the “MTsat estimation” section for human subjects.

MDM computation for phantoms

We computed the dependency of each qMRI parameter (R1, MTsat, and R2) on MTV in different lipids samples. This process was implemented in MATLAB (MathWorks, Natwick, MI, USA). To manipulate the MTV values, we scanned samples of the same lipid in varying concentrations. We computed the median MTV of each sample, along with the median of qMRI parameters. We used these data points to fit a linear model across all samples of the same lipid. The slope of this linear model represents the MTV derivative of the linear equation. We used this derivative estimate of three qMRI parameters (R1, R2, and MTsat) to compute the MDM signatures. The same procedure was used for the MDM computation of lipid mixtures.

 

MDM modeling of lipid mixtures

We tested the ability of MDM to predict the composition of lipid mixtures. For this analysis we used nine mixture phantoms (see “Phantom construction”), along with the three phantoms of the pure lipid constituents of the mixtures (PS, Spg, and Ptd-Cho).

In order to predict the qMRI parameters of a lipid mixture (Fig. 1d) we used Supplementary Eq. 1 (Supplementary Note 1). To further predict the composition of the mixtures (Fig. 1e) we used Supplementary Eq. 5 (Supplementary Note 2). We solved this equation using the QR factorization algorithm.

Ethics

Human experiments complied with all relevant ethical regations. The Helsinki Ethics Committee of Hadassah Hospital, Jerusalem, Israel approved the experimental procedure. Written informed consent was obtained from each participant prior to the procedure.

Human subjects

Human measurements were performed on 23 young adults (aged 27 ± 2 years, 11 females), and 18 older adults (aged 67 ± 6 years, five females). Healthy volunteers were recruited from the community surrounding the Hebrew University of Jerusalem.

MRI acquisition for human subjects

Data was collected on a 3 T Siemens MAGNETOM Skyra scanner equipped with a 32-channel head receive-only coil at the ELSC neuroimaging unit at the Hebrew University.

For quantitative R1, R2*, & MTV mapping, 3D Spoiled gradient (SPGR) echo images were acquired with different flip angles (α = 4°, 10°, 20°, and 30°). Each image included five equally spaced echoes (TE = 3.34–14.02 ms) and the TR was 19 ms (except for six young subjects for which the scan included only one TE = 3.34 ms). The scan resolution was 1 mm isotropic. For calibration, we acquired additional spin-echo inversion recovery scan with an echo-planar imaging (EPI) read-out (SEIR-epi). This scan was done with a slab-inversion pulse and spatial-spectral fat suppression. For SEIR-epi, the TE/TR was 49/2920 ms. TI were 200, 400, 1,200, and 2400 ms. We used 2-mm in-plane resolution with a slice thickness of 3 mm. The EPI read-out was performed using 2 × acceleration.

For quantitative T2 mapping, multi‐SE images were acquired with ten equally spaced spin echoes between 12 ms and 120 ms. The TR was 4.21 s. The scan resolution was 2 mm isotropic. T2 scans of four subjects (one young, three old) were excluded from the analysis due to motion.

For quantitative MTsat mapping, 3D Spoiled gradient (SPGR) echo image were acquired with an additional MT pulse. The flip angle was 10°, the TE/TR was 3.34/27 ms. The scan resolution was 1 mm isotropic.

Whole-brain DTI measurements were performed using a diffusion-weighted spin-echo EPI sequence with isotropic 1.5-mm resolution. Diffusion weighting gradients were applied at 64 directions and the strength of the diffusion weighting was set to b = 2000 s/mm2 (TE/TR = 95.80/6000 ms, G = 45mT/m, δ = 32.25 ms, Δ = 52.02 ms). The data includes eight non-diffusion-weighted images (b = 0). In addition, we collected non-diffusion-weighted images with reversed phase-encode blips. For five subjects (four young, one old) we failed to acquire this correction data and they were excluded from the diffusion analysis.

Anatomical images were acquired with 3D magnetization prepared rapid gradient echo (MP-RAGE) scans for 24 of the subjects (14 from the younger subjects, 10 from the older subjects). The scan resolution was 1 mm isotropic, the TE/TR was 2.98/2300 ms. Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) scans were acquired for the rest of the subjects. The scan resolution was 1 mm isotropic, the TE/TR was 2.98/5000 ms.

Estimation of qMRI parameters for human subjects

Whole-brain MTV and R1 maps, together with bias correction maps of B1 + and B1-, were computed using the mrQ software39,69 (https://github.com/mezera/mrQ). Voxels in which the B1 + inhomogeneities were extrapolated and not interpolated were removed from the MTV and R1 maps. While we did not correct our MTV estimates for R2*, we showed that employing such a correction does not significantly change our results (see Supplementary Note 6, Supplementary Figs. 20–27). MTV maps of four subjects had bias in the lower part of the brain and they were therefore excluded from the analysis presented in Fig. 3, which includes ROIs in the brainstem.

Whole-brain T2 maps were computed by implementing the echo‐modulation curve (EMC) algorithm68. To combine the MTV and T2 we co-registered the quantitative MTV map to the T2 map. We used the ANTS software package70 to calculate the transformation and to warp the MTV map and the segmentation. The registration was computed to match the T1 map to the T2 map. Next, we applied the calculated transformation to MTV map (since MTV and T1 are in the same imaging space) and resampled the MTV map to match the resolution of the T2 map. The same transformation was also applied to the segmentation. R2 maps were calculated as 1/T2.

Whole-brain MTsat maps were computed as described in Helms et al.37. The MTsat measurement was extracted from Eq. (1):

MTsat=𝑀0𝐵1𝛼𝑅1TR𝑆MT−(𝐵1𝛼)22−𝑅1TR
(1)
Where SMT is the signal of the SPGR scan with additional MT pulse, α is the flip angle and TR is the repetition time. Mo (the equilibrium magnetization parameter), B1 (the transmit inhomogeneity), and R1 estimations were computed from the non-MT weighted SPGR scans, during the pipeline described under “MTV & R1 estimation”. Registration of the SMT image to the imaging space of the MTV map was done using a rigid-body alignment (R1, B1, and MO are all in the same space as MTV).

Diffusion analysis was done using the FDT toolbox in FSL71,72. Susceptibility and eddy current induced distortions were corrected using the reverse phase-encode data, with the eddy and topup commands73,74. MD maps were calculated using vistasoft (https://github.com/vistalab/vistasoft/wiki). We used a rigid-body alignment to register the corrected dMRI data to the imaging space of the MTV map (Flirt, FSL). In order to calculate the MD-MTV derivatives, we resampled the MTV map and the segmentation to match the dMRI resolution.

We used the SPGR scans with multiple echoes to estimate R2*. Fitting was done through the MPM toolbox75. As we had four SPGR scans with variable flip angles, we averaged the R2* maps acquired from each of these scans for increased SNR.

Human brain segmentation

Whole-brain segmentation was computed automatically using the FreeSurfer segmentation algorithm76. For subjects who had an MP-RAGE scan, we used it as a reference. For the other subjects the MP2RAGE scan was used as a reference. These anatomical images were registered to the MTV space prior to the segmentation process, using a rigid-body alignment. Sub-cortical gray-matter structures were segmented with FSL’s FIRST tool77. To avoid partial volume effects, we removed the outer shell of each ROI and left only the core.

MDM computation in the human brain

We computed the dependency of each qMRI parameter (R1, MTsat, MD, and R2) on MTV in different brain areas. This process was implemented in MATLAB (MathWorks, Natwick, MI, USA). For each ROI, we extracted the MTV values from all voxels and pooled them into 36 bins spaced equally between 0.05 and 0.40. This was done so that the linear fit would not be heavily affected by the density of the voxels in different MTV values. We removed any bins in which the number of voxels was smaller than 4% of the total voxel count in the ROI. The median MTV of each bin was computed, along with the median of the qMRI parameter. We used these data points to fit the linear model across bins using Eq. (2):

qMRIparameters=𝑎∗MTV+𝑏
(2)
The slope of this linear model (“a”) represents the MTV derivative of the linear equation. We used this derivative estimate to compute the MDM signatures.

For each subject, ROIs in which the total voxel count was smaller than a set threshold of 500 voxels for the MTsat and R1 maps, 150 voxels for the MD map, and 50 voxels for the R2 map were excluded.

Principal component analysis (PCA) in the human brain

To estimate the variability in the MDM signatures across the brain, we computed the first principal component (PC) of MDM. For each MDM dimension (MTV derivatives of R1, MTsat, MD, and R2), we evaluated the median of the different brain areas across the young subjects. As each MDM dimension has different units, we then computed the z-score of each dimension across the different brain area. Finally, we performed PCA. The variables in this analysis were the different MDM dimensions, and the observations were the different brain areas. From this analysis, we derived the first PC that accounts for most of the variability in MDM signatures across the brain. To estimate the median absolute deviations (MAD) across subjects of each MDM measurement in the PC basis, we applied the z-score transformation to the original MAD and then projected them onto the PC basis.

To compute the first PC of standard qMRI parameters we followed the same procedure, but used R1, MTsat, MD, and R2 instead of their MTV derivatives.

For the first PC of molecular composition, we followed the same procedure, but used the phospholipid composition and the ratio between phospholipids to proteins and cholesterol as variables. The data was taken from eight post-mortem human brains7. Brains were obtained from individuals between 54 and 57 years of age, which were autopsied within 24 h after death.

Linear model for prediction of human molecular composition

We used MDM measurements in order to predict the molecular composition of different brain areas (Fig. 3c). For this analysis we used Supplementary Eq. 5 in the Supplementary Note 2. We solved this equation using QR factorization algorithm (for more details see Supplementary Note 3).

Gene-expression dataset

For the gene-expression analysis we followed the work of Ben-David and Shifman46. Microarray data was acquired from the Allen Brain Atlas (http://human.brain-map.org/well_data_files) and included a total of 1340 microarray profiles from donors H0351.2001 and H0351.2002, encompassing the different regions of the human brain. The donors were 24 and 39 years old, respectively, at the time of their death, with no known psychopathologies. We used the statistical analysis described by Ben-David and Shifman46. They constructed a gene network using a weighted gene co-expression network analysis. The gene network included 19 modules of varying sizes, from 38 to 7385 genes. The module eigengenes were derived by taking the first PC of the expression values in each module. In addition, we used the gene ontology enrichment analysis described by Ben-David and Shifman to define the name of each module. The colors of the different modules in the Fig. 4 and Supplementary Fig. 10 are the same as in the original paper.

Next, we matched between the gene-expression data and the MRI measurements. This analysis was done on 35 cortical regions extracted from FreeSurfer cortical parcellation. We downloaded the T1-weighted images of the two donors provided by the Allen Brain Atlas (http://human.brain-map.org/mri_viewers/data) and used them as a reference for FreeSurfer segmentation. We then found the FreeSurfer label of each gene-expression sample using the sample’s coordinates in brain space. We removed samples for which the FreeSurfer label and the label provided in the microarray dataset did not agree (there were 72 such samples out of 697 cortical samples). For each gene module, we averaged over the eigengenes of all samples from the same cortical area across the two donors.

Last, we compared the cortical eigengene of each module to the projection of cortical areas on the first PC of MDM. In addition, we compared the modules’ eigengenes to the MTV values of the cortical areas and to the projection of cortical areas on the first PC of standard qMRI parameters (Supplementary Fig. 10). These 57 correlations were corrected for multiple comparisons using the FDR method.

Brain region’s volume computation

To estimate the volume of different brain regions, we calculated the number of voxels in the FreeSurfer segmentation of each region (see “Brain segmentation”).

R2* correction for MTV
To correct the MTV estimates for R2* we used Eq. (3):

MTV𝐶=1−(1−MTV)⋅exp(TE⋅R2∗)
(3)
Where MTVC is the corrected MTV.

Statistical analysis

The statistical significance of the differences between the age groups was computed using an independent-sample t-test (alpha = 0.05, both right and left tail) and was corrected for multiple comparisons using the false-discovery rate (FDR) method. For this analysis, MRI measurements of both hemispheres of bilateral brain regions were joined together. R2 measurements were adjusted for the number of data points. All statistical tests were two-sided.

Post-mortem tissue acquisition

Two post-mortem porcine brains were purchased from BIOTECH FARM.

Post-mortem MRI acquisition

Brains were scanned fresh (without fixation) in water within 6 h after death. Data was collected on a 3 T Siemens MAGNETOM Skyra scanner equipped with a 32-channel head receive-only coil at the ELSC neuroimaging unit at the Hebrew University.

For quantitative R1, R2*, & MTV mapping, 3D Spoiled gradient (SPGR) echo images were acquired with different flip angles (α = 4°, 10°, 20°, and 30°). Each image included five equally spaced echoes (TE = 4.01 – 16.51 ms) and the TR was 22 ms. The scan resolution was 0.8 mm isotropic. For calibration, we acquired additional spin-echo inversion recovery scan with an echo-planar imaging (EPI) read-out (SEIR-epi). This scan was done with a slab-inversion pulse and spatial-spectral fat suppression. For SEIR-epi, the TE/TR was 49/2920 ms. TI were 50, 200, 400, 1200 ms. The scan resolution was 2 mm isotropic. The EPI read-out was performed using 2 × acceleration.

For quantitative T2 mapping, multi‐SE images were acquired with ten equally spaced spin echoes between 12 and 120 ms. The TR was 4.21 s. The scan resolution was 2 mm isotropic.

For quantitative MTsat mapping, 3D Spoiled gradient (SPGR) echo image were acquired with an additional MT pulse. The flip angle was 10°, the TE/TR was 4.01/40 ms. The scan resolution was 0.8 mm isotropic.

Whole-brain DTI measurements were performed using a diffusion-weighted spin-echo EPI sequence with isotropic 1.5-mm resolution. Diffusion weighting gradients were applied at 64 directions and the strength of the diffusion weighting was set to b = 2000 s/mm2 (TE/TR = 95.80/6000 ms, G = 45mT/m, δ = 32.25 ms, Δ = 52.02 ms). The data includes eight non-diffusion-weighted images (b = 0).

For anatomical images, 3D magnetization prepared rapid gradient echo (MP-RAGE) scans were acquired. The scan resolution was 1 mm isotropic, the TE/TR was 2.98/2300 ms.

