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Record W2332527509 · doi:10.5152/eajm.2011.24

Benefits of Estrogen Replacement for Skeletal Muscle Mass and Function in Post-Menopausal Females: Evidence from Human and Animal Studies

2011· review· en· W2332527509 on OpenAlexafffund
Peter M. Tiidus

Bibliographic record

VenueEurasian Journal of Medicine · 2011
Typereview
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEstrogenMedicineHormone replacement therapy (female-to-male)Skeletal muscleEndocrinologyMenopauseInternal medicineGynecologyPhysiology

Abstract

fetched live from OpenAlex

Age related loss of skeletal muscle mass and strength accelerates with the onset of menopause in women. Recent evidence from human and animal studies provides compelling evidence for the role of estrogen based hormone replacement therapy (HRT) in maintaining and enhancing muscle mass and strength and protecting against muscle damage. The physiological mechanisms by which estrogen can positively influence skeletal muscle mass and strength and protect against post-damage inflammation and disruption are also beginning to emerge. These less well known benefits of estrogen for skeletal muscle coupled with other benefits of estrogen to bone and metabolic health in older females provide further incentives for HRT use to enhance overall health in post-menopausal women. New research also attests to the safety of shorter term HRT in younger post-menopausal females. Overall the benefits of HRT to muscle health and function could assist in offsetting age related loss of muscle mass and function and delay age related morbidity and their use for overall health benefits in aging females should continue to be evaluated.

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 score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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 head0.220
GPT teacher head0.427
Teacher spread0.207 · 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

Citations81
Published2011
Admission routes2
Has abstractyes

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