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Record W4392975966 · doi:10.1139/apnm-2023-0599

Greater hyperthermia in men with type 2 diabetes does not lead to higher serum levels of cellular stress biomarkers following exercise-heat stress

2024· article· en· W4392975966 on OpenAlexafffundvenue
Nicholas Goulet, Emily J. Tetzlaff, James J. McCormick, Kelli E. King, Kristina‐Marie T. Janetos, Ronald J. Sigal, Pierre Boulay, Glen P. Kenny

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2024
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsOttawa HospitalUniversité de SherbrookeUniversity of CalgaryUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaMitacsCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsMedicineHyperthermiaType 2 diabetesHeat stressInternal medicineDiabetes mellitusLead (geology)EndocrinologyOxidative stressBiomarkerChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Type 2 diabetes (T2D) is associated with worsening age-related impairments in heat loss, causing higher core temperature during exercise. We evaluated whether these thermoregulatory impairments occur with altered serum protein responses to heat stress by measuring cytoprotection, inflammation, and tissue damage biomarkers in middle-aged-to-older men (50–74 years) with ( n = 16) and without ( n = 14) T2D following exercise in 40°C. There were no changes in irisin, klotho, HSP70, sCD14, TNF-α, and IL-6, whereas NGAL (+539 pg/mL, p = 0.002) and iFABP (+250 pg/mL, p < 0.001) increased similarly across groups. These similar response patterns occurred despite elevated core temperature in individuals with T2D, suggesting greater heat vulnerability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.255
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes3
Has abstractyes

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