Histological analysis

Following the MRI scans the brains were dissected. Total of 42 brain regions were identified. Four samples were excluded as we were not able to properly separate the WM from the GM. One sample was excluded as we could not properly identify its anatomical origin. Additional two samples were too small for TLC analysis.

The non-water fraction (MTV) was determined by desiccation, also known as the dry-wet method. A small fraction of each brain sample (~0.25 g) was weighed. In order to completely dehydrate the fresh tissues, they were left for several days in a vacuum dessicator over silica gel at 4 °C. The experiment ended when no further weight loss occurred. The MTV of each brain sample was calculated based on the difference between the wet (Wwet) and dry (Wdry) weights of the tissue (Eq. 4):

MTV=𝑊wet−𝑊dry𝑊wet
(4)
For lipid extraction and lipidomics analysis78, Brain samples were weighted and homogenized with saline in plastic tubes on ice at concentration of 1 mg/12.5 µL. Two-hundred fifty microliters from each homogenate were utilized for lipid extraction and analysis with thin-layer chromatography (TLC). The lipid species distribution was analyzed by TLC applying 150 µg aliquots. Samples were reconstituted in 10 µL of Folch mixture and spotted on Silica-G TLC plates. Standards for each fraction were purchased from Sigma Aldrich (Rehovot, Israel) and were spotted in separate TLC lanes, i.e., 50 µg of triacylglycerides (TG), cholesterol (Chol), cholesteryl esters (CE), free fatty acids (FFA), lysophospholipids (Lyso), sphingomyelin (Spg), phosphatidylcholine (PtdCho), phosphatidylinositol (PI), phosphatidylserine (PS), and phosphatidylethanolamine (PE). Plates were then placed in a 20 × 20 cm TLC chamber containing petroleum ether, ethyl ether, and acetic acid (80:20:1, v/v/v) for quantification of neutral lipids or chloroform, methanol, acetic acid, and water (65:25:4:2, v:v:v:v) for quantification of polar lipids and run for 45 min. TG, Chol, CE, FFA, phospholipids (PL), Lyso, Spg, PtdCho, PI, PS, and PE bands were visualized with Iodine, scanned and quantified by Optiquant after scanning (Epson V700). Lyso, CE, TG, and PI were excluded from further analysis as their quantification was noisy and demonstrated high variability across TLC plates. This analysis was conducted under the guidance of Prof. Alicia Leikin-Frenkel in the Bert Strassburger Lipid Center, Sheba, Tel Hashomer.

Estimation of qMRI parameters in the post-mortem brain

Similar to human subjects.

Brain segmentation of post-mortem brain

Brain segmentation was done manually. Five tissue samples were excluded as we could not identify their origin location in the MRI scans.

MDM computation in the post-mortem brain

We computed the dependency of each qMRI parameter (R1, MTsat, MD, and R2) on MTV in different brain areas similarly to the analysis of the human subjects.

Principal component analysis (PCA) in the post-mortem brain

To estimate the variability in the MDM signatures across the brain, we computed the first principal component (PC) of MDM. PCA analysis was performed with four variables corresponding to the MDM dimensions (MTV derivatives of R1, MTsat, MD, and R2), and 30 observations corresponding to the different brain regions. As each MDM dimension has different units, we first computed the z-score of each dimension across the different brain areas prior to the PCA. From this analysis we derived the first PC that accounts for most of the variability in MDM signatures across the brain.

To compute the first PC of standard qMRI parameters we followed the same procedure, but used R1, MTsat, MD, and R2 instead of their MTV derivatives.

To estimate the variability in the lipid composition across the brain, we computed the first principal component (PC) of lipidomics. PCA analysis was performed with seven variables corresponding to the different polar and neutral lipids (Chol, FFA, PL, Spg, PtdCho, PS, PE), and 30 observations corresponding to the different brain regions. From this analysis, we derived the first PC that accounts for most of the variability in lipid composition across the brain.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

A toolbox for computing MDM signatures is available at [https://github.com/MezerLab/MDM_toolbox].

The code generating the figures of in the paper is available at [https://github.com/MezerLab/MDM_Gen_Figs].

References
1.
Peters, R. Ageing and the brain. Postgrad. Med. J. 82, 84–88 (2006).

2.
Lockhart, S. N. & DeCarli, C. Structural imaging measures of brain aging. Neuropsychol. Rev. 24, 271–289 (2014).

3.
Wozniak, J. R. & Lim, K. O. Advances in white matter imaging: a review of in vivo magnetic resonance methodologies and their applicability to the study of development and aging. Neurosci. Biobehav. Rev. 30, 762–774 (2006).

4.
Frisoni, G. B., Fox, N. C., Jack, C. R., Scheltens, P. & Thompson, P. M. The clinical use of structural MRI in Alzheimer disease. Nat. Rev. Neurol. 6, 67–77 (2010).

5.
Mrak, R. E., Griffin, S. T. & Graham, D. I. Aging-associated changes in human brain. J. Neuropathol. Exp. Neurol. 56, 1269–1275 (1997).

6.
Yankner, B. A., Lu, T. & Loerch, P. The aging brain. Annu. Rev. Pathol. 3, 41–66 (2008).

7.
Söderberg, M., Edlund, C., Kristensson, K. & Dallner, G. Lipid compositions of different regions of the human brain during aging. J. Neurochem. 54, 415–423 (1990).

8.
Lauwers, E. et al. Membrane lipids in presynaptic function and disease. Neuron 90, 11–25 (2016).

9.
Li, Q. et al. Changes in lipidome composition during brain development in humans, chimpanzees, and Macaque monkeys. Mol. Biol. Evol. 34, 1155–1166 (2017).

10.
Müller, C. P. et al. Brain membrane lipids in major depression and anxiety disorders. Biochim. Biophys. Acta-Mol. Cell Biol. Lipids 1851, 1052–1065 (2015).

11.
Naudí, A. et al. Lipidomics of human brain aging and Alzheimer’s disease pathology. Int. Rev. Neurobiol. 122, 133–189 (2015).

12.
Walker, L. C. & Herndon, J. G. Mosaic aging. Med. Hypotheses 74, 1048–1051 (2010).

13.
Cole, J. H., Marioni, R. E., Harris, S. E. & Deary, I. J. Brain age and other bodily ‘ages’: implications for neuropsychiatry. Mol. Psychiatry 1 (2018). https://doi.org/10.1038/s41380-018-0098-1.

14.
Hayflick, L. Biological aging is no longer an unsolved problem. Ann. N. Y. Acad. Sci. 1100, 1–13 (2007).

15.
Christensen, H., Mackinnon, A. J., Korten, A. & Jorm, A. F. The ‘common cause hypothesis’; of cognitive aging: evidence for not only a common factor but also specific associations of age with vision and grip strength in a cross-sectional analysis. Psychol. Aging 16, 588–599 (2001).

16.
Cole, J. H. et al. Brain age predicts mortality. Mol. Psychiatry 23, 1385–1392 (2018).

17.
Sowell, E. R., Thompson, P. M. & Toga, A. W. Mapping changes in the human cortex throughout the span of life. Neuroscience 10, 372–392 (2004).

18.
Fjell, A. M. & Walhovd, K. B. Structural brain changes in aging: courses, causes and cognitive consequences. Rev. Neurosci. 21, 187–221 (2010).

19.
Gunning-Dixon, F. M., Brickman, A. M., Cheng, J. C. & Alexopoulos, G. S. Aging of cerebral white matter: a review of MRI findings. Int. J. Geriatr. Psychiatry 24, 109–117 (2009).

20.
Callaghan, M. F. et al. Widespread age-related differences in the human brain microstructure revealed by quantitative magnetic resonance imaging. Neurobiol. Aging 35, 1862–1872 (2014).

21.
Yeatman, J. D., Wandell, B. A. & Mezer, A. A. Lifespan maturation and degeneration of human brain white matter. Nat. Commun. 5, 4932 (2014).

22.
Cox, S. R. et al. Ageing and brain white matter structure in 3,513 UK Biobank participants. Nat. Commun. 7, 13629 (2016).

23.
Lorio, S. et al. Disentangling in vivo the effects of iron content and atrophy on the ageing human brain. Neuroimage 103, 280–289 (2014).

24.
Gracien, R.-M. et al. Evaluation of brain ageing: a quantitative longitudinal MRI study over 7 years. Eur. Radiol. 27, 1568–1576 (2017).

25.
Draganski, B. et al. Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ). Neuroimage 55, 1423–1434 (2011).

26.
Tardif, C. L. et al. Investigation of the confounding effects of vasculature and metabolism on computational anatomy studies. Neuroimage 149, 233–243 (2017).

27.
Carey, D. et al. Quantitative MRI provides markers of intra-, inter-regional, and age-related differences in young adult cortical microstructure. Neuroimage 182, 429–440 (2017).

28.
Cercignani, M., Dowell, N. G. & Tofts, P. S. Quantitative MRI of the Brain: Principles of Physical Measurement. (CRC Press, United States, 2018).

29.
Basser, P. J. & Pierpaoli, C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J. Magn. Reson. Ser. B 111, 209–219 (1996).

30.
Weiskopf, N., Mohammadi, S., Lutti, A. & Callaghan, M. F. Advances in MRI-based computational neuroanatomy. Curr. Opin. Neurol. 28, 313–322 (2015).

31.
Winklewski, P. J. et al. Understanding the physiopathology behind axial and radial diffusivity changes—what do we know? Front. Neurol. 9, 92 (2018).

32.
Heath, F., Hurley, S. A., Johansen-Berg, H. & Sampaio-Baptista, C. Advances in noninvasive myelin imaging. Dev. Neurobiol. 78, 136–151 (2018).

33.
Lutti, A., Dick, F., Sereno, M. I. & Weiskopf, N. Using high-resolution quantitative mapping of R1 as an index of cortical myelination. Neuroimage 93, 176–188 (2014).

34.
Filo, S. & Mezer, A. A. in Quantitative MRI of the Brain: Principles of Physical Measurement (eds Cercignani, M., Dowell, N. G. & Tofts, P. S.) 55–72 (CRC Press, United States, 2018).

35.
Fullerton, G. D., Cameron, I. L. & Ord, V. A. Frequency dependence of magnetic resonance spin-lattice relaxation of protons in biological materials. Radiology 151, 135–138 (1984).

36.
Does, M. D. Inferring brain tissue composition and microstructure via MR relaxometry. Neuroimage 182, 136–148 (2018).

37.
Helms, G., Dathe, H., Kallenberg, K. & Dechent, P. High-resolution maps of magnetization transfer with inherent correction for RF inhomogeneity and T 1 relaxation obtained from 3D FLASH MRI. Magn. Reson. Med. 60, 1396–1407 (2008).

38.
Rohrer, M., Bauer, H., Mintorovitch, J., Requardt, M. & Weinmann, H. -J. Comparison of magnetic properties of MRI contrast media solutions at different magnetic field strengths. Investig. Radiol. 40, 715–724 (2005).

39.
Mezer, A. et al. Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging. Nat. Med. 19, 1667–1672 (2013).

40.
Koenig, S. H. Cholesterol of myelin is the determinant of gray‐white contrast in MRI of brain. Magn. Reson. Med. 20, 285–291 (1991).

41.
Koenig, S. H., Brown, R. D., Spiller, M. & Lundbom, N. Relaxometry of brain: why white matter appears bright in MRI. Magn. Reson. Med. 14, 482–495 (1990).

42.
Kucharczyk, W., Macdonald, P. M., Stanisz, G. J. & Henkelman, R. M. Relaxivity and magnetization transfer of white matter lipids at MR imaging: importance of cerebrosides and pH. Radiology 192, 521–529 (1994).

43.
Fullerton, G. D., Potter, J. L. & Dornbluth, N. C. NMR relaxation of protons in tissues and other macromolecular water solutions. Magn. Reson. Imaging 1, 209–226 (1982).

44.
Morawski, M. et al. Developing 3D microscopy with CLARITY on human brain tissue: towards a tool for informing and validating MRI-based histology. Neuroimage 182, 417–428 (2018).

45.
Leuze, C. et al. The separate effects of lipids and proteins on brain MRI contrast revealed through tissue clearing. Neuroimage 156, 412–422 (2017).

46.
Ben-David, E. & Shifman, S. Networks of neuronal genes affected by common and rare variants in autism spectrum disorders. PLoS Genet. 8, e1002556 (2012).

47.
Zecca, L., Youdim, M. B. H., Riederer, P., Connor, J. R. & Crichton, R. R. Iron, brain ageing and neurodegenerative disorders. Nat. Rev. Neurosci. 5, 863–873 (2004).

48.
Langkammer, C. et al. Quantitative MR imaging of brain iron: a postmortem validation study. Radiology 257, 455–462 (2010).

49.
Freeman, S. H. et al. Preservation of neuronal number despite age-related cortical brain atrophy in elderly subjects without Alzheimer disease. J. Neuropathol. Exp. Neurol. 67, 1205–1212 (2008).

50.
Burke, S. N. & Barnes, C. A. Neural plasticity in the ageing brain. Nat. Rev. Neurosci. 7, 30–40 (2006).

51.
Bowley, M. P., Cabral, H., Rosene, D. L. & Peters, A. Age changes in myelinated nerve fibers of the cingulate bundle and corpus callosum in the rhesus monkey. J. Comp. Neurol. 518, 3046–3064 (2010).

52.
Callaghan, M. F., Helms, G., Lutti, A., Mohammadi, S. & Weiskopf, N. A general linear relaxometry model of R1 using imaging data. Magn. Reson. Med. 73, 1309–1314 (2015).

53.
Piomelli, D., Astarita, G. & Rapaka, R. A neuroscientist’s guide to lipidomics. Nat. Rev. Neurosci. 8, 743–754 (2007).

54.
Sethi, S., Hayashi, M. A., Sussulini, A., Tasic, L. & Brietzke, E. Analytical approaches for lipidomics and its potential applications in neuropsychiatric disorders. World J. Biol. Psychiatry 18, 506–520 (2017).

55.
Fantini, J. & Yahi, N. Brain Lipids in Synaptic Function and Neurological Disease: Clues to Innovative Therapeutic Strategies for Brain Disorders. (Academic Press, United States, 2015).

