Maternal high-fat diet induces sex-specific changes to glucocorticoid and inflammatory signaling in response to corticosterone and lipopolysaccharide challenge in adult rat offspring
Bibliographic record
Abstract
ABSTRACT Background Acute elevations in endogenous corticosterone (CORT) with psychosocial stress or exogenous administration potentiate inflammatory gene expression. Maternal obesity as a result of high-fat diet (HFD) consumption has been linked to higher basal levels of neuroinflammation, including increased expression of pro-inflammatory genes in the amygdala. These findings suggest that exposure to maternal HFD may elicit pro-inflammatory responses in the presence of an immune stressor such as lipopolysaccharide (LPS), a component of gram-negative bacteria, as well as acute elevated CORT. Methods Rat offspring were exposed to maternal HFD or control diet (CHD) throughout pre and postnatal development until weaning, when all offspring were provided CHD until adulthood. In adulthood, offspring were ‘challenged’ with administration of exogenous CORT, to simulate an acute physiological stress, LPS, to induce an immune stress, or both. qPCR was used to measure transcript abundance of CORT receptors and downstream inflammatory genes in the amygdala, hippocampus and prefrontal cortex, brain regions that mediate neuroendocrine and behavioral responses to stress. Results HFD female offspring exhibited elevations in anti-inflammatory transcripts, whereas HFD male offspring responded with greater pro-inflammatory gene expression to simultaneous CORT and LPS administration. Conclusions These findings suggest that exposure to maternal HFD leads to sex-specific alterations that may alter inflammatory responses in the brain, possibly as an adaptive response to basal inflammation.
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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) | 0.002 | 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".