MétaCan
Menu
Back to cohort
Record W2043406680 · doi:10.1139/y03-002

Renal responses to chronic cold exposure

2003· article· en· W2043406680 on OpenAlexvenueno aff
Zhongjie Sun, Zhonge Zhang, Robert Cade

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2003
Typearticle
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsnot available
FundersAmerican Heart Association
KeywordsEndocrinologyInternal medicineAntidiureticUrine osmolalityChemistryUrineKidneyReceptorDehydrationHormoneMedicineBiochemistry

Abstract

fetched live from OpenAlex

The aim of this study was to assess our hypothesis that the release of antidiuretic hormone (ADH), the renal concentrating response to ADH, or both is decreased by prolonged cold exposure. Six groups (n = 6/group) of rats were used. Three groups were exposed to cold (5 degrees C), whilethe remaining three groups were kept at room temperature (25 degrees C). It was found that urine osmolality decreased significantly and serum osmolality increased significantly during cold exposure. The ratio of water/food intake was not affected by prolonged cold exposure. However, prolonged cold exposure increased the ratio of urine output/food intake in the cold-exposed rats, indicating that more urine flow is required by the cold-exposed rats to excrete the osmotic substance at a given food intake. The difference between water intake and urine output decreased significantly in the cold-exposed rats. Thus, prolonged cold exposure increases water loss from excretion. Renal concentrating responses to 24-h dehydration and Pitressin were decreased significantly in the cold-exposed rats. Plasma ADH levels remained unchanged, but renal ADH receptor (V2 receptor) mRNA was decreased significantly in the cold-exposed rats. The results strongly support the conclusion that cold exposure increases excretive water loss, and this may be due to suppression of renal V2 receptors rather than inhibition of ADH release.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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.

Study designBench or experimental
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

Citations27
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and PharmacologySame topicElectrolyte and hormonal disordersFrench-language works237,207