Leaders in Pharmaceutical Business Intelligence Group, LLC, Doing Business As LPBI Group, Newton, MA

Archive for the ‘Population Health Management, Genetics & Pharmaceutical’ Category

Heart Risks and Hormones (HRT) in Menopause: Contradiction or Clarification?

Posted in Biomarkers & Medical Diagnostics, Bone Disease and Musculoskeletal Disease, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Chemical Biology and its relations to Metabolic Disease, FDA Regulatory Affairs, Health Economics and Outcomes Research, Origins of Cardiovascular Disease, Pharmaceutical R&D Investment, Population Health Management, Genetics & Pharmaceutical, Population Health Management, Nutrition and Phytochemistry, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Reproductive Biology & Bio Instrumentation, tagged Brigham and Women's Hospital, Estrogen patch, Hormone therapy, North American Menopause Society, Progesterone, WHI on October 3, 2012| Leave a Comment »

Reporter: Aviva Lev-Ari, PhD, RN

 

 

Study Counters WHI on Heart Risk of Hormones in Menopause

By Crystal Phend, Senior Staff Writer, MedPage Today

Published: October 03, 2012

 

 

 

 

Hormone therapy may actually help the heart in some respects for newly menopausal women, a randomized trial showed, although the impact on hard outcomes like stroke and breast cancer still remains to be seen.

Oral estrogen plus progesterone improved lipid levels, while a transdermal patch improved insulin sensitivity in the KEEPS trial, according to researchers led by S. Mitchell Harman, MD, PhD, of the nonprofit Kronos Longevity Research Institute, which sponsored the trial.

Neither combination hormone treatment altered atherosclerosis progression or raised blood pressure, according to a Kronos press release summarizing a report to be presented Wednesday at the North American Menopause Society meeting in Orlando.

“The results provide reassurance for women who are recently menopausal and taking hormone therapy for short-term treatment of menopausal symptoms,” the group concluded in the release.

The need for reassurance stems from results released a decade ago from the Women’s Health Initiative (WHI), which showed an elevated risk of cardiovascular disease, stroke, and thromboembolic events as well as breast cancer with estrogen plus progestin.

Subsequent studies largely affirmed those risks and pointed to others, including ovarian cancer, lung cancer mortality, and probable dementia.

Menopause organizations largely recommended “the lowest dose for the shortest time” but have started backing away from that stance, instead endorsing a more flexible approach based on type and timing of hormone therapy.

Contradiction or Clarification?

The new study didn’t show significant differences in adverse events between women taking oral or transdermal estrogen with progesterone and those on placebo, including:

• Breast cancer
• Endometrial cancer
• Myocardial infarction
• Transient ischemic attack
• Stroke
• Venous thromboembolic disease

“However, the absolute numbers of such events were extremely small in all three treatment groups, making definitive conclusions impossible,” the researchers acknowledged.

Nor is the KEEPS study ever likely to definitively determine safety, because it was too small to assess clinical events, session moderator and presenter JoAnn E. Manson, MD, DrPH, commented in an email to ABC News and MedPage Today.

But that wasn’t the point of the trial, said Manson, who serves as chief of preventive medicine at Brigham and Women’s Hospital in Boston and is outgoing president of the menopause society.

“The KEEPS trial does not challenge the conclusions of WHI about the risks of clinical events with hormone therapy,” she wrote. “KEEPS and WHI were addressing entirely different questions.”

The earlier study tested hormone therapy as it was in clinical use at the time, for cardiovascular prevention based on epidemiologic suggestion of benefit.

The evidence has clearly come down against hormone therapy for that use, Manson noted.

The question that KEEPS is now answering is how perimenopausal women should approach management of menopausal symptoms — if relatively short periods of hormone therapy are safe, noted Sharonne N. Hayes MD, of the Women’s Heart Clinic at the Mayo Clinic in Rochester, Minn.

So it may be enough that these risks weren’t substantially elevated in the trial, several experts contacted by ABC and MedPage Today agreed.

“The safety of HRT in this newly menopausal population is very reassuring and will likely increase usage as well as demand for HRT in women suffering with vasomotor symptoms,” commented neurologist Cynthia L. Harden, MD, of the North Shore-Long Island Jewish Health System in Great Neck, N.Y., who said the KEEPS data adds nuance rather than contradiction.

The results don’t change the post-WHI clinical approach of yearly reassessment targeting discontinuation after a few years of hormone therapy, added Wendy Vitek, MD, an ob/gyn at the University of Rochester Medical Center in Rochester, N.Y.

Different Populations, Different Drugs

There were some differences between the Women’s Health Initiative and the KEEPS trial that may lead to real differences in outcome, though, researchers suggested.

The KEEPS trial included 727 healthy women ages 42 to 58 who were all within 3 years of the onset of menopause at baseline.

The mean age was 52, whereas the vast majority of women in the nine hormone therapy trials done to date, including the WHI, were in their 60s.

KEEPS randomized its newly-menopausal population to double-blind treatment with cyclical micronized progesterone (Prometrium) plus one of the following:

•  

  Oral conjugated equine estrogen (Premarin) given at 0.45 mg/day, which was lower than the 0.625 mg/d used in the WHI

•  

  Transdermal estradiol (Climara) at 50 µg/day, an option not available in the WHI

• Placebo

 

Even the two different estrogen administration routes showed some differential effects on cardiovascular risk factors, the investigators pointed out.

HDL cholesterol and triglycerides rose while LDL fell with the oral estrogen.

The patch didn’t affect any lipid levels, but it did lower insulin resistance, which the oral form did not.

Neither drug boosted systolic or diastolic blood pressure, unlike the blood pressure increases seen with oral estrogen in the WHI.

Atherosclerosis neither accelerated nor reversed with 48 months of either treatment as monitored by carotid ultrasound, although there was a nonsignificant trend for less coronary artery calcium accumulation compared with placebo, noted Harman, who also practices at the Phoenix VA Medical System.

But that’s not necessarily reassuring with regard to cardiovascular outcomes for this younger group of women, Jacques Rossouw, MBChB, MD, chief of the WHI Branch of the National Heart, Lung and Blood Institute, noted in an email to ABC and MedPage Today.

“Changes in arteries in younger women have little relation to risk of stroke,” he explained. “Estrogen/progestin have [effects] on clotting mechanisms, on inflammation mechanisms. Those are things that trigger acute heart attack or stroke [in younger women]. Perfectly healthy young women can have strokes but have completely normal arteries. ”

Really, “the lack of effect on atherosclerosis reinforces the results of the WHI that hormone therapy is not good preventive therapy for heart disease,” added Lewis H. Kuller, MD, DrPH, of the University of Pittsburgh.

 

As expected, hormone therapy cut down on hot flashes and night sweats while raising bone density and mood, co-investigator Sanjay Asthana, MD, of the University of Wisconsin in Madison, said in the Kronos press release.

Sexual function also improved compared with placebo, in accord with the reduction in vaginal dryness although not the lack of improvement in sex drive seen in prior studies.

“KEEPS also highlights the need for individualized decision making about hormone therapy, given that oral conjugated equine estrogen and transdermal estradiol may have different profiles of effects, and different women have different symptom profiles and priorities for treatment,” the researchers noted in the press release.

KEEPS Sponsor Biased?

Kronos has long had an openly declared interest in countering the 2002 WHI findings of increased health risks from postmenopausal hormone therapy. In 2007, it issued a series of press releases attacking the WHI conclusions and touting KEEPS — one of which included a synopsis describing the nascent trial as “one of the studies to refute the WHI.”

The money behind Kronos comes from the Aurora Foundation. The latter was established by John Sperling, the billionaire founder of the University of Phoenix and other for-profit education ventures.

About 90% of Kronos’ $5.3 million in funding in 2010, the last year for which public records are available, came from Aurora. The $4.8 million given to Kronos that year was more than half of Aurora’s total giving.

Sperling, who is the foundation’s sole trustee, has a long history of involvement in sometimes controversial biological research involving life extension. He funded a successful, multimillion-dollar effort to clone his girlfriend’s dog in 2007, and later a similar cloning project for house cats.

Previously, he had bankrolled a medical clinic in a Phoenix suburb called the Kronos Group — not related to the Kronos Longevity Research Institute — that offered anti-aging remedies to older patients. It has since morphed into Kronos Optimal Health, which markets relatively conventional health and wellness programs to employers and individuals.

A 2004 article in Wired magazine reported that Sperling had also invested in a group of biotechnology companies seeking to develop anti-aging technologies based on cloning and stem cells.

The study was sponsored by the Kronos Longevity Research Institute with funding from the National Institutes of Health for the ancillary cognitive and affective portion.

The presentation was supported by grant funding from Noven Pharmaceuticals.

This article was developed in collaboration with ABC News. 

 

Primary source: North American Menopause Society
Source reference:
Manson JE, et al “New findings from the Kronos early estrogen prevention study (keeps) Randomized trial” NAMS2012.

---

Crystal Phend

Staff Writer

Crystal Phend joined MedPage Today in 2006 after roaming conference halls for publications including The Medical Post, Oncology Times, Doctor’s Guide, and the journal IDrugs. When not covering medical meetings, she writes from Silicon Valley, just south of the San Francisco fog.

SOURCE:

http://www.medpagetoday.com/MeetingCoverage/NAMS/35106?utm_source=breaking-news&utm_medium=email&utm_campaign=breaking-news

http://www.medpagetoday.com/OBGYN/HRT/32952

http://www.medpagetoday.com/OBGYN/HRT/31394

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading...

Read Full Post »

Mitochondria: Origin from oxygen free environment, role in aerobic glycolysis, metabolic adaptation

Posted in Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cardiovascular Pharmacogenomics, Cell Biology, Signaling & Cell Circuits, Chemical Biology and its relations to Metabolic Disease, Computational Biology/Systems and Bioinformatics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Glycobiology: Biopharmaceutical Production, Pharmacodynamics and Pharmacokinetics, International Global Work in Pharmaceutical, Metabolomics, Molecular Genetics & Pharmaceutical, Nutrigenomics, Nutrition, Personalized and Precision Medicine & Genomic Research, Pharmacotherapy of Cardiovascular Disease, Population Health Management, Genetics & Pharmaceutical, Population Health Management, Nutrition and Phytochemistry, Scientist: Career considerations, Systemic Inflammatory Response Related Disorders, Technology Transfer: Biotech and Pharmaceutical, tagged Acetyl-CoA, Adenosine triphosphate, anaerobic and aerobic gycolysis, ATP, ATP demands, Cellular respiration, Citric acid cycle, fermentation, gluconeogenesis, hydrophobic interaction, N:S, overflow at branch points, oxidative stress, Pasteur effect, PFK 2, plant protein diet, protein calorie malnutrition, pyruvate dehydrogenase, Saccharomyces cerevisiae, SIRT3, synthetic small DNA ligands, TCA cycle intermediates, Warburg Effect on September 26, 2012| 26 Comments »

 

English: A diagram of cellular respiration including glycolysis, Krebs cycle, citric acid cycle, and the electron transport chain (Photo credit: Wikipedia)

Reporter and Curator: Larry H Bernstein, MD, FACP

Introduction

Mitochondria are essential for life, and are critical for the generation of ATP. Otto Warburg won the Nobel Prize in 1918 for his studies of respiration and he described a situation of impaired respiration in cancer cells causing them to produce lactic acid, like bacteria. This has been termed facultative anaerobic glycolysis. The metabolic explanation for mitochondrial respiration had to await the Nobel discoveries of the Krebs cycle and high energy ~P in acetyl CoA by Fritz Lippman. The Krebs cycle generates 16 ATPs I respiration compared to 2 ATPs through glycolysis. The discovery of the genetic code with the “Watson-Crick” model and the identification of DNA polymerase opened a window for contuing discovery leading to the human genome project at 20th century end that has now been followed by “ENCODE” in the 21st century. This review opens a rediscovery of the metabolic function of mitochondria and adaptive functions with respect to cancer and other diseases.

Function in aerobic and anaerobic metabolism

Two-carbon compounds – the TCA, the pentose phosphate pathway, together with gluconeogenesis and the glyoxylate cycle are essential for the provision of anabolic precursors. Yeast environmental diversity mostly leads to a vast metabolic complexity driven by carbon and the energy available in environmental habitats. This resulted in much early research on analysis of yeast metabolism associated with glucose catabolism in Saccharomyces cerevisiae, under both aerobic and anaerobic environments. Yeasts may be physiologically classified with respect to the type of energy-generating process involved in sugar metabolism, namely non-, facultative- or obligate fermentative. The nonfermentative yeasts have exclusively a respiratory metabolism and are not capable of alcoholic fermentation from glucose, while the obligate-fermentative yeasts – “natural respiratory mutants” – are only capable of metabolizing glucose through alcoholic fermentation. Most of the yeasts identified are facultative-fermentative ones, and depending on the growth conditions, the type and concentration of sugars and/or oxygen availability, may display either a fully respiratory or a fermentative metabolism or even both in a mixed respiratory-fermentative metabolism (e.g., S. cerevisiae). The sugar composition of the media and oxygen availability are the two main environmental conditions that have a strong impact on yeast metabolic physiology, and three frequently observed effects associated with the type of energy-generating processes involved in sugar metabolism and/or oxygen availability are Pasteur, Crabtree and Custer. In modern terms the Pasteur effect refers to an activation of anaerobic glycolysis in order to meet cellular ATP demands owing to the lower efficiency of ATP production by fermentation compared with respiration. In 1861 Pasteur observed that S. cerevisiae consume much more glucose in the absence of oxygen than in its presence. S. cerevisiae only shows a Pasteur at low growth rates and at resting-cell conditions, where a high contribution of respiration to sugar catabolism occurs owing to the loss of fermentative capacity. The Crabtree effect is defined as the occurrence of alcoholic fermentation under aerobic conditions, explained by a theory involving “limited respiratory capacities” in the branching point of pyruvate metabolism. The Custer effect is known as the inhibition of alcoholic fermentation by the absence of oxygen. It is thought that the Custer effect is caused by reductive stress.

