Female Sex and Gender in Lung/Sleep Health and Disease: Increased Understanding of Basic Biological, Pathophysiological, and Behavioral Mechanisms Leading to Better Health for Female Patients with Lung Disease
Bibliographic record
Abstract
Female sex/gender is an undercharacterized variable in studies related to lung development and disease. Notwithstanding, many aspects of lung and sleep biology and pathobiology are impacted by female sex and female reproductive transitions. These may manifest as differential gene expression or peculiar organ development. Some conditions are more prevalent in women, such as asthma and insomnia, or, in the case of lymphangioleiomyomatosis, are seen almost exclusively in women. In other diseases, presentation differs, such as the higher frequency of exacerbations experienced by women with chronic obstructive pulmonary disease or greater cardiac morbidity among women with sleep-disordered breathing. Recent advances in -omics and behavioral science provide an opportunity to specifically address sex-based differences and explore research needs and opportunities that will elucidate biochemical pathways, thus enabling more targeted/personalized therapies. To explore the status of and opportunities for research in this area, the NHLBI, in partnership with the NIH Office of Research on Women's Health and the Office of Rare Diseases Research, convened a workshop of investigators in Bethesda, Maryland on September 18 and 19, 2017. At the workshop, the participants reviewed the current understanding of the biological, behavioral, and clinical implications of female sex and gender on lung and sleep health and disease, and formulated recommendations that address research gaps, with a view to achieving better health outcomes through more precise management of female patients with nonneoplastic lung disease. This report summarizes those discussions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".