Sex, hormones, and genotype interact to influence psychiatric disease, treatment, and behavioral research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sex differences exist in the vulnerability, incidence, manifestation, and treatment of numerous neurological and psychiatric diseases. Despite this observation prominent in the literature, little consideration has been given to possible sex differences in outcome in both preclinical and clinical research. This Mini-Review highlights evidence supporting why studying sex differences matter for advances in brain health as well as improving treatment for neurological and psychiatric disease. Additionally, we discuss some statistical and methodological considerations in evaluating sex differences as well as how differences in the physiology of the sexes can contribute to sex difference in disease incidence and manifestation. Furthermore, we review literature demonstrating that the reproductive experience in the female can render the female brain differentially vulnerable to disease across age. Finally, we discuss how genes interact with sex to influence disease risk and treatment and argue that sex must be considered in precision medicine. Together the evidence reviewed here supports the inclusion of males and females at all levels of neuroscience research. © 2016 Wiley Periodicals, Inc.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it