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Archive for the ‘Innovations in Neurophysiology & Neuropsychology’ Category

Developing Deep Learning Models (DL) for Classifying Emotions through Brainwaves

Reporter: Abhisar Anand, Research Assistant I
Research Team: Abhisar Anand, Srinivas Sriram

2021 LPBI Summer Internship in Data Science and Website construction.
This article reports on a research study conducted till December 2020.
Research completed before the 2021 LPBI Summer Internship began in 6/15/2021.

As the field of Artificial Intelligence progresses, various algorithms have been implemented by researchers to classify emotions from EEG signals. Few researchers from China and Singapore released a paper (“An Investigation of Deep Learning Models from EEG-Based Emotion Recognition”) analyzing different types of DL model architectures such as deep neural networks (DNN), convolutional neural networks (CNN), long short-term memory (LSTM), and a hybrid of CNN and LSTM (CNN-LSTM). The dataset used in this investigation was the DEAP Dataset which consisted of EEG signals of patients that watched 40 one-minute long music videos and then rated them in terms of the levels of arousal, valence, like/dislike, dominance and familiarity. The result of the investigation presented that CNN (90.12%) and CNN-LSTM (94.7%) models had the highest performance out of the batch of DL models. On the other hand, the DNN model had a very fast training speed but was not able to perform as accurately as other other models. The LSTM model was also not able to perform accurately and the training speed was much slower as it was difficult to achieve convergence.

This research in the various model architectures provides a sense of what the future of Emotion Classification with AI holds. These Deep Learning models can be implemented in a variety of different scenarios across the world, all to help with detecting emotions in scenarios where it may be difficult to do so. However, there needs to be more research implemented in the model training aspect to ensure the accuracy of the classification is top-notch. Along with that, newer and more reliable hardware can be implemented in society to provide an easy-to-access and portable EEG collection device that can be used in any different scenario across the world. Overall, although future improvements need to be implemented, the future of making sure that emotions are accurately detected in all people is starting to look a lot brighter thanks to the innovation of AI in the neuroscience field.

Emotions are a key factor in any person’s day to day life. Most of the time, we as humans can detect these emotions through physical cues such as movements, facial expressions, and tone of voice. However, in certain individuals, it can be hard to identify their emotions through their visible physical cues. Recent studies in the Machine Learning and AI field provide a particular development in the ability to detect emotions through brainwaves, more specifically EEG brainwaves. These researchers from across the world utilize the same concept of EEG implemented in AI to help predict the state an individual is in at any given moment.

Emotion classification based on brain wave: a survey (Figure 4)

Image Source: https://hcis-journal.springeropen.com/articles/10.1186/s13673-019-0201-x

EEGs can detect and compile normal and abnormal brain wave activity and indicate brain activity or inactivity that correlates with physical, emotional, and intellectual activities. EEG signals are classified mainly by brain wave frequencies. The most commonly studied are delta, theta, alpha, sigma, and beta waves. Alpha waves, 8 to 12 hertz, are the key wave that occurs in normal awake people. They are the defining factor for the everyday function of the adult brain. Beta waves, 13 to 30 hertz, are the most common type of wave in both children and adults. They are found in the frontal and central areas of the brain and occur at a certain frequency which, if slowed, is likely to cause dysfunction. Theta waves, 4 to 7 hertz, are also found in the front of the brain, but they slowly move backward as drowsiness increases and the brain enters the early stages of sleep. Theta waves are known as active during focal seizures. Delta waves, 0.5 to 4 hertz, are found in the frontal areas of the brain during deep sleep. Sigma waves, 12-16 hertz, are very slow frequency waves that occur during sleep. These EEG signals can help for the detection of emotions based on the frequencies that the signals happen in and the activity of the signals (whether they are active or relatively calm). 

Sources:

Zhang, Yaqing, et al. “An Investigation of Deep Learning Models for EEG-Based Emotion Recognition.” Frontiers in Neuroscience, vol. 14, 2020. Crossref, doi:10.3389/fnins.2020.622759.

Nayak, Anilkumar, Chetan, Arayamparambil. “EEG Normal Waveforms.” National Center for Biotechnology Information, StatPearls Publishing LLC., 4 May 2021, http://www.ncbi.nlm.nih.gov/books/NBK539805.

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

Supporting the elderly: A caring robot with ‘emotions’ and memory
Reporter: Aviva Lev-Ari, PhD, RN
https://pharmaceuticalintelligence.com/2015/02/10/supporting-the-elderly-a-caring-robot-with-emotions-and-memory/

Developing Deep Learning Models (DL) for the Instant Prediction of Patients with Epilepsy
Reporter: Srinivas Sriram, Research Assistant I
https://pharmaceuticalintelligence.com/2021/06/22/developing-deep-learning-models-dl-for-the-instant-prediction-of-patients-with-epilepsy/

Prediction of Cardiovascular Risk by Machine Learning (ML) Algorithm: Best performing algorithm by predictive capacity had area under the ROC curve (AUC) scores: 1st, quadratic discriminant analysis; 2nd, NaiveBayes and 3rd, neural networks, far exceeding the conventional risk-scaling methods in Clinical Use
Curator: Aviva Lev-Ari, PhD, RN
https://pharmaceuticalintelligence.com/2019/07/04/prediction-of-cardiovascular-risk-by-machine-learning-ml-algorithm-best-performing-algorithm-by-predictive-capacity-had-area-under-the-roc-curve-auc-scores-1st-quadratic-discriminant-analysis/

Developing Machine Learning Models for Prediction of Onset of Type-2 Diabetes
Reporter: Amandeep Kaur, B.Sc., M.Sc.
https://pharmaceuticalintelligence.com/2021/05/29/developing-machine-learning-models-for-prediction-of-onset-of-type-2-diabetes/

Deep Learning-Assisted Diagnosis of Cerebral Aneurysms
Reporter: Dror Nir, PhD
https://pharmaceuticalintelligence.com/2019/06/09/deep-learning-assisted-diagnosis-of-cerebral-aneurysms/

Mutations in a Sodium-gated Potassium Channel Subunit Gene related to a subset of severe Nocturnal Frontal Lobe Epilepsy
Reporter: Aviva Lev-Ari, PhD, RN
https://pharmaceuticalintelligence.com/2012/10/22/mutations-in-a-sodium-gated-potassium-channel-subunit-gene-to-a-subset-of-severe-nocturnal-frontal-lobe-epilepsy/

A new treatment for depression and epilepsy – Approval of external Trigeminal Nerve Stimulation (eTNS) in Europe
Reporter: Howard Donohue, PhD (EAW)
https://pharmaceuticalintelligence.com/2012/10/07/a-new-treatment-for-depression-and-epilepsy-approval-of-external-trigeminal-nerve-stimulation-etns-in-europe/

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Developing Deep Learning Models (DL) for the Instant Prediction of Patients with Epilepsy

Reporter: Srinivas Sriram, Research Assistant I
Research Team: Srinivas Sriram, Abhisar Anand

2021 LPBI Summer Intern in Data Science and Website Construction
This article reports on a research study conducted from January 2021 to May 2021.
This Research was completed before the 2021 LPBI Summer Internship that began on 6/15/2021.

The main criterion of this study was to utilize the dataset (shown above) to develop a DL network that could accurately predict new seizures based on incoming data. To begin the study, our research group did some exploratory data analysis on the dataset and we recognized the key defining pattern of the data that allowed for the development of the DL model. This pattern of the data can be represented in the graph above, where the lines representing seizure data had major spikes in extreme hertz values, while the lines representing normal patient data remained stable without any spikes. We utilized this pattern as a baseline for our model. 

