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Archive for the ‘Cardiovascular and Vascular Systems’ Category


Artificial Intelligence and Cardiovascular Disease

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

 

Cardiology is a vast field that focuses on a large number of diseases specifically dealing with the heart, the circulatory system, and its functions. As such, similar symptomatologies and diagnostic features may be present in an individual, making it difficult for a doctor to easily isolate the actual heart-related problem. Consequently, the use of artificial intelligence aims to relieve doctors from this hurdle and extend better quality to patients. Results of screening tests such as echocardiograms, MRIs, or CT scans have long been proposed to be analyzed using more advanced techniques in the field of technology. As such, while artificial intelligence is not yet widely-used in clinical practice, it is seen as the future of healthcare.

 

The continuous development of the technological sector has enabled the industry to merge with medicine in order to create new integrated, reliable, and efficient methods of providing quality health care. One of the ongoing trends in cardiology at present is the proposed utilization of artificial intelligence (AI) in augmenting and extending the effectiveness of the cardiologist. This is because AI or machine-learning would allow for an accurate measure of patient functioning and diagnosis from the beginning up to the end of the therapeutic process. In particular, the use of artificial intelligence in cardiology aims to focus on research and development, clinical practice, and population health. Created to be an all-in-one mechanism in cardiac healthcare, AI technologies incorporate complex algorithms in determining relevant steps needed for a successful diagnosis and treatment. The role of artificial intelligence specifically extends to the identification of novel drug therapies, disease stratification or statistics, continuous remote monitoring and diagnostics, integration of multi-omic data, and extension of physician effectivity and efficiency.

 

Artificial intelligence – specifically a branch of it called machine learning – is being used in medicine to help with diagnosis. Computers might, for example, be better at interpreting heart scans. Computers can be ‘trained’ to make these predictions. This is done by feeding the computer information from hundreds or thousands of patients, plus instructions (an algorithm) on how to use that information. This information is heart scans, genetic and other test results, and how long each patient survived. These scans are in exquisite detail and the computer may be able to spot differences that are beyond human perception. It can also combine information from many different tests to give as accurate a picture as possible. The computer starts to work out which factors affected the patients’ outlook, so it can make predictions about other patients.

 

In current medical practice, doctors will use risk scores to make treatment decisions for their cardiac patients. These are based on a series of variables like weight, age and lifestyle. However, they do not always have the desired levels of accuracy. A particular example of the use of artificial examination in cardiology is the experimental study on heart disease patients, published in 2017. The researchers utilized cardiac MRI-based algorithms coupled with a 3D systolic cardiac motion pattern to accurately predict the health outcomes of patients with pulmonary hypertension. The experiment proved to be successful, with the technology being able to pick-up 30,000 points within the heart activity of 250 patients. With the success of the aforementioned study, as well as the promise of other researches on artificial intelligence, cardiology is seemingly moving towards a more technological practice.

 

One study was conducted in Finland where researchers enrolled 950 patients complaining of chest pain, who underwent the centre’s usual scanning protocol to check for coronary artery disease. Their outcomes were tracked for six years following their initial scans, over the course of which 24 of the patients had heart attacks and 49 died from all causes. The patients first underwent a coronary computed tomography angiography (CCTA) scan, which yielded 58 pieces of data on the presence of coronary plaque, vessel narrowing and calcification. Patients whose scans were suggestive of disease underwent a positron emission tomography (PET) scan which produced 17 variables on blood flow. Ten clinical variables were also obtained from medical records including sex, age, smoking status and diabetes. These 85 variables were then entered into an artificial intelligence (AI) programme called LogitBoost. The AI repeatedly analysed the imaging variables, and was able to learn how the imaging data interacted and identify the patterns which preceded death and heart attack with over 90% accuracy. The predictive performance using the ten clinical variables alone was modest, with an accuracy of 90%. When PET scan data was added, accuracy increased to 92.5%. The predictive performance increased significantly when CCTA scan data was added to clinical and PET data, with accuracy of 95.4%.

 

Another study findings showed that applying artificial intelligence (AI) to the electrocardiogram (ECG) enables early detection of left ventricular dysfunction and can identify individuals at increased risk for its development in the future. Asymptomatic left ventricular dysfunction (ALVD) is characterised by the presence of a weak heart pump with a risk of overt heart failure. It is present in three to six percent of the general population and is associated with reduced quality of life and longevity. However, it is treatable when found. Currently, there is no inexpensive, noninvasive, painless screening tool for ALVD available for diagnostic use. When tested on an independent set of 52,870 patients, the network model yielded values for the area under the curve, sensitivity, specificity, and accuracy of 0.93, 86.3 percent, 85.7 percent, and 85.7 percent, respectively. Furthermore, in patients without ventricular dysfunction, those with a positive AI screen were at four times the risk of developing future ventricular dysfunction compared with those with a negative screen.

