Increased Hypothalamic Projections to the Lateral Hypothalamus and Responses to Leptin in Rat Neonates From High Fat Fed Mothers
Bibliographic record
Abstract
The lateral hypothalamus (LHA) is a central hub in the regulation of food intake and metabolism, as it integrates homeostatic and hedonic circuits. During early development, maturing input to and output from the LHA might be particularly sensitive to environmental dietary changes. We examined the effects of a maternal high fat diet (HFD, 60% Kcal in fat) on the density of hypothalamic projections to the orexin (ORX-A) field of the LHA in 10 day-old (PND10) rat pups using retrograde labelling with fluorescent microspheres. We also compared responsiveness of phenotypically identified LHA neurons to leptin administration (3mg/kg, bw) between pups from control (CD) or high fat (HFD) fed mothers on PND10 and 15-16, at the onset of independent feeding. HFD pups exhibited a higher density of LHA projections (p<0.05) from the ventromedial hypothalamus (VMH) compared to CD pups and these originated from both SF-1 and BDNF-positive neurons in the VMH. Increased circulating leptin levels in HFD pups, particularly on PND15-16 correlated with enhanced pSTAT3 responses to leptin in the orexin (ORX-A) field of the LHA, with some of the activated neurons expressing a GABA, but not CART phenotype. ORX-A neurons colocalizing with pERK were significantly higher in PND15-16 HFD pups compared to CD pups, and leptin-induced increase in pERK signaling was only observed in CD pups. There was no significant effect of leptin on pERK in HFD pups. These results suggest that perinatal maternal high fat feeding increases hypothalamic projections to the ORX-A field of the LHA, increases basal activation of ORX-A neurons and direct responsiveness of LHA neurons to leptin. Since these various LHA neuronal populations project quite heavily to Dopamine (DA) neurons in the ventral tegmental area, they might participate in the early dietary programming of mesocorticolimbic reward circuits and food intake.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".