Conclusions and Future Improvements:

Through our system, we were able to create a prototype solution that would predict when seizures happened in a potential patient using an accurate LSTM network and a reliable hardware system. This research can be implemented in hospitals with patients suffering from epilepsy in order to help them as soon as they experience a seizure to prevent damage. However, future improvements need to be made to this solution to allow it to be even more viable in the Healthcare Industry, which is listed below.

  • Needs to be implemented on a more reliable EEG headset (covers all neurons of the brain, less prone to electric disruptions shown in the prototype). 
  • Needs to be tested on live patients to deem whether the solution is viable and provides a potential solution to the problem. 
  • The network can always be fine-tuned to maximize performance. 
  • A better alert system can be implemented to provide as much help as possible. 

These improvements, when implemented, can help provide a real solution to one of the most common diseases faced in the world. 

Background Information:

Epilepsy is described as a brain disorder diagnostic category for multiple occurrences of seizures that happen within recurrent and/or a brief timespan. According to the World Health Organization, seizure disorders, including epilepsy, are among the most common neurological diseases. Those who suffer seizures have a 3 times higher risk of premature death. Epilepsy is often treatable, especially when physicians can provide necessary treatment quickly. When untreated, however, seizures can cause physical, psychological, and emotional, including isolation from others. Quick diagnosis and treatment prevent suffering and save lives. The importance of a quick diagnosis of epilepsy has led to our research team developing Deep Learning (DL) algorithms for the sole purpose of detecting epileptic seizures as soon as they occur. 

Throughout the years, one common means of detecting Epilepsy has emerged in the form of an electroencephalogram (EEG). EEGs can detect and compile “normal” and “abnormal “brain wave activity” and “indicate brain activity or inactivity that correlates with physical, emotional, and intellectual activities”. EEG waves are classified mainly by brain wave frequencies (EEG, 2020). The most commonly studied are delta, theta, alpha, sigma, and beta waves. Alpha waves, 8 to 12 hertz, are the key wave that occurs in normal awake people. They are the defining factor for the everyday function of the adult brain. Beta waves, 13 to 30 hertz, are the most common type of wave in both children and adults. They are found in the frontal and central areas of the brain and occur at a certain frequency which, if slow, is likely to cause dysfunction. Theta waves, 4 to 7 hertz, are also found in the front of the brain, but they slowly move backward as drowsiness increases and the brain enters the early stages of sleep. Theta waves are known as active during focal seizures. Delta waves, 0.5 to 4 hertz, are found in the frontal areas of the brain during deep sleep. Sigma waves, 12-16 hertz, are very slow frequency waves that occur during sleep. EEG detection of electrical brain wave frequencies can be used to detect and diagnose seizures based on their deviation from usual brain wave patterns.

In this particular research project, our research group hoped to develop a DL algorithm that when implemented on a live, portable EEG brain wave capturing device, could accurately predict when a particular patient was suffering from Epilepsy as soon as it occurred. This would be accomplished by creating a network that could detect when the brain frequencies deviated from the normal frequency ranges. 

The Study:

Line Graph representing EEG Brain Waves from a Seizure versus EEG Brain Waves from a normal individual. 

Source Dataset: https://archive.ics.uci.edu/ml/datasets/Epileptic+Seizure+Recognition

To expand more on the dataset, it is an EEG data set compiled by Qiuyi Wu and Ernest Fokoue (2021) from the work of medical researchers R.Andrzejak, M.D. et al. (2001) which had been made public domain through the UCI Machine Learning Repository We also confirmed fair use permission with UCI. The dataset had been gathered by Andrzejak during examinations of 500 patients with a chronic seizure disorder. R.G.Andrzejak, et al. (2001) recorded each entry in the EEG dataset used for this project within 23.6 seconds in a time-series data structure. Each row in the dataset represented a patient recorded. The continuous variables in the dataset were single EEG data points at that specific point in time during the measuring period. At the end of the dataset, was a y-variable that indicated whether or not the patient had a seizure during the period the data was recorded. The continuous variables, or the EEG data, for each patient, varied widely based on whether the patient was experiencing a seizure at that time. The Wu & Fokoue Dataset (2021) consists of one file of 11,500 rows, each with 178 sequential data points concatenated from the original dataset of 5 data folders, each including 100 files of EEG recordings of 23.6 seconds and containing 4097 data points. Each folder contained a single, original subset. Subset A contained EEG data gathering during epileptic seizure…. Subset B contained EEG data from brain tumor sites. Subset 3, from a healthy site where tumors had been located. Subsets 4 and 5 from non-seizure patients at rest with eyes open and closed, respectively. 

Based on the described data, our team recognized that a Recurrent Neural Network (RNN) was needed to input the sequential data and return an output of whether the sequential data was a seizure or not. However, we realized that RNN models are known to get substantially large over time, reducing computation speeds. To help provide a solution to this issue, our group decided to implement a long-short-term memory (LSTM) model. After deciding our model’s architecture, we proceeded to train our model in two different DL frameworks inside Python, TensorFlow, and PyTorch. Through various rounds of retesting and redesigning, we were able to train and develop two accurate models in each of the models that not only performed well while learning the data while training, but also could accurately predict new data in the testing set (98 percent accuracy on the unseen data). These LSTM networks could classify normal EEG data when the brain waves are normal, and then immediately predict the seizure data based on if a dramatic spike occurred in the data. 

After training our model, we had to implement our model in a real-life prototype scenario in which we utilized a Single Board Computer (SBC) in the Raspberry Pi 4 and a live capturing EEG headset in the Muse 2 Headband. The two hardware components would sync up through Bluetooth and the headband would return EEG data to the Raspberry Pi, which would process the data. Through the Muselsl API in Python, we were able to retrieve this EEG data in a format similar to the manner implemented during training. This new input data would be fed into our LSTM network (TensorFlow was chosen for the prototype due to its better performance than the PyTorch network), which would then output the result of the live captured EEG data in small intervals. This constant cycle would be able to accurately predict a seizure as soon as it occurs through batches of EEG data being fed into the LSTM network. Part of the reason why our research group chose the Muse Headband, in particular, was not only due to its compatibility with Python but also due to the fact that it was able to represent seizure data. Because none of our members had epilepsy, we had to find a reliable way of testing our model to make sure it worked on the new data. Through electrical disruptions in the wearable Muse Headband, we were able to simulate these seizures that worked with our network’s predictions. In our program, we implemented an alert system that would email the patient’s doctor as soon as a seizure was detected.

Individual wearing the Muse 2 Headband

Image Source: https://www.techguide.com.au/reviews/gadgets-reviews/muse-2-review-device-help-achieve-calm-meditation/

Sources Cited:

Wu, Q. & Fokoue, E. (2021).  Epileptic seizure recognition data set: Data folder & Data set description. UCI Machine Learning Repository: Epileptic Seizure Recognition. Jan. 30. Center for Machine Learning and Intelligent Systems, University of California Irvine.

Nayak, C. S. (2020). EEG normal waveforms.” StatPearls [Internet]. U.S. National Library of Medicine, 31 Jul. 2020, www.ncbi.nlm.nih.gov/books/NBK539805/#.