 

In recent years, the analysis of big data database combined with computer deep learning has gradually played an important role in biomedical technology. For a large number of medical record data analysis, image analysis, single nucleotide polymorphism difference analysis, etc., all relevant research on the development and application of artificial intelligence can be observed extensively. For clinical indication, patients may receive a variety of cardiovascular routine examination and treatments, such as: cardiac ultrasound, multi-path ECG, cardiovascular and peripheral angiography, intravascular ultrasound and optical coherence tomography, electrical physiology, etc. By using artificial intelligence deep learning system, the investigators hope to not only improve the diagnostic rate and also gain more accurately predict the patient’s recovery, improve medical quality in the near future.

 

The primary issue about using artificial intelligence in cardiology, or in any field of medicine for that matter, is the ethical issues that it brings about. Physicians and healthcare professionals prior to their practice swear to the Hippocratic Oath—a promise to do their best for the welfare and betterment of their patients. Many physicians have argued that the use of artificial intelligence in medicine breaks the Hippocratic Oath since patients are technically left under the care of machines than of doctors. Furthermore, as machines may also malfunction, the safety of patients is also on the line at all times. As such, while medical practitioners see the promise of artificial technology, they are also heavily constricted about its use, safety, and appropriateness in medical practice.

 

Issues and challenges faced by technological innovations in cardiology are overpowered by current researches aiming to make artificial intelligence easily accessible and available for all. With that in mind, various projects are currently under study. For example, the use of wearable AI technology aims to develop a mechanism by which patients and doctors could easily access and monitor cardiac activity remotely. An ideal instrument for monitoring, wearable AI technology ensures real-time updates, monitoring, and evaluation. Another direction of cardiology in AI technology is the use of technology to record and validate empirical data to further analyze symptomatology, biomarkers, and treatment effectiveness. With AI technology, researchers in cardiology are aiming to simplify and expand the scope of knowledge on the field for better patient care and treatment outcomes.

 

References:

 

https://www.news-medical.net/health/Artificial-Intelligence-in-Cardiology.aspx

 

https://www.bhf.org.uk/informationsupport/heart-matters-magazine/research/artificial-intelligence

 

https://www.medicaldevice-network.com/news/heart-attack-artificial-intelligence/

 

https://www.nature.com/articles/s41569-019-0158-5

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711980/

 

www.j-pcs.org/article.asp

http://www.onlinejacc.org/content/71/23/2668

http://www.scielo.br/pdf/ijcs/v30n3/2359-4802-ijcs-30-03-0187.pdf

 

https://www.escardio.org/The-ESC/Press-Office/Press-releases/How-artificial-intelligence-is-tackling-heart-disease-Find-out-at-ICNC-2019

 

https://clinicaltrials.gov/ct2/show/NCT03877614

 

https://www.europeanpharmaceuticalreview.com/news/82870/artificial-intelligence-ai-heart-disease/

 

https://www.frontiersin.org/research-topics/10067/current-and-future-role-of-artificial-intelligence-in-cardiac-imaging

 

https://www.news-medical.net/health/Artificial-Intelligence-in-Cardiology.aspx

 

https://www.sciencedaily.com/releases/2019/05/190513104505.htm

 

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Digital Therapeutics: A Threat or Opportunity to Pharmaceuticals


Digital Therapeutics: A Threat or Opportunity to Pharmaceuticals

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

 

Digital Therapeutics (DTx) have been defined by the Digital Therapeutics Alliance (DTA) as “delivering evidence based therapeutic interventions to patients, that are driven by software to prevent, manage or treat a medical disorder or disease”. They might come in the form of a smart phone or computer tablet app, or some form of a cloud-based service connected to a wearable device. DTx tend to fall into three groups. Firstly, developers and mental health researchers have built digital solutions which typically provide a form of software delivered Cognitive-Behaviour Therapies (CBT) that help patients change behaviours and develop coping strategies around their condition. Secondly there are the group of Digital Therapeutics which target lifestyle issues, such as diet, exercise and stress, that are associated with chronic conditions, and work by offering personalized support for goal setting and target achievement. Lastly, DTx can be designed to work in combination with existing medication or treatments, helping patients manage their therapies and focus on ensuring the therapy delivers the best outcomes possible.

