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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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Selye’s Riddle solved

Posted in Biochemical pathways, Curation, Developmental biology, Gene Regulation and Evolution, Human aging, Human Immune System in Health and in Disease, Human Sensation and Cellular Transduction: Physiology and Therapeutics, Inflammasome, Metabolism, Microbiology, Micronutrients, Nephrology, Stress Disorders, Systemic Inflammatory Response Related Disorders, tagged adaptation, Evolution, Fitness, General adaptation syndrome, Optimality, Physiology on March 26, 2016| Leave a Comment »

Selye’s Riddle solved

Larry H. Bernstein, mD, FCAP, Curator

LPBI

 

Mathematicians Solve 78-year-old Mystery

3/23/2016   University of Leicester        http://www.scientificcomputing.com/news/2016/03/mathematicians-solve-78-year-old-mystery

Mathematicians developed a solution to Selye’s riddle which has puzzled scientists for almost 80 years.

In previous research, it was suggested that adaptation of an animal to different factors looks like spending of one resource, and that the animal dies when this resource is exhausted. In 1938, Hans Selye introduced “adaptation energy” and found strong experimental arguments in favor of this hypothesis. However, this term has caused much debate because, as it cannot be measured as a physical quantity, adaptation energy is not strictly energy.

 

Evolution of adaptation mechanisms: Adaptation energy, stress, and oscillating death

Alexander N. Gorban^{a, ,} , Tatiana A. Tyukina^a, , Elena V. Smirnova^b, , Lyudmila I. Pokidysheva^b,

Journal of Theoretical Biology    19 Jan 2016   http://www.sciencedirect.com/science/article/pii/S0022519316000205   http://dx.doi.org:/10.1016/j.jtbi.2015.12.017

Highlights

•   We formalize Selye׳s ideas about adaptation energy and dynamics of adaptation.

•   A hierarchy of dynamic models of adaptation is developed.

•   Adaptation energy is considered as an internal coordinate on the ‘dominant path’ in the model of adaptation.

•   The optimal distribution of resources for neutralization of harmful factors is studied.

•   The phenomena of ‘oscillating death’ and ‘oscillating remission’ are predicted.       

In previous research, it was suggested that adaptation of an animal to different factors looks like spending of one resource, and that the animal dies when this resource is exhausted.

In 1938, Selye proposed the notion of adaptation energy and published ‘Experimental evidence supporting the conception of adaptation energy.’ Adaptation of an animal to different factors appears as the spending of one resource. Adaptation energy is a hypothetical extensive quantity spent for adaptation. This term causes much debate when one takes it literally, as a physical quantity, i.e. a sort of energy. The controversial points of view impede the systematic use of the notion of adaptation energy despite experimental evidence. Nevertheless, the response to many harmful factors often has general non-specific form and we suggest that the mechanisms of physiological adaptation admit a very general and nonspecific description.

We aim to demonstrate that Selye׳s adaptation energy is the cornerstone of the top-down approach to modelling of non-specific adaptation processes. We analyze Selye׳s axioms of adaptation energy together with Goldstone׳s modifications and propose a series of models for interpretation of these axioms. Adaptation energy is considered as an internal coordinate on the ‘dominant path’ in the model of adaptation. The phenomena of ‘oscillating death’ and ‘oscillating remission’ are predicted on the base of the dynamical models of adaptation. Natural selection plays a key role in the evolution of mechanisms of physiological adaptation. We use the fitness optimization approach to study of the distribution of resources for neutralization of harmful factors, during adaptation to a multifactor environment, and analyze the optimal strategies for different systems of factors.

In this work, an international team of researchers, led by Professor Alexander N. Gorban from the University of Leicester, have developed a solution to Selye’s riddle, which has puzzled scientists for almost 80 years.

Alexander N. Gorban, Professor of Applied Mathematics in the Department of Mathematics at the University of Leicester, said: “Nobody can measure adaptation energy directly, indeed, but it can be understood by its place already in simple models. In this work, we develop a hierarchy of top-down models following Selye’s findings and further developments. We trust Selye’s intuition and experiments and use the notion of adaptation energy as a cornerstone in a system of models. We provide a ‘thermodynamic-like’ theory of organism resilience that, just like classical thermodynamics, allows for economics metaphors, such as cost and bankruptcy and, more importantly, is largely independent of a detailed mechanistic explanation of what is ‘going on underneath’.”

Adaptation energy is considered as an internal coordinate on the “dominant path” in the model of adaptation. The phenomena of “oscillating death” and “oscillating remission,” which have been observed in clinic for a long time, are predicted on the basis of the dynamical models of adaptation. The models, based on Selye’s idea of adaptation energy, demonstrate that the oscillating remission and oscillating death do not need exogenous reasons. The developed theory of adaptation to various factors gives the instrument for the early anticipation of crises.

Professor Alessandro Giuliani from Istituto Superiore di Sanità in Rome commented on the work, saying: “Gorban and his colleagues dare to make science adopting the thermodynamics style: they look for powerful principles endowed with predictive ability in the real world before knowing the microscopic details. This is, in my opinion, the only possible way out from the actual repeatability crisis of mainstream biology, where a fantastic knowledge of the details totally fails to predict anything outside the test tube.¹”

Citation: Alexander N. Gorban, Tatiana A. Tyukina, Elena V. Smirnova, Lyudmila I. Pokidysheva. Evolution of adaptation mechanisms: Adaptation energy, stress, and oscillating death. Journal of Theoretical Biology, 2016; DOI:10.1016/j.jtbi.2015.12.017. Voosen P. (2015) Amid a Sea of False Findings NIH tries Reform, The Chronicle of Higher Education.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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