Bisphenol A and microglia: could microglia be responsive to this environmental contaminant during neural development?
Bibliographic record
Abstract
There is a growing interest in the functional role of microglia in the developing brain. In our laboratory, we have become particularly intrigued as to whether fetal microglia in the embryonic brain are susceptible to maternal challenges in utero (e.g., maternal infection, stress) and, if so, whether their precocious activation could then adversely influence brain development. One such challenge that is newly arising in this field is whether microglia might be downstream targets to endocrine-disrupting chemicals, such as the plasticizer bisphenol A (BPA), which functions in part by mimicking estrogen structure and function. A growing body of evidence demonstrates that gestational exposure to BPA has adverse effects on brain development, although the exact mechanisms are still emerging. Given that microglia express estrogen receptors and steroid-producing enzymes, microglia might be an unappreciated target of BPA. Mechanistically, we propose that BPA binding to estrogen receptors within microglia initiates transcription of downstream target genes, which then leads to activation of microglia that can then perhaps adversely influence brain development. Here, we first briefly outline the current understanding of how microglia may influence brain development and then describe how this literature overlaps with our understanding of BPA's effects during similar time points. We also outline the current literature demonstrating that BPA exposure affects microglia. We conclude by discussing our thoughts on the mechanisms through which exposure to BPA could disrupt normal microglia functions, ultimately affecting brain development that could potentially lead to lasting behavioral effects and perhaps even neuroendocrine diseases such as obesity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".