Accumbal μ-opioid receptors and salt taste-elicited hedonic responses in a rodent model of prenatal adversity, and their correlates using human functional genomics
Bibliographic record
Abstract
Prenatal adversity is associated with behavioral obesogenic features such as preference for palatable foods. Salt appetite may play a role in the development of adiposity and its consequences in individuals exposed to prenatal adversity, and sodium consumption involves individual differences in accumbal µ-opioid receptors function. We investigated the hedonic responses to salt and the levels of µ-opioid receptors and tyrosine hydroxylase in the nucleus accumbens (Nacc) of pups from an animal model of prenatal dietary restriction. In children, we evaluated the interaction between fetal growth and the genetic background associated with the accumbal µ-opioid receptor gene (OPRM1) expression on sodium consumption during a snack test. Sprague-Dawley dams were randomly allocated from pregnancy day 10 to receive an ad libitum (Adlib) or a 50% restricted (FR) diet. The pups’ hedonic responses to a salt solution (NaCl 2%) or water were evaluated on the first day of life. FR and Adlib pups differ in their hedonic responses to salt, and there were decreased levels of accumbal µ-opioid and p-µ-opioid receptors in FR pups. In humans, a test meal and genotyping from buccal epithelial cells were performed in 270 children (38 intrauterine growth restricted—IUGR) at 4 years old from a Canadian prospective cohort (MAVAN). The OPRM1 genetic score predicted the sodium intake in IUGR children, but not in controls. The identification of mechanisms involved in the brain response to prenatal adversity and its consequences in behavioral phenotypes and risk for chronic diseases later in life is important for preventive and therapeutic purposes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".