 

Pharmaceutical companies are clearly trying to understand what DTx will mean for them. They want to analyze whether it will be a threat or opportunity to their business. For a long time, they have been providing additional support services to patients who take relatively expensive drugs for chronic conditions. A nurse-led service might provide visits and telephone support to diabetics for example who self-inject insulin therapies. But DTx will help broaden the scope of support services because they can be delivered cost-effectively, and importantly have the ability to capture real-world evidence on patient outcomes. They will no-longer be reserved for the most expensive drugs or therapies but could apply to a whole range of common treatments to boost their efficacy. Faced with the arrival of Digital Therapeutics either replacing drugs, or playing an important role alongside therapies, pharmaceutical firms have three options. They can either ignore DTx and focus on developing drug therapies as they have done; they can partner with a growing number of DTx companies to develop software and services complimenting their drugs; or they can start to build their own Digital Therapeutics to work with their products.

 

Digital Therapeutics will have knock-on effects in health industries, which may be as great as the introduction of therapeutic apps and services themselves. Together with connected health monitoring devices, DTx will offer a near constant stream of data about an individuals’ behavior, real world context around factors affecting their treatment in their everyday lives and emotional and physiological data such as blood pressure and blood sugar levels. Analysis of the resulting data will help create support services tailored to each patient. But who stores and analyses this data is an important question. Strong data governance will be paramount to maintaining trust, and the highly regulated pharmaceutical industry may not be best-placed to handle individual patient data. Meanwhile, the health sector (payers and healthcare providers) is becoming more focused on patient outcomes, and payment for value not volume. The future will say whether pharmaceutical firms enhance the effectiveness of drugs with DTx, or in some cases replace drugs with DTx.

 

Digital Therapeutics have the potential to change what the pharmaceutical industry sells: rather than a drug it will sell a package of drugs and digital services. But they will also alter who the industry sells to. Pharmaceutical firms have traditionally marketed drugs to doctors, pharmacists and other health professionals, based on the efficacy of a specific product. Soon it could be paid on the outcome of a bundle of digital therapies, medicines and services with a closer connection to both providers and patients. Apart from a notable few, most pharmaceutical firms have taken a cautious approach towards Digital Therapeutics. Now, it is to be observed that how the pharmaceutical companies use DTx to their benefit as well as for the benefit of the general population.

 

References:

 

https://eloqua.eyeforpharma.com/LP=23674?utm_campaign=EFP%2007MAR19%20EFP%20Database&utm_medium=email&utm_source=Eloqua&elqTrackId=73e21ae550de49ccabbf65fce72faea0&elq=818d76a54d894491b031fa8d1cc8d05c&elqaid=43259&elqat=1&elqCampaignId=24564

 

https://www.s3connectedhealth.com/resources/white-papers/digital-therapeutics-pharmas-threat-or-opportunity/

 

http://www.pharmatimes.com/web_exclusives/digital_therapeutics_will_transform_pharma_and_healthcare_industries_in_2019._heres_how._1273671

 

https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/exploring-the-potential-of-digital-therapeutics

 

https://player.fm/series/digital-health-today-2404448/s9-081-scaling-digital-therapeutics-the-opportunities-and-challenges

 

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

 

Stroke is a leading cause of death worldwide and the most common cause of long-term disability amongst adults, more particularly in patients with diabetes mellitus and arterial hypertension. Increasing evidence suggests that disordered physiological variables following acute ischaemic stroke, especially hyperglycaemia, adversely affect outcomes.

 

Post-stroke hyperglycaemia is common (up to 50% of patients) and may be rather prolonged, regardless of diabetes status. A substantial body of evidence has demonstrated that hyperglycaemia has a deleterious effect upon clinical and morphological stroke outcomes. Therefore, hyperglycaemia represents an attractive physiological target for acute stroke therapies.

 

However, whether intensive glycaemic manipulation positively influences the fate of ischaemic tissue remains unknown. One major adverse event of management of hyperglycaemia with insulin (either glucose-potassium-insulin infusions or intensive insulin therapy) is the occurrence of hypoglycaemia, which can also induce cerebral damage.

 

Doctors all over the world have debated whether intensive glucose management, which requires the use of IV insulin to bring blood sugar levels down to 80-130 mg/dL, or standard glucose control using insulin shots, which aims to get glucose below 180 mg/dL, lead to better outcomes after stroke.

 

A period of hyperglycemia is common, with elevated blood glucose in the periinfarct period consistently linked with poor outcome in patients with and without diabetes. The mechanisms that underlie this deleterious effect of dysglycemia on ischemic neuronal tissue remain to be established, although in vitro research, functional imaging, and animal work have provided clues.

 

While prompt correction of hyperglycemia can be achieved, trials of acute insulin administration in stroke and other critical care populations have been equivocal. Diabetes mellitus and hyperglycemia per se are associated with poor cerebrovascular health, both in terms of stroke risk and outcome thereafter.