Epilepsy. (2019). World Health Organization Fact Sheet. Jun. https://www.who.int/ news-room/fact-sheet s/detail/epilepsy

Other Related Articles published in this Open Access Online Scientific Journal include the following:

Developing Deep Learning Models (DL) for Classifying Emotions through Brainwaves

Reporter: Abhisar Anand, Research Assistant I

https://pharmaceuticalintelligence.com/2021/06/22/developing-deep-learning-models-dl-for-classifying-emotions-through-brainwaves/

Machine Learning (ML) in cancer prognosis prediction helps the researcher to identify multiple known as well as candidate cancer diver genes

Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc

https://pharmaceuticalintelligence.com/2021/05/04/machine-learning-ml-in-cancer-prognosis-prediction-helps-the-researcher-to-identify-multiple-known-as-well-as-candidate-cancer-diver-genes/

Deep Learning-Assisted Diagnosis of Cerebral Aneurysms

Reporter: Dror Nir, PhD

https://pharmaceuticalintelligence.com/2019/06/09/deep-learning-assisted-diagnosis-of-cerebral-aneurysms/

Developing Machine Learning Models for Prediction of Onset of Type-2 Diabetes

Reporter: Amandeep Kaur, B.Sc., M.Sc.

https://pharmaceuticalintelligence.com/2021/05/29/developing-machine-learning-models-for-prediction-of-onset-of-type-2-diabetes/

Deep Learning extracts Histopathological Patterns and accurately discriminates 28 Cancer and 14 Normal Tissue Types: Pan-cancer Computational Histopathology Analysis

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2019/10/28/deep-learning-extracts-histopathological-patterns-and-accurately-discriminates-28-cancer-and-14-normal-tissue-types-pan-cancer-computational-histopathology-analysis/

A new treatment for depression and epilepsy – Approval of external Trigeminal Nerve Stimulation (eTNS) in Europe

Reporter: Howard Donohue, PhD (EAW)

https://pharmaceuticalintelligence.com/2012/10/07/a-new-treatment-for-depression-and-epilepsy-approval-of-external-trigeminal-nerve-stimulation-etns-in-europe/

Mutations in a Sodium-gated Potassium Channel Subunit Gene related to a subset of severe Nocturnal Frontal Lobe Epilepsy

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/10/22/mutations-in-a-sodium-gated-potassium-channel-subunit-gene-to-a-subset-of-severe-nocturnal-frontal-lobe-epilepsy/

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Contribution of Nervous System Functional Deterioration to late-life Mortality: The Role Neurofilament light chain (NfL) a Blood Biomarker for the Progression of Neurological Diseases and its Correlation to Age and Life Expectancy

 

Reporter: Aviva Lev-Ati, PhD, RN

 

A neuronal blood marker is associated with mortality in old age

Abstract

Neurofilament light chain (NfL) has emerged as a promising blood biomarker for the progression of various neurological diseases. NfL is a structural protein of nerve cells, and elevated NfL levels in blood are thought to mirror damage to the nervous system. We find that plasma NfL levels increase in humans with age (n = 122; 21–107 years of age) and correlate with changes in other plasma proteins linked to neural pathways. In centenarians (n = 135), plasma NfL levels are associated with mortality equally or better than previously described multi-item scales of cognitive or physical functioning, and this observation was replicated in an independent cohort of nonagenarians (n = 180). Plasma NfL levels also increase in aging mice (n = 114; 2–30 months of age), and dietary restriction, a paradigm that extends lifespan in mice, attenuates the age-related increase in plasma NfL levels. These observations suggest a contribution of nervous system functional deterioration to late-life mortality.

SOURCE

How long will a healthy older person live? A substance in blood may provide a clue

Levels of a substance in nonagenerians’ and centenarians’ blood accurately predict how much longer they’re going to live. The substance comes from the brain.

The findings, in a study published in Nature Aging, could prove useful in developing life-extending drugs. They also raise questions about the brain’s role in aging and longevity.

The study, conducted by Stanford investigators including neuroscientist Tony Wyss-Coray, PhD, in collaboration with researchers in Denmark and Germany, zeroed in on a substance whose technical name is neurofilament light chain (abbreviated NfL). A structural protein produced in the brain, NfL is found in trace amounts in cerebrospinal fluids and blood, where it’s an indicator of damage to long extensions of nerve cells called axons.

Axons convey signals from one nerve cell to the next and are critical to all brain function. You’d rather they remain intact.

Too much NfL (different from the NFL)

High NfL levels in the blood have previously been associated with Alzheimer’s disease, multiple sclerosis, Huntington’s disease, amyotrophic lateral sclerosis (Lou Gehrig’s disease) and other neurological disorders. But the people monitored in the new study were generally pretty healthy for their age.

The researchers first looked at 122 people whose ages ranged from 21 to 107, and found increasing blood levels of NfL — as well as increasing variation among individuals — with increasing age.

Next, the scientists followed the fates of 135 people age 100 or over for a four-year period. Most of those centenarians were in good shape to begin with, as shown by their performance on standard tests of mental ability and by a measure of their capacity to meet the routine demands of daily living.

Not unexpectedly, those whose mental tests indicated impairment had more NfL in their blood than those with the sharpest minds did. And those with low levels were substantially likelier to live longer than those with high levels.

A look at people in their 90s confirmed the findings in the over-100 group. Blood NfL levels among 180 93-year-olds not only predicted the duration of these folks’ survival, but did so better than mental or daily-coping test scores did.

The investigators showed that mice’s blood NfL levels, too, increase with age. But cutting their caloric intake, beginning in young adulthood — already known to prolong the lives of mice and numerous other species — chopped the little creatures’ blood levels of this substance in half in old age. (This new finding doesn’t prove that lowering NfL blood levels causes increased longevity, but it’s consistent with it.)

Tie to life expectancy?

At a minimum, NfL appears to accurately flag mortality’s approach. That means it might be possible to monitor it as a surrogate marker for remaining life expectancy, much as blood cholesterol levels are used as proxies for cardiovascular health. If so, it could someday help drug developers assess life-extending interventions’ efficacy.

Clinical trials of interventions believed to enhance longevity have been impractical, because it would almost certainly take so long to get a statistically significant result that such trials would be hugely expensive — a major hang-up for pharmas considering investment in longevity drugs. But monitoring a proxy such as NfL could cut years off of such trials’ duration, perhaps encouraging drug developers to dive into the clinical arena with life-prolonging pharmacological candidates.

Possibly most intriguing of all: The new findings hint that maintaining a healthy brain in old age is the best route to a long life.

“It will be interesting to see how and why the brain might be so important in counting down our final years and months,” Wyss-Coray told me.

Photo by Pablo Bendandi

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Reporter: Adina Hazan, PhD

Elizabeth Unger from the Tian group at UC Davis, Jacob Keller from the Looger lab from HHMI, Michael Altermatt from the Gradinaru group at California Institute of Technology, and colleagues did just this, by redesigned the binding pocket of periplasmic binding proteins (PBPs) using artificial intelligence, such that it became a fluorescent sensor specific for serotonin. Not only this, the group showed that it could express and use this molecule to detect serotonin on the cell, tissue, and whole animal level.

By starting with a microbial PBP and early version of an acetyl choline sensor (iAChSnFR), the scientists used machine learning and modeling to redesign the binding site to exhibit a higher affinity and specificity to serotonin. After three repeats of mutagenesis, modeling, and library readouts, they produced iSeroSnFR. This version harbors 19 mutations compared to iAChSnFR0.6 and a Kd of 310 µM. This results in an increase in fluorescence in HEK293T cells expressing the serotonin receptor of 800%. Of over 40 neurotransmitters, amino acids, and small molecules screened, only two endogenous molecules evoked some fluorescence, but at significantly higher concentrations.

To acutely test the ability of the sensor to detect rapid changes of serotonin in the environment, the researchers used caged serotonin, a technique in which the serotonin is rapidly released into the environment with light pulses, and showed that iSeroSnFR accurately and robustly produced a signal with each flash of light. With this tool, it was then possible to move to ex-vivo mouse brain slices and detect endogenous serotonin release patterns across the brain. Three weeks after targeted injection of iSeroSnFR to specifically deliver the receptor into the prefrontal cortex and dorsal striatum, strong fluorescent signal could be detected during perfusion of serotonin or electrical stimulation.

