Long‐lasting effects of elevated neonatal leptin on rat hippocampal function, synaptic proteins and NMDA receptor subunits
Bibliographic record
Abstract
The high circulating levels of leptin in neonatal rodents do not seem to be regulating energy balance at this age, but rather may play an important role for brain development. We tested the hypothesis that high neonatal leptin levels modify hippocampal function and production of synaptic proteins with possible long-term consequences on long-term potentiation (LTP) in adulthood. We first showed that in postnatal day (PND) 10 neonates, acute leptin treatment functionally activated leptin receptors (ObR) in the CA1 and DG regions of the hippocampus through the induction of phosphoERK1/2, but not phosphoSTAT3 protein although both phospho-proteins were induced in the arcuate nucleus. We next examined whether chronic leptin administration (3 mg/kg BW, intraperitoneally) during the first 2 weeks of life (postnatal day, PND 2-14) produces a functional signal in the hippocampus that alters the expression of NMDA receptor subunits (NR1, NR2A, NR2B), synaptic proteins and LTP in the short and long-term. In PND 10 as in adults (PND 70) rats, chronic leptin treatment increased NR1 expression in the hippocampus while reducing NR2B protein levels. Elevated hippocampal concentrations of synapsin2A and synaptophysin were detected during leptin treatment on PND 10 suggesting increased neurotransmitter release. In adults, only SNAP-25 expression was increased after neonatal leptin treatment. LTP was reduced dramatically by leptin treatment in preweaning rats although the changes did not persist until adulthood. Elevated exposure to leptin during a critical period of neonatal hippocampal development might serve to enhance NMDA-dependent functions other than LTP and have important effects on synaptogenesis and neurotransmitter release.
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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".