 

Interventions to control blood sugar are available but evidence of cerebrovascular efficacy are lacking. In diabetes, glycemic control should be part of a global approach to vascular risk while in acute stroke, theoretical data suggest intervention to lower markedly elevated blood glucose may be of benefit, especially if thrombolysis is administered.

 

Both hypoglycaemia and hyperglycaemia may lead to further brain injury and clinical deterioration; that is the reason these conditions should be avoided after stroke. Yet, when correcting hyperglycaemia, great care should be taken not to switch the patient into hypoglycaemia, and subsequently aggressive insulin administration treatment should be avoided.

 

Early identification and prompt management of hyperglycaemia, especially in acute ischaemic stroke, is recommended. Although the appropriate level of blood glucose during acute stroke is still debated, a reasonable approach is to keep the patient in a mildly hyperglycaemic state, rather than risking hypoglycaemia, using continuous glucose monitoring.

 

The primary results from the Stroke Hyperglycemia Insulin Network Effort (SHINE) study, a large, multisite clinical study showed that intensive glucose management did not improve functional outcomes at 90 days after stroke compared to standard glucose therapy. In addition, intense glucose therapy increased the risk of very low blood glucose (hypoglycemia) and required a higher level of care such as increased supervision from nursing staff, compared to standard treatment.

 

References:

 

https://www.nih.gov/news-events/news-releases/nih-study-provides-answer-long-held-debate-blood-sugar-control-after-stroke

 

https://www.ncbi.nlm.nih.gov/pubmed/27873213

 

https://www.ncbi.nlm.nih.gov/pubmed/19342845

 

https://www.ncbi.nlm.nih.gov/pubmed/20491782

 

https://www.ncbi.nlm.nih.gov/pubmed/21211743

 

https://www.ncbi.nlm.nih.gov/pubmed/18690907

 

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Live 11:00 AM- 12:00 Mediterranean Diet and Lifestyle: A Symposium on Diet and Human Health : Opening Remarks October 19, 2018

Reporter: Stephen J. Williams, Ph.D.

11:00 Welcome

 

 

Prof. Antonio Giordano, MD, PhD.

Director and President of the Sbarro Health Research Organization, College of Science and Technology, Temple University

Welcome to this symposium on Italian lifestyle and health.  This is similar to a symposium we had organized in New York.  A year ago Bloomberg came out with a study on higher longevity of the italian population and this study was concluded that this increased longevity was due to the italian lifestyle and diet especially in the southern part of Italy, a region which is older than Rome (actually founded by Greeks and Estonians).  However this symposium will delve into the components of this healthy Italian lifestyle which contributes to this longevity effect.  Some of this work was done in collaboration with Temple University and sponsored by the Italian Consulate General in Philadelphia ( which sponsors programs in this area called Ciao Philadelphia).

Greetings: Fucsia Nissoli Fitzgerald, Deputy elected in the Foreign Circumscription – North and Central America Division

Speaking for the Consulate General is Francesca  Cardurani-Meloni.   I would like to talk briefly about the Italian cuisine and its evolution, from the influence of the North and South Italy, economic factors, and influence by other cultures.  Italian cooking is about simplicity, cooking with what is in season and freshest.  The meal is not about the food but about comfort around the table, and comparible to a cullinary heaven, about sharing with family and friends, and bringing the freshest ingredients to the table.

Consul General, Honorable Pier Attinio Forlano, General Consul of Italy in Philadelphia

 

11:30 The Impact of Environment and Life Style in Human Disease

Prof. Antonio Giordano MD, PhD.

 

 

 

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  1. Lungs can supply blood stem cells and also produce platelets: Lungs, known primarily for breathing, play a previously unrecognized role in blood production, with more than half of the platelets in a mouse’s circulation produced there. Furthermore, a previously unknown pool of blood stem cells has been identified that is capable of restoring blood production when bone marrow stem cells are depleted.

 

  1. A new drug for multiple sclerosis: A new multiple sclerosis (MS) drug, which grew out of the work of UCSF (University of California, San Francisco) neurologist was approved by the FDA. Ocrelizumab, the first drug to reflect current scientific understanding of MS, was approved to treat both relapsing-remitting MS and primary progressive MS.

 

  1. Marijuana legalized – research needed on therapeutic possibilities and negative effects: Recreational marijuana will be legal in California starting in January, and that has brought a renewed urgency to seek out more information on the drug’s health effects, both positive and negative. UCSF scientists recognize marijuana’s contradictory status: the drug has proven therapeutic uses, but it can also lead to tremendous public health problems.

 

  1. Source of autism discovered: In a finding that could help unlock the fundamental mysteries about how events early in brain development lead to autism, researchers traced how distinct sets of genetic defects in a single neuronal protein can lead to either epilepsy in infancy or to autism spectrum disorders in predictable ways.