56.
Shinitzky, M. Patterns of lipid changes in membranes of the aged brain. Gerontology 33, 149–154 (1987).

57.
Martin, M., Dotti, C. G. & Ledesma, M. D. Brain cholesterol in normal and pathological aging. Biochim. Biophys. Acta-Mol. Cell Biol. Lipids 1801, 934–944 (2010).

58.
Calucci, L. & Forte, C. Proton longitudinal relaxation coupling in dynamically heterogeneous soft systems. Prog. Nucl. Magn. Reson. Spectrosc. 55, 296–323 (2009).

59.
Halle, B. Molecular theory of field-dependent proton spin-lattice relaxation in tissue. Magn. Reson. Med. 56, 60–72 (2006).

60.
West, M. J., Coleman, P. D., Flood, D. G. & Troncoso, J. C. Differences in the pattern of hippocampal neuronal loss in normal ageing and Alzheimer’s disease. Lancet (Lond., Engl.) 344, 769–772 (1994).

61.
West, M. J., Kawas, C. H., Stewart, W. F., Rudow, G. L. & Troncoso, J. C. Hippocampal neurons in pre-clinical Alzheimer’s disease. Neurobiol. Aging 25, 1205–1212 (2004).

62.
Slater, D. A. et al. Evolution of white matter tract microstructure across the life span. Hum. Brain Mapp. 40, 2252–2268 (2019).

63.
Jarmusch, A. K. et al. Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS. Proc. Natl Acad. Sci. U.S.A. 113, 1486–1491 (2016).

64.
Wenk, M. R. The emerging field of lipidomics. Nat. Rev. Drug Discov. 4, 594–610 (2005).

65.
Eberlin, L. S. et al. Classifying human brain tumors by lipid imaging with mass spectrometry. Cancer Res. 72, 645–654 (2012).

66.
Shtangel, O. & Mezer, A. A phantom system designed to assess the effects of membrane lipids on water proton relaxation. bioRxiv 387845 (2018). https://doi.org/10.1101/387845.

67.
Akbarzadeh, A. et al. Liposome: methods of preparation and applications. Liposome Technol. 6, 102 (2013).

68.
Ben-Eliezer, N., Sodickson, D. K. & Block, K. T. Rapid and accurate T 2 mapping from multi-spin-echo data using Bloch-simulation-based reconstruction. Magn. Reson. Med. 73, 809–817 (2015).

69.
Mezer, A., Rokem, A., Berman, S., Hastie, T. & Wandell, B. A. Evaluating quantitative proton-density-mapping methods. Hum. Brain Mapp. 37, 3623–3635 (2016).

70.
Avants, B. B., Tustison, N. & Song, G. Advanced normalization tools (ANTS). Insight J. (2009). http://hdl.handle.net/10380/3113

71.
Smith, S. M. et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage (2004). https://doi.org/10.1016/j.neuroimage.2004.07.051.

72.
Behrens, T. E. J. et al. Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn. Reson. Med. (2003). https://doi.org/10.1002/mrm.10609.

73.
Andersson, J. L. R., Skare, S. & Ashburner, J. How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. Neuroimage (2003). https://doi.org/10.1016/S1053-8119(03)00336-7.

74.
Andersson, J. L. R. & Sotiropoulos, S. N. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage (2016). https://doi.org/10.1016/j.neuroimage.2015.10.019.

75.
Weiskopf, N. et al. Quantitative multi-parameter mapping of R1, PD*, MT, and R2* at 3T: a multi-center validation. Front. Neurosci. (2013). https://doi.org/10.3389/fnins.2013.00095.

76.
Fischl, B. FreeSurfer. Neuroimage 62, 774–781 (2012).

77.
Patenaude, B., Smith, S. M., Kennedy, D. N. & Jenkinson, M. A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage (2011). https://doi.org/10.1016/j.neuroimage.2011.02.046.

78.
Shomonov-Wagner, L., Raz, A. & Leikin-Frenkel, A. Alpha linolenic acid in maternal diet halts the lipid disarray due to saturated fatty acids in the liver of mice offspring at weaning. Lipids Health Dis. (2015). https://doi.org/10.1186/s12944-015-0012-7.

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Acknowledgements

This work was supported by the ISF grant 0399306, awarded to A.A.M. We acknowledge Ady Zelman for the assistance in collecting the human MRI data. We thank Assaf Friedler for assigning research lab space and advising on the lipid sample experiments. We thank Inbal Goshen for assigning research lab space and advising on the protein and ion samples as well as the porcine brain experiments. We thank Magnus Soderberg for advising on histological data interpretation. We are grateful to Brian A. Wandell, Jason Yeatman, Hermona Soreq, Ami Citri, Mark Does, Yaniv Ziv, Ofer Yizhar, Shai Berman, Roey Schurr, Jonathan Bain, Asier Erramuzpe Aliaga, Menachem Gutman, and Esther Nachliel for their critical reading of the manuscript and very useful comments. We thank Prof. Alicia Leikin-Frenkel for her guidance with the TLC analysis. We thank Rona Shaharabani for guidance and support in the post-mortem experiments.

Affiliations

The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
Shir Filo, Oshrat Shtangel, Noga Salamon, Adi Kol, Batsheva Weisinger & Aviv A. Mezer
Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
Sagiv Shifman
Contributions
S.F., O.S., and A.A.M. conceived of the presented idea. S.F. and A.A.M. wrote the manuscript and designed the figures. S.F. collected the human and non-human brain datasets and analyzed them. O.S. performed the phantom experiments and analyzed them. B.W. performed the phantom experiments for non-lipid compounds. N.S. performed the gene-expression analysis. S.S. assisted and instructed with the gene-expression analysis. A.K. performed the porcine brain dissection.

Corresponding author

Correspondence to Aviv A. Mezer.

Ethics declarations & Competing interests

A.A.M, S.F., O.S. and the Hebrew University of Jerusalem have filed a patent application describing the technology used to measure MDM in this work. The other authors declare no competing interests.

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  • More than 77 percent of patients in the REMfresh® Patient Reported Outcomes DURation (REMDUR) study reported achieving 6 or more hours of sleep after taking REMfresh®, the first continuous release and absorption melatonin (CRA-melatonin)
  • More than 91 percent experienced improvements in sleep onset, sleep maintenance and total sleep quality, after taking REMfresh® (CRA-melatonin)
  • Post-marketing, patient-reported outcomes data reinforces clinical trial evidence demonstrating the potential of non-prescription REMfresh®, as a new, non-prescription, drug-free hypnotic (sleep) product designed to achieve 7-hour sleep
  • New data confirms previously presented SLEEP 2017 study showing the patented Ion Powered Pump (IPP) technology in REMfresh® helps extend melatonin-targeted sleep maintenance levels in the body from 3.7 hours (with marketed immediate-release melatonin) to 6.7 hours, while mimicking the pattern of the body’s natural melatonin blood levels during the nightly sleep cycle

Real Time Coverage at SLEEP 2018 meeting, Baltimore.

Reporters: Aviva Lev-Ari, PhD, RN, and Gail S. Thornton, MA

BALTIMORE – (June 6, 2018) – A patient-reported outcomes study presented at SLEEP 2018 provides confirmatory real-world evidence of the previously peer-reviewed and presented data showing the 7-hour action of REMfresh®, a new product for sleep. REMfresh® Ion-Powered Melatoninis the first and only, continuous release and absorption melatonin (CRA-melatonin) to mimic the body’s own 7-hour Mesa Wave, the natural pattern of melatonin blood levels during a normal night’s sleep cycle. This induces sleep onset and provides lasting and restorative sleep for up to 7 hours.

This new data shows a correlative relationship between a 7-hour Mesa Wave pharmacokinetic (PK) profile and real-world evidence of improvements in sleep duration, onset, maintenance and sleep quality after taking REMfresh® (CRA-melatonin).

The post-marketing REMfresh® Patient Reported Outcomes DURation (REMDUR) study was presented at SLEEP 2018, the 32nd Annual Meeting of the Associated Professional Sleep Societies (APSS), LLC, a joint partnership of the American Academy of Sleep Medicine (AASM) and the Sleep Research Society (SRS).

 

Brodner and Seiden

Pictured here is David C. Brodner, M.D., and David J. Seiden, M.D., FAASM, after presenting the latest study data which found REMfresh is the first and only continuous release and absorption melatonin™ to mimic the body’s own 7-hour Mesa Wave™.

 

In a sample of 500 patients on REMfresh® (CRA-melatonin) responding to an online survey, 77.6 percent achieved 6 or more hours of sleep compared to 23.6 percent who slept that duration prior to taking REMfresh® (p<.0001). A vast majority of respondents also reported a major or moderate improvement in sleep onset (91.6 percent, p<.0001), sleep maintenance (94.8 percent, p<.0001) and total sleep quality (97.2 percent, p<.0001). More than three-quarters (76.6 percent) of patients indicated they take REMfresh® (CRA-melatonin) nightly. The proportion of patients reporting nightly CRA-melatonin use was significantly greater than the proportion of patients with less than nightly use (p<.0001). Most importantly, over 98 percent of patients reported they were very likely or likely to continue taking REMfresh® (CRA-melatonin) to treat their sleep complaints.

“The real-world evidence reported today in REMDUR provides further confirmation that REMfresh® represents a significant advance in the use of melatonin as a baseline therapy for treating sleep complaints,” said David C. Brodner, M.D., a leading sleep specialist who is Double Board-Certified in Otolaryngology — Head and Neck Surgery and Sleep Medicine, founder and principle Physician at the Center for Sinus, Allergy, and Sleep Wellness, in Palm Beach County, Florida, and Senior Medical Advisor for Physician’s Seal, LLC®.

“REMfresh® Ion-Powered Melatoninhas been shown to be an effective drug-free solution that is now available to the millions of Americans in need of a good night’s sleep, many of whom seek new therapies that will induce sleep and keep them asleep until the morning, without causing residual effects they’ll feel the next day. With its unique delivery system that imitates the body’s own natural sleep pattern, REMfresh® has revolutionized the role of melatonin, when delivered in the CRA form. It is no longer just a treatment for jet lag, but the CRA-melatonin found in REMfresh® has been shown to provide substantial relief to individuals having nightly sleep challenges,” said Dr. Brodner.

The scientifically advanced, patented delivery system in REMfresh® (CRA-melatonin), called Ion Powered Pump (IPP™) technology, replicates the way in which the body naturally releases and absorbs melatonin, unlike conventional melatonin sleep products. Since REMfresh® is not a drug, there is no drug hangover.

Nearly one-third of U.S. adults sleep less than the recommended seven hours daily.[1],[2] Increasing evidence suggests an association between sub-optimal sleep duration and adverse health outcomes including a higher risk of diabetes, hypertension, heart attack, stroke, obesity and depression.[3] A pooled analysis of 16 studies and over one million patients found short sleep duration corresponded with greater risk of morbidity and mortality.[4]

 REMDUR Study Design

The post-marketing REMfresh® Patient Reported Outcomes DURation (REMDUR) study was designed to obtain real-world evidence about patients’ sleep patterns, duration of sleep before and after REMfresh® (CRA-melatonin), daily REMfresh® (CRA-melatonin) use, onset of action, sleep maintenance, quality of sleep, and overall satisfaction with REMfresh® (CRA-melatonin).

Patients with sleep disturbances in the general population who received a sample of CRA-melatonin (REMfresh®) from their physicians were invited to complete a 12-question survey. Survey responses were received from 500 patients.

Confirmation of the REMAKT Clinical Study

REMDUR confirmed clinical trial findings from REMAKT (REM Absorption Kinetics Trial), a U.S.-based randomized, crossover pharmacokinetic (PK) evaluation study in healthy, non-smoking adults that compared REMfresh® (CRA-melatonin) with a market-leading, immediate-release melatonin (IR-melatonin).[5]

The study results, peer-reviewed and presented last year at SLEEP 2017, showed that melatonin levels with REMfresh® (CRA-melatonin) exceeded the targeted sleep maintenance threshold for a median of 6.7 hours, compared with 3.7 hours with the leading IR-melatonin. Conversely, the levels of the market-leading IR-melatonin formulation dramatically increased 23 times greater than the targeted levels of exogenous melatonin for sleep maintenance and had a rapid decline in serum levels that did not allow melatonin levels to be maintained beyond 4 hours.

The REMfresh® (CRA-melatonin) studies build upon the body of evidence from prolonged-release melatonin (PR-M), marketed in Europe, which demonstrated in well-conducted, placebo-controlled studies, statistically significant improvement in sleep quality, morning alertness, sleep latency and quality of life in patients aged 55 years and older compared with placebo. REMfresh® (CRA-melatonin) was designed to overcome the challenges of absorption in the intestines, thereby extending the continual and gradual release pattern of melatonin through the night (known as the Mesa Wave, a flat-topped hill with steep sides). There was a fast time to Cmax, which is anticipated to result in improved sleep onset, while the extended median plateau time to 6.7 hours and rapid fall-off in plasma levels at the end of the Mesa Wave, may help to improve sleep maintenance and morning alertness.

Conventional melatonin products have had challenges at mimicking the profile of a Mesa Wave™. The scientific work behind REMfresh® (CRA-melatonin) sought to overcome these challenges by having the melatonin formulation in a matrix that maintains a patented, solubility-enhancing pH environment to help with the transport to the brush border of the gut and its subsequent absorption.

Designed as a hydrogel matrix tablet, REMfresh® (CRA-melatonin) provides rapid release of the melatonin from the surface of the tablet, as the hydrogel release-controlling matrix is setting up in the acidic environment (pH of 1 to 3.5) in the stomach. As the tablet moves into the higher pH (5.5 to 6.5) environment of the small-intestine, which is above the pKa of melatonin (~4.0), the acidic moiety in the tablet is designed to maintain the pH within the tablet below 4.0 for 7+ hours. The hydrogel matrix, after proper hydration, allows continuous release of the active melatonin and acidic moiety into the lumen of the intestines.

Melatonin: The Body’s Natural Sleep Ingredient

Melatonin is produced by the pineal gland in the brain and is the body’s natural sleep ingredient. Melatonin levels normally begin to rise in the mid-to late evening and remain high for the majority of the night. Levels begin to decline towards early morning, as the body’s wake cycle is triggered. As people age, melatonin levels can drop by as much as 70 percent[6] and their bodies may no longer produce enough melatonin to ensure adequate sleep.

