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Record W2763073966 · doi:10.3389/fphys.2017.00773

Role of Sex Hormones in the Control of Vegetative and Metabolic Functions of Middle-Aged Women

2017· article· en· W2763073966 on OpenAlexaff
Vincenzo Monda, Monica Salerno, Ines Villano, Andrea Viggiano, Francesco Sessa, Antonio Ivano Triggiani, Giuseppe Cibelli, Anna Valenzano, Gabriella Marsala, Christian Zammit, Maria Ruberto, Giovanni Messina, Marcellino Monda, Vincenzo De Luca, Antonietta Messina

Bibliographic record

VenueFrontiers in Physiology · 2017
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMenopauseMedicineObesityEstrogenEndocrinologyInternal medicineHormone replacement therapy (female-to-male)HormoneOxidative stressBody mass indexPhysiologyVasomotorTestosterone (patch)

Abstract

fetched live from OpenAlex

Aims: In women’s life, menopause is characterized by significant physiological changes often associated with an increase in body weight and obesity-related diseases. Many studies have been carried out to determine interdependencies of estrogen depletion, aging, and resting energy expenditure (REE) decline in menopause-related obesity. Methodology: In this study, we measured the body composition, the REE, the oxidative stress, the food intake, and the activity of the autonomic nervous system of three groups: pre-menopause women (n=50), post-menopause women following hormone-replacement therapy (HRT; n=50), and post-menopause women not following HRT (n=50). Results: In post-menopause women with HRT a significant increase was found in: 1) the sympathetic activity, measured by the power spectral analysis of the heart rate variability; 2) REE, measured by indirect calorimetry; 3) oxidative stress, measured by FRAS 4 compared to the value of the other two, while fat mass, measured by BIA, was reduced in favor of a recovery of free fat mass. Conclusion: The study highlights the importance of the HRT-related physiological changes that influence body weight in menopause women.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.021
GPT teacher head0.283
Teacher spread0.262 · 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

Citations31
Published2017
Admission routes1
Has abstractyes

Explore more

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