 

  1. Protein found in diet responsible for inflammation in brain: Ketogenic diets, characterized by extreme low-carbohydrate, high-fat regimens are known to benefit people with epilepsy and other neurological illnesses by lowering inflammation in the brain. UCSF researchers discovered the previously undiscovered mechanism by which a low-carbohydrate diet reduces inflammation in the brain. Importantly, the team identified a pivotal protein that links the diet to inflammatory genes, which, if blocked, could mirror the anti-inflammatory effects of ketogenic diets.

 

  1. Learning and memory failure due to brain injury is now restorable by drug: In a finding that holds promise for treating people with traumatic brain injury, an experimental drug, ISRIB (integrated stress response inhibitor), completely reversed severe learning and memory impairments caused by traumatic brain injury in mice. The groundbreaking finding revealed that the drug fully restored the ability to learn and remember in the brain-injured mice even when the animals were initially treated as long as a month after injury.

 

  1. Regulatory T cells induce stem cells for promoting hair growth: In a finding that could impact baldness, researchers found that regulatory T cells, a type of immune cell generally associated with controlling inflammation, directly trigger stem cells in the skin to promote healthy hair growth. An experiment with mice revealed that without these immune cells as partners, stem cells cannot regenerate hair follicles, leading to baldness.

 

  1. More intake of good fat is also bad: Liberal consumption of good fat (monounsaturated fat) – found in olive oil and avocados – may lead to fatty liver disease, a risk factor for metabolic disorders like type 2 diabetes and hypertension. Eating the fat in combination with high starch content was found to cause the most severe fatty liver disease in mice.

 

  1. Chemical toxicity in almost every daily use products: Unregulated chemicals are increasingly prevalent in products people use every day, and that rise matches a concurrent rise in health conditions like cancers and childhood diseases, Thus, researcher in UCSF is working to understand the environment’s role – including exposure to chemicals – in health conditions.

 

  1. Cytomegalovirus found as common factor for diabetes and heart disease in young women: Cytomegalovirus is associated with risk factors for type 2 diabetes and heart disease in women younger than 50. Women of normal weight who were infected with the typically asymptomatic cytomegalovirus, or CMV, were more likely to have metabolic syndrome. Surprisingly, the reverse was found in those with extreme obesity.

 

References:

 

https://www.ucsf.edu/news/2017/12/409241/most-popular-science-stories-2017

 

https://www.ucsf.edu/news/2017/03/406111/surprising-new-role-lungs-making-blood

 

https://www.ucsf.edu/news/2017/03/406296/new-multiple-sclerosis-drug-ocrelizumab-could-halt-disease

 

https://www.ucsf.edu/news/2017/06/407351/dazed-and-confused-marijuana-legalization-raises-need-more-research

 

https://www.ucsf.edu/news/2017/01/405631/autism-researchers-discover-genetic-rosetta-stone

 

https://www.ucsf.edu/news/2017/09/408366/how-ketogenic-diets-curb-inflammation-brain

 

https://www.ucsf.edu/news/2017/07/407656/drug-reverses-memory-failure-caused-traumatic-brain-injury

 

https://www.ucsf.edu/news/2017/05/407121/new-hair-growth-mechanism-discovered

 

https://www.ucsf.edu/news/2017/06/407536/go-easy-avocado-toast-good-fat-can-still-be-bad-you-research-shows

 

https://www.ucsf.edu/news/2017/06/407416/toxic-exposure-chemicals-are-our-water-food-air-and-furniture

 

https://www.ucsf.edu/news/2017/02/405871/common-virus-tied-diabetes-heart-disease-women-under-50

 

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Regulatory MicroRNAs in Aberrant Cholesterol Transport and Metabolism

Curator: Marzan Khan, B.Sc

Aberrant levels of lipids and cholesterol accumulation in the body lead to cardiometabolic disorders such as atherosclerosis, one of the leading causes of death in the Western World(1). The physical manifestation of this condition is the build-up of plaque along the arterial endothelium causing the arteries to constrict and resist a smooth blood flow(2). This obstructive deposition of plaque is merely the initiation of atherosclerosis and is enriched in LDL cholesterol (LDL-C) as well foam cells which are macrophages carrying an overload of toxic, oxidized LDL(2). As the condition progresses, the plaque further obstructs blood flow and creates blood clots, ultimately leading to myocardial infarction, stroke and other cardiovascular diseases(2). Therefore, LDL is referred to as “the bad cholesterol”(2).