Other available products, such as immediate-release melatonin, help initiate the onset of sleep but are usually unable to sustain prolonged sleep maintenance due to an immediate burst of melatonin, which is quickly degraded due to its relatively short half-life (60 minutes). Absorption in the lower digestive tract is limited by melatonin’s limited ability to be absorbed in a low acidity or neutral pH environment.

Importance of Sleep

Sleep is an essential part of every person’s life. The body requires a certain amount of sleep in order to properly rest, repair and renew itself. Sleep is customarily divided in four different stages, with each stage having a different effect. These four stages are:

N1, N2, deep sleep and REM sleep. The body moves among these four stages several times while asleep. If sleep is disrupted for any reason, a person’s body may not have a chance to properly restore itself, especially if it is struggling to get to the later stages, called deep sleep and REM sleep. Studies have shown that sound and sufficient sleep is important for learning, memory and a healthy immune system. A regular pattern of deep sleep and REM sleep will help a person begin the next day feeling refreshed and ready to go.

About Non-Prescription REMfresh®

REMfresh® (CRA-melatonin) is the first and only, continuous release and absorption formulation of UltraMel® melatonin (available as 2 mg and 5 mg and with a 0.5 mg anticipated in the second half of 2018). UltraMel® melatonin is a high-quality, 99 percent ultra-pure melatonin sourced from Western Europe exclusively for Physician’s Seal®.

REMfresh® (CRA-melatonin) is a dietary supplement and is regulated under the Federal Dietary Supplement Health and Education Act, which does not require pre-approval. Melatonin has been in common use for over two decades and has a well-established profile of safe use by millions of people around the world. As with all supplements, individual results may vary.

REMfresh® (CRA-melatonin) is non-habit forming and does not contain narcotics, hypnotics, barbiturates, sedatives, antihistamines, alcohol or other harsh or additive chemicals. The usual adult recommended dose is 1-2 tablets 30-60 minutes before bedtime. Follow specific dosing instructions found on the back of the box for proper use of supplements.

REMfresh® (CRA-melatonin) is available at Walmart, Rite Aid and CVS/pharmacy. In 2017 REMfresh® was ranked as  the #1 recommended brand for sleep management by sleep doctors[7].

About Physician’s Seal®

Physician’s Seal® is the innovator of REMfresh®, the first and only continuous release and absorption, 99 percent ultra-pure melatonin (CRA-melatonin) that mimics the way the body naturally releases and maintains melatonin over a 7-hour period. Physician’s Seal®, founded in 2015, is a privately held company based in Boca Raton, Florida. It is committed to bringing cutting-edge life science applications to doctors and their patients. For more information, visit www.remfresh.com and connect with us on Facebook and You Tube.

Its sister subsidiary, IM HealthScience® (IMH) is the innovator of IBgard® and FDgard® for the dietary management of Irritable Bowel Syndrome (IBS) and Functional Dyspepsia (FD), respectively. In 2017, IMH added Fiber Choice®, a line of prebiotic fibers, to its product line via an acquisition. IMH® is a privately held company based in Boca Raton, Florida. It was founded in 2010 by a team of highly experienced pharmaceutical research and development and management executives. The company is dedicated to developing products to address overall health and wellness, including conditions with a high unmet medical need, such as digestive health. The IM HealthScience® advantage comes from developing products based on its patented, targeted-delivery technologies called Site Specific Targeting® (SST®). For more information, visit www.imhealthscience.com to learn about the company, or www.IBgard.com,  www.FDgard.com,and www.FiberChoice.com.

This information is for educational purposes only and is not meant to be a substitute for the advice of a physician or other health care professional. You should not use this information for diagnosing a health problem or disease. The company will strive to keep information current and consistent but may not be able to do so at any specific time. Generally, the most current information can be found on www.remfresh.com. Individual results may vary.

Data Presented at SLEEP 2018 Poster Session on Sleep Maintenance/Sleep Quality

Tuesday, June 5, 2018, 5-7pm

  • (Abstract 0419, Poster Board #104) Improvement in Sleep Maintenance and Sleep Quality with Ion Powered Pump Continuous Release and Absorption Melatonin: Results from a Self-Reported Patient Outcomes Study
    • David J. Seiden, M.D., FAASM, David C. Brodner, M.D., Syed M. Shah, Ph.D.

Visit Physician’s Seal® at booth 220 to learn more about REMfresh®.

The abstract is published in an online supplement of the journal, Sleep, which is available at http://www.sleepmeeting.org/docs/default-source/default-document-library/abstractbook2018.pdf?sfvrsn=2

[1] Ford, E.S., Cunningham, T.J., & Croft, J.B. (2015, May 1). Trends in Self-Reported Sleep Duration among US Adults from 1985 to 2012. Sleep, 38(5):829-832. doi: 10.5665/sleep.4684.

[2] Watson, N.F., Badr, M.S., Belenky, G., Bliwise, D.L., Buxton, G.M., Buysse, D.,…Tasali, E. (2015). Joint Consensus Statement of the American Academy of Sleep Medicine and Sleep Research Society on the Recommended Amount of Sleep for a Healthy Adult: Methodology and Discussion. Journal of Clinical Sleep Medicine, 11(8):931-952. doi:10.1176/appi.ajp.158.11.1856.

[3] Colten, H.R., & Altevogt, B.M. (Eds). (2006). Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem.  Institute of Medicine (US) Committee on Sleep Medicine and Research. Washington, DC: National Academies Press (US). doi: https://doi.org/10.17226/11617.

[4] Cappuccio, F.P., D’Elia, L., Strazzullo, P.,&  Miller, M.A. (2010). Sleep duration and all-cause mortality: a systematic review and meta-analysis of prospective studies. Sleep, 33(5):585-592

[5] For this clinical trial, the head-to-head comparison was with the 5 mg form; a 2 mg form of the comparator was not available.

[6] Zisapel, N. (2010). Melatonin and sleep. The Open Neuroendocrinology Journal, 3: 85-95.

[7] Among primary care physicians with a certification in sleep disorders who recommended a brand of modified-release melatonin. Quintiles IMS ProVoice July-September 2017 survey.

REFERENCE/SOURCE

Physician’s Seal® and REMfresh® (www.remfresh.com)

Dr. David C. Brodner, Center for Sinus, Allergy, and Sleep Wellness (http://www.brodnermd.com/sleep-hygiene.html)

Other related articles published in this Open Access Online Scientific Journal include the following:

2017

Ultra-Pure Melatonin Product Helps Maintain Sleep for Up to 7 Hours

https://pharmaceuticalintelligence.com/2017/06/11/ultra-pure-melatonin-product-helps-maintain-sleep-for-up-to-7-hours/

2016

Sleep Science

Genetic link to sleep and mood disorders

https://pharmaceuticalintelligence.com/2016/02/27/genetic-link-to-sleep-and-mood-disorders/

2015

Sleep quality, amyloid and cognitive decline

https://pharmaceuticalintelligence.com/2015/10/31/sleep-quality-amyloid-and-cognitive-decline/

2013

Day and Night Variation in Melatonin Level affects Plasma Membrane Redox System in Red Blood Cells

https://pharmaceuticalintelligence.com/2013/02/23/httpwww-ncbi-nlm-nih-govpubmed22561555/

 

Read Full Post »


Ultra-Pure Melatonin Product Helps Maintain Sleep for Up to 7 Hours

Curator: Gail S. Thornton, M.A.

Co-Editor: The VOICES of Patients, Hospital CEOs, HealthCare Providers, Caregivers and Families: Personal Experience with Critical Care and Invasive Medical Procedures

 

The role of melatonin is important in regulating natural sleep and wake cycles. Typically, melatonin levels decline with age, significantly decreasing after age 40. An estimated 50 to 70 million Americans are affected by sleep difficulties – a process regulated by melatonin — and long-term sleep deprivation has been associated with negative health consequences, including an increased risk of diabetes, hypertension, heart attack, stroke, obesity, and depression.

Clinical data from a new pharmacokinetic study suggests that REMfresh®, the first and only continuous release and absorption melatonin (CRA-melatonin), helps maintain sleep for up to 7 hours. REMfresh® contains 99 percent ultra-pure melatonin and is sourced in Western Europe, a factor that is significant and important to many sleep specialists.

Three research abstracts on the REMfresh® data were published in an online supplement in the journal, Sleep, and were presented recently at the 31st Annual Meeting of the Associated Professional Sleep Societies LLC (APSS).

REMfresh Photo

Image SOURCE: Photograph courtesy of Physician’s Seal®

How REMfresh® Works

REMfresh® (CRA-melatonin) mimics the body’s own 7-hour Mesa Wave™, a natural pattern of melatonin blood levels during a normal night’s sleep cycle.

The study demonstrated the continuous release and absorption of 99 percent ultra-pure melatonin in REMfresh® (CRA-melatonin) was designed to induce sleep onset and provide continuous, lasting restorative sleep over 7 hours.

The scientifically advanced, patented formulation, called Ion Powered Pump (IPP™) technology, replicates the way in which the body naturally releases and absorbs melatonin, unlike conventional melatonin sleep products.

Since REMfresh® (CRA-melatonin) is not a drug, there is no drug hangover.

REMfresh MesaCurveNew-1

Image SOURCE: Diagram courtesy of Physician’s Seal®

 

Data Based on Scientifically Advanced Delivery Technology

According to the primary study author, David C. Brodner, M.D., “These study results represent an unparalleled breakthrough in drug-free, sleep maintenance that physicians and patients have been waiting for in a sleep product.” Dr. Brodner is a sleep specialist who is double board-certified in Otolaryngology – Head and Neck Surgery and Sleep Medicine and is the founder and principle physician at the Center for Sinus, Allergy, and Sleep Wellness in Palm Beach County, Florida.

Dr. Brodner said, “Melatonin products have been used primarily as a chronobiotic to address sleep disorders, such as jet lag and shift work. The patented delivery system in REMfresh mimics the body’s own natural sleep pattern, so individuals may experience consistent, restorative sleep and have an improved quality of life with this drug-free product.”

Study Findings With REMAKT

The study findings are based on REMAKT™ (REM Absorption Kinetics Trial), a U.S.-based randomized, crossover pharmacokinetic (PK) evaluation study in healthy, non-smoking adults that compared REMfresh® (CRA-melatonin) with a market-leading, immediate-release melatonin (IR-melatonin).

The study found that melatonin levels with REMfresh® exceeded the targeted sleep maintenance threshold for a median of 6.7 hours, compared with 3.7 hours with the leading IR-melatonin. Conversely, the levels of the market-leading IR-melatonin formulation dramatically increased 23 times greater than the targeted levels of exogenous melatonin for sleep maintenance and had a rapid decline in serum levels that did not allow melatonin levels to be maintained beyond 4 hours.

Additional analysis presented showed that REMfresh® (CRA-melatonin) builds upon the body of evidence from prolonged-release melatonin (PR-M), which demonstrated in well-conducted, placebo-controlled studies, statistically significant improvement in sleep quality, morning alertness, sleep latency and quality of life in patients aged 55 years and older compared with placebo.

REMfresh® (CRA-melatonin) was designed to overcome the challenges of absorption in the intestines, thereby extending the continual and gradual release pattern of melatonin through the night (known as the Mesa Wave™, a flat-topped hill with steep sides). There was a faster time to Cmax, which is anticipated to result in improved sleep onset, while the extended median plateau time to 6.7 hours and rapid fall-off in plasma levels at the end of the Mesa Wave™ may help to improve sleep maintenance and morning alertness.

REFERENCE/SOURCE

Physician’s Seal® and REMfresh® (www.remfresh.com)

REMfresh® press release, June 5, 2017 (http://www.prnewswire.com/news-releases/scientifically-advanced-delivery-technology-in-sleep-management-debuts-at-sleep-2017-with-clinical-data-showing-remfresh-the-first-and-only-continuous-release-and-absorption-melatonin-helps-maintain-sleep-for-up-to-7-hours-300468218.html)

Dr. David C. Brodner, Center for Sinus, Allergy, and Sleep Wellness  (http://www.brodnermd.com/sleep-hygiene.html)

Other related articles published in this Open Access Online Scientific Journal include the following:

2017

Sleep Research Society announces 2017 award recipients including Thomas S. Kilduff, PhD, Director, Center for Neuroscience at SRI International in Menlo Park, California

https://pharmaceuticalintelligence.com/2017/04/28/sleep-research-society-announces-2017-award-recipients-including-thomas-s-kilduff-phd-director-center-for-neuroscience-at-sri-international-in-menlo-park-california/

2016

Sleep Science

Genetic link to sleep and mood disorders

https://pharmaceuticalintelligence.com/2016/02/27/genetic-link-to-sleep-and-mood-disorders/

2015

Sleep quality, amyloid and cognitive decline

https://pharmaceuticalintelligence.com/2015/10/31/sleep-quality-amyloid-and-cognitive-decline/

2013

Day and Night Variation in Melatonin Level affects Plasma Membrane Redox System in Red Blood Cells

https://pharmaceuticalintelligence.com/2013/02/23/httpwww-ncbi-nlm-nih-govpubmed22561555/

Read Full Post »


Swiss Paraplegic Centre, Nottwil, Switzerland – A World-Class Clinic for Spinal Cord Injuries

Author: Gail S. Thornton, M.A.

Co-Editor: The VOICES of Patients, Hospital CEOs, HealthCare Providers, Caregivers and Families: Personal Experience with Critical Care and Invasive Medical Procedures

 

The Swiss Paraplegic Centre (SPC, www.paraplegie.ch) in Nottwil, Switzerland, is a privately owned, leading acute care and specialist hospital employing more than 1,500 health professionals in 80 different occupations that focuses on world-class primary care and comprehensive rehabilitation of patients with spinal cord injuries. In addition to the SPC’s extensive range of medical and therapeutic care, treatment and services, the hospital offers advisory services, as well as research in the areas of paraplegia [paralysis of the legs and lower body, typically caused by spinal injury or disease], tetraplegia [also known as quadriplegia, paralysis caused by illness or injury that results in the partial or total loss of use of all four limbs and torso], prevention and related conditions. With 150 beds, the SPC provides modern facilities for rehabilitation and therapy, diagnostics, surgery, ongoing care, orthopedic technology, as well as social services and 24-hour emergency care.

