Bisphenol A Alters the Levels of miRNAs That Directly and/or Indirectly Target Neuropeptide Y in Murine Hypothalamic Neurons
Bibliographic record
Abstract
The hypothalamus is a vital regulator of energy homeostasis. Orexigenic neuropeptide Y (NPY) neurons within the hypothalamus can stimulate feeding and suppress energy expenditure, and dysregulation of these neurons may contribute to obesity. We previously reported that bisphenol A (BPA), an endocrine disruptor with obesogenic properties, alters Npy transcription in hypothalamic neurons by inducing oxidative stress. We hypothesized that hypothalamic microRNAs (miRNAs), a class of small non-coding RNAs, could directly regulate Npy gene expression by binding the 3′ untranslated region (UTR). Five predicted Npy-targeting miRNA candidates were uncovered through TargetScan and were detected in Npy-expressing hypothalamic neuronal cell models and hypothalamic neuronal primary cultures. BPA dysregulated the expression of a number of these hypothalamic miRNAs. We examined the effects of putative Npy-targeting miRNAs using miRNA mimics, and we found that miR-143-3p, miR-140-5p, miR-29b-1-5p, and let-7b-3p altered Npy expression in the murine hypothalamic cell lines. Importantly, miR-143-3p targets the mouse Npy 3′ UTR, as detected using a luciferase construct containing the potential 3′ UTR binding sites. Overall, this study established the first hypothalamic miRNA that directly targets the 3′ UTR of mouse Npy, emphasizing the involvement of miRNAs in the NPY system and providing an alternative target for control of NPY levels.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".