Glycolysis

Once inside the cell, glucose is phosphorylated by kinases to glucose 6-phosphate and then isomerized to fructose 6-phosphate, by phosphoglucose isomerase. The next enzyme is phospho-fructokinase, which is subject to regulation by several metabolites, and further phosphorylates fructose 6-phosphate to fructose 1,6-bisphosphate. These steps of glycolysis require energy in the form of ATP. Glycolysis leads to pyruvate formation associated with a net production of energy and reducing equivalents. Approximately 50% of glucose 6-phosphate is metabolized via glycolysis and 30% via the pentose phosphate pathway in Crabtree negative yeasts. However, about 90% of the carbon going through the pentose phosphate pathway reentered glycolysis at the level of fructose 6-phosphate or glyceraldehyde 3-phosphate. The pentose phosphate pathway in Crabtree positive yeasts (S. cerevisiae) is predominantly used for NADPH production but not for biomass production or catabolic reactions.
Pyruvate branch point. At the pyruvate (the end product of glycolysis) branching point, pyruvate can follow three different metabolic fates depending on the yeast species and the environmental conditions. On the other hand, the carbon flux may be distributed between the respiratory and fermentative pathways. Pyruvate might be directly converted to acetyl–cofactor A (CoA) by the mitochondrial multienzyme complex pyruvate dehydrogenase (PDH) after its transport into the mitochondria by the mitochondrial pyruvate carrier. Alternatively, pyruvate can also be converted to acetyl–CoA in the cytosol via acetaldehyde and to acetate by the so-called PDH-bypass pathway. Compared with cytosolic pyruvate decarboxylase, the mitochondrial PDH complex has a higher affinity for pyruvate and therefore most of the pyruvate will flow through the PDH complex at low glycolytic rates. However, at increasing glucose concentrations, the glycolytic rate will increase and more pyruvate is formed, saturating the PDH bypass and shifting the carbon flux through ethanol production. In the yeast S. cerevisiae, the external glucose level controls the switch between respiration and fermentation.

Rodrigues F, Ludovico P and Leão C. Sugar Metabolism in Yeasts: an Overview of Aerobic and Anaerobic Glucose Catabolism. In Molecular and Structural Biology. Chapter 6. qxd 07/23/05 P117
Eriksson P, Andre L, Ansell R, Blomberg A, Adler L (1995) Cloning and characterization of GPD2, a second gene encoding sn-glycerol 3-phosphate dehydrogenase (NAD+) in Saccharomyces cerevisiae, and its comparison with GPD1. Mol Microbiol 17:95–107.
Flikweert MT, van der Zanden L, Janssen WM, Steensma HY, van Dijken JP, Pronk JT (1996)Pyruvate decarboxylase: an indispensable enzyme for growth of Saccharomyces cerevisiae on glucose. Yeast 12:247–257.

Biogenesis of mitochondrial structures from aerobically grown S. cerevisiae

Under aerobic conditions S. cerevisiae forms mitochondria which are classical in their properties,
but the number, morphology, and enzyme activity of these mitochondria are also affected by catabolite repression, but it cannot respire under anaerobic conditions and lacks cytochromes. These structures were isolated from anaerobically grown yeast cells and contain malate and succinate dehydrogenases, ATPase, and DNA characteristic of yeast mitochondria. These lipid-complete structures consist predominantly of double-membrane vesicles enclosing a dense matrix which contains a folded inner membrane system bordering electron-transparent regions similar to the cristae of mitochondria.

• The morphology of the structures is critically dependent on their lipid composition
• Their unsaturated fatty acid content is similar to that of mitochondria from aerobically grown cells
• The structures from cells grown without lipid supplements have simpler morphology – a dense granular matrix surrounded by a double membrane but have no obvious folded inner membrane system within the matrix
• The lipid-depleted structures are only isolated in intact form from protoplasts
• The synthesis of ergosterol and unsaturated fatty acids is oxygen-dependent and anaerobically grown cells may be depleted of these lipid components
• The cytology of anaerobically grown yeast cells is profoundly affected by both lipid-depletion and catabolite repression
• Lipid-depleted anaerobic cells, membranous mitochondrial profiles were not demonstrable
• The structures from the aerobically and anaerobically grown cells are markedly different in morphology and fatty acid composition, but both contain mitochondrial DNA and a number of mitochondrial enzymes

The phospholipid composition of various strains of Saccharomyces cerevisiae, wild type and petite (cytoplasmic respiratory deficient) yeasts and derived mitochondrial mutants grown under conditions designed to induce variations in the complement of mitochondrial were fractionated into various subcellular fractions and analyzed for cytochrome oxidase (in wild type) and phospholipid composition . 90% or more of the phospholipid, cardiolipin was found in the mitochondrial membranes of wild type and petite yeast . Cardiolipin content differed markedly under various growth conditions .

• Stationary yeast grown in glucose had better developed mitochondria and more cardiolipin than repressed log phase yeast .
• Aerobic yeast contained more cardiolipin than anaerobic yeast .
• Respiration-deficient cytoplasmic mitochondrial mutants, both suppressive and neutral, contained less cardiolipin than corresponding wild types .
• A chromosomal mutant lacking respiratory function had normal cardiolipin content .
• Log phase cells grown in galactose and lactate, which do not readily repress the development of mitochondrial membranes, contained as much cardiolipin as stationary phase cells grown in glucose .
• Cytoplasmic mitochondrial mutants respond to changes in the glucose concentration of the growth medium by variations in their cardiolipin content in the same way as wild type yeast does under similar growth conditions.
• It is of interest that the chromosomal petite, which as far as can be ascertained has qualitatively normal mitochondrial DNA and a normal cardiolipin content when grown under maximally derepressed conditions .

Thus, the genetic defect in this case probably does not diminish the mass of inner mitochondrial membrane under appropriate conditions . This suggests the cardiolipin content of yeast is a good indicator of the state of development of mitochondrial membrane.
Jakovcic S, Getz Gs, Rabinowitz M, Jakob H, Swift H. Cardiolipin Content Of Wild Type and Mutant Yeasts in Relation to Mitochondrial Function and Development. JCB 1971. jcb.rupress.org
Jakovcic S, Haddock J, Getz GS, Rabinowitz M, Swift H. Biochem J. 1971; 121 :341 .
EPHRUSSI, B . 1953 . Nucleocytoplasmic Relations in Microorganisms . Clarendon Press, Oxford.

Mitochondria, hydrogenosomes and mitosomes

Before and after the publication of an unnoticed article in 1905 by Mereschkowsky there were many publications dealing with plant “chimera’s” and cytoplasmic inheritance in plants, which should have favoured the interpretation of plastids as “semi-autonomous” symbiotic entities in the cytoplasm of the eukaryotic plant cell. Twenty years after Mereschkowsky’s plea for an endosymbiotic origin of plastids, Wallin (1925, 1927) postulated the “bacterial nature of mitochondria”. And so it is one of the mysteries of the 20th century that an endosymbiotic origin of plastids had not been generally accepted before the 1970s, primarily because one cannot experience the consequences of mutations in the mitochondrial genome by naked eye.

• Mitochondrial DNA is usually present in multiple copies in one and the same mitochondrion and those in the hundreds to thousands of mitochondria in a single cell are not necessarily identical.
• The random partitioning of the mitochondria in mitosis (and meiosis) frequently results in a more or less biased distribution of the diverent mitochondria in the daughter cells, eventually causing diverent phenotypes in different tissues obscuring the maternal inheritance
• It was not until the 1990s that certain diseases—which had been interpreted as being X-chromosomal with incomplete penetrance—eventually turned out to be

Lastly, the vast majority of mitochondrial proteins are encoded in the nucleus and, consequently, mutations in the corresponding genes exhibit a Mendelian, and not a cytoplasmic, maternal inheritance
In the 1970s and 1980s the unequivocal demonstration of mitochondrial DNA occurred
and mitochondrial mutations at the DNA level provided the final proof for the role of such mutations in a wealth of hereditary diseases in man.

• The genomics era provided the tools to prove the endosymbiont-hypothesis for the origin of the eukaryotic cell

Since DNA does not arise de novo, the genomes of organisms and organelles provide a historical record for the evolution of the eukaryotic cell and its organelles. The DNA sequences of two to three genomes of the eukaryotic cell turned out to be a record of the evolution of the eukaryotic life on earth. The analysis of organelle genomes unequivocally revealed a cyanobacterial origin for plastids and an -proteobacterial origin for mitochondria. Both plastids and mitochondria appear to be monophyletic, i.e. plastids derived from one and the same cyanobacterial ancestor, and mitochondria from one and the same -proteobacterial ancestor.
The evolution of the eukaryotic cell appears to have involved one (in the case of animals) or two (in the case of plants) events that took place 1.5 to 2 billion years ago. However, it appears that symbioses involving one or the other eubacterium arose repeatedly during the billions of years available. For example, photosynthetic algae by phagotrophic eukaryotes, negating the hypothesis of a single eukaryotic event, rather than stringent selection shaping the diversity of present-day life. Recent hypotheses for the origin of the nucleus have postulated that introns, which could be acquired by the uptake of the -proteobacterial endosymbiont, forced the nucleus-cytosol compartmentalization. Lateral gene transfer among eukaryotes is more frequent than was assumed earlier, and “mitochondrial genes” in the nuclear genomes of amitochondrial organisms are not necessarily the consequence of a transient presence of a DNA-containing mitochondrial-like organelle.
To cope with the obvious ubiquity of “mitochondrial” genes and the chimerism of the DNA of present day eukaryotes, the hydrogen hypothesis postulates that an archaeal host took up a eubacterial symbiont that became the ancestor of mitochondria and hydrogenosomes. The hydrogen hypothesis has the potential to explain both the monophyly of the mitochondria, and the existence of “anaerobic” and “aerobic” variants of one and the same original organelle. Based on these observations we have only the terms “mitochondrion”, “hydrogenosome” and “mitosome” to classify the various variants of the mitochondrial family.
Hackstein JHP, Joachim Tjaden J , Huynen M. Mitochondria, hydrogenosomes and mitosomes: products of evolutionary tinkering! Curr Genet (2006) 50:225–245. DOI 10.1007/s00294-006-0088-8.

Lineages

A look at the phylogenetic distribution of characterized anaerobic mitochondria among animal lineages shows that these are not clustered but spread across metazoan phylogeny. The biochemistry and the enzyme equipment used in the facultatively anaerobic mitochondria of metazoans is nearly identical across lineages, strongly indicating a common origin from an archaic metazoan ancestor. The organelles look like hydrogenosomes – anaerobic forms of mitochondria that generate H2 and adenosine triphosphate (ATP) from pyruvateoxidation and which were previously found only in unicellular eukaryotes. The animals harbor structures resembling prokaryotic endosymbionts, reminiscent of the methanogenic endosymbionts found in some hydrogenosome-bearing protists; fluorescence of F420, a typical methanogen cofactor, or lack thereof, will bring more insights as to what these structures are. If we follow the anaerobic lifestyle further back into evolutionary history, beyond the origin of the metazoans, we see that the phylogenetic distribution of eukaryotes with facultative anaerobic mitochondria, eukaryotes with hydrogenosomes and eukaryotes that possess mitosomes (reduced forms of mitochondria with no direct role in ATP synthesis) the picture is similar to that seen for animals. In all six of the major lineages (or supergroups) of eukaryotes that are currently recognized, forms with anaerobic mitochondria have been found. The newest additions to the growing collection of anaerobic mitochondrial metabolisms are the denitrifying foraminiferans. A handful of about a dozen enzymes make the difference between a ‘normal’ O2-respiring mitochondrion found in mammals, and the energy metabolism of eukaryotes with anaerobic mitochondria, hydrogenosomes or mitosomes. Notably, the full complement of those enzymes, once thought to be specific to eukaryotic anaerobes, surprisingly turned up in the green alga Chlamydomonas reinhardtii , which produces O2 in the light, has typical O2-respiring mitochondria but, within about 30 min of exposure to heterotrophic, anoxic and dark conditions, expresses its anaerobic biochemistry to make H2 in the same way as trichomonads, the group in which hydrogenosomes were discovered. Chlamydomonas provides evidence which indicates that the ability to inhabit oxygen-harbouring, as well as anoxic environments, is an ancestral feature of eukaryotes and their mitochondria. The prokaryote inhabitants have existed for well over a billion years, and have reached this new habitat by dispersal, not by adaptive evolution de novo and in situ. Indeed, geochemical evidence has shown that methanogenesis and sulphate reduction, and the niches in which they occur, are truly ancient.
Mentel and Martin. Anaerobic mitochondria: more common all the time. BMC Biology 2010; 8:32. BioMed Central Ltd. http://www.biomedcentral.com/1741-7007/8/32.