Until now, statins are most widely prescribed as lipid-lowering drugs that inhibit the enzyme 3-hydroxy-3methylgutaryl-CoA reductase (HMGCR), the rate-limiting step in de-novo cholesterol biogenesis (1). But some people cannot continue with the medication due to it’s harmful side-effects(1). With the need to develop newer therapeutics to combat cardiovascular diseases, Harvard University researchers at Massachusetts General Hospital discovered 4 microRNAs that control cholesterol, triglyceride, and glucose homeostasis(3)

MicroRNAs are non-coding, regulatory elements approximately 22 nucleotides long, with the ability to control post-transcriptional expression of genes(3). The liver is the center for carbohydrate and lipid metabolism. Stringent regulation of endogenous LDL-receptor (LDL-R) pathway in the liver is crucial to maintain a minimal concentration of LDL particles in blood(3). A mechanism whereby peripheral tissues and macrophages can get rid of their excess LDL is mediated by ATP-binding cassette, subfamily A, member 1 (ABCA1)(3). ABCA1 consumes nascent HDL particles- dubbed as the “good cholesterol” which travel back to the liver for its contents of triglycerides and cholesterol to be excreted(3).

Genome-wide association studies (GWASs) meta-analysis carried out by the researchers disclosed 4 microRNAs –(miR-128-1, miR-148a, miR-130b, and miR-301b) to lie close to single-nucleotide polymorphisms (SNPs) associated with abnormal metabolism and transport of lipids and cholesterol(3) Experimental analyses carried out on relevant cell types such as the liver and macrophages have proven that these microRNAs bind to the 3’ UTRs of both LDL-R and ABCA1 transporters, and silence their activity. Overexpression of miR-128-1 and miR148a in mice models caused circulating HDL-C to drop. Corroborating the theory under investigation further, their inhibition led to an increased clearance of LDL from the blood and a greater accumulation in the liver(3).

That the antisense inhibition of miRNA-128-1 increased insulin signaling in mice, propels us to hypothesize that abnormal expression of miR-128-1 might cause insulin resistance in metabolic syndrome, and defective insulin signaling in hepatic steatosis and dyslipidemia(3)

Further examination of miR-148 established that Liver-X-Receptor (LXR) activation of the Sterol regulatory element-binding protein 1c (SREBP1c), the transcription factor responsible for controlling  fatty acid production and glucose metabolism, also mediates the expression of miR-148a(4,5) That the promoter region of miR-148 contained binding sites for SREBP1c was shown by chromatin immunoprecipitation combined with massively parallel sequencing (ChIP-seq)(4). More specifically, SREBP1c attaches to the E-box2, E-box3 and E-box4 elements on miR-148-1a promoter sites to control its expression(4).

Earlier, the same researchers- Andres Naars and his team had found another microRNA called miR-33 to block HDL generation, and this blockage to reverse upon antisense targeting of miR-33(6).

These experimental data substantiate the theory of miRNAs being important regulators of lipoprotein receptors and transporter proteins as well as underscore the importance of employing antisense technologies to reverse their gene-silencing effects on LDL-R and ABCA1(4). Such a therapeutic approach, that will consequently lower LDL-C and promote HDL-C seems to be a promising strategy to treat atherosclerosis and other cardiovascular diseases(4).

References:

1.Goedeke L1,Wagschal A2,Fernández-Hernando C3, Näär AM4. miRNA regulation of LDL-cholesterol metabolism. Biochim Biophys Acta. 2016 Dec;1861(12 Pt B):. Biochim Biophys Acta. 2016 Dec;1861(12 Pt B):2047-2052

https://www.ncbi.nlm.nih.gov/pubmed/26968099

2.MedicalNewsToday. Joseph Nordgvist. Atherosclerosis:Causes, Symptoms and Treatments. 13.08.2015

http://www.medicalnewstoday.com/articles/247837.php

3.Wagschal A1,2, Najafi-Shoushtari SH1,2, Wang L1,2, Goedeke L3, Sinha S4, deLemos AS5, Black JC1,6, Ramírez CM3, Li Y7, Tewhey R8,9, Hatoum I10, Shah N11, Lu Y11, Kristo F1, Psychogios N4, Vrbanac V12, Lu YC13, Hla T13, de Cabo R14, Tsang JS11, Schadt E15, Sabeti PC8,9, Kathiresan S4,6,8,16, Cohen DE7, Whetstine J1,6, Chung RT5,6, Fernández-Hernando C3, Kaplan LM6,10, Bernards A1,6,16, Gerszten RE4,6, Näär AM1,2. Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis. . Nat Med.2015 Nov;21(11):1290

https://www.ncbi.nlm.nih.gov/pubmed/26501192

4.Goedeke L1,2,3,4, Rotllan N1,2, Canfrán-Duque A1,2, Aranda JF1,2,3, Ramírez CM1,2, Araldi E1,2,3,4, Lin CS3,4, Anderson NN5,6, Wagschal A7,8, de Cabo R9, Horton JD5,6, Lasunción MA10,11, Näär AM7,8, Suárez Y1,2,3,4, Fernández-Hernando C1,2,3,4. MicroRNA-148a regulates LDL receptor and ABCA1 expression to control circulating lipoprotein levels. Nat Med. 2015 Nov;21(11):1280-9.