Most significantly, this molecule was also shown to be detected in freely moving mice, a tool which could offer critical insight into the acute role of serotonin regulation during important functions such as mood and alertness. Through optical fiber placements in the basolateral amygdala and prefrontal cortex, the team measured dynamic and real-time changes in serotonin release in fear-trained mice, social interactions, and sleep wake cycles. For example, while both areas of the brain have been established as relevant to the fear response, they reliably tracked that the PFC response was immediate, while the BSA displayed a delayed response. This additional temporal resolution of neuromodulation may have important implications in neurotransmitter pharmacology of the central nervous system.

This study provided the scientific community with several insights and tools. The serotonin sensor itself will be a critical tool in the study of the central nervous system and possibly beyond. Additionally, an AI approach to mutagenesis in order to redesign a binding pocket of a receptor opens new avenues to the development of pharmacological tools and may lead to many new designs in therapeutics and research.

SOURCE:

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Sleep Deprivation Death Linked Causally to the Gut

Reporter : Irina Robu, PhD

Neuroscientists at Harvard Medical School identified an unexpected link between sleep deprivation and premature death. Their findings show that the possibility that animals might be able to survive without sleep, under certain circumstances. Their study with sleep-deprived fruit flies found that death was continuously by the accumulation of reactive oxidative species in the gut. And when the flies were given antioxidant compounds that neutralized and cleared ROS from the gut, the sleep-deprived animals remained active and had normal lifespans. Extra experiments in mice confirmed that ROS accumulated in the gut when they didn’t get enough sleep.

Yet, in spite of decades of study, researchers still haven’t revealed why animals die when they don’t sleep. In attempts to answer how sleep deprivation culminates in death, most research has focused on the brain, where sleep originates. However, studies have yet to yield conclusive results. In addition to impairing cognition, sleep loss leads to dysfunction of the gastrointestinal, immune, metabolic, and circulatory systems.

The Harvard Medical School team carried out a sequence of experiments in fruit flies to search throughout the body for signs of damage caused by sleep deprivation. Fruit flies share many sleep-regulating genes with humans. To screen sleep, the investigators used infrared beams to constantly track the movement of flies housed in individual tubes. Scientist show that flies can sleep through physical shaking, so they genetically manipulated fruit flies to express a heat-sensitive protein in specific neurons, the activity of which are known to suppress sleep. When flies were housed at 29°C the protein induced neurons to remain constantly active, thus preventing the flies from sleeping.

The scientists discovered that fruit fly mortality spiked after 10 days of temperature-induced sleep deprivation and all of the flies died by around day 20 and control flies that had normal sleep lived up to approximately 40 days in the same environmental conditions. Since mortality increased around day 10, the scientists looked for markers of cell damage on that and the preceding days. They noticed that the guts of sleep-deprived flies had a dramatic build-up of ROS. The buildup of ROS in the fruit fly guts peaked around day 10 of sleep deprivation, and when deprivation was stopped, ROS levels decreased.

To find out if ROS in the gut plays a causal role in sleep deprivation-induced death, the researchers next looked at whether preventing ROS accumulation could prolong survival. They tested dozens of compounds with antioxidant properties known to neutralize ROS and identified 11 that, when given as a food supplement, allowed sleep-deprived flies to have a normal or near-normal lifespan. These compounds, such as melatonin, lipoic acid, and NAD, were particularly effective at clearing ROS from the gut. Notably, the supplements did not extend the lifespan of non-sleep-deprived flies.

The role of ROS removal in preventing death was also confirmed by experiments in which flies were genetically manipulated to overproduce antioxidant enzymes in their guts. These flies had normal to near-normal lifespans when sleep deprived, but flies that overproduced antioxidant enzymes in their nervous systems weren’t protected from sleep-deprivation-related death. While the results demonstrated that ROS build up in the gut plays a central role in causing premature death from sleep deprivation, the researchers acknowledged that many questions are still without answers. At the same time, they found that insufficient sleep is identified to restrict with the body’s hunger signaling pathways, which lead to measure the fruit fly food intake to analyze whether there were potential associations between feeding and death. They found that some sleep-deprived flies ate more throughout the day compared with non-deprived controls.

The researchers are now working to identify the biological pathways that lead to ROS accumulation in the gut and subsequent physiological disruptions.

SOURCE

Death Due to Sleep Deprivation Linked Causally to the Gut, and is Preventable in Flies

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Parkinson’s Disease (PD), characterized by both motor and non-motor system pathology, is a common neurodegenerative disorder affecting about 1% of the population over age 60. Its prevalence presents an increasing social burden as the population ages. Since its introduction in the 1960’s, dopamine (DA)-replacement therapy (e.g., L-DOPA) has remained the gold standard treatment. While improving PD patients’ quality of life, the effects of treatment fade with disease progression and prolonged usage of these medications often (>80%) results in side effects including dyskinesias and motor fluctuations. Since the selective degeneration of A9 mDA neurons (mDANs) in the substantia nigra (SN) is a key pathological feature of the disease and is directly associated with the cardinal motor symptoms, dopaminergic cell transplantation has been proposed as a therapeutic strategy.

 

Researchers showed that mammalian fibroblasts can be converted into embryonic stem cell (ESC)-like induced pluripotent stem cells (iPSCs) by introducing four transcription factors i.e., Oct4, Sox2, Klf4, and c-Myc. This was then accomplished with human somatic cells, reprogramming them into human iPSCs (hiPSCs), offering the possibility of generating patient-specific stem cells. There are several major barriers to implementation of hiPSC-based cell therapy for PD. First, probably due to the limited understanding of the reprogramming process, wide variability exists between the differentiation potential of individual hiPSC lines. Second, the safety of hiPSC-based cell therapy has yet to be fully established. In particular, since any hiPSCs that remain undifferentiated or bear sub-clonal tumorigenic mutations have neoplastic potential, it is critical to eliminate completely such cells from a therapeutic product.

 

In the present study the researchers established human induced pluripotent stem cell (hiPSC)-based autologous cell therapy. Researchers reported a platform of core techniques for the production of mDA progenitors as a safe and effective therapeutic product. First, by combining metabolism-regulating microRNAs with reprogramming factors, a method was developed to more efficiently generate clinical grade iPSCs, as evidenced by genomic integrity and unbiased pluripotent potential. Second, a “spotting”-based in vitro differentiation methodology was established to generate functional and healthy mDA cells in a scalable manner. Third, a chemical method was developed that safely eliminates undifferentiated cells from the final product. Dopaminergic cells thus produced can express high levels of characteristic mDA markers, produce and secrete dopamine, and exhibit electrophysiological features typical of mDA cells. Transplantation of these cells into rodent models of PD robustly restored motor dysfunction and reinnervated host brain, while showing no evidence of tumor formation or redistribution of the implanted cells.

 

Together these results supported the promise of these techniques to provide clinically applicable personalized autologous cell therapy for PD. It was recognized by researchers that this methodology is likely to be more costly in dollars and manpower than techniques using off-the-shelf methods and allogenic cell lines. Nevertheless, the cost for autologous cell therapy may be expected to decrease steadily with technological refinement and automation. Given the significant advantages inherent in a cell source free of ethical concerns and with the potential to obviate the need for immunosuppression, with its attendant costs and dangers, it was proposed that this platform is suitable for the successful implementation of human personalized autologous cell therapy for PD.