Anaerobic mitochondrial enzymes

Mitochondria from the muscle of the parasitic nematode Ascaris lumbricoides var. suum function anaerobically in electron transport-associated phosphorylations under physiological conditions. These helminth organelles have been fractionated into inner and outer membrane, matrix, and inter-membrane space fractions. The distributions of enzyme systems were determined and compared with corresponding distributions reported in mammalian mitochondria. Succinate and pyruvate dehydrogenases as well as NADH oxidase, Mg++-dependent ATPase, adenylate kinase, citrate synthase, and cytochrome c reductases were determined to be distributed as in mammalian mitochondria. In contrast with the mammalian systems, fumarase and NAD-linked “malic” enzyme were isolated primarily from the intermembrane space fraction of the worm mitochondria. These enzymes are required for the anaerobic energy-generating system in Ascaris and would be expected to give rise to NADH in the intermembrane space.
Pyruvate kinase activity is barely detectable in Ascaris muscle. Therefore, rather than giving rise to cytoplasmic pyruvate, CO2 is fixed into phosphoenolpyruvate, resulting in the formation of oxalacetate which, in turn, is reduced by NADH to form malate regenerating glycolytic NAD . Ascaris muscle mitochondria utilize malate anaerobically as their major substrate by means of a dismutation reaction. The “malic” enzyme in the mitochondrion catalyzes theoxidation of malate to form pyruvate, CO2, and NADH. This reaction serves to generate intramitochondrial reducing power in the form of NADH. Concomitantly, fumarase catalyzes thedehydration of an equivalent amount of malate to form fumarate which, in turn, is reduced by an NADH-linked fumarate reductase to succinate. The flavin-linked fumarate reductase reaction results in a site I electron transport-associated phosphorylation of ADP, giving rise to ATP. This identifies a proton translocation system to obtain energy generation.
Rew RS, Saz HJ. Enzyme Localization in the Anaerobic Mitochondria Of Ascaris Lumbricoides. The Journal Of Cell Biology 1974; 63: 125-135. jcb.rupress.org

Mitochondrial redox status

Tumor cells are characterized by accelerated growth usually accompanied by up-regulated pathways that ultimately increase the rate of ATP production. These cells can suffer metabolic reprogramming, resulting in distinct bioenergetic phenotypes, generally enhancing glycolysis channeled to lactate production. These investigators showed metabolic reprogramming by means of inhibitors of histone deacetylase (HDACis), sodium butyrate and trichostatin. This treatment was able to shift energy metabolism by activating mitochondrial systems such as the respiratory chain and oxidative phosphorylation that were largely repressed in the untreated controls.
Amoêdo ND, Rodrigues MF, Pezzuto P, Galina A, et al. Energy Metabolism in H460 Lung Cancer Cells: Effects of Histone Deacetylase Inhibitors. PLoS ONE 2011; 6(7): e22264. doi:10.1371/ journal.pone.0022264
Antioxidant pathways that rely on NADPH are needed for the reduction of glutathione and maintenance of proper redox status. The mitochondrial matrix protein isocitrate dehydrogenase 2 (IDH2) is a major source of NADPH. NAD+-dependent deacetylase SIRT3 is essential for the prevention of age related hearing loss of caloric restricted mice. Oxidative stress resistance by SIRT3 was mediated through IDH2. Inserting SIRT3 Nε-acetyl-lysine into position 413 of IDH2 and has an activity loss by as much as 44-fold. Deacetylation by SIRT3 fully restored maximum IDH2 activity. The ability of SIRT3 to protect cells from oxidative stress was dependent on IDH2, and the deacetylated mimic, IDH2K413R variant was able to protect Sirt3-/- MEFs from oxidative stress through increased reduced glutathione levels. The increased SIRT3 expression protects cells from oxidative stress through IDH2 activation. Together these results uncover a previously unknown mechanism by which SIRT3 regulates IDH2 under dietary restriction. Recent findings demonstrate that IDH2 activities are a major factor in cancer, and as such, these results implicate SIRT3 as a potential regulator of IDH2-dependent functions in cancer cell metabolism.
Wei Yu, Dittenhafer-Reed KE and JM Denu. SIRT3 Deacetylates Isocitrate Dehydrogenase 2 (IDH2) and Regulates Mitochondrial Redox Status. JBC Papers in Press. Published on March 13, 2012 as Manuscript M112.355206. http://www.jbc.org
Computationally designed drug small molecules targeted for metabolic processes: a bridge from the genome to repair of dysmetabolism
New druglike small molecules with possible anticancer applications were computationally designed. The molecules formed stable complexes with antiapoptotic BCL-2, BCL-W, and BFL-1 proteins. These findings are novel because, to the best of the author’s knowledge, molecules that bind all three of these proteins are not known. A drug based on them should be more economical and better tolerated by patients than a combination of drugs, each targeting a single protein. The calculated drug-related properties of the molecules were similar to those found in most commercial drugs. The molecules were designed and evaluated following a simple, yet effective procedure. The procedure can be used efficiently in the early phases of drug discovery to evaluate promising lead compounds in time- and cost-effective ways.
Keywords: small molecule mimetics, antiapoptotic proteins, computational drug design.

Tardigrades

Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant.
Keywords: RNA, expressed sequence tag, cluster, protein family, adaptation, tardigrada, transcriptome

Epicrisis

This discussion has disparate pieces that are tied together by dysfunctional changes that are

• adaptations from metabolic process in the channeling of energy dependent of mitochondrial enzymes in interaction with three to 6 carbon carbohydrates, high energy phosphate, oxygen and membrane lipid structures, as well as
• proteins rich or poor in sulfur linked with genome specific targets, and semisynthetic modifications, oxidative stress
• leading to a new approach to pharmaceutical targeted drug design.

Related articles

• Determinants of Brain Cell Metabolic Phenotypes and Energy Substrate Utilization Unraveled with a Modeling Approach (ploscompbiol.org)
• Mitochondria and Cancer: An overview of mechanisms (pharmaceuticalintelligence.com)
• Making a molecular micromap: Imaging the yeast 26S proteasome at near-atomic resolution (phys.org)
• Fermentation (ahschoolapbio2013.wordpress.com)
• Nitric Oxide has a ubiquitous role in the regulation of glycolysis -with a concomitant influence on mitochondrial function (pharmaceuticalintelligence.com)
• What Causes Aging and How Does Dietary Restriction Increase Life Span? (understandnutrition.com)
• Diaz-Cano SJ. Tumor heterogeneity: mechanisms and bases for a reliable application of molecular marker design. Int J Mol Sci 2012; 13(2):1951-2011 PMID 22408433Bernstein LH. Expanding the Genetic Alphabet and linking the genome to the metabolome.PharmaIntell.wordpress.com. luly 24, 2012.
• Sainani K. Meet the Skeptics: Why Some Doubt Biomedical Models – and What it Takes to Win Them Over.  IMAG Futures meeting.   2009
• Ritusaxena. ENCODE: the key to unlocking the secrets of complex genetic diseases.  PharmaIntell.wordpress.com  2012.
• Ritusaxena. Scientists use natural agents for prostate cancer bone metastasis treatment. PharmaIntell.wordpress.com. 2012
• Ritusaxena. β Integrin emerges as an important player in mitochondrial dysfunction associated Gastric Cancer. PharmaIntell.wordpress.com 2012

 

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading...

Read Full Post »

Expanding the Genetic Alphabet and Linking the Genome to the Metabolome

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Chemical Biology and its relations to Metabolic Disease, Chemical Genetics, Computational Biology/Systems and Bioinformatics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Liver & Digestive Diseases Research, Medical and Population Genetics, Metabolomics, Molecular Genetics & Pharmaceutical, Nutrigenomics, Nutrition, Personalized and Precision Medicine & Genomic Research, Pharmaceutical Analytics, Pharmaceutical Industry Competitive Intelligence, Pharmaceutical R&D Investment, Population Health Management, Genetics & Pharmaceutical, Population Health Management, Nutrition and Phytochemistry, Proteomics, Scientist: Career considerations, Systemic Inflammatory Response Related Disorders, Technology Transfer: Biotech and Pharmaceutical, tagged adenine, ATP, biodiversity, Cancer - General, Cancer Genome Atlas, cystathionine beta synthase, cytosine, DNA, fumarate, gene modification, genetic code, genetic engineering, genetics, genome, guanine, H2S, homocysteine, inosine, malnutrition, metabolome, methionine, Nature (journal), Nature Chemical Biology, Nucleic acid double helix, nucleosides, oncometabolite, oxidative stress, proteome, regulatory pathways, S-adenosylmethionine, Scripps Research Institute, Sulfur, synthetic nucleotides, thymidine, Warburg Effect, Watson-Crick Model, xanthine on September 24, 2012| 13 Comments »

English: The citric acid cycle, also known as the tricarboxylic acid cycle (TCA cycle) or the Krebs cycle. Produced at WikiPathways. (Photo credit: Wikipedia)

Expanding the Genetic Alphabet and Linking the Genome to the Metabolome

 

Reporter& Curator:  Larry Bernstein, MD, FCAP

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Unlocking the diversity of genomic expression within tumorigenesis and “tailoring” of therapeutic options

1. Reshaping the DNA landscape between diseases and within diseases by the linking of DNA to treatments

In the NEW York Times of 9/24,2012 Gina Kolata reports on four types of breast cancer and the reshaping of breast cancer DNA treatment based on the findings of the genetically distinct types, which each have common “cluster” features that are driving many cancers.  The discoveries were published online in the journal Nature on Sunday (9/23).  The study is considered the first comprehensive genetic analysis of breast cancer and called a roadmap to future breast cancer treatments.  I consider that if this is a landmark study in cancer genomics leading to personalized drug management of patients, it is also a fitting of the treatment to measurable “combinatorial feature sets” that tie into population biodiversity with respect to known conditions.   The researchers caution that it will take years to establish transformative treatments, and this is clearly because in the genetic types, there are subsets that have a bearing on treatment “tailoring”.   In addition, there is growing evidence that the Watson-Crick model of the gene is itself being modified by an expansion of the alphabet used to construct the DNA library, which itself will open opportunities to explain some of what has been considered junk DNA, and which may carry essential information with respect to metabolic pathways and pathway regulation.  The breast cancer study is tied to the  “Cancer Genome Atlas” Project, already reported.  It is expected that this work will tie into building maps of genetic changes in common cancers, such as, breast, colon, and lung.  What is not explicit I presume is a closely related concept, that the translational challenge is closely related to the suppression of key proteomic processes tied into manipulating the metabolome.

Saha S. Impact of evolutionary selection on functional regions: The imprint of evolutionary selection on ENCODE regulatory elements is manifested between species and within human populations. 9/12/2012. PharmaceuticalIntelligence.Wordpress.com

Hawrylycz MJ, Lein ES, Guillozet-Bongaarts AL, Shen EH, Ng L, et al. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature  Sept 14-20, 2012

Sarkar A. Prediction of Nucleosome Positioning and Occupancy Using a Statistical Mechanics Model. 9/12/2012. PharmaceuticalIntelligence.WordPress.com

Heijden et al.   Connecting nucleosome positions with free energy landscapes. (Proc Natl Acad Sci U S A. 2012, Aug 20 [Epub ahead of print]).  http://www.ncbi.nlm.nih.gov/pubmed/22908247

2. Fiddling with an expanded genetic alphabet – greater flexibility in design of treatment (pharmaneogenesis?)

Diagram of DNA polymerase extending a DNA strand and proof-reading. (Photo credit: Wikipedia)

A clear indication of this emerging remodeling of the genetic alphabet is a new
study led by scientists at The Scripps Research Institute appeared in the
June 3, 2012 issue of Nature Chemical Biology that indicates the genetic code as
we know it may be expanded to include synthetic and unnatural sequence pairing (Study Suggests Expanding the Genetic Alphabet May Be Easier than Previously Thought, Genome). They infer that the genetic instructions for living organisms
that is composed of four bases (C, G, A and T)— is open to unnatural letters. An expanded “DNA alphabet” could carry more information than natural DNA, potentially coding for a much wider range of molecules and enabling a variety of powerful applications. The implications of the application of this would further expand the translation of portions of DNA to new transciptional proteins that are heretofore unknown, but have metabolic relavence and therapeutic potential. The existence of such pairing in nature has been studied in Eukariotes for at least a decade, and may have a role in biodiversity. The investigators show how a previously identified pair of artificial DNA bases can go through the DNA replication process almost as efficiently as the four natural bases.  This could as well be translated into human diversity, and human diseases.

The Romesberg laboratory collaborated on the new study and his lab have been trying to find a way to extend the DNA alphabet since the late 1990s. In 2008, they developed the efficiently replicating bases NaM and 5SICS, which come together as a complementary base pair within the DNA helix, much as, in normal DNA, the base adenine (A) pairs with thymine (T), and cytosine (C) pairs with guanine (G). It had been clear that their chemical structures lack the ability to form the hydrogen bonds that join natural base pairs in DNA. Such bonds had been thought to be an absolute requirement for successful DNA replication, but that is not the case because other bonds can be in play.

The data strongly suggested that NaM and 5SICS do not even approximate the edge-to-edge geometry of natural base pairs—termed the Watson-Crick geometry, after the co-discoverers of the DNA double-helix. Instead, they join in a looser, overlapping, “intercalated” fashion that resembles a ‘mispair.’ In test after test, the NaM-5SICS pair was efficiently replicable even though it appeared that the DNA polymerase didn’t recognize it. Their structural data showed that the NaM-5SICS pair maintain an abnormal, intercalated structure within double-helix DNA—but remarkably adopt the normal, edge-to-edge, “Watson-Crick” positioning when gripped by the polymerase during the crucial moments of DNA replication. NaM and 5SICS, lacking hydrogen bonds, are held together in the DNA double-helix by “hydrophobic” forces, which cause certain molecular structures (like those found in oil) to be repelled by water molecules, and thus to cling together in a watery medium.

The finding suggests that NaM-5SICS and potentially other, hydrophobically bound base pairs could be used to extend the DNA alphabet and that Evolution’s choice of the existing four-letter DNA alphabet—on this planet—may have been developed allowing for life based on other genetic systems.

3.  Studies that consider a DNA triplet model that includes one or more NATURAL nucleosides and looks closely allied to the formation of the disulfide bond and oxidation reduction reaction.

This independent work is being conducted based on a similar concep. John Berger, founder of Triplex DNA has commented on this. He emphasizes Sulfur as the most important element for understanding evolution of metabolic pathways in the human transcriptome. It is a combination of sulfur 34 and sulphur 32 ATMU. S34 is element 16 + flourine, while S32 is element 16 + phosphorous. The cysteine-cystine bond is the bridge and controller between inorganic chemistry (flourine) and organic chemistry (phosphorous). He uses a dual spelling, using  sulfphur to combine the two referring to the master catalyst of oxidation-reduction reactions. Various isotopic alleles (please note the duality principle which is natures most important pattern). Sulfphur is Methionine, S adenosylmethionine, cysteine, cystine, taurine, gluthionine, acetyl Coenzyme A, Biotin, Linoic acid, H2S, H2SO4, HSO3-, cytochromes, thioredoxin, ferredoxins, purple sulfphur anerobic bacteria prokaroytes, hydrocarbons, green sulfphur bacteria, garlic, penicillin and many antibiotics; hundreds of CSN drugs for parasites and fungi antagonists. These are but a few names which come to mind. It is at the heart of the Krebs cycle of oxidative phosphorylation, i.e. ATP. It is also a second pathway to purine metabolism and nucleic acids. It literally is the key enzymes between RNA and DNA, ie, SH thiol bond oxidized to SS (dna) cysteine through thioredoxins, ferredoxins, and nitrogenase. The immune system is founded upon sulfphur compounds and processes. Photosynthesis Fe4S4 to Fe2S3 absorbs the entire electromagnetic spectrum which is filtered by the Allen belt some 75 miles above earth. Look up chromatium vinosum or allochromatium species.  There is reasonable evidence it is the first symbiotic species of sulfphur anerobic bacteria (Fe4S4) with high potential mvolts which drives photosynthesis while making glucose with H2S.
He envisions a sulfphur control map to automate human metabolism with exact timing sequences, at specific three dimensional coordinates on Bravais crystalline lattices. He proposes adding the inosine-xanthosine family to the current 5 nucleotide genetic code. Finally, he adds, the expanded genetic code is populated with “synthetic nucleosides and nucleotides” with all kinds of customized functional side groups, which often reshape nature’s allosteric and physiochemical properties. The inosine family is nature’s natural evolutionary partner with the adenosine and guanosine families in purine synthesis de novo, salvage, and catabolic degradation. Inosine has three major enzymes (IMPDH1,2&3 for purine ring closure, HPGRT for purine salvage, and xanthine oxidase and xanthine dehydrogenase.

