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Record W4386918243 · doi:10.14814/phy2.15768

Menopausal stage differences in endothelial resistance to ischemia‐reperfusion injury

2023· article· en· W4386918243 on OpenAlexfundno aff
Jocelyn M. Delgado Spicuzza, David N. Proctor, Dick H. J. Thijssen, Yasina B. Somani

Bibliographic record

VenuePhysiological Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicNitric Oxide and Endothelin Effects
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health ResearchGovernment of CanadaNational Institutes of HealthNational Institute of General Medical Sciences
KeywordsMedicineMenopausePostmenopausal womenEndothelial dysfunctionInternal medicineStage (stratigraphy)Ischemia

Abstract

fetched live from OpenAlex

BACKGROUND: In postmenopausal women, reduced ovarian function precedes endothelial dysfunction and attenuated endothelial resistance to ischemia-reperfusion (IR) injury. We hypothesized that IR injury would lower endothelial function, with premenopausal women demonstrating the greatest protection from injury, followed by early, then late postmenopausal women. METHODS: Flow-mediated dilation (FMD) was assessed at baseline and following IR injury in premenopausal (n = 11), early (n = 11; 4 ± 1.6 years since menopause), and late (n = 11; 15 ± 5.5 years since menopause) postmenopausal women. RESULTS: There were significant group differences in baseline FMD (p = 0.007); post hoc analysis revealed a similar resting FMD between premenopausal (7.8% ± 2.1%) and early postmenopausal (7.1% ± 2.7%), but significantly lower FMD in late postmenopausal women (4.5% ± 2.3%). Results showed an overall decline in FMD after IR injury (p < 0.001), and a significant condition*time interaction (p = 0.048), with early postmenopausal women demonstrating the most significant decline in FMD following IR. CONCLUSION: Our findings indicate that endothelial resistance to IR injury is attenuated in healthy early postmenopausal 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.459
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.038
GPT teacher head0.313
Teacher spread0.275 · 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 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

Citations5
Published2023
Admission routes1
Has abstractyes

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