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Record W4321333024 · doi:10.1089/ars.2021.0277

Integrated Redox-Metabolic Orchestration Sustains Life in Hibernating Ground Squirrels

2023· article· en· W4321333024 on OpenAlexaff
Aleksandra Janković, Andjelika Kalezic, Aleksandra Korać, Biljana Buzadžić, Kenneth B. Storey, Bato Korać

Bibliographic record

VenueAntioxidants and Redox Signaling · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsHibernation (computing)BioenergeticsTorporBiologyOrganismMitochondrionEcologyCell biologyThermoregulationGenetics

Abstract

fetched live from OpenAlex

Significance:The ultimate manifestations of life, birth, survival under various environmental pressures and death are based on bioenergetics. Hibernation is a unique survival strategy for many small mammals that is characterised by severe metabolic depression and transition from euthermia to hypothermia (torpor) at body temperatures close to 0°C. These manifestations of life were made possible by the remarkable “social” behavior of biomolecules during billions of years of evolution: the evolution of life with oxygen. Oxygen was necessary for energy production and the evolutionary explosion of aerobic organisms. Recent Advances:Nevertheless, reactive oxygen species, formed through oxidative metabolism, are dangerous—they can kill a cell and, on the other hand, play a plethora of fundamentally valuable roles. Therefore, the evolution of life depended on energy metabolism and redox-metabolic adaptations. The more extreme the conditions for survival are, the more sophisticated the adaptive responses of organisms become. Hibernation is a beautiful illustration of this principle. Hibernating animals use evolutionarily conserved molecular mechanisms to survive adverse environmental conditions, including reducing body temperature to ambient levels (often to ∼0°C) and severe metabolic depression. This long-built secret of life lies at the intersection of oxygen, metabolism, and bioenergetics, and hibernating organisms have learned to exploit all the underlying capacities of molecular pathways to survive. Critical Issues:Despite such drastic changes in phenotype, tissues and organs of hibernators sustain no metabolic or histological damage during hibernation or upon awakening from hibernation. This was made possible by the fascinating integration of redox-metabolic regulatory networks whose molecular mechanisms remain undisclosed to this day. Future Directions:Discovering these molecular mechanisms is not warranted only to understand hibernation in itself but to help explain complex medical conditions (hypoxia/reoxygenation, organ transplantation, diabetes, and cancer) and to even help overcome limitations associated with space travel. This is a review of integrated redox-metabolic orchestration in hibernation. Antioxid. Redox Signal. 40, 345–368.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.249
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

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