Editorial: Women in developmental and reproductive toxicology: 2021
Bibliographic record
Abstract
Editorial on the Research Topic Women in developmental and reproductive toxicology: 2021Women remain a minority group in toxicology, both as lead investigators and in terms of using the tools of toxicology to understand environmental influences on women's health.While the fields of toxicology and environmental medicine are diversifying, underrepresented groups, including women and women of color, face unique challenges.When unmet, this can lead to isolation, lack of support, career dissatisfaction, and ultimately higher rates of attrition.This special issue was therefore conceived to highlight the work of women toxicologists to emphasize their unique mentorship and support needs, and to maximize career success.Given this focus, the scientific work primarily addresses women and child health (i.e., pregnancy and health of the next generation).This special issue contains two original data papers, a mini-review, and a perspective piece on what is needed to support and mentor women in what remains a male-dominated field.In their mini-review, Björvang and Mamsen provide evidence that many man-made chemicals, including persistent organic pollutants (POPs) accumulate in the placenta in human fetuses.Notably, some pollutants accumulate to a higher degree in male fetal tissues and their associated placentas suggesting that gestational exposure can be sexually dimorphic.Their call for greater attention on sexual differences in adverse health outcomes in toxicological studies aligns with efforts by NIH and others to consider sexual dimorphism and include sex as a biological variable in all biomedical research.Blake et al. also focused on the placenta in their paper and took a high-throughput toxicity screening approach to examine the impact of 42 unique per-and polyfluoroalkyl (PFAS) compounds on trophoblast cell viability and function.Using the human placental trophoblast JEG-3 cell line, the team found that some common PFAS impaired cell migration, induced oxidative stress, and impaired cellular response to xenobiotic stress.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.024 | 0.020 |
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".