 

References:

 

https://www.jci.org/articles/view/130767/pdf?elqTrackId=2fd7d0edee744f9cb6d70a686d7b273b

 

https://www.ncbi.nlm.nih.gov/pubmed/31714896

 

https://www.ncbi.nlm.nih.gov/pubmed/23666606

 

https://www.ncbi.nlm.nih.gov/pubmed/27343168

 

https://www.ncbi.nlm.nih.gov/pubmed/21495962

 

https://www.ncbi.nlm.nih.gov/pubmed/28083784

 

https://www.ncbi.nlm.nih.gov/pubmed/20336395

 

https://www.ncbi.nlm.nih.gov/pubmed/28585381

 

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Contributions to Neuronal Systems by University Professors Eve Marder and Irv Epstein at Brandeis University

Reporter: Aviva Lev-Ari, PhD, RN

Oscillators: Chemicals, Neurons and People: A Celebration of Eve Marder, Irving Epstein and the Volen Center for Complex Systems
Sunday, Nov. 17, 2019, 1 – 5:30 p.m.
Location Schwartz
Room Auditorium
Event Sponsor(S) Office of the Provost
Website www.brandeis.edu…

A celebration for new university professors Eve Marder and Irving Epstein, and the 25th anniversary of the Volen Center!

Schedule of Events

  • 1p.m. – Opening remarks: Leslie Griffith, Nancy Lurie Marks Professor of Neuroscience and Director of the Volen National Center for Complex Systems
  • 1:30 p.m. – Panel Discussion: “Oscillators: Chemicals, Neurons and People”
    • Moderator: Gina Turrigiano, Joseph Levitan Professor of Vision Science
    • Panelist: Jorge Golowasch, Professor, Department of Biological Sciences, New Jersey Institute of Technology
    • Panelist: Nancy Kopell, Professor of Mathematics, Boston University
    • Panelist: Horacio Rotstein, Professor of Mathematical Biology & Computational Neuroscience, Department of Biological Sciences, New Jersey Institute of Technology
    • Panelist: Frances Skinner, Senior Scientist, Krembil Research Institute and Professor, Division of Neurology, Department of Medicine and Department of Physiology, University of Toront
  • 2:30 p.m. – Coffee
  • 3 p.m. – Irving Epstein: “How I Wandered into an Oscillatory State”
  • 4 p.m. – Eve Marder: “The Challenges Posed by Neuronal Oscillators that are both Stable and Plastic”
  • 5 p.m. – Closing remarks: Leslie Griffith

 

Eve Marder and Irv Epstein recall the collaborations that started it all

The University Professors will lead a public symposium on Nov. 17

headshots of University Professors Eve Marder, left, and Irv EpsteinPhoto/Mike LovettUniversity professors Eve Marder ’69, Left, and Irving R. Epstein

University Professors Eve Marder ’69 and Irv Epstein will help celebrate the 25th anniversary of the Volen National Center for Complex Systems in a public symposium November 17.

Marder, the Victor and Gwendolyn Beinfield Professor of Neuroscience, and Epstein, the Henry F. Fischbach Professor of Chemistry, were named University Professors last spring in recognition of their pioneering interdisciplinary achievements. At the symposium, they will each deliver a lecture drawing on their collaborative research on oscillators. In the case of Epstein, these are oscillating chemical reactions. In Marder’s case, it is rhythmically active neurons and/or circuits.   

But some 35 years ago, before they were leaders in their fields, Epstein and Marder saw the benefit of sharing ideas. A mutual colleague noticed that the chemical reactions recorded on the chart recorder Epstein was using looked intriguingly similar to the neuronal signals Marder was recording in her research.

“It’s relatively unusual behavior for chemistry, but it’s sort of the essence of what goes on in neuronal systems,” said Epstein, who soon learned some rudiments of neuroscience from Marder and began mathematically modeling groups of neurons. For her part, Marder “got an appreciation for what interacting with theorists could bring, to help her answer the kind of questions she wanted to answer,” said Epstein.

These days, Marder’s research on small neural circuits found in lobsters and crabs is credited with revolutionizing understanding of the fundamental nature of neuronal circuit operation, including how neuromodulators control behavioral outputs and how the stability of circuits is maintained over time. She has won many top prizes in neuroscience, including the Gruber Award in Neuroscience, the Kavli Prize in Neuroscience, and the National Academy of Sciences Neuroscience Prize. In March, she will receive the Carnegie Prize in Mind and Brain Science from Carnegie Mellon University.

Epstein, a Howard Hughes Medical Institute professor, pioneered the field of chemical oscillators. “When we got into the field of oscillating reactions, there were just three that were known, and they were all discovered accidentally,” said Epstein. “We decided that if we really understood these systems, we should be able to design them.”

Although it took him several years and three unsuccessful grant applications to secure funding for his ideas, Epstein and his lab ultimately won funding, and within a few months succeeded in developing their first novel chemical oscillating reaction.

Writ large, Marder and Epstein collaboratively demonstrate that the kinds of phenomena seen in neurons are also found in chemical and physical systems. “What you learn from modeling chemical reactions can help you understand how neurons work, and vice versa,” said Epstein.

“Volen is a place where you get all kinds of collaborations,” said Marder. “One of Brandeis’ strengths is its interactivity; those early days were quite catalytic.”

 

Categories: ResearchScience and Technology

SOURCE

https://www.brandeis.edu/now/2019/november/eve-irv-volen.html

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NSPR1 and DEC2 genes: Survival on 4.5 hours of Sleep per night: A mutation in the β1-adrenergic receptor gene in humans who require fewer hours of sleep than most, ADRB1 + neurons are active during rapid eye movement (REM) sleep and wakefulness

 

Reporter: Aviva Lev-Ari, PhD, RN

 

10/2019 RESEARCH ARTICLE SLEEP

Mutant neuropeptide S receptor reduces sleep duration with preserved memory consolidation

 See all authors and affiliations

Science Translational Medicine  16 Oct 2019:
Vol. 11, Issue 514, eaax2014
DOI: 10.1126/scitranslmed.aax2014

Abstract

Sleep is a crucial physiological process for our survival and cognitive performance, yet the factors controlling human sleep regulation remain poorly understood. Here, we identified a missense mutation in a G protein–coupled neuropeptide S receptor 1 (NPSR1) that is associated with a natural short sleep phenotype in humans. Mice carrying the homologous mutation exhibited less sleep time despite increased sleep pressure. These animals were also resistant to contextual memory deficits associated with sleep deprivation. In vivo, the mutant receptors showed increased sensitivity to neuropeptide S exogenous activation. These results suggest that the NPS/NPSR1 pathway might play a critical role in regulating human sleep duration and in the link between sleep homeostasis and memory consolidation.

It is possible that drugs could be developed to target either the NSPR1 or DEC2 genes, as a treatment for insomnia or other sleep disorders. However, further understanding of exactly how these genes function would be required before this stage. Both are involved in brain function, so targeting them could lead to negative neural side effects.

 

Neuron

Volume 103, Issue 6, 25 September 2019, Pages 1044-1055.e7

A Rare Mutation of β1-Adrenergic Receptor Affects Sleep/Wake Behaviors

Highlights

  • A mutation in ADRB1 leads to natural short sleep trait in humans
  • Mice engineered with same mutation have similar short sleep behavior as humans
  • Activity of dorsal pons ADRB1 + neurons associates with REM sleep and wakefulness
  • Mutation increases the population activity of dorsal pons ADRB1 + neurons

Summary

Sleep is crucial for our survival, and many diseases are linked to long-term poor sleep quality. Before we can use sleep to enhance our health and performance and alleviate diseases associated with poor sleep, a greater understanding of sleep regulation is necessary. We have identified a mutation in the β 1-adrenergic receptor gene in humans who require fewer hours of sleep than most. In vitro, this mutation leads to decreased protein stability and dampened signaling in response to agonist treatment. In vivo, the mice carrying the same mutation demonstrated short sleep behavior. We found that this receptor is highly expressed in the dorsal pons and that these ADRB1 + neurons are active during rapid eye movement (REM) sleep and wakefulness. Activating these neurons can lead to wakefulness, and the activity of these neurons is affected by the mutation. These results highlight the important role of β 1-adrenergic receptors in sleep/wake regulation.