https://www.ncbi.nlm.nih.gov/pubmed/26437365

5.Eberlé D1, Hegarty B, Bossard P, Ferré P, Foufelle F. SREBP transcription factors: master regulators of lipid homeostasis. Biochimie. 2004 Nov;86(11):839-48.

https://www.ncbi.nlm.nih.gov/pubmed/15589694

6.Harvard Medical School. News. MicoRNAs and Metabolism.

https://hms.harvard.edu/news/micrornas-and-metabolism

7. MGH – Four microRNAs identified as playing key roles in cholesterol, lipid metabolism

http://www.massgeneral.org/about/pressrelease.aspx?id=1862

 

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

 

  • Cardiovascular Diseases, Volume Three: Etiologies of Cardiovascular Diseases: Epigenetics, Genetics and Genomics,

on Amazon since 11/29/2015

http://www.amazon.com/dp/B018PNHJ84

 

HDL oxidation in type 2 diabetic patients

Larry H. Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/27/hdl-oxidation-in-type-2-diabetic-patients/

 

HDL-C: Target of Therapy – Steven E. Nissen, MD, MACC, Cleveland Clinic vs Peter Libby, MD, BWH

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/11/07/hdl-c-target-of-therapy-steven-e-nissen-md-macc-cleveland-clinic-vs-peter-libby-md-bwh/

 

High-Density Lipoprotein (HDL): An Independent Predictor of Endothelial Function & Atherosclerosis, A Modulator, An Agonist, A Biomarker for Cardiovascular Risk

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/03/31/high-density-lipoprotein-hdl-an-independent-predictor-of-endothelial-function-artherosclerosis-a-modulator-an-agonist-a-biomarker-for-cardiovascular-risk/

 

Risk of Major Cardiovascular Events by LDL-Cholesterol Level (mg/dL): Among those treated with high-dose statin therapy, more than 40% of patients failed to achieve an LDL-cholesterol target of less than 70 mg/dL.

Reporter: Aviva Lev-Ari, PhD., RN

https://pharmaceuticalintelligence.com/2014/07/29/risk-of-major-cardiovascular-events-by-ldl-cholesterol-level-mgdl-among-those-treated-with-high-dose-statin-therapy-more-than-40-of-patients-failed-to-achieve-an-ldl-cholesterol-target-of-less-th/

 

LDL, HDL, TG, ApoA1 and ApoB: Genetic Loci Associated With Plasma Concentration of these Biomarkers – A Genome-Wide Analysis With Replication

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/12/18/ldl-hdl-tg-apoa1-and-apob-genetic-loci-associated-with-plasma-concentration-of-these-biomarkers-a-genome-wide-analysis-with-replication/

 

Two Mutations, in the PCSK9 Gene: Eliminates a Protein involved in Controlling LDL Cholesterol

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/04/15/two-mutations-in-a-pcsk9-gene-eliminates-a-protein-involve-in-controlling-ldl-cholesterol/

Artherogenesis: Predictor of CVD – the Smaller and Denser LDL Particles

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/11/15/artherogenesis-predictor-of-cvd-the-smaller-and-denser-ldl-particles/

 

A Concise Review of Cardiovascular Biomarkers of Hypertension

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/04/25/a-concise-review-of-cardiovascular-biomarkers-of-hypertension/

 

Triglycerides: Is it a Risk Factor or a Risk Marker for Atherosclerosis and Cardiovascular Disease ? The Impact of Genetic Mutations on (ANGPTL4) Gene, encoder of (angiopoietin-like 4) Protein, inhibitor of Lipoprotein Lipase

Reporters, Curators and Authors: Aviva Lev-Ari, PhD, RN and Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/03/13/triglycerides-is-it-a-risk-factor-or-a-risk-marker-for-atherosclerosis-and-cardiovascular-disease-the-impact-of-genetic-mutations-on-angptl4-gene-encoder-of-angiopoietin-like-4-protein-that-in/

 

Excess Eating, Overweight, and Diabetic

Larry H Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/15/excess-eating-overweight-and-diabetic/

 

Obesity Issues

Larry H. Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/12/obesity-issues/

 

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3D Printing for Surgical Planning: The Clinical and Economic Promise using Quantitative Clinical Evidence

Reporter: Aviva Lev-Ari, PhD, RN

The Clinical and Economic Promise of 3D Printing for Surgical Planning

M A K I N G  T H E  C A S E  T H R O U G H  Q U A N T I TAT I V E CLINICAL EVIDENCE

Stratasys engaged Quorum Consulting, experts in health economics and outcomes research, to conduct a comprehensive analysis of the clinical and economic evidence on 3D printing for surgical planning. This white paper, authored by Quorum Consulting, summarizes the result of that analysis.