English: DNA replication or DNA synthesis is the process of copying a double-stranded DNA molecule. This process is paramount to all life as we know it. (Photo credit: Wikipedia)

3. Nutritional regulation of gene expression,  an essential role of sulfur, and metabolic control 

Finally, the research carried out for decades by Yves Ingenbleek and the late Vernon Young warrants mention. According to their work, sulfur is again tagged as essential for health. Sulfur (S) is the seventh most abundant element measurable in human tissues and its provision is mainly insured by the intake of methionine (Met) found in plant and animal proteins. Met is endowed with unique functional properties as it controls the ribosomal initiation of protein syntheses, governs a myriad of major metabolic and catalytic activities and may be subjected to reversible redox processes contributing to safeguard protein integrity.

Consuming diets with inadequate amounts of methionine (Met) are characterized by overt or subclinical protein malnutrition, and it has serious morbid consequences. The result is reduction in size of their lean body mass (LBM), best identified by the serial measurement of plasma transthyretin (TTR), which is seen with unachieved replenishment (chronic malnutrition, strict veganism) or excessive losses (trauma, burns, inflammatory diseases).  This status is accompanied by a rise in homocysteine, and a concomitant fall in methionine.  The ratio of S to N is quite invariant, but dependent on source.  The S:N ratio is typical 1:20 for plant sources and 1:14.5 for animal protein sources.  The key enzyme involved with the control of Met in man is the enzyme cystathionine-b-synthase, which declines with inadequate dietary provision of S, and the loss is not compensated by cobalamine for CH3- transfer.

As a result of the disordered metabolic state from inadequate sulfur intake (the S:N ratio is lower in plants than in animals), the transsulfuration pathway is depressed at cystathionine-β-synthase (CβS) level triggering the upstream sequestration of homocysteine (Hcy) in biological fluids and promoting its conversion to Met. They both stimulate comparable remethylation reactions from homocysteine (Hcy), indicating that Met homeostasis benefits from high metabolic priority. Maintenance of beneficial Met homeostasis is counterpoised by the drop of cysteine (Cys) and glutathione (GSH) values downstream to CβS causing reducing molecules implicated in the regulation of the 3 desulfuration pathways

4. The effect on accretion of LBM of protein malnutrition and/or the inflammatory state: in closer focus

Hepatic synthesis is influenced by nutritional and inflammatory circumstances working concomitantly and liver production of  TTR integrates the dietary and stressful components of any disease spectrum. Thus we have a depletion of visceral transport proteins made by the liver and fat-free weight loss secondary to protein catabolism. This is most accurately reflected by TTR, which is a rapid turnover protein, but it is involved in transport and is essential for thyroid function (thyroxine-binding prealbumin) and tied to retinol-binding protein. Furthermore, protein accretion is dependent on a sulfonation reaction with 2 ATP.  Consequently, Kwashiorkor is associated with thyroid goiter, as the pituitary-thyroid axis is a major sulfonation target. With this in mind, it is not surprising why TTR is the sole plasma protein whose evolutionary patterns closely follow the shape outlined by LBM fluctuations. Serial measurement of TTR therefore provides unequaled information on the alterations affecting overall protein nutritional status. Recent advances in TTR physiopathology emphasize the detecting power and preventive role played by the protein in hyper-homocysteinemic states.

Individuals submitted to N-restricted regimens are basically able to maintain N homeostasis until very late in the starvation processes. But the N balance study only provides an overall estimate of N gains and losses but fails to identify the tissue sites and specific interorgan fluxes involved. Using vastly improved methods the LBM has been measured in its components. The LBM of the reference man contains 98% of total body potassium (TBK) and the bulk of total body sulfur (TBS). TBK and TBS reach equal intracellular amounts (140 g each) and share distribution patterns (half in SM and half in the rest of cell mass). The body content of K and S largely exceeds that of magnesium (19 g), iron (4.2 g) and zinc (2.3 g).

TBN and TBK are highly correlated in healthy subjects and both parameters manifest an age-dependent curvilinear decline with an accelerated decrease after 65 years. Sulfur Methylation (SM) undergoes a 15% reduction in size per decade, an involutive process. The trend toward sarcopenia is more marked and rapid in elderly men than in elderly women decreasing strength and functional capacity. The downward SM slope may be somewhat prevented by physical training or accelerated by supranormal cytokine status as reported in apparently healthy aged persons suffering low-grade inflammation or in critically ill patients whose muscle mass undergoes proteolysis.

5.  The results of the events described are:

• Declining generation of hydrogen sulfide (H2S) from enzymatic sources and in the non-enzymatic reduction of elemental S to H2S.
• The biogenesis of H2S via non-enzymatic reduction is further inhibited in areas where earth’s crust is depleted in elemental sulfur (S8) and sulfate oxyanions.
• Elemental S operates as co-factor of several (apo)enzymes critically involved in the control of oxidative processes.

Combination of protein and sulfur dietary deficiencies constitute a novel clinical entity threatening plant-eating population groups. They have a defective production of Cys, GSH and H2S reductants, explaining persistence of an oxidative burden.

6. The clinical entity increases the risk of developing:

• cardiovascular diseases (CVD) and
• stroke

in plant-eating populations regardless of Framingham criteria and vitamin-B status.
Met molecules supplied by dietary proteins are submitted to transmethylation processes resulting in the release of Hcy which:

• either undergoes Hcy — Met RM pathways or
• is committed to transsulfuration decay.

Impairment of CβS activity, as described in protein malnutrition, entails supranormal accumulation of Hcy in body fluids, stimulation of activity and maintenance of Met homeostasis. The data show that combined protein- and S-deficiencies work in concert to deplete Cys, GSH and H2S from their body reserves, hence impeding these reducing molecules to properly face the oxidative stress imposed by hyperhomocysteinemia.

Although unrecognized up to now, the nutritional disorder is one of the commonest worldwide, reaching top prevalence in populated regions of Southeastern Asia. Increased risk of hyperhomocysteinemia and oxidative stress may also affect individuals suffering from intestinal malabsorption or westernized communities having adopted vegan dietary lifestyles.

Ingenbleek Y. Hyperhomocysteinemia is a biomarker of sulfur-deficiency in human morbidities. Open Clin. Chem. J. 2009 ; 2 : 49-60.

7. The dysfunctional metabolism in transitional cell transformation

A third development is also important and possibly related. The transition a cell goes through in becoming cancerous tends to be driven by changes to the cell’s DNA. But that is not the whole story. Large-scale techniques to the study of metabolic processes going on in cancer cells is being carried out at Oxford, UK in collaboration with Japanese workers. This thread will extend our insight into the metabolome. Otto Warburg, the pioneer in respiration studies, pointed out in the early 1900s that most cancer cells get the energy they need predominantly through a high utilization of glucose with lower respiration (the metabolic process that breaks down glucose to release energy). It helps the cancer cells deal with the low oxygen levels that tend to be present in a tumor. The tissue reverts to a metabolic profile of anaerobiosis.  Studies of the genetic basis of cancer and dysfunctional metabolism in cancer cells are complementary. Tomoyoshi Soga’s large lab in Japan has been at the forefront of developing the technology for metabolomics research over the past couple of decades (metabolomics being the ugly-sounding term used to describe research that studies all metabolic processes at once, like genomics is the study of the entire genome).

Their results have led to the idea that some metabolic compounds, or metabolites, when they accumulate in cells, can cause changes to metabolic processes and set cells off on a path towards cancer. The collaborators have published a perspective article in the journal Frontiers in Molecular and Cellular Oncology that proposes fumarate as such an ‘oncometabolite’. Fumarate is a standard compound involved in cellular metabolism. The researchers summarize that shows how accumulation of fumarate when an enzyme goes wrong affects various biological pathways in the cell. It shifts the balance of metabolic processes and disrupts the cell in ways that could favor development of cancer.  This is of particular interest because “fumarate” is the intermediate in the TCA cycle that is converted to malate.

Animation of the structure of a section of DNA. The bases lie horizontally between the two spiraling strands. (Photo credit: Wikipedia)

The Keio group is able to label glucose or glutamine, basic biological sources of fuel for cells, and track the pathways cells use to burn up the fuel.  As these studies proceed, they could profile the metabolites in a cohort of tumor samples and matched normal tissue. This would produce a dataset of the concentrations of hundreds of different metabolites in each group. Statistical approaches could suggest which metabolic pathways were abnormal. These would then be the subject of experiments targeting the pathways to confirm the relationship between changed metabolism and uncontrolled growth of the cancer cells.

Related articles

• Junk DNA codes for valuable miRNAs (pharmaceuticalintelligence.com)
• Molecular milestone: scientists unravel the human genome – Fox News (foxnews.com)
• The Story of You: Encode and the human genome – video | Martin Robbins (guardian.co.uk)
• Science takes a giant leap in its understanding of genetics (jessiebaldwin.wordpress.com)
• Critical Breakthrough: Study Overturns Theory of ‘Junk DNA’ (the2012scenario.com)
• The ENCODE delusion (scienceblogs.com)

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading...

Read Full Post »

Amplifying Information Using S-Clustering and Relationship to Kullback-Liebler Distance: An Application to Myocardial Infarction

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biomarkers & Medical Diagnostics, Chemical Biology and its relations to Metabolic Disease, Computational Biology/Systems and Bioinformatics, Ecosystems & Industrial Concentration in the Medical Device Sector, FDA Regulatory Affairs, Health Economics and Outcomes Research, Health Law & Patient Safety, HealthCare IT, International Global Work in Pharmaceutical, Medical Devices R&D Investment, Personalized and Precision Medicine & Genomic Research, Pharmaceutical Analytics, Population Health Management, Genetics & Pharmaceutical, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Scientist: Career considerations, Statistical Methods for Research Evaluation, tagged Anomaly identification, Bernoulli trial, clustering methods, combinatorial analysis, EHR, IT validation, Kullback-Liebler Distance, learning algorithms, multivariate classification, S-clustering, Shannon-Weaver Information theory on September 22, 2012| 3 Comments »

typical changes in CK-MB and cardiac troponin in Acute Myocardial Infarction (Photo credit: Wikipedia)

Reporter and curator:

Larry H Bernstein, MD, FCAP

This posting is a followup on two previous posts covering the design and handling of HIT to improve healthcare outcomes as well as lower costs from better workflow and diagnostics, which is self-correcting over time.

The first example is a non technology method designed by Lee Goldman (Goldman Algorithm) that was later implemented at Cook County Hospital in Chicago with great success.     It has been known that there is over triage of patients to intensive care beds, adding to the costs of medical care.  If the differentiation between acute myocardial infarction and other causes of chest pain could be made more accurate, the quantity of scare resources used on unnecessary admissions could be reduced.  The Goldman algorithm was introduced in 1982 during a training phase at Yale-New Haven Hospital based on 482 patients, and later validated at the BWH (in Boston) on 468 patients.They demonstrated improvement in sensitivity as well as specificity (67% to 77%), and positive predictive value (34% to 42%).  They modified the computer derived algorithm in 1988 to achieve better results in triage of patients to the ICU of patients with chest pain based on a study group of 1379 patients.  The process was tested prospectively on 4770 patients at two university and 4 community hospitals.  The specificity improved by 74% vs 71% in recognizing absence of AMI by the algorithm vs physician judgement. The sensitivity was not different for admission (88%).  Decisions based solely on the protocol would have decreased admissions of patients without AMI by 11.5% without adverse effects.  The study was repeated by Qamar et al. with equal success.

Pain in acute myocardial infarction (front) (Photo credit: Wikipedia)

An ECG showing pardee waves indicating acute myocardial infarction in the inferior leads II, III and aVF with reciprocal changes in the anterolateral leads. (Photo credit: Wikipedia)

Acute myocardial infarction with coagulative necrosis (4) (Photo credit: Wikipedia)

Goldman L, Cook EF, Brand DA, Lee TH, Rouan GW, Weisberg MC, et al. A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med. 1988;318:797-803.

A Qamar, C McPherson, J Babb, L Bernstein, M Werdmann, D Yasick, S Zarich. The Goldman algorithm revisited: prospective evaluation of a computer-derived algorithm versus unaided physician judgment in suspected acute myocardial infarction. Am Heart J 1999; 138(4 Pt 1):705-709. ICID: 825629

The usual accepted method for determining the decision value of a predictive variable is the Receiver Operator Characteristic Curve, which requires a mapping of each value of the variable against the percent with disease on the Y-axis.   This requires a review of every case entered into the study.  The ROC curve is done to validate a study to classify data on leukemia markers for research purposes as shown by Jay Magidson in his demonstation of  Correlated Component Regression (2012)(Statistical Innovations, Inc.)  The test for the contribution of each predictor is measured by Akaike Information Criteria and Bayes Information Criteria, which have proved to be critically essential tests over the last 20 years.

I go back 20 years and revisit the application of these principles in clinical diagnostics, but the ROC was introduced to medicine in radiology earlier.   A full rendering of this matter can be found in the following:
R A Rudolph, L H Bernstein, J Babb. Information induction for predicting acute myocardial infarction.Clin Chem 1988; 34(10):2031-2038. ICID: 825568.

Rypka EW. Methods to evaluate and develop the decision process in the selection of tests. Clin Lab Med 1992; 12:355

Rypka EW. Syndromic Classification: A process for amplifying information using S-Clustering. Nutrition 1996;12(11/12):827-9.

Christianson R. Foundations of inductive reasoning. 1964.  Entropy Publications. Lincoln, MA.

Inability to classify information is a major problem in deriving and validating hypotheses from PRIMARY data sets necessary to establish a measure of outcome effectiveness.  When using quantitative data, decision limits have to be determined that best distinguish the populations investigated.   We are concerned with accurate assignment into uniquely verifiable groups by information in test relationships.  Uncertainty in assigning to a supervisory classification can only be relieved by providing suffiuciuent data.