In its 26-year history, the SPC has provided treatment and care to more than 20,000 in-patients. That number continues to grow exponentially due to the reputation of the SPC. In fact, the SPC’s staff performs their duties with effectiveness, expediency and cost-efficiency measures, requiring highly developed process-led medicine, centered around the needs of the patient.

The areas of medical specialty and centers of excellence include the Swiss Paraplegic Centre (SPC), the Swiss Spinal Column and Spinal Cord Centre (SWRZ), the Centre for Pain Medicine (ZSM) and the Swiss Olympic Medical Center (SOMC). These centers respectively offer patients cutting-edge medical treatment based on the most advanced research in areas covering treatment and rehabilitation cases of acute paraplegia, vertebral and spinal cord surgery, as well as services relating to pain management, sports medicine and preventive health checks.

Alongside the core focus on paraplegiology, the SPC is also equipped with the necessary medical facilities, allowing for the lifelong care of paraplegic patients. The SPC provides individually-tailored, comprehensive treatment in three phases (acute, reactivation and integration) using highly skilled staff and state-of-the-art equipment. The aim is always to re-establish a patient’s personal functionality, self-image and lifestyle to the fullest possible extent, with a holistic approach to treatment that includes mental, physical and psycho-social aspects, such as career, family and leisure activities.

Specialist services available at the SPC include amongst others orthopedics, neuro-urology, pain medicine, sports medicine, prevention, clinical research, emergency medicine, vehicle conversion and rehabilitation techniques. Medico-therapeutic treatments, such as physiotherapy, ergotherapy and training therapy are available, alongside advice and counseling services, such as professional reintegration.

The SPC is the largest of Switzerland’s four special hospitals for paraplegics and tetraplegics located in Nottwil/Lucerne, a town in central Switzerland on the shores of Lake Sempach. The other three facilities are in Basel, Sion and Zurich. Nowadays, the SPC consistently treats more than 60 percent of people with spinal cord injury in Switzerland and is fully occupied year-round. 

Image SOURCE: Photographs courtesy of Swiss Paraplegic Centre, Nottwil, Switzerland.  Interior and exterior photographs of the hospital.

 

Below is my interview with Hospital Director Dr. Med. Hans Peter Gmünder, M.D., which occurred in March, 2017.

 As a privately owned clinic with a specialty in the rehabilitation of patients with spinal cord injuries, how do you keep the spirit of research and innovation alive?

Dr. Med. (medicinae) Gmünder: The goal of the Swiss Paraplegic Foundation, an umbrella organization that encompasses the Swiss Paraplegic Centre, is to create a unique network of services for people with spinal cord injury, from primary care through to the end of their lives. Its aim is to provide comprehensive rehabilitation and to reintegrate those affected into family life, society and the working environment.

We want to maintain our pioneering and leading role in the fields of acute medicine, rehabilitation and lifelong assistance to people with spinal cord injuries. By providing a comprehensive network of services featuring solidarity, medical care, integration and lifelong assistance, as well as research all in one place, we are unique in Switzerland and in other countries around the world.

People with spinal cord injury rely upon our network of services, which are at their disposal throughout their lives. The challenge facing us is to continually adapt these services to reflect current research and treatment to comply with our mission of delivering high-quality services. The trust which has been placed in us obliges us to continue our success story.

We have our own research department, closely linked to the Swiss Paraplegic Centre, and dedicated employees who draw upon their wide-ranging professional networks to stay on top of the latest international research.

We have a few examples that we’d like to share with you.

  • In 2013, the World Health Organization (WHO) published its first international health report on the topic of spinal cord injury, “International Perspectives on Spinal Cord Injury.” It was developed in collaboration with Swiss Paraplegic Research in Nottwil and a team of international experts.
  • In the summer of 2014, the Swiss Paraplegic Centre became the first rehabilitation center in Switzerland to implement exoskeletons [external covering for the body that provides both support and protection] in the rehabilitation and training of patients with spinal cord injury. Our experiences are included in an international study, and will contribute to the development of useful mobility aids for people with spinal cord injuries.

At the end of October 2016, an estimated 9,000 visitors came to Nottwil for two days of celebrations to mark five anniversaries — the Swiss Paraplegic Foundation turned 40, the Swiss Paraplegics Association was 35, the Swiss Paraplegic Centre celebrated 25 years, Swiss Paraplegic Research reached 15 years, and it was the 80th birthday of the founder and honorary president, Dr. Med. Guido A. Zäch, M.D.

What draws patients to the Swiss Paraplegic Centre?

Dr. Gmünder: We support people with spinal cord injuries throughout their lives. It is the unique, holistic approach to acute medicine, rehabilitation and lifelong medical, professional and social assistance that draws patients from Switzerland and many other countries to our clinic in Nottwil.

For example, in cases where we have individuals involved in serious accidents, the comprehensive rehabilitation of a patient with spinal cord injury begins at the scene of the accident. The aim of comprehensive assistance follows in three stages – acute, reactivation and integration phase – through the appropriate, individual deployment of specialist personnel and instruments. We rescue the individual at the scene of the accident and provide the right acute therapy. What follows is an initial rehabilitation through specialists in diagnosis, surgery, therapy and care, and then comes lifelong support and care with the aid of specialists.

Following the disproportionately high percentage of people with tetraplegia admitted to the Centre for initial rehabilitation in 2014, our specialist clinic reported a higher proportion of people with paraplegia in 2015. Spinal cord injuries resulted from an accident in around half of all initial rehabilitation cases: falls led to the spinal cord injury in the case of 43 percent of people affected, sports accidents with 35 percent and road traffic accidents in 18 percent. In fact, 52,482 nursing days were clocked for a total of 1,085 in-patients who were discharged from the clinic after initial rehabilitation or follow-up treatment in 2015.

In fact, some of our patient success stories mentioned on our web site involve these individuals:

“I was a cheesemaker for 33 years with my own dairy; gardening was my second love. That was before I had my accident helping out on my son’s farm. I need a new hobby now that I will enjoy, that will fill my time and give me something to do when I get back home. Making art out of lime wood could appeal to me. While it is difficult for me to make the small cuts in the wood as I lack strength in my hand, patience will reap rewards. My most important objective? To be able to stand on my own feet and take a few steps again. I should have achieved that by the time I am discharged from the clinic in five months.” — Josef Kobler (58), tetraplegic following an accident.

“Since being diagnosed with a spinal cord injury, I come back to Nottwil a lot. For instance, to go the Wheelchair Mechanics Department to have the settings of my new wheelchair optimized. It replaces my legs and must fit my body perfectly. However, in most cases I attend the Centre for Pain Medicine of the SPC as an outpatient in order to have the extremely severe pains and muscle cramps, which I suffer from every day, alleviated. They became so severe that I had a pain pump with medication implanted at the SPC. It is apparent now that unfortunately the effect isn’t permanent. We are now giving electrostimulation a try. This involves applying electrodes to the vertebral canal. If I could finally get my pain under control, I would be able to return to work and set up my own business. That is my biggest wish. I have had an idea about what I could do.” — Hervé Brohon (41), paraplegic following an accident.

“I have always been passionate about cooking and have enjoyed treating my family and guests to my dishes and to the aperitifs that I have created myself. I absolutely want to be able to do that again. As independently as possible, of course. That is my objective. I have availed of the opportunity on a few occasions to try out the obstacle-free practice apartment and kitchen at the SPC. If I am able to go home in four weeks, my kitchen will also be adapted to be wheelchair-friendly. Whether I am cooking for two, four or six people is a much bigger consideration as a wheelchair user. I now have to consciously allow for time and effort. However, one thing is certain: I can’t wait to welcome my first guests.” — Isa Bapst (73), paraplegic following an accident.

How is the Swiss Paraplegic Centre transforming health care?

Dr. Gmünder: The Swiss Paraplegic Centre offers an integrated healthcare structure, including a wide range of medical specialists covering every aspect of medical care for those with spinal cord injuries.

In selected core disciplines for the care of people with spinal cord injuries, we also treat a large number of patients without spinal cord injuries. This relates primarily to pain medicine, spine- and spinal cord surgery and respiratory medicine.

In fact, the Swiss Paraplegic Foundation, our umbrella organization, has been an unbelievable success story, operating a network of services to benefit people with spinal cord injury.

Our Chairman of the Board of Trustees, Dr. Sc. Techn. (scientiae technicarum) Daniel Joggi, knows what it’s like to become totally dependent as he has been in a wheelchair for the past four decades.

Dr. Joggi tells his story: “I have been a wheelchair user ever since I had a skiing accident 39 years ago. I know what it is like to become totally dependent from one second to the next. How doggedly you have to battle to recover as much of your mobility as possible and, more especially, to be able to live a self-determined life again after a long process of resilience. The inner resolve it takes to plot a new course in life, to have relationships with others from a different perspective and to acquire new job skills. Therefore, I am eternally grateful along with all the other people in Switzerland with paraplegia and tetraplegia for the help, support and great solidarity that allow the Foundation to deliver all the services which are so immensely valuable to us.”

At the Swiss Paraplegic Centre, a 24-hour emergency department is staffed to handle any emergency. Please provide your thoughts on this critical component of diagnosis and care for newly diagnosed patients.

Dr. Gmünder: Yes, our Centre is recognized by the Swiss Union of Surgical Societies as a specialist clinic for first-aid treatment of paraplegics.

Statistics and experience clearly show that in 80 out of 100 cases, the damage to the spine and the spinal cord is not definite immediately after an accident. In the first six hours, there are real chances to mitigate or even avoid an imminent cross-paralysis. After that it is usually too late.

In addition to transferring an individual directly to the SPC, appropriate acute care is another important criterion for the success of the individual affected by spinal cord issues. That means that individuals are in the right place for the subsequent, comprehensive rehabilitation.

The benefits for our patients are:

  • Emergency service around the clock by specialists trained to minimize damage to the spinal cord and spine;
  • Admission and treatment of all patients with paraplegia from all over Switzerland;
  • Specific knowledge and practical experience in comprehensive rehabilitation of paraplegics;
  • Comprehensive range of medical and therapeutic services under one roof;
  • Modern equipment for precise, careful diagnostics and operations;
  • Consultancy and network for external experts in areas not covered by the SPC;
  • Interdisciplinary work in well-established teams; and
  • Central location proximity and quick access from all parts of the country.

What is your connection to the Swiss Paraplegic Research and its mission of getting “strategy into research” and “research into practice?”

Dr. Gmünder: The Swiss Paraplegic Research (SPR), connected to the Swiss Paraplegic Centre, is part of the Swiss Paraplegic Foundation (SPF) and is an integral part of the Nottwil campus.

It is the mission of Swiss Paraplegic Research to sustainably improve the situation of people with paraplegia or tetraplegia through clinical and interdisciplinary research in the long-term. The areas that are aimed to be improved are functioning, social integration, equality of opportunity, health, self-determination and quality of life.

Our Swiss Paraplegic Research has been supported by the Federal Government of Switzerland and by the Canton of Lucerne for eight years as a non-university research institution. We are proud of this accomplishment.

Our main research domains are in the areas of aging, neuro-rehabilitation, musculo-skeletal health, preserving and improving function of upper limbs, pain, pressure sores, respiration, urology and orthopedics.

The goal of Swiss Paraplegic Research is to promote the study of health from a holistic point of view, by focusing on the ‘lived experience’ of persons with health conditions and their interaction with society. We are, therefore, establishing a research network for rehabilitation research from a comprehensive perspective on a national and international level. This network will make it possible to practically apply the latest research findings to provide the best possible care and reintegration for people with paraplegia or tetraplegia.

This year, we received the approval of 18 new research projects and we had a total of 36 studies in progress under review, undertaken by and with the involvement of the Clinical Trial Unit (CTU), the department for clinical research at the Centre. For example, the successful implementation of a multi-center study on the use of walking robots (exoskeleton) merits special mention. Research was carried out in that study into the wide range of effects of maintaining movement for people with spinal cord injury.

The CTU will continue to carry out research in Rehabilitation Engineering in a cooperation with Burgdorf University of Applied Science and the research group headed by Professor Kenneth Hunt. The “Life and Care” symposium on breathing and respiration organized by the CTU provided a platform for an international knowledge exchange with national and international experts. This is crucial for further scientific development in respiratory medicine. In 2015, the CTU also launched the CTU Central Switzerland, in association with Lucerne Cantonal Hospital and the University of Lucerne. It supports clinics which are actively engaged in research with specific services, thereby enhancing Switzerland’s standing as a center of research.

How does the Swiss Paraplegic Foundation support your vision?

Dr. Gmünder: The Swiss Paraplegic Group includes the Swiss Paraplegic Foundation, which was established in 1975, two partner organizations — the Benefactors’ Association and the Swiss Paraplegics Association, and six companies owned by the Foundation. Those six companies are the Swiss Paraplegic Centre, the Swiss Paraplegic Research, Orthotec AG, ParaHelp AG, Sirmed Swiss Institute of Emergency Medicine AG, Seminarhotel Sempachersee AG.

The Swiss Paraplegic Foundation, founded by Dr. Med. Guido A. Zäch in 1975, is a solidarity network for people with spinal cord injuries, unrivaled anywhere in the world. Its work is based on the vision of medical care and comprehensive rehabilitation for people with paraplegia and tetraplegia, with a view towards enabling them to lead their lives with self-determination and with as much independence as possible, supported by the latest advances in science and technology.

The unique network of services of the Foundation is a strategic mix of Solidarity, Research, Medicine and Integration and Lifelong Assistance. Let me elaborate on these services.