Keywords

Additional SOURCES

Second Gene Mutation that Lets People Survive on Less Sleep

 

Other related articles on Circadian Rhythm and Sleep published in this Open Access Online Scientific Journal include the following:

 

2017 Nobel Prize in Physiology or Medicine jointly to Jeffrey C. Hall (ex-Brandeis, University of Maine), Michael Rosbash (Brandeis University) and Michael W. Young (Rockefeller University in New York) for their discoveries of molecular mechanisms controlling the circadian rhythm

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/10/02/2017-nobel-prize-in-physiology-or-medicine-jointly-to-jeffrey-c-hall-michael-rosbash-and-michael-w-young-for-their-discoveries-of-molecular-mechanisms-controlling-the-circadian-rhythm/

 

Patient-Reported Outcomes Study, Presented at SLEEP 2018, Provides Confirmatory Real-World Evidence of the Previously Presented 7-hour Action of REMfresh®, the First Continuous Release and Absorption Melatonin™

Reporter: Gail S. Thornton, PhD(c)

https://pharmaceuticalintelligence.com/2018/06/10/patient-reported-outcomes-study-presented-at-sleep-2018-provides-confirmatory-real-world-evidence-of-the-previously-presented-7-hour-action-of-remfresh-the-first-continuous-release-and-absorp/

 

Clinically Studied, Continuous Release and Absorption Melatonin, REMfresh, Designed to Give Patients Up to 7 Hours of Sleep Support

Reporter: Gail S. Thornton, M.A.

https://pharmaceuticalintelligence.com/2019/06/19/clinically-studied-continuous-release-and-absorption-melatonin-remfresh-designed-to-give-patients-up-to-7-hours-of-sleep-support/

 

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

Reporter: Aviva Lev-Ari, PhD, RN

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/

 

Sleep and Memory

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/03/26/sleep-and-memory/

 

Sleep Science

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/03/16/sleep-science/

 

Genetic Link to Sleep and Mood Disorders

Curator: Larry H. Bernstein, MD, FCAP

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

 

Sleep Apnea Insular Glutamate and GABA Levels

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/02/12/sleep-apnea-insular-glutamate-and-gaba-levels/

 

Fat, Sleep and the Gut

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/02/06/fat-sleep-and-the-gut/

 

23andMe Genome-Wide Association Study on Human propensity to Get up early or Sleep in the Morning

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/02/02/23andme-genome-wide-association-study-on-human-propensity-to-get-up-early-or-sleep-in-the-morning/

 

Sleep Quality, Amyloid and Cognitive Decline

Curator: Larry H. Bernstein, MD, FCAP

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

 

Study Shows Learning Is Best Enhanced During Sleep – Jewish Business News

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/09/02/study-shows-learning-is-best-enhanced-during-sleep-jewish-business-news/

 

Beta-Blockers Cause Lack Of Restful Sleep – Life Extension

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/08/04/beta-blockers-cause-lack-of-restful-sleep-life-extension/

 

Topical Antispasmodics conducive for Uninterrupted Sleep – A Potential Cardiovascular Chrono-therapeutics

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/02/13/topical-antispasmodics-conducive-for-uninterrupted-sleep-a-potential-cardiovascular-chrono-therapeutics/

 

Prolonged Wakefulness: Lack of Sufficient Duration of Sleep as a Risk Factor for Cardiovascular Diseases – Indications for Cardiovascular Chrono-therapeutics

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/02/02/prolonged-wakefulness-lack-of-sufficient-duration-of-sleep-as-a-risk-factor-for-cardiovascular-diseases-indications-for-cardiovascular-chrono-therapeutics/

 

Sleep Apnea and Non-invasive positive Pressure Breathing

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/06/11/sleep-apnea-and-non-invasive-positive-pressure-breathing/

 

How Might Sleep Apnea Lead to Serious Health Concerns like Cardiac and Cancer?

Author: Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/03/20/how-might-sleep-apnea-lead-to-serious-health-concerns-like-cardiac-and-cancers/

 

2019 Warren Alpert Foundation Award goes to Four Scientists for Seminal Discoveries in OptoGenetics – Illuminating the Human Brain

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2019/07/18/2019-warren-alpert-foundation-award-goes-to-four-scientists-for-seminal-discoveries-in-optogenetics-illuminating-the-human-brain/

 

 

 

 

 

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Novel delivery system in REMfresh mimics the way the body naturally releases and maintains melatonin over a 7-hour period

Real-world evidence confirms previous clinical data on improved sleep duration and sleep quality with REMfresh

Reporter: Gail S. Thornton, M.A.

Chronic disorders of sleep and wakefulness affect an estimated 50-70 million adults in the United States.[i] The cumulative long term effects of sleep loss have been associated with a wide range of damaging health consequences, including obesity, diabetes, impaired glucose tolerance, cardiovascular disease, hypertension, anxiety and depression.[ii]In terms of preventing health consequences, sleeping 6-8 hours per night consistently may provide optimal health outcomes.[iii]

This month, real-world evidence from two recently completed patient-reported outcomes (PRO) studies presented at SLEEP 2019 in San Antonio, Texas, confirms previous clinical data demonstrating statistically significant improvements in sleep onset, sleep duration, sleep maintenance and sleep quality with REMfresh®, the first and only continuous release and absorption melatonin (CRA-Melatonin™). This data supports and reinforces the benefits of REMfresh, which is designed to give patients up to 7 hours of sleep support. PRO studies of this kind, which more closely address real-world patient experience, are increasingly being recognized by regulatory authorities and academia in evaluating new therapies.

The REMfresh Duration Validation (REMVAL) study provides further evidence of a correlative relationship between the 7-hour pharmacokinetic profile observed in the earlier clinical study, REM Absorption Kinetics Trial (REMAKT), and the hypnotic effects of REMfresh, observed in subsequent studies, as demonstrated by improvements in sleep onset, sleep duration, sleep maintenance, sleep quality and patient satisfaction. This latest study further validates the findings of past studies that have been presented and undergone peer review at major sleep conferences:  

  • REMfresh Patient Reported Outcomes DURation (REMDUR), the first, 500-patient, PRO study of this sleep brand, presented at the annual meeting for sleep specialists, SLEEP 2018, which demonstrated that more than 77 percent of patients achieved 6 or more hours of sleep compared to 23.6 percent who slept that duration prior to taking REMfresh (p<.0001)[iv], and
  • REM Absorption Kinetics Trial (REMAKT), a pharmacokinetic study presented at SLEEP 2017 and 2018, which demonstrated that REMfresh mimics the body’s own seven-hour Mesa-Wave® release profile, a natural pattern of melatonin blood levels during a normal night’s sleep cycle.[v] 

An additional PRO subset study, part of REMVAL, called the REMfresh Short Sleep Cohort Assessment (REMSS), assessed improvements in sleep duration and sleep maintenance among 311 patients with morbid or extreme short sleep duration of 4 hours or less.

These two PRO studies (REMVAL and REMSS) were presented at SLEEP 2019, the 33rd Annual Meeting of the Associated Professional Sleep Societies (APSS), which is a joint meeting of the American Academy of Sleep Medicine and the Sleep Research Society, held in San Antonio, Texas, from June 8-12.

“These latest findings provide further confirmation of the potential for nonprescription REMfresh to help address the public health issue of  the cumulative effects of sleep loss,” said David C. Brodner, M.D., a leading sleep specialist who is Double Board-Certified in Otolaryngology — Head and Neck Surgery as well as 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. “Based on a novel Ion Powered Pump® (IPP®) delivery system that provides a pharmacokinetic (PK) profile that more closely aligns with the body’s own natural sleep pattern, REMfresh has demonstrated once again promising results and high levels of satisfaction in a real-world population of patients who have had chronic difficulties sleeping, providing up to seven hours of sleep support,” said Dr. Brodner.