A method for examining the endogenous information in the data is used to determine decision points.  The reference or null set is defined as a class having no information.  When information is present in the data, the entropy (uncertainty in the data set) is reduced by the amount of information provided.  This is measureable and may be referred to as the Kullback-Liebler distance, which was extended by Akaike to include statistical theory.   An approach is devised using EW Rypka’s S-Clustering has been created to find optimal decision values that separate the groups being classified.  Further, it is possible to obtain PRIMARY data on-line and continually creating primary classifications (learning matrices).  From the primary classifications test-minimized sets of features are determined with optimal useful and sufficient information for accurately distinguishing elements (patients).  Primary classifications can be continually created from PRIMARY data.  More recent and complex work in classifying hematology data using a 30,000 patient data set and 16 variables to identify the anemias, moderate SIRS, sepsis, lymphocytic and platelet disorders has been  published and recently presented.  Another classification for malnutrition and stress hypermetabolism is now validated and in press in the journal Nutrition (2012), Elsevier.
G David, LH Bernstein, RR Coifman. Generating Evidence Based Interpretation of Hematology Screens via Anomaly Characterization. Open Clinical Chemistry Journal 2011; 4 (1):10-16. 1874-2416/11 2011 Bentham Open.  ICID: 939928

G David; LH Bernstein; RR Coifman. The Automated Malnutrition Assessment. Accepted 29 April 2012.
http://www.nutritionjrnl.com. Nutrition (2012), doi:10.1016/j.nut.2012.04.017.

Keywords: Network Algorithm; unsupervised classification; malnutrition screening; protein energy malnutrition (PEM); malnutrition risk; characteristic metric; characteristic profile; data characterization; non-linear differential diagnosis

Summary: We propose an automated nutritional assessment (ANA) algorithm that provides a method for malnutrition risk prediction with high accuracy and reliability. The problem of rapidly identifying risk and severity of malnutrition is crucial for minimizing medical and surgical complications. We characterized for each patient a unique profile and mapped similar patients into a classification. We also found that the laboratory parameters were sufficient for the automated risk prediction.
We here propose a simple, workable algorithm that provides assistance for interpreting any set of data from the screen of a blood analysis with high accuracy, reliability, and inter-operability with an electronic medical record. This has been made possible at least recently as a result of advances in mathematics, low computational costs, and rapid transmission of the necessary data for computation.  In this example, acute myocardial infarction (AMI) is classified using isoenzyme CKMB activity, total LD, and isoenzyme LD-1, and repeated studies have shown the high power of laboratory features for diagnosis of AMI, especially with NSTEMI.  A later study includes the scale values for chest pain and for ECG changes to create the model.

LH Bernstein, A Qamar, C McPherson, S Zarich.  Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72(4):259-268. ICID: 825617

The quantitative measure of information, Shannon entropy treats data as a message transmission.  We are interested in classifying data with near errorless discrimination.  The method assigns upper limits of normal to tests computed from Rudolph’s maximum entropy definitions of group-based normal reference.  Using the Bernoulli trial to determine maximum entropy reference, we determine from the entropy in the data a probability of a positive result that is the same for each test and conditionally independent of other results by setting the binary decision level for each test.  The entropy of the discrete distribution is calculated from the probabilities of the distribution. The probability distribution of the binary patterns is not flat and the entropy decreases when there is information in the data.  The decrease in entropy is the Kullback-Liebler distance.

The basic principle of separatory clustering is extracting features from endogenous data that amplify or maximize structural information into disjointed or separable classes.  This differs from other methods because it finds in a database a theoretic – or more – number of variables with required VARIETY that map closest to an ideal, theoretic, or structural information standard. Scaling allows using variables with different numbers of message choices (number bases) in the same matrix, binary, ternary, etc (representing yes-no; small-modest, large, largest).   The ideal number of class is defined by x^n.   In viewing a variable value we think of it as low, normal, high, high high, etc.  A system works with related parts in harmony.  This frame of reference improves the applicability of S-clustering.  By definition, a unit of information is log.r r = 1.

The method of creating a syndromic classification to control variety in the system also performs a semantic function by attributing a term to a Port Royal Class.  If any of the attributes are removed, the meaning of the class is made meaningless.  Any significant overlap between the groups would be improved by adding requisite variety.  S-clustering is an objective and most desirable way to find the shortest route to diagnosis, and is an objective way of determining practice parameters.

Multiple Test Binary Decision Patterns where CK-MB = 18 u/l, LD-1 = 36 u/l, %LD1 = 32 u/l.

No.               Pattern       Freq                   P1                       Self information                Weighted information

0                    000             26                   0.1831                    2.4493                                     0.4485
1                    001                3                    0.0211                   5.5648                                     0.1176
2                    010               4                    0.0282                   5.1497                                     0.1451
3                    011                2                    0.0282                   6.1497                                     0.0866
4                    100               6                    0.0423                   4.5648                                     0.1929
6                    110                8                    0.0563                  4.1497                                     0.2338
7                    111               93                   0.6549                  0.6106                                     0.3999

Entropy: sum of weighted information (average)           1.6243 bits

The effective information values are the least-error points. Non AMI patients exhibit patterns 0, 1, 2, 3, and 4: AMI patients are 6 and 7.  There is 1 fp 4, and 1 fn 6.  The error rate is 1.4%.

Summary:

A major problem in using quantitative data is lack of a justifiable definition of reference (normal).  Our information model consists of a population group, a set of attributes derived from observations, and basic definitions using Shannon’s information measure entropy. In this model, the population set and its values for its variables are considered to be the only information available.  The finding of a flat distribution with the Bernoulli test defines the reference population that has no information.  The complementary syndromic group, treated in the same way, produces a distribution that is not flat and has a less than maximum information uncertainty.

The vector of probabilities – (1/2), (1/2), …(1/2), can be related to the path calculated from the Rypka-Fletcher equation, which

Ct = 1 – 2^-k/1 -2^-n

determines the theoretical maximum comprehension from the test of n attributes.  We constructed a ROC curve from theoriginal IRIS  data of R Fisher from four measurements of leaf and petal with a result obtained using information-based induction principles to determine discriminant points without the classification that had to be used for the discriminant analysis.   The principle of maximum entropy, as formu;ated by Jaynes and Tribus proposes that for problems of statistical inference – which as defined, are problems of induction – the probabilities should be assigned so that the entropy function is maximized.  Good proposed that maximum entropy be used to define the null hypothesis and Rudolph proposed that medical reference be defined as at maximum entropy.

Rudolph RA. A general purpose information processing automation: generating Port Royal Classes with probabilistic information. Intl Proc Soc Gen systems Res 1985;2:624-30.

Jaynes ET. Information theory and statistical mechanics. Phys Rev 1956;106:620-30.

Tribus M. Where do we stand after 30 years of maximum entropy? In: Levine RD, Tribus M, eds. The maximum entropy formalism. Cambridge, Ma: MIT Press, 1978.

Good IJ. Maximum entropy for hypothesis formulation, especially for multidimensional contingency tables. Ann Math Stat 1963;34:911-34.

The most important reason for using as many tests as is practicable is derived from the prominent role of redundancy in transmitting information (Noisy Channel Theorem).  The proof of this theorem does not tell how to accomplish nearly errorless discrimination, but redundancy is essential.

In conclusion, we have been using the effective information (derived from Kullback-Liebler distance) provided by more than one test to determine normal reference and locate decision values.  Syndromes and patterns that are extracted are empirically verifiable.

Related articles

• Entropy and Syntropy (photoatelier.org)
• A Software Agent for Diagnosis of ACUTE MYOCARDIAL INFARCTION (pharmaceuticalintelligence.com)
• K-Nearest-Neighbors and Handwritten Digit Classification (jeremykun.wordpress.com)
• Data Mining: Classification VS Clustering (cluster analysis) (parasdoshi.com)
• Myocardial Infarction Algorithm Strategy 77% Effective In One Hour (guardianlv.com)
• Scale‑Free Diagnosis of AMI from Clinical Laboratory Values (pharmaceuticalintelligence.com)
• The great healthcare chasm: Patients want to email, access EMRs, but physicians still can’t (medcitynews.com)
• Guidelines Updated for Unstable Angina/Non-ST Elevation Myocardial Infarction (pharmaceuticalintelligence.com)

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading...

Read Full Post »

NATIONAL CENTERS FOR BIOMEDICAL COMPUTING: Resources

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biomarkers & Medical Diagnostics, Cell Biology, Signaling & Cell Circuits, Computational Biology/Systems and Bioinformatics, FDA Regulatory Affairs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Proteomics, Scientist: Career considerations, Statistical Methods for Research Evaluation, Technology Transfer: Biotech and Pharmaceutical, tagged Aviva Lev-Ari, Bioinformatics, Biology, Brigham and Women's Hospital, Cellular network, genetics, genomics, National Centers for Biomedical Computing, National Institutes of Health, Stanford University, systems biology on September 20, 2012| Leave a Comment »

 

Reporter: Aviva Lev-Ari, PhD, RN

NATIONAL CENTERS FOR BIOMEDICAL COMPUTING

An overarching approach to several disciplines:

• Genomics

Major research areas of Genomics: 2.1 Bacteriophage genomics 2.2 Cyanobacteria genomics 2.3 Human genomics 2.4 Metagenomics 2.5 Pharmacogenomics

• Other Genomics related subdisciplines:

• Computational genomics
• Epigenomics
• Whole genome sequencing
• Functional genomics
• Genomics of domestication
• Immunomics
• Metagenomics
• Nitrogenomics
• Personal genomics
• Proteomics
• Psychogenomics

• The Biomedical Computing Space

• Bioinformatics
• Computational biology
• Network Biology
• Synthetic biology
• List of omics topics in biology
• List of systems biology research groups
• Category:Systems biologists
• Systems microbiology
• Systems biomedicine
• Flux balance analysis
• Metabolic network modelling
• System biology

An illustration of the systems approach to biology

http://en.wikipedia.org/wiki/Systems_biology

 

The National Centers for Biomedical Computing (NCBCs) are part of the U.S. NIH plan to develop and implement the core of a universal computing infrastructure that is urgently needed to speed progress in biomedical research. Their mission is to create innovative software programs and other tools that will enable the biomedical community to integrate, analyze, model, simulate, and share data on human health and disease.

Biomedical Information Science and Technology Initiative (BISTI): Recognizing the potential benefits to human health that can be realized from applying and advancing the field of biomedical computing, the Biomedical Information Science and Technology Initiative (BISTI) was launched at the NIH in April 2000. This initiative is aimed at making optimal use of computer science and technology to address problems in biology and medicine. The full text of the original BISTI Report (June 1999) is available.

Current Centers

• Center for Computational Biology
• National Center for Multi-Scale Study of Cellular Networks
• National Center for Biomedical Ontology
• Simbios: Physics-based Simulation of Biological Structures, Stanford University
• National Alliance for Medical Imaging Computing
• Informatics for Integrating Biology and the Bedside
• National Center for Integrative Biomedical Informatics

National Center for Simulation of Biological Structures (SimBioS) at Stanford University

National Center for the Multiscale Analysis of Genomic and Cellular Networks (MAGNet) at Columbia University

National Alliance for Medical Image Computing (NA-MIC) at Brigham and Women’s Hospital, Boston, MA

Integrating Biology and the Bedside (I2B2) at Brigham and Women’s Hospital, Boston, MA

National Center for Biomedical Ontology (NCBO) at Stanford University

Integrate Data for Analysis, Anonymization, and Sharing (IDASH) at the University of California, San Diego

https://commonfund.nih.gov/bioinformatics/

A Biositemap is a way for a biomedical research institution of organisation to show how biological information is distributed throughout their Information Technology systems and networks. This information may be shared with other organisations and researchers.

The Biositemap enables web browsers, crawlers and robots to easily access and process the information to use in other systems, media and computational formats. Biositemaps protocols provide clues for the Biositemap web harvesters, allowing them to find resources and content across the whole interlink of the Biositemap system. This means that human or machine users can access any relevant information on any topic across all organisations throughout the Biositemap system and bring it to their own systems for assimilation or analysis.

http://en.wikipedia.org/wiki/Biositemaps

• Home
• NCBC Summary
• Calendar
• All Hands Meetings
• Biological Projects
• Biositemaps Projects
• Working Group Archive

• 
• 
• 
• 
• 
• 
• 
• 
• 

Search for NCBC resources in the new Resource Discovery System (RDS)

The NIH Common Fund

http://www.ncbcs.org/

For

Genome and Genetics: Resources @Stanford, @MIT, @NIH’s NCBCS

go to

http://pharmaceuticalintelligence.com/2012/09/18/genome-and-genetics-resources/

 

Biomedical Computation Review (BCR) is a quarterly, open-access magazine funded by the National Institutes of Health and published by Simbios, one of the National Centers for Biomedical Computing located at Stanford University. First published in 2005, BCR covers such topics as molecular dynamics, genomics, proteomics, physics-based simulation, systems biology, and other research involvingcomputational biology. BCR’s articles are targeted to those with a general science or biology background, in order to build a community among biomedical computational researchers who come from a variety of disciplines.

http://en.wikipedia.org/wiki/Biomedical_Computation_Review

 

REFERENCES on BIOINFORMATICS

1. ^ Biositemaps online editor
2. ^ ^a b Dinov ID, Rubin D, Lorensen W, et al. (2008). “iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources”. PLoS ONE 3 (5): e2265. doi:10.1371/journal.pone.0002265. PMC 2386255. PMID 18509477.
3. ^ M.L. Nelson, J.A. Smith, del Campo, H. Van de Sompel, X. Liu (2006). “Efficient, Automated Web Resource Harvesting”. WIDM’06.
4. ^ Brandman O, Cho J, Garcia-Molina H, Shivakumar N (2000). “Crawler-friendly Web Servers”. ACM SIGMETRICS Performance Evaluation Review 28 (2). doi:10.1145/362883.362894.
5. ^ Cannata N, Merelli E, Altman RB (December 2005). “Time to organize the bioinformatics resourceome”. PLoS Comput. Biol. 1 (7): e76.doi:10.1371/journal.pcbi.0010076. PMC 1323464. PMID 16738704.
6. ^ Chen YB, Chattopadhyay A, Bergen P, Gadd C, Tannery N (January 2007). “The Online Bioinformatics Resources Collection at the University of Pittsburgh Health Sciences Library System—a one-stop gateway to online bioinformatics databases and software tools”.Nucleic Acids Res. 35 (Database issue): D780–5. doi:10.1093/nar/gkl781. PMC 1669712. PMID 17108360.
7. • Kitano, Hiroaki (15 October 2001). Foundations of Systems Biology. MIT Press. pp. 320.ISBN 978-0-262-11266-6.
   • Werner, Eric (29 March 2007). “All systems go”. Nature 446 (7135): 493–494. Bibcode2007Natur.446..493W. doi:10.1038/446493a. provides a comparative review of three books:
     • Alon, Uri (7 July 2006). An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall. pp. 301. ISBN 978-1-58488-642-6.
     • Kaneko, Kunihiko (15 September 2006). Life: An Introduction to Complex Systems Biology. Springer-Verlag. pp. 371. ISBN 978-3-540-32666-3.
     • Palsson, Bernhard O (16 January 2006). Systems Biology: Properties of Reconstructed Networks. Cambridge University Press. pp. 334. ISBN 978-0-521-85903-5.

