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Eight Subcellular Pathologies driving Chronic Metabolic Diseases – Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics: Impact on Pharmaceuticals in Use

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Eight Subcellular Pathologies driving Chronic Metabolic Diseases – Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics: Impact on Pharmaceuticals in Use

Curators:

• Cardiovascular Expertise – Dr. Justin D. Pearlman, MD, PhD, FACC
• Pharmacology and Oncology Expertise – Dr. Stephen J. Williams, PhD
• Principal Investigator, initiator of the project – Aviva Lev-Ari, PhD, RN

 

THE VOICE of Aviva Lev-Ari, PhD, RN

In this curation we wish to present two breaking through goals:

Goal 1:

Exposition of a new direction of research leading to a more comprehensive understanding of Metabolic Dysfunctional Diseases that are implicated in effecting the emergence of the two leading causes of human mortality in the World in 2023: (a) Cardiovascular Diseases, and (b) Cancer

Goal 2:

Development of Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics for these eight subcellular causes of chronic metabolic diseases. It is anticipated that it will have a potential impact on the future of Pharmaceuticals to be used, a change from the present time current treatment protocols for Metabolic Dysfunctional Diseases.

According to Dr. Robert Lustig, M.D, an American pediatric endocrinologist. He is Professor emeritus of Pediatrics in the Division of Endocrinology at the University of California, San Francisco, where he specialized in neuroendocrinology and childhood obesity, there are eight subcellular pathologies that drive chronic metabolic diseases.

These eight subcellular pathologies can’t be measured at present time.

In this curation we will attempt to explore methods of measurement for each of these eight pathologies by harnessing the promise of the emerging field known as Bioelectronics.

Unmeasurable eight subcellular pathologies that drive chronic metabolic diseases

1. Glycation
2. Oxidative Stress
3. Mitochondrial dysfunction [beta-oxidation Ac CoA malonyl fatty acid]
4. Insulin resistance/sensitive [more important than BMI], known as a driver to cancer development
5. Membrane instability
6. Inflammation in the gut [mucin layer and tight junctions]
7. Epigenetics/Methylation
8. Autophagy [AMPKbeta1 improvement in health span]

Diseases that are not Diseases: no drugs for them, only diet modification will help

Image source

Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease

https://www.youtube.com/watch?v=Ee_uoxuQo0I

 

Exercise will not undo Unhealthy Diet

Image source

Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease

https://www.youtube.com/watch?v=Ee_uoxuQo0I

 

These eight Subcellular Pathologies driving Chronic Metabolic Diseases are becoming our focus for exploration of the promise of Bioelectronics for two pursuits:

1. Will Bioelectronics be deemed helpful in measurement of each of the eight pathological processes that underlie and that drive the chronic metabolic syndrome(s) and disease(s)?
2. IF we will be able to suggest new measurements to currently unmeasurable health harming processes THEN we will attempt to conceptualize new therapeutic targets and new modalities for therapeutics delivery – WE ARE HOPEFUL

In the Bioelecronics domain we are inspired by the work of the following three research sources:

1. Biological and Biomedical Electrical Engineering (B2E2) at Cornell University, School of Engineering https://www.engineering.cornell.edu/bio-electrical-engineering-0
2. Bioelectronics Group at MIT https://bioelectronics.mit.edu/
3. The work of Michael Levin @Tufts, The Levin Lab

Michael Levin is an American developmental and synthetic biologist at Tufts University, where he is the Vannevar Bush Distinguished Professor. Levin is a director of the Allen Discovery Center at Tufts University and Tufts Center for Regenerative and Developmental Biology. Wikipedia

Born: 1969 (age 54 years), Moscow, Russia

Education: Harvard University (1992–1996), Tufts University (1988–1992)

Affiliation: University of Cape Town

Research interests: Allergy, Immunology, Cross Cultural Communication

Awards: Cozzarelli prize (2020)

Doctoral advisor: Clifford Tabin

Fields: Developmental biology, synthetic biology

SOURCE

https://www.google.com/search?q=Michael+Levin+%40Tufts&oq=Michael+Levin+%40Tufts&aqs=chrome..69i57j69i58.894128314j0j15&sourceid=chrome&ie=UTF-8