Topline findings of these studies are as follows:

  • The 1,116 patient-reported outcomes (PRO) study, REMfresh Duration Validation (REMVAL), found that after taking 99 percent ultra-pure, continuous release and absorption melatonin (REMfresh®, CRA-melatonin™), the majority (78.8 percent) of patients involved achieved a sleep duration of greater than or equal to 6 hours (p<.0001), while more than 91 percent of patients reported a major/moderate improvement in sleep onset, sleep maintenance and sleep quality (p<.0001).  Of the 30.7 percent of patients (342 in total), who reported never having taken other brands of melatonin, 99.4 percent indicated they were likely or very likely to continue taking CRA-melatonin for their sleep issues (p<.0001).
  • REMVAL provides further real-world evidence of a correlative relationship between the originally observed 7-hour pharmacokinetic profile in the REM Absorption Kinetics Trial (REMAKT) and the strong observed hypnotic effects of CRA-melatonin, as demonstrated by improvements in sleep onset, sleep duration, sleep maintenance and sleep quality.
  • A second PRO subset study, REMfresh Short Sleep Cohort Assessment (REMSS), involving 311 patients who reported sleeping four hours or less nightly from the REMVAL study, found that 95.8 percent of patients who previously experienced daily, morbid short sleep duration of less than or equal to 4 hours reported an improvement in sleep duration (p<.0001), including more than 46 percent who achieved a sleep duration of greater than or equal to 6 hours (p<.0001). More than 93 percent of patients reported a major/moderate improvement in sleep onset, sleep maintenance and sleep quality (p<.0001).
  • REMVAL and REMSS also provides validation of the results from the previously peer-reviewed and presented clinical study, REMAKT, which demonstrated that REMfresh mimics the body’s own 7-hour Mesa Wave®, a natural pattern of melatonin blood levels during a normal night’s sleep cycle and the 500-patient, peer-reviewed and presented  REMfresh® Patient Reported Outcomes DURation (REMDUR) study, that demonstrated statistically significant improvements in sleep onset, sleep maintenance and sleep quality.

REMVAL Study Describes Improvements in Sleep Duration and Sleep Quality

The poster entitled, “Observed Hypnotic Effects with a Continuous-Release Ion Powered Pump Melatonin Delivery System: Self-Reported Patient Outcomes Study Results Demonstrating Improvement in Sleep Duration and Quality,” reported findings provides further real-world evidence of a correlative relationship between the originally observed 7-hour pharmacokinetic profile in the REM Absorption Kinetics Trial (REMAKT) and the strong hypnotic effects of CRA-melatonin observed in subsequent studies and may offer a new low-dose, drug-free alternative to prescription hypnotics to treat chronic sleep disturbances.

The 1,116-patient REMVAL study was designed to obtain clinically relevant information about patients’ past usage of melatonin and non-melatonin sleep aids, sleep patterns prior to taking CRA-melatonin, sleep duration before and after taking CRA-melatonin, frequency of CRA-melatonin usage, improvement in sleep onset, sleep maintenance and sleep quality after taking CRA-melatonin, and overall satisfaction with CRA-melatonin.

In the study, patients with sleep disturbances in the general population received a sample of REMfresh from their physicians and were invited to complete a 13-question online survey. After taking REMfresh, the majority (78.8 percent) of patients achieved a sleep duration of greater than or equal to 6 hours (p<.0001). More than 91 percent of patients reported a major/moderate improvement in sleep onset, sleep maintenance and sleep quality (p<.0001). Of the 30.7 percent of patients (342 in total), who reported never having taken other brands of melatonin, 99.4 percent indicated they were likely or very likely to continue taking REMfresh for their sleep issues (p<.0001).

REMSS Study Shows Improvement in Patients with Chronic, Extreme Short Sleep

The poster entitled, “Improvement in Sleep Duration and Maintenance with Ion Powered Continuous Release and Absorption Melatonin in a Cohort of Patients with Chronic Short Sleep Duration: Results from a Patient-Reported Outcomes Study,” highlighted findings from the REMfresh Short Sleep Cohort Assessment (REMSS), involving a cohort of 311 patients from the REMVAL study who reported sleeping four hours or less nightly. This cohort analysis was designed to obtain clinically relevant information from these patients experiencing morbid short sleep disturbances, including sleep patterns and melatonin usage before taking REMfresh, sleep duration before and after taking REMfresh, improvement in sleep onset, sleep maintenance and sleep quality after taking REMfresh, and overall product satisfaction.

Data from this cohort show that 95.8 percent of patients who previously experienced daily, morbid short sleep duration of less than or equal to 4 hours reported an improvement in sleep duration (p<.0001), including more than 46 percent who achieved a sleep duration of greater than or equal to 6 hours (p<.0001). This increase from less than or equal to 4 hours to greater than or equal to 6 hours represents a major sleep duration upgrade in this group facing morbid sleep disturbances. More than 93 percent of patients reported a major/moderate improvement in sleep onset, sleep maintenance and sleep quality (p<.0001). Ninety-nine percent of the patients suffering with morbid short sleep (27.2 percent of whom had never previously tried a melatonin brand) reported that they were very likely or likely to continue using CRA-melatonin. These results provide real-world evidence that CRA-melatonin with its extended 7-hour pharmacokinetic  plateau time and benign safety-profile may be a practical baseline therapy to improve sleep duration and other key sleep parameters, including, sleep maintenance and sleep quality in this group of patients who have a higher risk of all-cause mortality.[vi]˒[vii]˒[viii]˒[ix]

Statistics & Data Corporation (SDC), a top-tier clinical data services provider, has independently determined that the number of participants in the study provides adequate power (>90%) to detect even small improvements in sleep outcomes. This high power, or probability of seeing statistically significant results if CRA-melatonin is truly working to improve sleep outcomes, applies to the overall study population (REMVAL) as well as the cohort of short sleepers (REMSS). SDC has subsequently independently validated the statistical results achieved, (e.g., p-values and statistical language).

The Increasing Appreciation of PRO Studies to Include Patient Experience 
Increasingly, there is an appreciation by the U.S. Congress, regulatory authorities and academia, of the substantive value that real-world patient experience brings to assessing new therapies. In addition to the traditional randomized, placebo-controlled trial studies, regulatory authorities are now incorporating the patient perspective in their decision making, including PRO studies. A PRO study is a measurement based on a report that comes directly from the patient about the status or change in their health condition and without amendment or interpretation of the patient’s response by health-care intermediaries. PRO measures can be used to capture a patient’s everyday experience outside of the clinician’s office, and the effects of a treatment on the patient’s activities of daily living.[x]˒[xi]Together, clinical measures and PRO measures can provide a fuller picture of patient benefit.

REMAKT Clinical Study Presented at Past Medical Meetings 
Pharmacokinetic data on REMfresh® was peer-reviewed and then presented in 2017 and 2018 at SLEEP, the Annual Meeting of the Associated Professional Sleep Societies LLC (APSS), and a joint meeting of the American Academy of Sleep Medicine (AASM) and the Sleep Research Society (SRS). 

The study, REM Absorption Kinetics Trial (REMAKT), was 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 then had a rapid decline in serum levels that did not allow melatonin levels to be maintained beyond 4 hours. 

Analysis presented at SLEEP 2017 and 2018 showed that REMfresh builds upon the body of evidence from prolonged-release melatonin (PR-M), approved by the European Medicines Agency (EMA) in 2007 as a prescription drug for insomnia, which demonstrated in well-conducted, placebo-controlled studies, statistically significant improvement in sleep quality, morning alertness, sleep onset and quality of life in patients aged 55 years and older compared with placebo.[xv] REMfresh was designed to overcome the challenges of continuous release and 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).[xvi] There was the desirable fast time to reach the sleep threshold level, 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. 