 REFERENCES on GENOMICS

1. ^ National Human Genome Research Institute (2010-11-08).“FAQ About Genetic and Genomic Science”. Genome.gov. Retrieved 2011-12-03.
2. ^ EPA Interim Genomics Policy
3. ^ [1]
4. ^ Min Jou W, Haegeman G, Ysebaert M, Fiers W (1972). “Nucleotide sequence of the gene coding for the bacteriophage MS2 coat protein”. Nature 237 (5350): 82–88. Bibcode1972Natur.237…82J. doi:10.1038/237082a0.PMID 4555447.
5. ^ Fiers W, Contreras R, Duerinck F, Haegeman G, Iserentant D, Merregaert J, Min Jou W, Molemans F, Raeymaekers A, Van den Berghe A, Volckaert G, Ysebaert M (1976). “Complete nucleotide sequence of bacteriophage MS2 RNA: primary and secondary structure of the replicase gene”. Nature 260 (5551): 500–507.Bibcode 1976Natur.260..500F. doi:10.1038/260500a0.PMID 1264203.
6. ^ Sanger F, Air GM, Barrell BG, Brown NL, Coulson AR, Fiddes CA, Hutchison CA, Slocombe PM, Smith M (1977). “Nucleotide sequence of bacteriophage phi X174 DNA”. Nature 265 (5596): 687–695. Bibcode 1977Natur.265..687S.doi:10.1038/265687a0. PMID 870828.
7. ^ Fleischmann RD, Adams MD, White O, Clayton RA, Kirkness EF, Kerlavage AR, Bult CJ, Tomb JF, Dougherty BA, Merrick JM, et al. (1995). “Whole-genome random sequencing and assembly of Haemophilus influenzae Rd”. Science 269 (5223): 496–512.Bibcode 1995Sci…269..496F. doi:10.1126/science.7542800.PMID 7542800.
8. ^ “Complete genomes: Viruses”. NCBI. 2011-11-17. Retrieved 2011-11-18.
9. ^ “Genome Project Statistics”. Entrez Genome Project. 2011-10-07. Retrieved 2011-11-18.
10. ^ Hugenholtz, Philip (2002). “Exploring prokaryotic diversity in the genomic era”. Genome Biology 3 (2): reviews0003.1-reviews0003.8. ISSN 1465-6906.
11. ^ BBC article Human gene number slashed from Wednesday, 20 October 2004
12. ^ CBSE News, Thursday, 16 October 2003
13. ^ National Human Genome Research Institute (2004-07-14).“Dog Genome Assembled: Canine Genome Now Available to Research Community Worldwide”. Genome.gov. Retrieved 2012-01-20.
14. ^ McGrath S and van Sinderen D, ed. (2007). Bacteriophage: Genetics and Molecular Biology (1st ed.). Caister Academic Press. ISBN 978-1-904455-14-1.
15. ^ Herrero A and Flores E, ed. (2008). The Cyanobacteria: Molecular Biology, Genomics and Evolution (1st ed.). Caister Academic Press. ISBN 978-1-904455-15-8.
16. ^ McElheny, Victor (2010). Drawing the map of life : inside the Human Genome Project. New York NY: Basic Books. ISBN 978-0-465-04333-0.
17. ^ Hugenholz, P; Goebel BM, Pace NR (1 September 1998).“Impact of Culture-Independent Studies on the Emerging Phylogenetic View of Bacterial Diversity”. J. Bacteriol 180 (18): 4765–74. PMC 107498. PMID 9733676.
18. ^ Eisen, JA (2007). “Environmental Shotgun Sequencing: Its Potential and Challenges for Studying the Hidden World of Microbes”. PLoS Biology 5 (3): e82.doi:10.1371/journal.pbio.0050082. PMC 1821061.PMID 17355177.
19. ^ Marco, D, ed. (2010). Metagenomics: Theory, Methods and Applications. Caister Academic Press. ISBN 978-1-904455-54-7.
20. ^ Marco, D, ed. (2011). Metagenomics: Current Innovations and Future Trends. Caister Academic Press. ISBN 978-1-904455-87-5.
21. ^ Wang L (2010). “Pharmacogenomics: a systems approach”.Wiley Interdiscip Rev Syst Biol Med 2 (1): 3–22.doi:10.1002/wsbm.42. PMID 20836007.
22. ^ Becquemont L (June 2009). “Pharmacogenomics of adverse drug reactions: practical applications and perspectives”.Pharmacogenomics 10 (6): 961–9. doi:10.2217/pgs.09.37.PMID 19530963.
23. ^ “Guidance for Industry Pharmacogenomic Data Submissions” (PDF). U.S. Food and Drug Administration. March 2005. Retrieved 2008-08-27.
24. ^ Squassina A, Manchia M, Manolopoulos VG, Artac M, Lappa-Manakou C, Karkabouna S, Mitropoulos K, Del Zompo M, Patrinos GP (August 2010). “Realities and expectations of pharmacogenomics and personalized medicine: impact of translating genetic knowledge into clinical practice”.Pharmacogenomics 11 (8): 1149–67. doi:10.2217/pgs.10.97.PMID 20712531.

http://en.wikipedia.org/wiki/Genomics

 

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading...

Read Full Post »

« Newer Posts - Older Posts »

• Follow Blog via Email

  Enter your email address to follow this blog and receive notifications of new posts by email.

  Email Address

  Follow

  Join 2,056 other subscribers

• Recent Posts

  • Grok thinks like PhDs – Hybrid Model for Autonomous Update of Doctoral Dissertations with Original PhD Student Author editing and acceptance of Grok’s updated output. 3rd Joint article, a pilot study for Validation of an Autonomous Journal Articles Updating System (AJAUS) tested on Autonomous Update of Aviva Lev-Ari, PhD, RN Doctoral Thesis, UC, Berkeley, 1983. January 31, 2026
  • 2026 World Economic Forum, 1/19 – 1/23/2026, Davos, Switzerland, LPBI Group’s KOLs interpretation of AI in Health Videos January 24, 2026
  • Evolving LPBI Group’s Portfolio of Intellectual Properties (IP): From 2021 Vision to 2026 Reality January 12, 2026
  • Aviva Lev-Ari, PhD, RN – Biography ->> Grokepedia Entry January 11, 2026
  • List of Articles included in the Article SELECTION from Collection of Aviva Lev-Ari, PhD, RN Scientific Articles on PULSE on LinkedIn.com for Training Small Language Models (SLMs) in Domain-aware Content of Medical, Pharmaceutical, Life Sciences and Healthcare by 15 Subjects Matter January 10, 2026
  • Article SELECTION from Collection of Aviva Lev-Ari, PhD, RN Scientific Articles on PULSE on LinkedIn.com for Training Small Language Models (SLMs) in Domain-aware Content of Medical, Pharmaceutical, Life Sciences and Healthcare by 15 Subjects Matter January 10, 2026
  • Collection of Aviva Lev-Ari, PhD, RN Scientific Articles on PULSE on LinkedIn.com January 10, 2026
  • The youngest leader in AI in Health: Tanishq Mathew Abraham, Ph.D. (@iScienceLuvr) January 8, 2026
  • 2026 Grok Multimodal Causal Reasoning on Proprietary Cariovascular Corpus: From 2021 Wolfram NLP Baseline to Thousands of Novel Relationships – A Second Head-to-Head Validation of LPBI’s Domain-Aware Training Advantage January 6, 2026
  • Workflow for Dynamic Linkage and Transition between two Authoring Systems: LPBI Group’s WordPress.com Multi-Authors Authoring System and Microsoft PowerPoint product for Slide show presentation – Part 10.1 in Composition of Methods January 6, 2026

• Archives

  Archives Select Month January 2026  (10) December 2025  (8) November 2025  (8) October 2025  (12) September 2025  (2) July 2025  (4) June 2025  (8) May 2025  (4) April 2025  (2) March 2025  (1) February 2025  (2) January 2025  (3) December 2024  (1) November 2024  (5) October 2024  (7) September 2024  (7) August 2024  (1) June 2024  (1) May 2024  (2) April 2024  (2) January 2024  (1) November 2023  (1) October 2023  (3) September 2023  (3) August 2023  (2) July 2023  (2) June 2023  (7) May 2023  (4) April 2023  (2) March 2023  (5) February 2023  (2) January 2023  (3) December 2022  (2) October 2022  (6) September 2022  (2) August 2022  (1) July 2022  (3) June 2022  (3) May 2022  (8) April 2022  (10) March 2022  (7) February 2022  (7) January 2022  (3) December 2021  (3) November 2021  (4) October 2021  (11) September 2021  (5) August 2021  (8) July 2021  (21) June 2021  (8) May 2021  (10) April 2021  (8) March 2021  (15) February 2021  (17) January 2021  (20) December 2020  (10) November 2020  (12) October 2020  (26) September 2020  (17) August 2020  (22) July 2020  (27) June 2020  (33) May 2020  (26) April 2020  (42) March 2020  (22) February 2020  (11) January 2020  (7) December 2019  (20) November 2019  (13) October 2019  (11) September 2019  (3) August 2019  (8) July 2019  (25) June 2019  (47) May 2019  (40) April 2019  (27) March 2019  (29) February 2019  (17) January 2019  (50) December 2018  (14) November 2018  (17) October 2018  (18) September 2018  (17) August 2018  (8) July 2018  (20) June 2018  (22) May 2018  (17) April 2018  (12) March 2018  (20) February 2018  (26) January 2018  (16) December 2017  (6) November 2017  (20) October 2017  (13) September 2017  (16) August 2017  (16) July 2017  (19) June 2017  (20) May 2017  (32) April 2017  (21) March 2017  (10) February 2017  (24) January 2017  (21) December 2016  (43) November 2016  (8) October 2016  (40) September 2016  (67) August 2016  (59) July 2016  (75) June 2016  (37) May 2016  (95) April 2016  (152) March 2016  (175) February 2016  (196) January 2016  (139) December 2015  (90) November 2015  (287) October 2015  (237) September 2015  (115) August 2015  (96) July 2015  (63) June 2015  (44) May 2015  (53) April 2015  (76) March 2015  (95) February 2015  (83) January 2015  (75) December 2014  (75) November 2014  (88) October 2014  (135) September 2014  (117) August 2014  (88) July 2014  (88) June 2014  (109) May 2014  (60) April 2014  (85) March 2014  (58) February 2014  (72) January 2014  (107) December 2013  (104) November 2013  (136) October 2013  (62) September 2013  (32) August 2013  (46) July 2013  (74) June 2013  (110) May 2013  (112) April 2013  (86) March 2013  (92) February 2013  (63) January 2013  (63) December 2012  (46) November 2012  (71) October 2012  (84) September 2012  (82) August 2012  (122) July 2012  (59) June 2012  (34) May 2012  (46) April 2012  (2)