Most recent 20 Publications by Michael Levin, PhD

SOURCE

https://facultyprofiles.tufts.edu/michael-levin-1/publications

SCHOLARLY ARTICLE

The nonlinearity of regulation in biological networks

1 Dec 2023npj Systems Biology and Applications9(1)

Co-authorsManicka S, Johnson K, Levin M…1 more

VIEW PDF10.1038/S41540-023-00273-W

3

SCHOLARLY ARTICLE

Toward an ethics of autopoietic technology: Stress, care, and intelligence

1 Sep 2023BioSystems231

Co-authorsWitkowski O, Doctor T, Solomonova E…2 more

VIEW PDF10.1016/J.BIOSYSTEMS.2023.104964

SCHOLARLY ARTICLE

Closing the Loop on Morphogenesis: A Mathematical Model of Morphogenesis by Closed-Loop Reaction-Diffusion

14 Aug 2023Frontiers in Cell and Developmental Biology11:1087650

Co-authorsGrodstein J, McMillen P, Levin M

VIEW PDF10.3389/FCELL.2023.1087650

SCHOLARLY ARTICLE

Correcting instructive electric potential patterns in multicellular systems: External actions and endogenous processes.

30 Jul 2023Biochim Biophys Acta Gen Subj1867(10):130440

Co-authorsCervera J, Levin M, Mafe S

VIEW MORE INFO10.1016/J.BBAGEN.2023.130440

SCHOLARLY ARTICLE

Regulative development as a model for origin of life and artificial life studies

1 Jul 2023BioSystems229

Co-authorsFields C, Levin M

10.1016/J.BIOSYSTEMS.2023.104927

1

SCHOLARLY ARTICLE

The Yin and Yang of Breast Cancer: Ion Channels as Determinants of Left–Right Functional Differences

1 Jul 2023International Journal of Molecular Sciences24(13)

Co-authorsMasuelli S, Real S, McMillen P…3 more

VIEW PDF10.3390/IJMS241311121

SCHOLARLY ARTICLE

Bioelectricidad en agregados multicelulares de células no excitables- modelos biofísicos

Jun 2023Revista Española de Física32(2)

Co-authorsCervera J, Levin M, Mafé S

SCHOLARLY ARTICLE

Bioelectricity: A Multifaceted Discipline, and a Multifaceted Issue!

1 Jun 2023Bioelectricity5(2):75

Co-authorsDjamgoz MBA, Levin M

10.1089/BIOE.2023.0022.EDITORIAL

SCHOLARLY ARTICLE

Control Flow in Active Inference Systems – Part I: Classical and Quantum Formulations of Active Inference

1 Jun 2023IEEE Transactions on Molecular, Biological, and Multi-Scale Communications9(2):235-245

Co-authorsFields C, Fabrocini F, Friston K…4 more

10.1109/TMBMC.2023.3272150

2

SCHOLARLY ARTICLE

Control Flow in Active Inference Systems – Part II: Tensor Networks as General Models of Control Flow

1 Jun 2023IEEE Transactions on Molecular, Biological, and Multi-Scale Communications9(2):246-256

Co-authorsFields C, Fabrocini F, Friston K…4 more

10.1109/TMBMC.2023.3272158

2

SCHOLARLY ARTICLE

Darwin’s agential materials: evolutionary implications of multiscale competency in developmental biology

1 Jun 2023Cellular and Molecular Life Sciences80(6)

Co-authorsLevin M

VIEW PDF10.1007/S00018-023-04790-Z

1

SCHOLARLY ARTICLE

Morphoceuticals: Perspectives for discovery of drugs targeting anatomical control mechanisms in regenerative medicine, cancer and aging

1 Jun 2023Drug Discovery Today28(6)

Co-authorsPio-Lopez L, Levin M

VIEW PDF10.1016/J.DRUDIS.2023.103585

1

SCHOLARLY ARTICLE

Morphoceuticals: Perspectives for discovery of drugs targeting anatomical control mechanisms in regenerative medicine, cancer and aging

Jun 2023DRUG DISCOVERY TODAY28(6):1-13

Co-authorsPio-Lopez L, Levin M

VIEW MORE INFO10.1016/J.DRUDIS.2023.103585THIS

SCHOLARLY ARTICLE

Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine

12 May 2023Patterns4(5)

Co-authorsMathews J, Chang A, Devlin L…1 more

VIEW PDF10.1016/J.PATTER.2023.100737

3

SCHOLARLY ARTICLE

Making and breaking symmetries in mind and life

14 Apr 2023Interface Focus13(3)

Co-authorsSafron A, Sakthivadivel DAR, Sheikhbahaee Z…3 more

VIEW PDF10.1098/RSFS.2023.0015

SCHOLARLY ARTICLE

The scaling of goals from cellular to anatomical homeostasis: an evolutionary simulation, experiment and analysis