  • Solidarity
    • The Foundation provides a comprehensive range of services for every area of a person’s life who has a spinal cord injury. The Nottwil campus serves to be a center of excellence for integration, assistance and lifelong learning for our patients.
    • The Foundation ensures that its benefactors and donors are aware of our list of services and can support us longer term.
    • The Foundation establishes a national and international network that will guarantee better basic conditions for people with spinal cord injury.
    • The Foundation encourages training of specialized personnel in the field of spinal cord injury.
  • Research
    • The Foundation contributes to the sustainable improvement of health, social integration, equal opportunities and self-determination of people with spinal cord injury by carrying out rehabilitation research.
    • The Foundation works closely with the World Health Organization (WHO) and encourages exchanges with universities and institutions locally and globally for the latest scientific findings and conducts academic training at the University of Lucerne.
    • The Foundation develops high-quality care standards for its patients.
  • Medicine
    • The Foundation offers all medical services needed for professional acute care and rehabilitation of people with spinal cord injury and encourages patients to become involved in their therapy and to take responsibility for their lives.
    • The Foundation strengthens relationships with partners in specific disciplines and local institutions to benefit people with spinal cord injury.
    • The Foundation is a member of committees with political influence to ensure that its patients receive highly specialized medical care.
  • Integration and Lifelong Assistance
    • The Foundation establishes a network throughout Switzerland to help people with spinal cord injury.
    • The Foundation offers comprehensive services to meet people’s needs to improve their integration into society.
    • The Foundation encourages people with spinal cord injury to lead an independent life and educate family and friends so they can provide the necessary support.

Moreover, in cases of hardship, the Foundation makes contributions towards the cost of walking aids, equipment and amenities for people with paraplegia and tetraplegia. It also takes on uncovered hospital and care costs.

 Current market research shows that the Swiss Paraplegic Foundation ranks among the three most highly rated aid organizations in Switzerland. Can you please elaborate on why?

Dr. Gmünder: That is true. The Foundation is highly rated in terms of goodwill, innovation, competence and effectiveness. In addition, it is regarded as undoubtedly the most competent organization representing people with disabilities in Switzerland, according to several market research surveys.

So that we can continue to meet the demand for our patients, families and other visitors, plans are under way to upgrade our clinic and hotel on our premises.

We generally have interest from visitors to visit our Centre. Our guided tours and events enabled the general public to see how the foundation concept is put into practice, day in, day out. In Nottwil, 160 guides provided more than 11,000 visitors with a glimpse into the operations at our specialist clinic.

Additionally, we organized more than 5,000 scientific meetings attended by more than 170,000 people in 2015. And our wheelchair athletes take part in two major competitions, the IPC Athletics Grand Prix and the UCI Para-cycling World Championships, at our Nottwil site. It is our hope to continue to motivate individuals with spinal cord injuries to be involved in healthy exercise.

Since you became Hospital Director, how have you changed the way that you deliver health care or interact with patients?

Dr. Gmünder: It is important to me that the patients and their needs are the focus of our efforts. As such, one of my main tasks is to align our processes with our patients.

Here are some examples:

We started construction with a newly expanded Intensive Care Medicine, Pain Medicine and Surgical Medicine department last year to provide patients with an expanded variety of cross-linked treatments.

Certified as a nationwide trauma center, our Swiss Spinal Column and Spinal Cord Centre has become increasingly recognized throughout the country with large numbers of non-paralyzed patients, who have severe spinal cord injury, being referred to our facility. It is under the medical leadership of the Head of Department Dr. Med. Martin Baur, M.D. This highly specialized acute care facility recently received certification as a specialist center for traumatology within the Central Swiss Trauma Network.

We believe in developing the next generation of professionals and our Department of Anesthesia was recognized as a center of further training; the first two junior doctors have been appointed and postgraduate courses in anesthesia nursing are already available.

Our Swiss Weaning Centre, where individuals learn to breathe without a machine, has brought specialists from Intensive Care Medicine, Speech Therapy, RespiCare and Spinal Cord Medicine even closer together in a new process structure for respiratory medicine. At the same time, the Swiss Weaning Centre reported increased referrals from university hospitals and private clinics, as well as numerous successes with patients who had proved to be difficult to wean from respiratory equipment.

Our Centre for Pain Medicine, one of the largest pain facilities in the country, reported a further increase in inpatient treatments. Epiduroscopy, which was introduced in 2014, has proved to be a success. It is a percutaneous, minimally invasive procedure which is used in the diagnosis and treatment of pain syndromes near the spinal cord.

We reached a milestone in tetra hand surgery. The team of our doctors has been consulting at two other spinal cord injury centers and have used these occasions to show doctors around the country what possibilities there are for improved hand and grip functions, leading to an enhanced quality of life.

In what ways do you rehabilitate the whole patient? Why is this important early on in treatment?

Dr. Gmünder: In accordance with our vision, we are not just focusing on physical rehabilitation but on the entire person in their social environment (leisure, work, housing, mobility). Due to our broad organizational structure, we have many resources at our disposal. The rate of reintegration for people who did their primary rehabilitation at the Swiss Paraplegic Centre is almost 65 percent – one of the highest in the world.

Because we work to address diagnosis, treatment and management of traumatic spinal cord injuries with our patients, we take great care in working with patients on their medical disabilities, physical disabilities, psychological disabilities, vocational disabilities, social aspects and any health complications. That means that we not only treat patient’s medically, but also we treat them through therapy and complementary medicine, such as art therapy, sports and water therapy and homeopathic medicine.

At the SPC, we nurture a culture which is characterized by common values and shared objectives, namely commitment, leadership, a humane approach, cooperation and openness and fairness in our dealing with one another and with our patients.

As you follow patients throughout their rehabilitation and treatment, what are you most proud of at the Centre? 

Dr. Gmünder: Research has shown that early referral of a patient with a traumatic spinal injury lessens the complications, shortens the length of time in the hospital and is, therefore, more cost-effective.

We are confronted by individuals every day whose abilities have been limited by disease, trauma, congenital disorders or pain – and we are focused on enabling them to achieve their maximum functional abilities. Our patients have a better outcome and quality of life, patient-focused treatment, ongoing case management, and lifelong care.

It’s important to emphasize that our comprehensive rehabilitation of individuals with spinal cord injuries begins on the first day after the accident or trauma. On one hand, the medical treatments with paraplegia or tetraplegia are performed by a multidisciplinary medical team. And on the other hand, it is our goal to give those individuals their personality and life structure as quickly – and as best – as possible. An individual’s medical condition affects their psychological, physical and social aspects of life.

We focus on individualized treatment for the greatest possible independence for our patients. When patients are satisfied with our work and its results, they can resume a self-determined life. That is our greatest joy.

Hans Peter Gmuender

Image SOURCE: Photograph of Hospital Director Hans Peter Gmünder, M.D., courtesy of Swiss Paraplegic Centre, Nottwil, Switzerland.

Hans Peter Gmünder, M.D.
Hospital Director

Hans Peter Gmünder, M.D., assumed the role of Hospital Director of the Swiss Paraplegic Centre in 2011.  He is a German-Belgian double citizen.

Previously, Dr. Gmünder was Chief Physician and Medical Director of the Rehaklinik Bellikon, a rehabilitation and specialist clinic for traumatic acute rehabilitation, sports medicine, professional integration and medical expertise for 10 years in the canton of Aargau, Switzerland. He began his career at the Swiss Paraplegic Centre in the 1990s as Assistant and Senior Physician, and later as Chief Physician and Deputy Chief Physician.

He completed a B.S. degree in Business Administration at SRH FernHochschule Riedlingen in 2010 and an M.D. degree at Freie Universität Berlin in 1987.

He is married to Sabeth and is the father of two children.

 

Editor’s note:

We would like to thank Claudia Merkel, head of public relations, Swiss Paraplegic Centre,  for the help and support she provided during this interview.

 

REFERENCE/SOURCE

The Swiss Paraplegic Centre (http:// www.paraplegie.ch), Nottwil, Switzerland.

Choosing the right rehabilitation facility is one of the most important decisions a survivor of a brain or spinal cord injury will make as the type and quality of care will have a significant impact on the patient’s long-term outcome. The top 10 rehabilitation centers in the United States are (http://www.brainandspinalcord.org/2016/04/15/top-ten-rehabilitation-hospitals-usa/):

  1. Rehabilitation Institute of Chicago
  2. TIRR Memorial Hermann
  3. Kessler Institute for Rehabilitation
  4. University of Washington Medical Center
  5. Spaulding Rehabilitation Hospital, Massachusetts General Hospital
  6. Mayo Clinic
  7. Craig Hospital
  8. Shepard Center
  9. Rusk Rehabilitation at NYU Langone Medical Center
  10. Moss Rehab

The Rehabilitation Institute of Chicago (https://www.sralab.org/new-ric), located in Chicago, Illinois, has been ranked as the number one rehabilitation hospital in the United States for the past 24 years by U.S. News and World Report. It is a 182-bed research facility that focuses solely on rehabilitation in many areas, including spinal cord, brain, nerve, muscle and bone, cancer and pediatric. For example, the rehabilitation course for patients with spinal cord injury requires precise medical and nursing expertise, respiratory and pulmonary care and sophisticated diagnostic and therapeutic equipment. For several years, the hospital has dedicated investments in talent, space and equipment that attract a high volume of patients with challenging conditions. The high volume, diversity of condition and greater complexity enables them to expand their experience in helping patients recover from spinal cord injury. Primary goals for patients include the emergence of meaningful motor function, sensation, coordination and endurance, resolution of respiratory and vascular instability, and overall continued medical recovery from the injury or disease.

The Spaulding Rehabilitation Hospital Boston (http://spauldingrehab.org/about/facts-statistics) is ranked number five in the country by U.S. News and World Report and number one in New England.  As a unique center of treatment excellence and a leading physical medicine and rehabilitation research institution, Spaulding Boston is comprised of major departments in all areas of medicine requiring rehabilitation. They are a nationally recognized leader in innovation, research and education.  The facility also has been the source of significant treatment innovations with dramatic implications for a range of conditions, including amputation and limb deficiencies, brain injury, cardiac rehabilitation, pulmonary rehabilitation and spinal cord injuries, to name a few. http://spauldingrehab.org/conditions-and-treatments/list.

Whether individuals are adjusting to a life-altering illness or recovering from a back injury, they will find the care they need within the Spaulding Rehabilitation Network.  Rehabilitation specialists have the training, experience, resources and dedication to help individuals:

  • Regain function after a devastating illness or injury,
  • Develop skills to be active and independent when living with chronic illness and/or disability,
  • Recover from surgery, work and sports injuries, and
  • Grow to the fullest physical, emotional, cognitive and social potential. http://spauldingrehab.org/conditions-and-treatments/

The ACGME accredited Harvard Medical School/ Spaulding/ VA Boston Fellowship Program in  Spinal Cord Injury (SCI) Medicine is a 12-month training program that offers advanced clinical training in SCI, a strong didactic component, and opportunities for research with protected elective time.  The curriculum is designed to provide exposure to the full spectrum of SCI care and includes rotations at VA Boston, Spaulding Rehabilitation Hospital, and Brigham & Woman’s Hospital. Requirements include prior completion of an approved residency program in a specialty such as physical medicine and rehabilitation, neurology, internal medicine, family practice, surgery, or other specialties relevant to spinal cord injury.  http://spauldingrehab.org/education-and-training/spinal-cord-fellowship.

Specifically, the Spaulding Rehabilitation Network is at the forefront of innovative treatment for major disabling conditions, including spinal cord injury (SCI), traumatic brain injury (TBI), other traumatic injuries, stroke, and neuromuscular disorders such as multiple sclerosis, cerebral palsy, and Parkinson’s disease. At Spaulding, the treatment goals go far beyond immediate rehabilitation to address long-term health and function, as well as giving patients encouragement and hope as they return to their lives in the community.

The hub of their spinal cord injury program is the Spaulding-Harvard Spinal Cord Injury Model Systems (SCIMS) Rehabilitation Program, led by experts at Spaulding Boston, a Center of Excellence in spinal cord injury rehabilitation. With the guidance of their  physicians and other rehabilitation specialists and access to some of the most advanced technologies available today, their patients have the resources to strive for their highest level of neurorecovery – and to develop successful, enriching strategies for independent living.

When potentially life-altering spinal cord injury occurs, the Spaulding Rehabilitation Network clinicians are dedicated to pioneering improved therapies that can make all the difference to a patient’s immediate and long-term recovery. Their goal is to support a patient’s return to an active, productive and fulfilling life.

Whether the spinal cord injury is due to traumatic injury or illness, their team of experts will develop a treatment plan in collaboration with the patient and family. Depending on the severity of the injury, their teams work on improving function in: walking, balance and mobility; speech, swallowing and breathing; thinking (cognition), behavior and safety; dressing, bathing and other activities of daily living; incontinence, bowel and bladder function.

Their commitment is to offer a full spectrum of rehabilitation services for adults and children with spinal cord injury:

  • Intensive, hospital-level rehabilitation with goal-directed therapy 3 – 5 hours a day, at least 5 days a week for inpatients.
  • Long-term care and rehabilitation for patients with complicating conditions.
  • Cutting-edge spinal cord injury technologies and therapeutic techniques.
  • Emphasis on family participation throughout the course of care. with an inpatient comprehensive training and education series.
  • Seamless transition to multi-disciplinary outpatient rehabilitation.
  • Coordination of care with Spaulding’s outpatient centers.
  • Vocational training, participation in research, support groups.

Spaulding Rehabilitation Network is the official teaching partner of the Harvard Medical School Department of Physical Medicine and Rehabilitation (PM&R). The Spaulding network’s facilities are members of Partners HealthCare, founded by Massachusetts General Hospital and Brigham and Women’s Hospital. The knowledge and expertise of this entire healthcare system is available to patients and caregivers. Their continuum of superb healthcare ensures that patients will find the care they need throughout their journey and the strength they need to live their life to the fullest.

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Other related articles were published in this Open Access Online Scientific Journal include the following:

2016

Use of Sensors, Data and Devices to improve Health, San Francisco, April 5-6, 2016: Wearable Tech + Digital Health Conferences

https://pharmaceuticalintelligence.com/2016/01/25/use-of-sensors-data-and-devices-to-improve-health-san-francisco-april-5-6-2016-wearable-tech-digital-health-conferences/

2015

New Spinal Cord Repair Strategy using 3D Cell Growth

https://pharmaceuticalintelligence.com/2015/10/31/new-spinal-cord-repair-strategy-using-3d-cell-growth/

Unsupervised, Mobile and Wireless Brain–Computer Interfaces on the Horizon

https://pharmaceuticalintelligence.com/2015/11/21/unsupervised-mobile-and-wireless-brain-computer-interfaces-on-the-horizon/

Diffuse optics detects spinal cord ischemia – Optics.org

https://pharmaceuticalintelligence.com/2015/05/07/diffuse-optics-detects-spinal-cord-ischemia-optics-org/

Essential for Rehabilitation

https://pharmaceuticalintelligence.com/2015/12/03/essential-for-rehabilitation/

Read Full Post »


Medical 3D Printing and Metals in use in Medical Devices,
Presentation by Danut Dragoi, PhD

The main objective of medical 3D printing (M3DP) is to build solid / semi-solid / scaffolds / or gel structures from bio-compatible materials that can be utilized in medicine in order to correct, alleviate, support certain surgeries, or even cure some diseases based on medical / biological principles applied to human body.