• Categories

  Categories Select Category 3D Printing for Medical Application  (239)    3D Plotting Scaffolds  (44)    BioInks  (34)       Biopolymer Blend Open Porous  (18)       Dental Applications  (10)    BioPrinting in Regenerative Medicine  (77)       Cell Level  (16)       MicroEngineering Cell-Tissue & Systems  (31)       Tissue Engineering  (37)    Cardiovascular and Vascular Systems  (30)       Artificial Vascular Structures  (9)       Cardiovascular Tissue  (8)    Drug Development using MultiOrgan Chip  (11)    Drug Development/Formulation using 3D Printing  (10)    MEMS  (16)       Bio-MEMS  (12)    Organ-on-a-Chip  (11)    Programmable Sensors (Carbon Nano Tubes)  (5) 3rd Party IP: Drug DIscovery  (1) 4D Printing and Meta Materials  (10) Academic Publishing  (223)    Key Opinion Leaders in eScientific Publishing – Interviews with  (8) Advanced Drug Manufacturing Technology  (96)    Antimalarial Preparation  (8)    Autologous Cell Therapy  (14)    Automated Cell Processing  (13) Allergy and Infectious Diseases  (12) Alzheimer’s Disease  (163)    Etiology  (77)    Medical Device Therapies for Altzheimer’s Disease  (15)    Pharmacotherapy and Cell Activity  (51) Anticancer Resistance  (31) Art Exhibits on the Human Condition  (1) Art Inspires Science  (4) Article Type  (2)    Authored  (1)    Curated  (2)    Scientific report  (1) Artificial Heart  (2) Artificial Intelligence – General  (232)    An executive’s guide to AI  (10)    Artificial Intelligence – Breakthroughs in Theories and Technologies  (115)    Artificial Intelligence Applications in Health Care  (125)       Artificial Intelligence in CANCER  (39)       Artificial Intelligence in Health Care – Tools & Innovations  (74)    Artificial Intelligence in Medicine – Application for Diagnosis  (69)       Artificial intelligence applications for cardiology  (31)          AI-assisted Cardiac MRI  (10)       Artificial Intelligence in Psychiatry  (6)       Deep Learning in Pathology  (18)    Artificial Intelligence in Medicine – Applications in Therapeutics  (64)    ChatGPT, GPT-4  (7)       ChatGPT at LPBI Group  (3)       ChatGPT in Academic Education  (3)    Machine Learning  (71)       Deep Learning  (25)       Natural Language Processing (NLP)  (45)    Machine learning in predicting type 2 diabetes  (5) Auditory and vision  (13) Autism Spectrum Disorders  (10) Autoimmune Inflammatory DIseases  (24)    Crohn’s disease  (5)    Tolerance-inducing Autoimmune Disease Therapeutics  (6)    Ulcerative Colitis  (3) Autophagosome  (4) Bacterial Resistance  (25) Behavior  (26) Behavioral Genetics  (21) Big Data  (88)    Intelligent Information Systems  (51) Bio Instrumentation in Experimental Life Sciences Research  (368)    Analytical Instruments Industry  (5)    Microfuidics  (8) Bio-Ethics  (15) BioBanking  (36) Biodegradable Drug-eluting Material  (8) Bioengineering & reverse engineering design  (43) BioIT: BioInformatics  (147) BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics  (135)    Advanced Computing Platform  (32)       Blockchain Transactions System  (6)          Platform for Content Monetization embedded Content Promotion  (1)    Pancreatic adenocarcinoma classifier  (4)    Simulation Modeling in NGS  (5) Biological Engineering  (43) Biological Networks  (193) Biological Networks, Gene Regulation and Evolution  (479)    Virology  (10) Biomarkers & Medical Diagnostics  (571)    VOC – Volatile Organic Compounds as BioMarkers  (2) Biomedical Measurement Science  (173) BioSimilars  (112) BioTechnology – Venture Creation  (131)    Foundations for supporting Science and Education  (14)    Philanthropy to Academic Institution  (3) BioTechnology – Venture Creation, Venture Capital  (108)    Seeking Talent  (3) BiVAD  (1) Blindness  (6) Bone Disease and Musculoskeletal Disease  (82) Brain Basis of Emotion  (5) Business Career Consideration  (1) Ca2+ triggered activation  (61) Calcium  (21) Calcium Signaling  (71) Calmodulin Kinase and Contraction  (36) Cancer – General  (186) Cancer and Current Therapeutics  (411)    interventional oncology  (49)       Breast Cancer – impalpable breast lesions  (20)       Prostate Cancer: Monitoring vs Treatment  (9) CANCER BIOLOGY & Innovations in Cancer Therapy  (1,122)    Anaerobic Glycolysis  (51)    Cachexia  (18)    Cancer Genomics  (84)       Circulating Tumor Cells (CTC)  (27)          Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood  (17)             mRNA  (6)          MagSifter chip  (1)       KRAS Mutation  (9)       Li-fraumeni syndrome.  (3)       TP53 – Germline mutations  (8)    cancer metabolism  (28)    Funding Opportunities for Cancer Research  (12)    Genomic Expression  (150)    Glioblastoma  (7)    Hexokinase  (14)    Loss of function gene  (18)    Metabolic Immuno-Oncology  (21)    Metastasis Process  (15)    Methylation  (33)    Microbiome and Responses to Cancer Therapy  (10)    Monoclonal Immunotherapy  (29)    mtDNA  (13)    Oxidative phosphorylation  (56)    Pancreatic cancer  (10)    Pyruvate Kinase  (27)    The NCI Formulary  (1)    tumor microenvironment  (16)    Warburg effect  (50) Cancer Informatics  (104) Cancer Prevention: Research & Programs  (131) Cancer Screening  (108) Cancer Vaccines: Targeting Cancer Genes for Immunotherapy  (30)    Engineering Enhanced Cancer Vaccines  (3) cancer-general  (6) Cardiac and Cardiovascular Surgical Procedures  (328)    Aortic Valve: TAVR, TAVI vs Open Heart Surgery  (91)       Prosthesis-Patient Mismatch (PPM) in TAVI vs SAVR  (2)       TAVI vs Open Heart Surgery  (6)       Transcatheter Aortic Valve Replacement via the Transcarotid Access  (3)       Transcaval TAVR Procedure  (3)       Valve-in-Valve Procedure  (5)    Atrial Fibrilation (a-Fib), Cardiac Pacing and Arrhythmias  (18)    BackBeat’s Cardiac Neuromodulation Therapy (CNT) bioelectronic therapy  (1)    CABG  (47)    Cancer Surgery of the Heart  (10)    Cardiovascular Fluid Management: algorithms  (1)    Heart Transplant  (16)    Heart-Lung Transplant  (11)    Implantation  (3)    Left Main Coronary Artery Disease (LMCAD)  (3)    Mechanical Assist Devices: LVAD, RVAD, BiVAD, Artificial Heart  (22)    Mitral Valve: Repair and Replacement  (64)       TMVR – Transcatheter Mitral Valve Repair  (5)    PCI  (108)       Bioresorbable Vascular Scaffold (BVS)  (4)       Invasive FFR for PCI  (2)       Multivessel PCI FFR Guidance  (1)       Robotic-assisted percutaneous coronary intervention  (2)       Stent Retriever in endovascular thrombectomy  (3)    Peripheral Arterial Disease & Peripheral Vascular Surgery  (65)       Abdominal Aorta  (20)       Carotid Artery  (15)       Limb ischemia  (4)       Thoracic Aorta  (16)    Pulmonary Valve Replacement and Repair  (3)    Renal Denervation  (20)    Replacement  (1)    Robotically assisted Cardiothoracic Surgery  (2)    Tricuspid Valve Repair  (7)    Vena Caval Filters: Device for Prevention of Pulmonary Embolism and Thrombosis  (2) Cardiovascular Pharmacogenomics  (171) Cargo  (3) Cell Biology  (323) Cell Biology, Signaling & Cell Circuits  (672)    Apoptosis  (17)    Autophagy-Modulating Proteins  (6)    “Antibody–enzyme conjugates”  (6)    Cell Processing System in Cell Therapy Process Development  (27)    Endoplasmic reticulum  (3)    Enzymatic mechanism underlying the synthesis of adenosine triphosphate (ATP)  (3)    Ubiquitin  (11) Cerebrovascular and Neurodegenerative Diseases  (123)    Stroke  (9) Chemical Biology and its relations to Metabolic Disease  (464)    #BIGAxisSummit  (1)    Gut Microbiome and Obesity  (8) Chemical Genetics  (350) Child and Adolescent Psychiatry  (13) Childhood cancer  (17) Childhood malnutrition  (3) children  (3) Circulating Progenitor Cells  (27)    Bone marrow derived cells  (17)    Endothelial cells  (7)    Umbilical cord cells  (6) Clinical & Translational  (238) Clinical Diagnostics  (220)    Mass automation of plasma proteins  (13) Clinical Genomics  (144) Coagulation Therapy and Internal Bleeding  (83) Cognition  (47) Commercialization  (20) Components and IRB related issues  (4) Computational Biology/Systems and Bioinformatics  (470)    Computational Histopathology  (3)    Meta-analysis of transcriptome data  (10) Conference Coverage with Social Media  (494)    MassBio  (3) coronavirus  (18) COVID-19  (20) CRISPR/Cas9 & Gene Editing  (192)    CRISPR alternative for editing genes without cutting  (14)       CAST – Alternative to CRISPR/Cas9  (3)       Transposon-encoded CRISPR–Cas systems direct RNA-guided DNA integration  (4)    CRISPR applied to Human Germ Line  (13)       Gene Editing Impact on Longevity  (6) CT  (20) Cytokines  (20) Cytoskeleton  (85) Developmental biology  (107) Diabetes Mellitus  (146)    Artificial Pancreas for Type 2 Diabetes  (4)    Artificial Pancreas for Type1 Diabetes  (8)    Gestational diabetes  (5) Diagnostic Immunology  (61) Diagnostics and Lab Tests  (128)    Liquid Biopsy: Circulating Tumor Cells in Urine and Blood  (9) Digital HealthCare – biotech & internet joint ventures  (47) Disease Biology  (334) Disease Biology, Small Molecules in Development of Therapeutic Drugs  (487) DNA repair  (73)    Apoptosis  (13)    Autophagy  (13)    Cell death pathways  (19)    Proteolysis  (8)    Proteosome  (8) Drug Delivery Platform Technology  (157)    Drug Carrier Design  (21)       Medication Remote Compliance Monitoring  (3)    Exosomes: Natural Carriers for siRNA Delivery  (9) Drug Toxicity  (74) Ecosystems & Industrial Concentration in the Medical Device Sector  (172)    Cardiac & Vascular Repair Tools Subsegment  (128)    Exec Compensation in the Cardiac & Vascular Repair Tools Subsegment  (14)    Massachusetts Niche Suppliers and National Leaders  (20) Electronic Health Record  (10) Embryology  (24) Empathy  (6) Endocrine Diseases  (60) Enzyme Induction  (46)    ion-transporting enzyme  (2)    K + -ATPase.  (1)    Na +  (2) Epigenetics and Environmental Factors  (35) Ethics and Leadership  (10) Executive Compensation – Big Pharma  (3) Fat soluble vitamins  (4) FDA  (71) FDA Regulatory Affairs  (358)    FDA, CE Mark & Global Regulatory Affairs: process management and strategic planning – GCP, GLP, ISO 14155  (52)    ISO 10993 for Product Registration: FDA & CE Mark for Development of Medical Devices and Diagnostics  (30) Fetal Ultrasound  (2) Fiction and medicine  (5) Frontiers in Cardiology and Cardiovascular Disorders  (929)    Acute Myocardial Infarction  (63)       Cardiogenic Shock  (5)    Anemia in CVD Patients  (6)    Cardio-Oncology  (4)    Cardiomyopathy  (57)    Cardiovascular Research  (187)       Myocardial metabolism, Myocardial ischemia, myocardial perfusion, Myocardial adenine nucleotide metabolism  (64)       Pre-Clinical Animal Model Development  (23)    Chronic Thromboembolic Pulmonary Hypertension (CTEPH) and Pulmonary Arterial Hypertension (PAH)  (20)    Cost of Inpatient Stay for Cardiovascular Diagnosis for Admission  (1)    Electrophysiology  (111)       Ablation Procedure vs Drug Therapy  (2)       Arrhythmia Detection with Machine Learning Algorithms  (7)       Cardiotoxic Risks of Immune Checkpoint Inhibitors  (1)       Genomic Analysis of EKG Electrophysiology Genomics  (3)       implantable cardioverter defibrillator (ICD) and External Defibrillation  (1)       implantable pacemaker  (2)       Rare heart rhythm disorders and Long QT syndrome (LQTS)  (7)    Epigenetics and Cardiovascular Risks  (57)    Heart Failure (HF)  (51)       Acute coronary syndrome  (7)       congestive heart failure  (19)       Hypertensive Disorders of Pregnancy  (1)    Medical Devices R&D and Inventions  (212)       Assist Devices: LV  (3)       RV  (1)       Stents & Tools  (90)       Valves & Tools  (67)    Origins of Cardiovascular Disease  (422)       Atherogenic Processes & Pathology  (180)       Congenital Heart Disease  (34)          Genetic Mutations in Congenital Heart Disease  (4)       inflammation independent of lipid levels  (13)       Systemic Inflammatory Diseases as CVD Risk  (12)    Pharmacotherapy of Cardiovascular Disease  (356)       HTN  (176)       HTN in Youth  (8)       Resident-cell-based  (43)       Subarachnoid Hemorrhage (SAH)  (1)       Transthyretin amyloid cardiomyopathy (ATTR-CM)  (1)    Spontaneous Coronary Artery Dissection (SCAD)  (6)    Stroke  (15)       endovascular thrombectomy  (6)    Vascular Diseases  (21)       mesenteric ischemia  (3) Future Pandemics Inform-graphics  (1) Gastroenterology  (38) Gene Regulation  (232) Gene Regulation and Evolution  (137) Genetics & Innovations in Treatment  (176) Genetics & Pharmaceutical  (203) Genome Biology  (967)    Exosomes  (25)    Gene Therapy & Gene Editing Development  (42)    mRNA Therapeutics  (20)    Mutagenesis  (27)    Single Cell Genomics  (25)    Single-cell sequencing  (20)    Variation in human protein-coding regions  (35) Genomic Endocrinology  (42) Genomic Testing: Methodology for Diagnosis  (416) Genomics Pharmacy  (40) Global Market of Medical Devices Technology  (2) Global Medical Publishers by Country  (3) Global Partnering & Biotech Investment  (47) GLP  (4) Glycobiology: Biopharmaceutical Production  (16) Glycobiology: Biopharmaceutical Production, Pharmacodynamics and Pharmacokinetics  (28) Health Care System by Country  (58)    AI Models in Healthcare  (12)    Centers for Medicare & Medicaid Services  (8)    Health in Israel  (2)    India  (1)    United States  (27)       Hospital-based Medical Innovations  (10)       Medical Recertification and Maintenance of Certification (MOC)  (1) Health Economics and Outcomes Research  (384)    Women Health  (18)       Heart and Brain Disease in Women  (3) Health Law & Patient Safety  (165)    and Bioethics  (14)    Biotechnology  (12)    Health Law Policy  (13) HealthCare IT  (138) Healthcare Reform  (117)    Accountable Care Organizations  (26)    Affordable Care Act  (29)       Repair  (1)       Repeal ACA  (1)       Replace  (1)    Federal Budget Appropriations  (26)    Healthcare costs and reimbursement  (59)    Indigent Nutrition  (14)    Medicare and Medicaid  (20)    Prescription Drugs Costs  (21)    Skilled Nursing Facilities  (6)    Technology Capital Expenses  (15)    Uninsured and Underinsured  (20) Hematology  (100)    Acute lymphocytic leukemia  (18)    Acute myelocytic leukemia  (21)    Hematopoiesis  (48)    Lymphoma  (21) History and physical exam  (6) Human aging  (27) Human Immune System in Health and in Disease  (246) Human Sensation and Cellular Transduction: Physiology and Therapeutics  (21) Image Processing/Computing  (41) Imaging-based Cancer Patient Management  (116) Immuno-Oncology & Genomics  (133)    mRNA platform in Drug DIscovery  (6) Immunodiagnostics  (139)    Cancer-Immune Interactions  (29)    CNS-Immune Interface  (5)    Neuronal Circuits  (4) Immunology  (123)    Adaptive Immune Response to Biomaterials and Tissue Repair  (13)    Antibody Responses Predict Antigen Exposure  (17)    Cytokine Receptor Structure  (8)    Human Antibody Response  (18)    Human Circulating Antibody Repertoire  (11)    Human Naive B Cell Repertoire  (8)    MHC Repertoires for Antigen Prediction  (8)    Protection Against Autoimmune Disease  (11)    Synthetic Immunology: Hacking Immune Cells  (15) Immunotherapy  (133)    CAR-T  (14)    combination immunotherapies.  (14)    Efficacy of Anti-Tumor T Cells  (13)    Engineering Better T Cells  (8)    Immune Engineering  (17)    Immune Modulatory  (15)    Integrin-targeted Combination Immunotherapy  (6)    Modulating Macrophages in Cancer Immunotherapy  (16)    NK Cell-Based Cancer Immunotherapy  (19)    Synergistic Innate and Adaptive Immunotherapy  (14) Income Disparity  (2) Infectious Disease & New Antibiotic Targets  (162)    Antibiotic resistance  (7)    Viral diseases  (37)       Myocarditis  (1) Infectious Disease Immunodiagnostics  (58)    Virology – Vector-borne DIsease  (17) Inflammasome  (29)    Anti-tumor necrosis factor drugs (TNF inhibitors)  (3) Innovation in Immunology Diagnostics  (111)    Universal Immune Cell Therapies (uICT)  (11) Innovations  (186)    R&D Expenditure  (8) Innovations in Neurophysiology & Neuropsychology  (145)    Age and Life Expectancy  (3)    autism spectrum disorder  (1)    Circadian Rhythm and Sleep  (6)    hNPCs  (1)    Nervous System Function  (2)    Relapsing Multiple Sclerosis  (1) Intellectual Property  (83)    Disputes and Settlements  (9)    IP Valuation Models – Pricing Intangible Assets  (7)    Patent Law in Biotech  (12) Intellectual Property, Innovations, Commercialization, Investment in technological breakthrough  (119) International Global Work in Pharmaceutical  (190) Interventional Oncology: Radiofrequency Ablation, Transarterial Chemoembolization, Microwave Ablation and Irreversible Electroporation (IRE)  (12) Interviews with Scientific Leaders  (315)    Albany Medical Center Prize in Medicine and Biomedical Research  (2)    Annual Breakthrough Prize  (4)    Annual Lewis S. Rosenstiel Award  (2)    Awards in Cardiology and Cardiovascular Medicine  (6)    CEOs of Biotech Companies  (3)    Gerald D Aurbach Award for Outstanding Translational Research  (2)    Interviews with Key Opinion Leaders (KOLs)  (10)    James Prize in Science and Technology Integration  (2)    Jessie Stevenson Kovalenko Medal – Medical Sciences  (2)    Lemelson-MIT Prize  (2)    Life Sciences Breakthrough Prize  (5)    Mosteller Statistician of the Year Award  (2)    Mourning the Loss of a Scientific Leader  (3)    National Academy of Sciences AWARDS  (4)    Nobel Prize Winners  (29)    Noble Prize (Not Nobel Prize)  (2)    Paul Marks Prize for Cancer Research  (2)    Russ Prize recognizes bioengineering achievements worldwide  (2)    The Dan David Prize  (6)    Warren Alpert Foundation Prize Recipients  (4)    Wolf Prize  (2)    Wolf Prize in Medicine  (2)    women in science  (5) Investment in Technological Breakthrough  (60) Ionic Transporters Na+  (25) IP Development by LPBI Group Team  (14) IP Development by LPBI Group Team & Other Organizations  (8) ISO 14155  (3) Joint Venture – SBH & M3DP: SOP and Arrangements  (1) Justice & Law  (1) K  (15) Lab-on-a-chip  (2) Landscape  (1) Lasers and photonics  (18)    Midrange IR spectroscopy  (1) Law and Medicine Conflicts  (14) Leadership, Power, Social Interlocking Connections  (13) Lipid metabolism  (109)    Fatty acids  (38)    Lipids  (38)    PCSK9 Inhibitor Therapy  (19) Lipidomics  (11) Liposome  (4) Liver & Digestive Diseases Research  (122) LPBI Group, e-Scientific Media, DFP, R&D-M3DP, R&D-Drug Discovery, US Patents: SOPs and Team Management  (143)    Award Nominations  (5)    BioMed e-Books e-Series by LPBI Group  (9)    Feedback from Investors: LPBI Portfolio of Five Businesses  (2)    LPBI Group Founder – Aviva Lev-Ari  (27)    PhD  (1)    RN  (1) LPBI Management  (23) Massachusetts Academy of Sciences (MAS)    (2) Materials Science & Engineering  (37)    Organic BioElectronics  (2) Math  (13)    Great Discoveries  (7) Mechanical Assist Devices: LVAD  (4) Medical and Population Genetics  (193) Medical Devices R&D Investment  (242)    21st Century Cures Act  (2)    CE Mark & Global Regulatory Affairs: process management and strategic planning – GCP  (14)    Rhythm management device hardware: dual-chamber pacemakers  (1)       Systolic HTN  (1) Medical Imaging Technology  (59) Medical Imaging Technology, Image Processing/Computing, MRI, CT, Nuclear Medicine, Ultra Sound  (164)    Circumferential-Intravascular-Radioluminescence-Photoacoustic-Imaging (CIRPI)  (3)    Echocardiography  (3)    MRI  (18)    Noninvasive Diagnostic Fractional Flow Reserve (FFR) CT  (6)    Ultra Sound  (10) Melatonin & Circadian Regulation  (9) memory loss  (1) Metabolism  (239)    Biochemical pathways  (144)       Enzymes and isoenzymes  (73)          Dehydrogenase  (16)          Kinase  (28)          Phosphatase  (9)          Phosphorylase  (22)          tyrosine decarboxylases  (3)    Inosine nucleotides  (9)    Leloir pathway  (6)    microbiome  (7)    Pentose monophosphate shunt  (14)    Pyridine nucleotides  (28)       Pyridine nucleotide transhydrogenase  (7) Metabolomics  (321) Methods  (37) Mg++  (10) Microbiologial genetics  (36) Microbiology  (68)    Virology  (14) Micronutrients  (16) Microvesicle  (7) Microwave Ablation and Irreversible Electroporation (IRE)  (1) Mobile Healthcare  (5) Molecular Genetics & Pharmaceutical  (377)    Organoids  (3) Monoclonal antibody therapy  (14) Mutant Gene Expression  (42) Myocardial adenine nucleotide metabolism  (6) Myocardial Ischemia  (26) Myocardial Metabolism  (36) Na-K transport  (40) Na-K-ATPase  (27) Nanotechnology for Drug Delivery  (99) Nephrology  (46) Nephrology & Regenerative medicine  (9) Neurodegenerative Diseases  (89)    hNPCs  (3)    MS  (5) Neurohumoral Transmission  (68)    Ca2+ triggered activation  (21)    Calmodulin  (13)    Parkinson’s disease dyskinesia levodopa  (3)    PKC  (13)    Synaptic vesicle  (20) Neurological Diseases  (121) Neuroscience  (126) Next Generation Sequencing (NGS)  (27)    Nanopore sequencing  (1) NIH Common Fund  (1) Nitric Oxide in Health and Disease  (136) Nuclear Medicine  (11) Nutrigenomics  (68) Nutrition  (195)    Nutritional Supplements: Atherogenesis, lipid metabolism  (50) Nutrition and Phytochemistry  (62)    Minerals in Medicine  (4)    Plant extract  (22) Nutrition Disorders  (31) Nutritional Supplements: Atherogenesis  (31) Obesity  (19) Oligonucleotide Therapeutics & Delivery  (7) Oncolytic virus & OncoViro-Therapy  (22)    Synthetic Virology  (1) Organ-on-a-Chip & 3D Printing in Life Sciences  (7) Pain: Etiology, Genetics & Innovations in Treatment  (24) Parasitology  (5)    Malaria  (4)    Tropical diseases  (1) Patents  (34) Patient Experience  (66)    Art therapy  (1)    Hospital reputation  (7)    Humor  (1)    Music therapy  (2)    Pain Alleviation  (7)    Patient Outlook  (28)    Reputation of Interventionist  (4)    Support Staff  (13)    Supportive therapies  (6)       laughfter  (1)    Surgical Procedure  (9) Patient Experience: Personal Memories of Invasive Medical Intervantion  (30) Patient’s Voice: Personal Experience with Invasive Medical Procedures  (18) Perioperative Statins at Noncardiac Surgery  (2) Personal Health Applications: Tech Innovations serves HealhCare  (43) Personalized and Precision Medicine & Genomic Research  (736)    Longevity  (3)    New Drug Approval  (5)    Patient-centered Medicine  (39)       cell-based therapy  (9)       stem cell biology and patient-specific  (7)    Personalized Medicine Coalition  (10)    Precision Cancer Medicine  (31) Phagophore  (2) Pharmaceutical Analytics  (261)    Pharmacologic toxicities  (62) Pharmaceutical Discovery  (109)    Rapid automation of plasma protein pools  (17) Pharmaceutical Drug Discovery  (200)    Drug Development Process  (55)       Drug Discovery Chemistry  (29)    drug repurposing  (10) Pharmaceutical Industry Competitive Intelligence  (343)    Pharmacovigilance  (7)    Value-based Drug Pricing  (8) Pharmaceutical R&D Informatics  (44) Pharmaceutical R&D Investment  (299) Pharmacodynamics and Pharmacokinetics  (24) Pharmacogenomics  (159) Photography Collection  (1) Physics  (12) Placenta  (7) Population genetics  (27) Population Health Management  (204)    Evolution of Biology Through Culture  (14)    U.S. Employment-to-Population Ratio  (8) Population Health Management, Genetics & Pharmaceutical  (643)    COVID-19  (157)       Biomarkers: Inflammation  (37)       Cancer Researchers Fighting COVID-19  (14)       COVID-19 effects on Human Heart  (15)       COVID-19: Pandemic Surgery Guidance  (19)       Economic Impact of Coronavirus Pandemic  (41)       number of asymptomatic infections  (27)       Treatment Protocols for COVID-19  (62)    SARS-CoV-2  (141)       Coronavirus Gene Expression  (66)          SARS-CoV-2 circulating variants   (14)          SARS-CoV-2 Viral Variants  (19)       Glycosylation and its Role in SARS-CoV-2 Viral Pathogenesis  (2)       Immune-Mediation (independent immunopathology: lung and reticuloendothelial system)  (30)       Mechanisms of infection by SARS-CoV-2  (21)       SAR-Cov-2 a vasculotropic (blood vessels) RNA Virus  (35)          SARS-COV2 Hijacking the Complement and Coagulation Systems  (19)       Seasonality & Environmental Factors in Resurgence  (26)       Serology tests for coronavirus antibodies  (44)       T-cell response to SARS-CoV-2 infection  (14)       Vaccinology  (51)          Mechanism of Thrombosis with AZ & J&J COVID-19 Vaccines  (5)       Virtual Drug Molecule Screening targeting SAR-CoV-2 proteins  (8)    Virus Infective Acute Respiratory Syndrome: SARS-CoV  (92) Population Health Management, Nutrition and Phytochemistry  (162) Preimplantation Genetic Diagnosis and Reproductive Genomics  (13) Protein-energy malnutrition  (12) Proteomics  (367)    Amino acids  (54)    Proteins  (138) Pulmonary diseases  (16)    Lung and pulmonology  (15) Pulmonary pathology  (8) Radio Frequency (RF)-based Surgical Solutions  (2) REAL TIME Conference Coverage Twitter’s Hashtags and Handles per Presentation/session  (50) Regenerative Biology and Medicine  (92) Regulated Clinical Trials: Design, Methods, Components and IRB related issues  (265) Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics  (113) Reproductive Biology & Bio Instrumentation  (78) RNA Biology  (81)    RNA interference (RNAi) therapeutic  (4) RNA Biology, Cancer and Therapeutics  (64) RVAD  (1) SBIR, SBA, NIH, NSF  (3) Schizophrenia  (16) Scientific & Biotech Conferences: Press Coverage  (182) Scientific Publishing  (609)    Curation  (585)       Curation methodology  (40)       De novo synthesis  (16)       Dialectic  (17)       Discovery process  (72)       Evolutionary cognition  (52)       Experimental validation  (91)       Explanatory  (91)       Historical relevance  (71)       Technology Advance Assessment of  (69)       Theoretic convergence  (27)    Open Access Journals  (37) Scientist: Career considerations  (197)    Big Data & Analytics  (17)    Data Science  (13)    Women in Life Sciences  (12) Scoop.it  (19) Sensors & Analytics  (18) Sepsis  (2) Severe Autism  (3) Signaling  (102)    Phosphorylation  (43)    S-nitrosylation  (13)    Ubiquitinylation  (34) Signaling & Cell Circuits  (130) single cell sequencing  (3) Small Molecules in Development of Therapeutic Drugs  (71) Social Development  (15) Specialized 3D BioPrinters (Cornea  (1) Statistical Methods for Research Evaluation  (137) Stem Cells for Regenerative Medicine  (177)    Cardiac muscle regeneration  (19)    Competition in regenerative stem cell science  (18)    Human neural progenitor cells  (8)    Skeletal muscle regeneration  (9) STORM  (2) Stress Disorders  (19) Substance Abuse  (4) Systemic Inflammatory Response Related Disorders  (161)    Inflammatory Pathophysiology  (9) Technology Transfer: Biotech and Pharmaceutical  (354) therapeutics  (3) Tissue Engineering and Regenerative Medicine  (22) Tissue Microenvironment  (5) Transarterial Chemoembolization  (2) Transcriptomics  (47) Transformative Technologies in Healthcare  (23) Translational Science  (230)    Best evidence  (52)    Bias measurement tools  (2)    Evidence-based decision-making  (29)    Inferential analysis  (25)    Intra-rater error  (1)    Quality Assurance  (8)    Random Error  (2)    Systematic Error (Bias)  (6)    Total error  (2)    Translational Effectiveness  (49)    Translational Research  (92) Trends in Global Economy  (6) Uncategorized  (1,019) Unfolded Protein Response (UPR)  (6) US and Global Economy: Trends and Findings  (9) Venture Capital  (47)    Income Geographic Distribution  (3)    Institutional Capital Raised by Female Founders  (6) virology  (10) Vision  (7) Voices of Patients and Healthcare Providers  (22) Water Transporters  (8) Wearable Tech + Digital Health  (5) Anemia  (22) Neutropenia  (8) Neutrophilia  (9) Platelet count disorder  (9) Folate and B12  (7) Iron deficiency  (5) Myelodysplasia  (13) Myelofibrosis  (10)

• Meta

  • Log in
  • Entries feed
  • Comments feed
  • WordPress.org

• • 2012pharmaceutical
  • sjwilliamspa