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Record W4401588510 · doi:10.3389/fendo.2024.1451286

Editorial: Impact of female hormones on the brain

2024· editorial· en· W4401588510 on OpenAlexaff
Jean‐Michel Le Mellédo, Caroline Gurvich, Jayashri Kulkarni

Bibliographic record

VenueFrontiers in Endocrinology · 2024
Typeeditorial
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHormoneEndocrinologyInternal medicineMedicineNeuroscienceBiology

Abstract

fetched live from OpenAlex

Impact of female hormones on the brainThe specificities of women, including women's brains, have been neglected in research over many years.Discussions about the inclusion of women in research only became topical in the 1970s, as part of the women's health movement.However, in 1977, a Food and Drug Administration policy recommended excluding women of childbearing potential from Phase I and early Phase II drug trials (1).This policy was a reaction to adverse drug-related incidents in pregnant women who had participated in clinical trials; however, the implications of this led to a shortage of data on how many drugs affect women, as well as broader gap in knowledge about neuroscience related to sex and gender.In response to this knowledge gap, NIH developed a policy on the inclusion of women in clinical research, which became law in 1993.Since that time, the importance of reporting of research results with specification of both biological sex and gender has been recognised (2).The more specific impacts of female hormones on the brain has only attracted interest in recent decades and investigations on this topic are leading to dramatic advances in clinical understanding and applications.Hantsoo et al. elegantly reviewed female-specific mood disorders such as premenstrual dysphoric disorder, postpartum depression and perimenopausal depression. They stressed the tremendous interplay, especially in women with a history of trauma, between the hypothalamic-pituitary-adrenal (HPA) axis and female hormones in the occurrence of depression across the female reproductive lifecycle. Interestingly, Hantsoo et al. suggest that studies comparing HPA axis function between females with premenstrual dysphoric disorder with and without a history of trauma are needed.This is the objective of the investigation by Nayman et al..This research team demonstrated that women with premenstrual dysphoric disorder and a history of childhood trauma exhibited lower cortisol levels during the luteal phase of the menstrual cycle compared to the follicular phase of the menstrual cycle whereas no such cyclicity was observed with women with premenstrual dysphoric disorder without such a history.These results illustrate substantial heterogeneity in the physiopathology of premenstrual dysphoric disorder.In their research on the role of endogenous and exogenous sex hormones (i.e.oral contraceptives) on morphologic alterations of the fear circuitry Brouillard et al. found that both endogenous and exogenous sex hormones can affect brain morphology.They demonstrated sex differences in grey matter volume in brain regions associated with fear Frontiers in Endocrinology frontiersin.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0050.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0040.001
Science and technology studies0.0030.003
Scholarly communication0.0060.005
Open science0.0050.001
Research integrity0.0180.019
Insufficient payload (model declined to judge)0.0210.016

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 head0.017
GPT teacher head0.306
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2024
Admission routes1
Has abstractyes

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