Materials that replace bones are metals like Ti, Ti alloys, Tantalum, Gold, Silver, Zr and other. For replacement of teeth is traditionally used a combination of Ti-pivots and ceramic / polymers / or in some cases Hydroxylapatite (HA) coated Ti.

In order to produce a metallic object implantable in the human body, most useful technology is 3D printing of metals, commonly known as AT (addition manufacturing) technology. A definition of 3D printing is a process for making a physical object from a three-dimensional digital model, typically by laying down many successive thin layers of a material. If a printer system uses metal powders and binder instead of normal ink the printed layer by layer will develop a 3D object.

The printed object may be an orthopedic bone replacement, a tooth pivot or an artificial tooth. The picture on Slide 4 shows a Laser Sintering System (SLM) for Medical 3D Printing for metals, find specs in here.

Slide 4

Slide4

The machine shown on Slide 5 is one of the three metal printers from SLM Solutions using the technology of Selective Laser Melting, find specs in here,
Slide 5

Slide5
Feature highlight: for aerospace and medical orthopedics. Large build volume.
Material: Stainless steel, tool steel, aluminium, titanium, cobalt-chrome, inconel
Build capacity: 19.68 x 11.02 x 12.80 in. / (500 x 280 x 325 mm)
Build rate: 70 cm³/h
Resolution/Layer thickness: 20 – 200µm
Machine dimensions: 118 x 98 x 43 in.

An important aspect of metal source for M3DP is the shape of the particles, uniform size distribution and chemical purity. Using a new manufacturing approach, Zecotek, a company in Germany, link in here, developed metallic powders that can be successfully used in M3DP. Next Slide 6 shows some characteristics of this breakthrough technology.

Slide6
Slide 7

Slide7

More information on Slide 7 can be found in here.

Slide 8

Slide8

Information on Slide 8 can be found in here .
Slide 9

Slide9

Information on Slide 9 can be found in here, which is a novelty in terms of materials, the fusion for the first time between a Ti alloy and a ceramic.
Slide 10

Slide10The schematic on Slide 10 can be found in here . SLS technology is in wide use around the world due to its ability to easily make very complex geometries directly from digital CAD data. While it began as a way to build prototype parts early in the design cycle, it is increasingly being used in limited-run manufacturing to produce end-use parts. Here is how it is working. The powders are in a compartment controlled by a piston going one small step up, the roller swipes to the right a thin layer of metallic powder on the second compartment controlled by a piston that goes only one small step down, due to the fact that the printed model starts to grow up. The tip of the laser beam melts the powder or fusion the particles according with a real drawing section of the model. The process is repeated until the model is done. The key element of this technology is the laser scan device that follows exactly the drawing section of the model.

Slide 12

Slide12

Slide 12 shows a 3D printed foot that is light and well manageable for the patient. The picture can be found at this link in here. This prosthetic introduces the traces concept on light-weighting of replaceable parts for human body.
Slide 13

Slide13

Slide 13 shows a 3D printed light orthopedic pieces that are using the concept of light-weighting using traces. Their picture can be found here.

Slide 14

Slide14

Slide 14 shows tiny parts obtained with 3D printing technology, details in here.

Slide 15

Slide15

A second way to obtain solid parts is using a 3D Bioplotter, link in here .

EnvisionTec’s 3D-Bioplotter builds its products in much the same way as a traditional 3D printer. However, instead of using plastics, metals or resins, the Bioplotter uses biologic materials to form a scaffold that will be used to grow more advanced cellular cultures.

Just like a traditional 3D printer, the 3D-Bioplotter can be fed a 3D model generated in a CAD program or from a CT scan. Users can slice and hatch a 3D model to define how it will be printed. That information is then translated to code and shipped off to the Bioplotter where the real work begins.

While prototype objects in the mechanical, architectural and civil worlds can be built from a single material, in the biological world it’s rare that the desired objects have a uniform material. To meet that reality, the Bioplotter can print a model in 5 different materials making it suitable for more complex cellular assemblies.

This ability to jet different materials during a single build requires the 3D-Bioplotter to change print heads. It comes equipped with a CNC-like tool holder that can be programmed to change “print-heads” based on the material being extruded. Most bio-engineering builds favor porosity. This machine’s ability to change print heads can also help alter the flow and spacing of successive print layers to give users greater control of their models.

Slide 16

Slide16

The scaffold on slide 16 obtained with a 3D Bioploter, is useful in dentistry to augment the base of the future implantable tooth. The fixation in the picture is made of Vivos Dental’s OsteoFlux product, link see in here.
Slide 17

Slide17

Slide 17 Metals in medical dental implants, Ti becomes fused with the bone, and the tooth attached to one end of the Ti pivot, see link in here.

Slide 18

Slide18

Slide 18, Hot plasma spray bio-ceramics is the solution that doctors used for biocompatibility of an artificial jaws, link in here.

Slide 20

Slide20On slide 20 the traditional Ti casting is compared with Ti 3D printing from the powders. The advantage of 3D method is low cost and high productivity. This link in here is for traditional method, and this link here for 3D printing method.
Slide 21

Slide21Slide 21 For 3D Bioploter made by EnvisionTec we notice the usage of materials such as metal followed by post-processing sintering, Hydroxylapatite, TCP, Titanium. Using a preciptation method the machine can handle Chitosan, Collagen, 2-component system of the two possible combination: Alginate, Fibrin, PU, and Silicone. More details in here.

Slide 26

Slide26

Slide 26 shows two ultra-miniature medical pressure sensors in the eye of a needle, for details see the link in here.

Slide 27

Slide27

Slide 27 The electrodes of the bio-mems implanted on the surface of the heart are made of Gold for the electrical contact and good bio-compatibility. Classes of materials and assembly approaches that enable electronic devices with features – area coverage, mechanical properties, or geometrical forms – that would be impossible to achieve using traditional, wafer-based technologies. Examples include ’tissue-like’ bio-integrated electronics for high resolution mapping of electrophysiology in the heart and brain. The research on bio-integrated electronics can be found here.

Slide 28

Slide28

Slide 28 shows a polymeric material for determining pressure inside the eye, which is useful to monitor patients at risk from glaucoma. Again the circular electrode is made of Gold and its role is that of an antena to transmit data to a iPhone / receiver about the intraocula pressure data.
Slide 29

Slide29

The device in slide 29 is a bio-MEMS implantable for drug dosage. It has multiple micro-needles that are equivalent to a needle of a normal syringe, but painless since theyr tips do not reach the pain receptors. This picture taken from here, shows a side size of the MEMS of about 25 mm.

Slide 30

Slide30

Slide 30 lists some effects of metals in human body. Traces of heavy metals are dangerous for human body. Human body is made of light elements C,H,N,O. Heavy metals: Pb, Hg, accumulate in the body, they disrupt the metabolic processes since they are very toxic to humans. Therefore, heavy metals don’t have “+” physiological effects and Al as element is known to produce Alzheimer’s which has been implicated as a factor. According to the Alzheimer’s Society, the medical and scientific opinion is that studies have not convincingly demonstrated a causal relationship between aluminium and Alzheimer’s disease. Nevertheless, some studies, cite aluminium exposure as a risk factor for Alzheimer’s disease. Some brain plaques have been found to contain increased levels of the metal. Research in this area has been inconclusive; aluminium accumulation may be a consequence of the disease rather than a causal agent, see link in here.
Slide 31

Slide31

Slide 31 shows percent distribution of elements in human bodies, It is interesting that Ti is not making the list, see link in here.

Slide 32

Slide32

Slide 32 has Ti element circled on the Table of the elements, we notice that Zr as element was found to be a bio-compatible element too just like Ti. It is very possible from chemical point of view that all elements in Ti group have same property. The only inconvenient of elements bellow Ti is that they are heavier and their density should be adapted closer to that of human body.
Slide 33

Slide33

Slide 33 is a plot of stress (MPa) of some human implantable materials as a function of Young modulus E (GPa), their principal mechanical characteristic. There are crystalline materials such as: MgZnCa, MgZr, etc.) as well as amorphous materials bio-compatible such as: MgZnCa BMG, Ca based BMG, Sr based BMG, etc.) that have important mechanical strength that can be used in various applications. The circle in green centered on the point (75GPa, 650 MPa) is that for HydroxylApatite, which is a component of teeth and bones. Further details on this plot can be found at this link here,  .

Magnesium and its alloys are suitable materials for biomedical applications due to their low weight, high specific strength, stiffness close to bone and good biocompatibility. Specifically, because magnesium exhibits a fast biodegradability, it has attracted an increasing interest over the last years for its potential use as “biodegradable implants”. However, the main limitation is that Mg degrades too fast and that the corrosion process is accompanied by hydrogen evolution. In these conditions, magnesium implants lose their mechanical integrity before the bone heals and hydrogen gas accumulates inside the body. To overcome these limitations different methods have been pursued to decrease the corrosion rate of magnesium to acceptable levels, including the growth of coatings (conversion and deposited coatings), surface modification treatments (ion implantation, plasma surface modification, etc) or via the control of the composition and microstructure of Mg alloys themselves.

Slide 34

Slide34

Slide 34 shows two types of three point bending tests, one in which the flexural stress is plotted against displacement and second in which the stress intensity factor is plotted against the length of the crack extended beyond the notch. It is interesting that both plots can differentiate between young and aged bones. The plots can be downloaded from here,  where more experimental details and explanation can be found.

Slide 35

Slide35

Slide 35 shows the geometry for 3 point bending for fracture toughness testing. in which the stress intensity factor can be considered as a function of delta a, the depth of the notch at various values of loads. The equation of stress intensity factor can be found here.

Slide 36

Slide36

Slide 36 describes a family of stress-strain curves as function of composition for four Ti alloys. As we can see the mechanical strength of Ti alloys is well above 400 MPa, which is more than enough for replacement of bones that have a lower mechanical strength of about 175 MPa. The plot in this slide can be reviewed at this site.
Slide 37

Slide37

Slide 37 Mechanical strength of cortical bone, see link in here,  and mechanical strength of Ti alloys, seen in here.

The comparison shows a limit of elasticity of 160 MPa which is well below 400 MPa of Ti alloys or even simply Ti element which has a yield strength of 434 MPa, see link video here.
Slide 38

Slide38

Slide 38 provides information about the oxide layer on Ti binding biological tissues. Rutile and Anatase, are the two crystalline species of TiO2 formation on Ti surface. Rutile is less bio-reactive than Anatase, info in here, http://cdn.intechopen.com/pdfs-wm/33623.pdf . The metal work function changes as a consequence of the formation of the passivisation layer (the oxide), but ΔΦ is positive for rutile and negative for anatase, info in here, http://pubs.acs.org/doi/abs/10.1021/jp309827u?journalCode=jpccck .

Slide 39

Slide39

Slide 39 provides information about the crystal structures of three species of Titanium oxide: Rutile, Anatase, and Brookite. As seen from the slide, the density varies with the crystal structure. The valence of Ti in these structures is 4+, same as Carbon in many organic molecules.
Slide 40

Slide40

Slide 40 provides information about the crystal structures of Titanium monoxide. As seen from the slide, the density is the highest among all Titanium oxides. The crystal structure of Titanium monoxide is shown in this slide. The valence of Ti in these structure is 2+, that makes this oxide special in applications.
Slide 41

Slide41

Slide 41 provides information about two metals, Ti and Zr that are used in human body implantable. An explanation of why these two metals are bio-compatible is given in this slide. As we know not all metals are inert/not reactive in human body environment. As a fact bulk cubic structures of metals is less preferred such as Al, Cu, Nb, Pb, etc.. Based on a symmetry remark for living structures (carbohydrates, nucleic acids, lipids and proteins), the lower implantable metals symmetry the better. As an example Lysozyme (S.G. P43212, space group number 96) as a possible interface material with an implantable metal such as Au, Ti, Zr, admits lower space groups such as Ti ( P63/mmc. Space group number: 194). Gold is not preferred for multiple reasons too: it has a high symmetry S.G. 225 (Fm-3m) 96<225, it has has a high density 19.32 g/cc, and it is expensive.

Many metals have a degree of leachability in human body fluids except the rare/precious metals Au, Pt, Ir that are expensive as implants. The coatings of Ti with a tiny thin layer of oxide or laser coated organic ceramics, makes Ti as the best choice as human body implantable with extremely low leachability in human body fluids.
Slide 42

Slide42

Slide 42 provides crystallographic information on Ti crystal structure, unit cell size and directions.
Slide 43

Slide43

Slide 43 provides information on Zr metal as the second choice on human body implantables. The crystal structure of Zr is same as Ti, with hexagonal close packed (HCP) unit cell. The HCP cell is shown together with a body center cubic (BCC) unit and face close cubic (FCC) unit for comparison reason.
Slide 44

Slide44

Slide 44 shows the Table of major biomedical metals and alloys and their applications. More details about materials in the Table can be found here.

Slide 45

Slide45

The Table on Slide 45 shows a comparison of mechanical properties for three metal alloys. Notice the the increase of the ultimate tensile strength of Ti 64, from 434 MPa for Titanium (see slide 37) to 900 MPa for Ti 64. More data about other materials can be found here.

Slide 46

Slide46

Slide 46 lists some medical devices as they were created by the inventor Alfred Mann’s companies. Such devices are:
-rechargeable pacemaker,
-an implant for deaf people,
-an insulin pump and a
-prosthetic retina. (Mel Melcon, Los Angeles Times)
Slide 47

Slide47

Slide 47 As we imagine, the implanted devices should be coated with one of these Ti, Zr, ceramic coated Ti and Stainless Steel. Three example are given as: Ti-plates and rods, 3D printed Jaws + plasma coated HAp, Gold nano-wires.
Slide 48

Slide48

In the example on slide Slide 48, the pacemaker casing is made of titanium or a titanium alloy, electrodes are made of metal alloy insulated with polyurethan polymers, more info in here.