Wade Aubry1,2, Raj Stewart1 , Chance Scott1 , Jeffrey Chu1

The modern emphasis on evidence-based medicine centers on three core tenets: • Best available research findings • Clinical expertise • Patient value Incorporating cutting-edge technology alongside these principles – often delicately balancing material innovation against scientific rigor, state-of-the-art professional training and experience, and attempts to provide the best care while respecting patient perspectives – is a challenge. 3D printing, however, aligns with the first two tenets, and when appropriately employed, may inform and indirectly influence the third.1

1 Quorum Consulting, Inc., San Francisco, CA, USA

2 University of California, San Francisco; San Francisco, CA, USA

 

3D printing was used in surgical planning applications in a wide range of specialties including cardiothoracic, orthopedic, neurological, reconstructive and transplant surgeries, as well as gastroenterology and surgical oncology. When examining these use cases, five general benefits emerge in association with 3D printing for surgical planning:

  • Patient communication
  • Anatomic familiarity
  • Procedure practice
  • Procedure selection
  • Patient selection / rule-out

 

INDICATION-SPECIFIC UTILIZATION AND EVIDENCEBASED EFFECTIVENESS DATA / RESULTS

  • Cardiothoracic surgery
  • Neurosurgery
  • Reconstructive surgeries

 

CONCLUSION

In a healthcare environment continuing to shift towards value- and outcome-contingent systems that penalize providers for inefficiencies and suboptimal outcomes in rendered care, 3D printed models for surgical planning – with their ability to facilitate procedural efficiency, improve treatment outcomes, and reduce downstream re-intervention costs – offer high potential value. Patients, clinicians and hospitals all have a vested interest in quality, affordable patient care and service, and surgical planning with 3D models appeals to each of these stakeholders.

Accordingly, results and trends from published literature and healthcare data support the effectiveness of 3D printing for surgical planning. As shown for several surgical procedures, clinicians with access to 3D printed models are able to provide better, more efficient care likely to improve patient outcomes and reduce the need for additional surgical interventions. Procedures that would most justify the financial and resource cost in creating 3D printed patient models are those with long operating times, high Relative Value Units (RVUs), greater risk and uncertainty, and risk of complications. Concurrently, this quality care is also potentially less costly and more profitable to providers. Amidst the growing commercial market for 3D printers and related technologies, there are some key differentiators when evaluating utility for surgical planning. As reflected in clinician surveys, the most effective 3D models should capably depict complex, fine anatomy with high fidelity to actual patient physiologies. This degree of fidelity crosses several characteristics:

  • Accurate depiction of a variety of colors
  • Simulation of multiple textures
  • Manipulability,

including the ability to be dissected or probed with surgical instruments.22 Given these real-world requirements, next generation multi-material and multi-color 3D printers likely represent the best option for facilities and clinicians. Viewed objectively, additional data addressing the quantitative impact of 3D printed models is needed. Preferably, this data will be generated from well-designed, patient outcome-oriented studies. However, in the interim, the tide of evidence favors 3D printed models for surgical planning, particularly for leading-edge clinicians and healthcare administrators who are able to recognize its value.

A Brief RVU Primer:

Relative Value Units (RVUs) are used by Medicare to determine reimbursement rates for a given service:

• For each service, Medicare determines the cost value of three primary components – physician’s work, practice expenses and malpractice insurance.

• These three components are then adjusted based on differences in living and business costs nationwide, using a factor called the Geographic Practice Cost Index (GPCI).

• The adjusted values are multiplied by an annual conversion factor, established by the U.S. Congress, and totaled to calculate final reimbursement rates.

SOURCE

http://s3.amazonaws.com/engineering.whitepapers/Stratasys/SurgicalPlanningPromise_Quorum_WP.pdf

From: Medical Design & Outsourcing <newsletters@e.medicaldesignandoutsourcing.com>

Reply-To: <newsletters@e.medicaldesignandoutsourcing.com>

Date: Wednesday, February 15, 2017 at 2:00 PM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: The Clinical and Economic Promise of Surgical Planning Using 3D Printing

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

Curator: Aviva Lev-Ari, PhD, RN

 

Technologies for Patient-centered Medicine: From R&D in Biologics to New Medical Devices

 

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