MétaCan
Menu
Back to cohort

Effects of ovarian hormones on exercise metabolism

2001· review· en· W2049965556 on OpenAlexaff
Shannon E. Campbell, Mark A. Febbraio

Bibliographic record

VenueCurrent Opinion in Clinical Nutrition & Metabolic Care · 2001
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEndocrinologyInternal medicineCarbohydrate metabolismEstrogenHormoneGlucose uptakeMetabolismAdipose tissueLipid metabolismBiologyGlucose transporterSkeletal muscleChemistryInsulinMedicine

Abstract

fetched live from OpenAlex

Growing evidence suggests that the ovarian hormones have major effects on lipid and carbohydrate metabolism, and may also play a major role in up-stream molecular signaling mechanisms for regulating substrate metabolism. It appears that the absence of estrogen can impair glucose uptake during exercise. In contrast, progesterone not only impairs contraction-mediated glucose uptake when solely administered, but impairs glucose uptake when physiological concentrations of both estrogen and progesterone are administered. Likewise, progesterone administered to rodents for 14 days decreases glucose transporter (GLUT) 4 protein content in skeletal muscle and adipose tissue. Furthermore removing the ovaries decreases the activity of key oxidative enzymes while estrogen treatment restores the activity of these enzymes. It appears, therefore, that estrogen increases the metabolic capacity for both carbohydrate and lipid metabolism, perhaps increasing the overall metabolic flexibility of skeletal muscle. Conversely, progesterone negates both these effects, and could therefore result in a state of relative metabolic inflexibility, similar to that observed in the metabolic syndrome.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.898
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.127
GPT teacher head0.465
Teacher spread0.338 · 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 designOther design
Domainnot available
GenreReview

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

Citations54
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in Clinical Nutrition & Metabolic CareSame topicAdipose Tissue and MetabolismFrench-language works237,207