Slide 49

Slide49

The second device shown in slide 49 is an implant for deaf people, whose surface in contact with human body fluids is coated with Ti. More info on how this implant works can be found in here.
Slide 50Slide50The insulin pump shown in slide 50 is a schematic of the pump controlled electronically by a control algorithm device, a sensor, an electronic receiver that connects with an iPhone through an wireless channel.
Slide 51Slide51

The prosthetic retina on slide 51 is an example of a bio-MEMS based optical sensor that takes the outside image through a tiny camera, the electrical signal of the camera is sent to a receiver and then to an array of micro-electrodes tacked to the retina which send electrical impulses to the brain through the optical nerve. More details can be found in here.

Slide 52Slide52Slide 52 describes how easily available bio-compatible metal powders
can revolutionize 3D printing for medical implants. The surgical implants need to generate expected responses from neighboring cells and tissues. Cell behavior (adhesion, functional alteration, morphological changes, and proliferation) is strongly affected by the surgical implants’ surface properties. Surface topography, surface chemistry, and surface energy influence decisively the biological response to an implanted device.
The well controlled 3D printing atmosphere (neutral gases and restricted oxygen) guarantees the high purity of the 3D printed parts and preserves the materials’ properties.
The advantages of 3D printing for medical applications is thoroughly discussed in here.

Slide 53Slide53

Slide 53 shows five conclusions of the presentation, in which 1) many engineered metals are mechanically resistant in human body, but prone to certain corrosion if not coated,
2) Ti, Zr coated bio-ceramics are bio-compatible materials in human body, 3) medical devices implants and MEMS are useful as heart stent, orthopedic prosthetic, prosthetic retina, 3) M3DP has low costs, high quality, long life cycle and 4) Metal/bio-ceramic and Vivos dental’s synthetic bone for oral augmentation is a solution for today’s dental health care.
Slide 54Slide54Slide 54 shows conclusions regarding the hardware of the presentation, in which: 6) there are two types of metal 3D printing hardware for medical applications: Selective Laser Melting / Selective Laser Sintering, and 3D Bioploter (metal powder mixed with binder and further thermal treatment to remove binder and sinter the metallic matrix in a solid object that can be used as a replacement. Thank you for your attention!

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Novel Mechanisms of Resistance to Novel Agents

 

Curators: Larry H. Berstein, M.D. FACP & Stephen J. Williams, Ph.D.

For most of the history of chemotherapy drug development, predicting the possible mechanisms of drug resistance that ensued could be surmised from the drug’s pharmacologic mechanism of action. In other words, a tumor would develop resistance merely by altering the pathways/systems which the drug relied on for mechanism of action. For example, as elucidated in later chapters in this book, most cytotoxic chemotherapies like cisplatin and cyclophosphamide were developed to bind DNA and disrupt the cycling cell, thereby resulting in cell cycle arrest and eventually cell death or resulting in such a degree of genotoxicity which would result in great amount of DNA fragmentation. These DNA-damaging agents efficacy was shown to be reliant on their ability to form DNA adducts and lesions. Therefore increasing DNA repair could result in a tumor cell becoming resistant to these drugs. In addition, if drug concentration was merely decreased in these cells, by an enhanced drug efflux as seen with the ABC transporters, then there would be less drug available for these DNA adducts to be generated. A plethora of literature has been generated on this particular topic.

However in the era of chemotherapies developed against targets only expressed in tumor cells (such as Gleevec against the Bcr-Abl fusion protein in chronic myeloid leukemia), this paradigm had changed as clinical cases of resistance had rapidly developed soon after the advent of these compounds and new paradigms of resistance mechanisms were discovered.

speed of imitinib resistance

Imatinib resistance can be seen quickly after initiation of therapy

mellobcrablresistamplification

Speed of imatinib resistance a result of rapid gene amplification of BCR/ABL target, thereby decreasing imatinib efficacy

 

 

 

 

 

 

 

 

 

 

Although there are many other new mechanisms of resistance to personalized medicine agents (which are discussed later in the chapter) this post is a curation of cellular changes which are not commonly discussed in reviews of chemoresistance and separated in three main categories:

Cellular Diversity and Adaptation

Identifying Cancers and Resistance

Cancer Drug-Resistance Mechanism

p53 tumor drug resistance gene target

Variability of Gene Expression and Drug Resistance

 

Expression of microRNAs and alterations in RNA resulting in chemo-resistance

Drug-resistance Mechanism in Tumor Cells

Overexpression of miR-200c induces chemoresistance in esophageal cancers mediated through activation of the Akt signaling pathway

 

The miRNA–drug resistance connection: a new era of personalized medicine using noncoding RNA begins

 

Gene Duplication of Therapeutic Target

 

The advent of Gleevec (imatinib) had issued in a new era of chemotherapy, a personalized medicine approach by determining the and a lifesaver to chronic myeloid leukemia (CML) patients whose tumors displayed expression of the Bcr-Abl fusion gene. However it was not long before clinical resistance was seen to this therapy and, it was shown amplification of the drug target can lead to tumor outgrowth despite adequate drug exposure. le Coutre, Weisberg and Mahon23, 24, 25 all independently generated imatinib-resistant clones through serial passage of the cells in imatinib-containing media and demonstrated elevated Abl kinase activity due to a genetic amplification of the Bcr–Abl sequence. However, all of these samples were derived in vitro and may not represent a true mode of clinical resistance. Nevertheless, Gorre et al.26 obtained specimens, directly patients demonstrating imatinib resistance, and using fluorescence in situ hybridization analysis, genetic duplication of the Bcr–Abl gene was identified as one possible source of the resistance. Additional sporadic examples of amplification of the Bcr–Abl sequence have been clinically described, but the majority of patients presenting with either primary or secondary imatinib resistance fail to clinically demonstrate Abl amplification as a primary mode of treatment failure.

This is seen in the following papers:

Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification.Gorre ME, Mohammed M, Ellwood K, Hsu N, Paquette R, Rao PN, Sawyers CL. Science. 2001 Aug 3;293(5531):876-80. Epub 2001 Jun 21.

and in another original paper by le Coutre et. al.

Induction of resistance to the Abelson inhibitor STI571 in human leukemic cells through gene amplification. le Coutre P1, Tassi E, Varella-Garcia M, Barni R, Mologni L, Cabrita G, Marchesi E, Supino R, Gambacorti-Passerini C. Blood. 2000 Mar 1;95(5):1758-66

The 2-phenylaminopyrimidine derivative STI571 has been shown to selectively inhibit the tyrosine kinase domain of the oncogenic bcr/abl fusion protein. The activity of this inhibitor has been demonstrated so far both in vitro with bcr/abl expressing cells derived from leukemic patients, and in vivo on nude mice inoculated with bcr/abl positive cells. Yet, no information is available on whether leukemic cells can develop resistance to bcr/abl inhibition. The human bcr/abl expressing cell line LAMA84 was cultured with increasing concentrations of STI571. After approximately 6 months of culture, a new cell line was obtained and named LAMA84R. This newly selected cell line showed an IC50 for the STI571 (1.0 microM) 10-fold higher than the IC50 (0.1 microM) of the parental sensitive cell line. Treatment with STI571 was shown to increase both the early and late apoptotic fraction in LAMA84 but not in LAMA84R. The induction of apoptosis in LAMA84 was associated with the activation of caspase 3-like activity, which did not develop in the resistant LAMA84R cell line. LAMA84R cells showed increased levels of bcr/abl protein and mRNA when compared to LAMA84 cells. FISH analysis with BCR- and ABL-specific probes in LAMA84R cells revealed the presence of a marker chromosome containing approximately 13 to 14 copies of the BCR/ABL gene. Thus, overexpression of the Bcr/Abl protein mediated through gene amplification is associated with and probably determines resistance of human leukemic cells to STI571 in vitro. (Blood. 2000;95:1758-1766)

This is actually the opposite case with other personalized therapies like the EGFR inhibitor gefinitib where actually the AMPLIFICATION of the therapeutic target EGFR is correlated with better response to drug in

Molecular mechanisms of epidermal growth factor receptor (EGFR) activation and response to gefitinib and other EGFR-targeting drugs.Ono M, Kuwano M. Clin Cancer Res. 2006 Dec 15;12(24):7242-51. Review.

Abstract

The epidermal growth factor receptor (EGFR) family of receptor tyrosine kinases, including EGFR, HER2/erbB2, and HER3/erbB3, is an attractive target for antitumor strategies. Aberrant EGFR signaling is correlated with progression of various malignancies, and somatic tyrosine kinase domain mutations in the EGFR gene have been discovered in patients with non-small cell lung cancer responding to EGFR-targeting small molecular agents, such as gefitinib and erlotinib. EGFR overexpression is thought to be the principal mechanism of activation in various malignant tumors. Moreover, an increased EGFR copy number is associated with improved survival in non-small cell lung cancer patients, suggesting that increased expression of mutant and/or wild-type EGFR molecules could be molecular determinants of responses to gefitinib. However, as EGFR mutations and/or gene gains are not observed in all patients who respond partially to treatment, alternative mechanisms might confer sensitivity to EGFR-targeting agents. Preclinical studies showed that sensitivity to EGFR tyrosine kinase inhibitors depends on how closely cell survival and growth signalings are coupled with EGFR, and also with HER2 and HER3, in each cancer. This review also describes a possible association between EGFR phosphorylation and drug sensitivity in cancer cells, as well as discussing the antiangiogenic effect of gefitinib in association with EGFR activation and phosphatidylinositol 3-kinase/Akt activation in vascular endothelial cells.

 

Mutant Variants of Therapeutic Target

 

resistant subclones in tissue samples and Tyrosine Kinase tumor activity

 

Mitochondrial Isocitrate Dehydrogenase and Variants

Mutational Landscape of Rare Childhood Brain Cancer: Analysis of 60 Intercranial Germ Cell Tumor Cases using NGS, SNP and Expression Array Analysis – Signaling Pathways KIT/RAS are affected by mutations in IGCTs

 

AND seen with the ALK inhibitors as well (as seen in the following papers

Acquisition of cancer stem cell-like properties in non-small cell lung cancer with acquired resistance to afatinib.

Hashida S, Yamamoto H, Shien K, Miyoshi Y, Ohtsuka T, Suzawa K, Watanabe M, Maki Y, Soh J, Asano H, Tsukuda K, Miyoshi S, Toyooka S. Cancer Sci. 2015 Oct;106(10):1377-84. doi: 10.1111/cas.12749. Epub 2015 Sep 30.

In vivo imaging models of bone and brain metastases and pleural carcinomatosis with a novel human EML4-ALK lung cancer cell line.

Nanjo S, Nakagawa T, Takeuchi S, Kita K, Fukuda K, Nakada M, Uehara H, Nishihara H, Hara E, Uramoto H, Tanaka F, Yano S. Cancer Sci. 2015 Mar;106(3):244-52. doi: 10.1111/cas.12600. Epub 2015 Feb 17.

Identification of a novel HIP1-ALK fusion variant in Non-Small-Cell Lung Cancer (NSCLC) and discovery of ALK I1171 (I1171N/S) mutations in two ALK-rearranged NSCLC patients with resistance to Alectinib. Ou SH, Klempner SJ, Greenbowe JR, Azada M, Schrock AB, Ali SM, Ross JS, Stephens PJ, Miller VA.J Thorac Oncol. 2014 Dec;9(12):1821-5

Reports of chemoresistance due to variants have also been seen with the BRAF inhibitors like vemurafenib and dabrafenib:

The RAC1 P29S hotspot mutation in melanoma confers resistance to pharmacological inhibition of RAF.

Watson IR, Li L, Cabeceiras PK, Mahdavi M, Gutschner T, Genovese G, Wang G, Fang Z, Tepper JM, Stemke-Hale K, Tsai KY, Davies MA, Mills GB, Chin L.Cancer Res. 2014 Sep 1;74(17):4845-52. doi: 10.1158/0008-5472.CAN-14-1232-T. Epub 2014 Jul 23

 

 

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Huge advance in burn surgery

Curator: Larry H. Bernstein, MD, FCAP

 

 

26-Hour Face Transplant Made Possible with 3D Printing

By On Thu, Nov 19, 2015

One fateful night back in 2001, a former volunteer firefighter from Mississippi named Patrick Hardison bravely entered a burning home seeking to rescue anyone who might be stuck inside. When the burning house collapsed upon Hardison, he was left with critical injuries that completely disfigured his facial features, leaving him complete unrecognizable even to his own wife and children. This horrific accident forced Hardison onto the operating table over 70 times, where traditional surgical operations were only adding to the mental and physical strain he had been undergoing since the fire had left him disfigured.

 

3dprint)nyu_rodriguez_patrick_smaller

It wasn’t until Dr. Eduardo D. Rodriguez, a plastic surgeon at NYU’s Langone Medical Center, came up with a plan to give Hardison a full face transplant. The plan involved finding a ‘donor’ who matched in hair color, skin color, blood type, and who also has a similar skeletal structure to Hardinson. Once the selected donor was found, Rodriguez and his staff utilized 3D Systems’ Virtual Surgical Planning (VSP) technology, which allows for adequate surgical preparation by offering cutting guides over an actual 3D scan of the bone structure of both the patient and the donor.

 

VSP Technology

 

VSP Technology

VSP technology is able to create these surgical templates by using medical scan data, which are transformed into 3D models and, in some cases, are even 3D printed for a visual aid. 3D Systems’ Medical Modeling team actually assisted in the printing of these templates, using a biocompatible 3D printing material that is easily sterilized, and can, therefore, be safely utilized within the confines of an operating room.

 

 

3dprint)nyu_before_after

 

Using the careful surgical plan the Rodriguez and his team prepared on 3D Systems’ VSP technology, Hardinson received an extremely successful surgery and suddenly had all of the features of a human face again for the first time in years. Although the intensive surgery took Rodriguez and over 100 other individuals who assisted in the operation a whopping 26 hours to complete, the surgery would have likely been impossible to even plan without the preparation help offered by 3D Systems and their Virtual Surgical Planning technology. Now, thanks to Dr. Rodriguez, 3D Systems’ Medical Modeling team, and the rest of the NYU’s Langone Medical Center staff, Patrick Hardison can finally smile at the world, once again.

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