14 Apr 2023Interface Focus13(3)

Co-authorsPio-Lopez L, Bischof J, LaPalme JV…1 more

VIEW PDF10.1098/RSFS.2022.0072

1

SCHOLARLY ARTICLE

The collective intelligence of evolution and development

Apr 2023Collective Intelligence2(2):263391372311683SAGE Publications

Co-authorsWatson R, Levin M

VIEW PDF10.1177/26339137231168355

SCHOLARLY ARTICLE

Bioelectricity of non-excitable cells and multicellular pattern memories: Biophysical modeling

13 Mar 2023Physics Reports1004:1-31

Co-authorsCervera J, Levin M, Mafe S

10.1016/J.PHYSREP.2022.12.003

2

SCHOLARLY ARTICLE

There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines

1 Mar 2023Biomimetics8(1)

Co-authorsBongard J, Levin M

VIEW PDF10.3390/BIOMIMETICS8010110

4

SCHOLARLY ARTICLE

Transplantation of fragments from different planaria: A bioelectrical model for head regeneration

7 Feb 2023Journal of Theoretical Biology558

Co-authorsCervera J, Manzanares JA, Levin M…1 more

VIEW PDF10.1016/J.JTBI.2022.111356

SCHOLARLY ARTICLE

Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind

1 Jan 2023Animal Cognition

Co-authorsLevin M

VIEW PDF10.1007/S10071-023-01780-3

2

SCHOLARLY ARTICLE

Biological Robots: Perspectives on an Emerging Interdisciplinary Field

1 Jan 2023Soft Robotics

Co-authorsBlackiston D, Kriegman S, Bongard J…1 more

10.1089/SORO.2022.0142

1

SCHOLARLY ARTICLE

Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model

1 Jan 2023Entropy25(1)

Co-authorsShreesha L, Levin M

VIEW PDF10.3390/E25010131

5

SCHOLARLY ARTICLE

Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms (July, blac073, 2022)

1 Jan 2023BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY138(1):141

Co-authorsClawson WP, Levin M

VIEW PDFVIEW MORE INFO10.1093/BIOLINNEAN/BLAC116

SCHOLARLY ARTICLE

Future medicine: from molecular pathways to the collective intelligence of the body

1 Jan 2023Trends in Molecular Medicine

Co-authorsLagasse E, Levin M

10.1016/J.MOLMED.2023.06.007

THE VOICE of Dr. Justin D. Pearlman, MD, PhD, FACC

PENDING

THE VOICE of  Stephen J. Williams, PhD

Ten TakeAway Points of Dr. Lustig’s talk on role of diet on the incidence of Type II Diabetes

 

1. 25% of US children have fatty liver
2. Type II diabetes can be manifested from fatty live with 151 million  people worldwide affected moving up to 568 million in 7 years
3. A common myth is diabetes due to overweight condition driving the metabolic disease
4. There is a trend of ‘lean’ diabetes or diabetes in lean people, therefore body mass index not a reliable biomarker for risk for diabetes
5. Thirty percent of ‘obese’ people just have high subcutaneous fat.  the visceral fat is more problematic
6. there are people who are ‘fat’ but insulin sensitive while have growth hormone receptor defects.  Points to other issues related to metabolic state other than insulin and potentially the insulin like growth factors
7. At any BMI some patients are insulin sensitive while some resistant
8. Visceral fat accumulation may be more due to chronic stress condition
9. Fructose can decrease liver mitochondrial function
10. A methionine and choline deficient diet can lead to rapid NASH development

 

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Knowing the genetic vulnerability of bladder cancer for therapeutic intervention

Posted in Anticancer Resistance, Apoptosis, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Biological Networks, Biological Networks, Gene Regulation and Evolution, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Informatics, cancer metabolism, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell death pathways, Cell Processing System in Cell Therapy Process Development, Childhood cancer, Clinical Diagnostics, Clinical Genomics, Gene Regulation, Gene Therapy & Gene Editing Development, Genome Biology, Genomic Endocrinology, interventional oncology, Metabolic Immuno-Oncology, Metastasis Process, Microbiome and Responses to Cancer Therapy, mRNA Therapeutics, Mutagenesis, Personalized and Precision Medicine & Genomic Research, Population genetics, Population Health Management, Population Health Management, Genetics & Pharmaceutical, RNA Biology, RNA Biology, Cancer and Therapeutics, Signaling, tagged bladder, Cancer, classification, invasive, Ral, Ras, therapeutic on November 21, 2017| Leave a Comment »

Knowing the genetic vulnerability of bladder cancer for therapeutic intervention

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

 

A mutated gene called RAS gives rise to a signalling protein Ral which is involved in tumour growth in the bladder. Many researchers tried and failed to target and stop this wayward gene. Signalling proteins such as Ral usually shift between active and inactive states.

