Compulsive Eating in a Rat Model of Binge Eating Disorder Under Conditioned Fear and Exploration of Neural Mechanisms With c-fos mRNA Expression
Bibliographic record
Abstract
Compulsive eating is the most obstinate feature of binge eating disorder. In this study, we observed the compulsive eating in our stress-induced binge-like eating rat model using a conflicting test, where sucrose and an aversively conditioned stimulus were presented at the same time. In this conflicting situation, the binge-like eating prone rats (BEPs), compared to the binge-like eating resistant rats (BERs), showed persistent high sucrose intake and inhibited fear response, respectively, indicating a deficit in palatability devaluation and stronger anxiolytic response to sucrose in the BEPs. We further analyzed the neuronal activation with c-fos mRNA in situ hybridization. Surprisingly, the sucrose access under conditioned fear did not inhibit the activity of amygdala; instead, it activated the central amygdala. In the BEPs, sucrose reduced the response of the paraventricular hypothalamic nucleus (PVN), while enhancing activities in the lateral hypothalamic area (LHA) to the CS. The resistance to devaluating the palatable food in the BEPs could be a result of persistent Acb response to sucrose intake and attenuated recruitment of the medial prefrontal cortex (mPFC). We interpret this finding as that the reward system of the BEPs overcame the homeostasis system and the stress-responding system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".