Over 5,000 healthcare practitioners are estimated to have used REMfresh for their patients and about 320,000 patients are estimated to have purchased and used REMfresh. The continuing, rapid acceptance of REMfresh by patients is observable by several markers, including rapid sales growth and availability among major drug retailers.

###

Data Presented at SLEEP 2019 Poster Sessions:

Monday, June 10, 2019, 5:15-7:15pm

  • (Abstract 0398, Poster Board #135) Improvement in Sleep Duration and Maintenance with Ion Powered Continuous Release and Absorption Melatonin in a Cohort of Patients with Chronic Short Sleep Duration: Results from a Patient-Reported Outcomes Study
    • David J. Seiden, M.D., FAASM,  David Brodner, M.D., Syed M. Shah, Ph.D.
  • (Abstract 0399, Poster Board #136) Observed Hypnotic Effects with a Continuous-Release Ion Powered Pump Melatonin Delivery System: Self-Reported Patient Outcomes Study Results Demonstrating Improvement in Sleep Duration and Quality
    • David J. Brodner, M.D., David J. Seiden, M.D. FAASM, Syed M. Shah, Ph.D.

The abstracts are published in an online supplement of the journal, Sleep, which is available at https://sleepmeeting.org/wp-content/uploads/2019/04/SLEEP_42_S1-Website-Final.pdf.

REFERENCES:


[i] 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

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

[iii] Watson, N.F., Badr, M.S., Belenky, G., et al. (2015). Joint Consensus Statement of the American Academy of Sleep  Medicine and Sleep Research Society on the Recommended Amount of Sleep for the Healthy Adult, Methodology and Discussion. Journal of Clinical Sleep Medicine, 11(6); 591-592.

[iv] Seiden,D.J., Brodner, D.C., & Shah, S.M. (2018, June 2-6). Improvement in Sleep Maintenance and Sleep Quality with Ion-Powered Pump Continuous Release and Absorption Melatonin: Results from a Self-Reported Patient Outcomes Study (Abstract #0419). Poster presented at SLEEP 2018, Baltimore, Maryland.

[v] Brodner, D.C., Shah, S.M. (2017, June 3-7). REM Absorption Kinetics Trial: A Randomized, Crossover, Pharmacokinetics Evaluation of a Novel Continuous Release and Absorption Melatonin Formulation versus a Same Strength Immediate-Release Formulation in Healthy Adults (Abstract #0396). Poster presented at: SLEEP 2017, Boston, Massachusetts.

[vi] Knutsen, K.L., Turek,, F.W., Patel, S.R., et al (2006). The u-shaped association between sleep and health: the 2 peaks do not mean the same thing.  Comment on Patel, SR, et al. Sleep, 29(7): 878-879.

[vii] Lubetkin,, E.I., & Haomiao, J. (2018). Burden of disease due to sleep duration and sleep problems in the elderly. Sleep Health, 4; 182-187.

[viii] Hafner M, et al. (2017). Why sleep matters-the economic costs of insufficient sleep: A cross-country comparative analysis, Rand Quarterly.

[ix] Ikehara, S, et al. (2009). Association of Sleep Duration with Mortality  from Cardiovascular Disease and other Causes for Japanese Men and Women: the JACC Study. Sleep, 32(3); 295-301.

[x] U.S. Food and Drug Administration. Real World Evidence. Retrieved from https://www.fda.gov/scienceresearch/specialtopics/realworldevidence/default.htm

[xi] U.S. Food and Drug Administration. 21st Century Cures Act. Retrieved from https://www.fda.gov/regulatoryinformation/lawsenforcedbyfda/significantamendmentstothefdcact/21stcenturycuresact/default.htm.

[xii] 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

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

[xiv] Watson, N.F., Badr, M.S., Belenky, G., et al. (2015). Joint Consensus Statement of the American Academy of Sleep  Medicine and Sleep Research Society on the Recommended Amount of Sleep for the Healthy Adult, Methodology and Discussion. Journal of Clinical Sleep Medicine, 11(6); 591-592.

[xv] European Medicines Agency.(2007). Assessment Report for CIRCADIN.

[xvi] Brodner, D.C. & Shah, S.M. (2017, June 3-7). A Continuous Release Ion Powered Pump Melatonin Delivery System that Overcomes Challenges of Release and Absorption in the Intestines (Abstract #0385). Poster presented at: SLEEP 2017,  Boston, Massachusetts.

SOURCES:

https://finance.yahoo.com/news/significant-real-world-evidence-confirms-123000247.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:

2018

https://pharmaceuticalintelligence.com/2018/06/10/patient-reported-outcomes-study-presented-at-sleep-2018-provides-confirmatory-real-world-evidence-of-the-previously-presented-7-hour-action-of-remfresh-the-first-continuous-release-and-absorp/

2017

https://pharmaceuticalintelligence.com/2017/10/02/2017-nobel-prize-in-physiology-or-medicine-jointly-to-jeffrey-c-hall-michael-rosbash-and-michael-w-young-for-their-discoveries-of-molecular-mechanisms-controlling-the-circadian-rhythm/

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

2016

https://pharmaceuticalintelligence.com/2016/03/16/sleep-science/

2013

https://pharmaceuticalintelligence.com/2013/03/09/melatonin-and-its-effect-on-acetylcholinesterase-activity-in-erythrocytes/

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

The relationship between gut microbial metabolism and mental health is one of the most intriguing and controversial topics in microbiome research. Bidirectional microbiota–gut–brain communication has mostly been explored in animal models, with human research lagging behind. Large-scale metagenomics studies could facilitate the translational process, but their interpretation is hampered by a lack of dedicated reference databases and tools to study the microbial neuroactive potential.

 

Out of all the many ways, the teeming ecosystem of microbes in a person’s gut and other tissues might affect health. But, its potential influences on the brain may be the most provocative for research. Several studies in mice had indicated that gut microbes can affect behavior, and small scale studies on human beings suggested this microbial repertoire is altered in depression. Studies by two large European groups have found that several species of gut bacteria are missing in people with depression. The researchers can’t say whether the absence is a cause or an effect of the illness, but they showed that many gut bacteria could make substances that affect the nerve cell function—and maybe the mood.

 

Butyrate-producing Faecalibacterium and Coprococcus bacteria were consistently associated with higher quality of life indicators. Together with DialisterCoprococcus spp. was also depleted in depression, even after correcting for the confounding effects of antidepressants. Two kinds of microbes, Coprococcus and Dialister, were missing from the microbiomes of the depressed subjects, but not from those with a high quality of life. The researchers also found the depressed people had an increase in bacteria implicated in Crohn disease, suggesting inflammation may be at fault.

 

Looking for something that could link microbes to mood, researchers compiled a list of 56 substances important for proper functioning of nervous system that gut microbes either produce or break down. They found, for example, that Coprococcus seems to have a pathway related to dopamine, a key brain signal involved in depression, although they have no evidence how this might protect against depression. The same microbe also makes an anti-inflammatory substance called butyrate, and increased inflammation is implicated in depression.

 

Still, it is very much unclear that how microbial compounds made in the gut might influence the brain. One possible channel is the vagus nerve, which links the gut and brain. Resolving the microbiome-brain connection might lead to novel therapies. Some physicians and companies are already exploring typical probiotics, oral bacterial supplements, for depression, although they don’t normally include the missing gut microbes identified in the new study.

 

References:

 

https://www.sciencemag.org/news/2019/02/evidence-mounts-gut-bacteria-can-influence-mood-prevent-depression?utm_source=Nature+Briefing

 

https://www.nature.com/articles/s41564-018-0337-x

 

https://www.ncbi.nlm.nih.gov/pubmed/22968153

 

https://www.ncbi.nlm.nih.gov/pubmed/24888394

 

https://www.ncbi.nlm.nih.gov/pubmed/27067014

 

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