 

So, researchers next tried to stop Ral to get into active state. In inacvtive state Ral exposes a pocket which gets closed when active. After five years, the researchers found a small molecule dubbed BQU57 that can wedge itself into the pocket to prevent Ral from closing and becoming active. Now, BQU57 has been licensed for further development.

 

Researchers have a growing genetic data on bladder cancer, some of which threaten to overturn the supposed causes of bladder cancer. Genetics has also allowed bladder cancer to be reclassified from two categories into five distinct subtypes, each with different characteristics and weak spots. All these advances bode well for drug development and for improved diagnosis and prognosis.

 

Among the groups studying the genetics of bladder cancer are two large international teams: Uromol (named for urology and molecular biology), which is based at Aarhus University Hospital in Denmark, and The Cancer Genome Atlas (TCGA), based at institutions in Texas and Boston. Each team tackled a different type of cancer, based on the traditional classification of whether or not a tumour has grown into the muscle wall of the bladder. Uromol worked on the more common, earlier form, non-muscle-invasive bladder cancer, whereas TCGA is looking at muscle-invasive bladder cancer, which has a lower survival rate.

 

The Uromol team sought to identify people whose non-invasive tumours might return after treatment, becoming invasive or even metastatic. Bladder cancer has a high risk of recurrence, so people whose non-invasive cancer has been treated need to be monitored for many years, undergoing cystoscopy every few months. They looked for predictive genetic footprints in the transcriptome of the cancer, which contains all of a cell’s RNA and can tell researchers which genes are turned on or off.

 

They found three subgroups with distinct basal and luminal features, as proposed by other groups, each with different clinical outcomes in early-stage bladder cancer. These features sort bladder cancer into genetic categories that can help predict whether the cancer will return. The researchers also identified mutations that are linked to tumour progression. Mutations in the so-called APOBEC genes, which code for enzymes that modify RNA or DNA molecules. This effect could lead to cancer and cause it to be aggressive.

 

The second major research group, TCGA, led by the National Cancer Institute and the National Human Genome Research Institute, that involves thousands of researchers across USA. The project has already mapped genomic changes in 33 cancer types, including breast, skin and lung cancers. The TCGA researchers, who study muscle-invasive bladder cancer, have looked at tumours that were already identified as fast-growing and invasive.

 

The work by Uromol, TCGA and other labs has provided a clearer view of the genetic landscape of early- and late-stage bladder cancer. There are five subtypes for the muscle-invasive form: luminal, luminal–papillary, luminal–infiltrated, basal–squamous, and neuronal, each of which is genetically distinct and might require different therapeutic approaches.

 

Bladder cancer has the third-highest mutation rate of any cancer, behind only lung cancer and melanoma. The TCGA team has confirmed Uromol research showing that most bladder-cancer mutations occur in the APOBEC genes. It is not yet clear why APOBEC mutations are so common in bladder cancer, but studies of the mutations have yielded one startling implication. The APOBEC enzyme causes mutations early during the development of bladder cancer, and independent of cigarette smoke or other known exposures.

 

The TCGA researchers found a subset of bladder-cancer patients, those with the greatest number of APOBEC mutations, had an extremely high five-year survival rate of about 75%. Other patients with fewer APOBEC mutations fared less well which is pretty surprising.

 

This detailed knowledge of bladder-cancer genetics may help to pinpoint the specific vulnerabilities of cancer cells in different people. Over the past decade, Broad Institute researchers have identified more than 760 genes that cancer needs to grow and survive. Their genetic map might take another ten years to finish, but it will list every genetic vulnerability that can be exploited. The goal of cancer precision medicine is to take the patient’s tumour and decode the genetics, so the clinician can make a decision based on that information.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/29117162

 

https://www.ncbi.nlm.nih.gov/pubmed/27321955

 

https://www.ncbi.nlm.nih.gov/pubmed/28583312

 

https://www.ncbi.nlm.nih.gov/pubmed/24476821

 

https://www.ncbi.nlm.nih.gov/pubmed/28988769

 

https://www.ncbi.nlm.nih.gov/pubmed/28753430

 

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