Leptin enhances hypothalamic lactate dehydrogenase A (LDHA)–dependent glucose sensing to lower glucose production in high-fat–fed rats
Bibliographic record
Abstract
The responsiveness of glucose sensing per se to regulate whole-body glucose homeostasis is dependent on the ability of a rise in glucose to lower hepatic glucose production and increase peripheral glucose uptake in vivo . In both rodents and humans, glucose sensing is lost in diabetes and obesity, but the site(s) of impairment remains elusive. Here, we first report that short-term high-fat feeding disrupts hypothalamic glucose sensing to lower glucose production in rats. Second, leptin administration into the hypothalamus of high-fat–fed rats restored hypothalamic glucose sensing to lower glucose production during a pancreatic (basal insulin)-euglycemic clamp and increased whole-body glucose tolerance during an intravenous glucose tolerance test. Finally, both chemical inhibition of hypothalamic lactate dehydrogenase (LDH) (achieved via hypothalamic LDH inhibitor oxamate infusion) and molecular knockdown of LDHA (achieved via hypothalamic lentiviral LDHA shRNA injection) negated the ability of hypothalamic leptin infusion to enhance glucose sensing to lower glucose production in high fat–fed rats. In summary, our findings illustrate that leptin enhances LDHA-dependent glucose sensing in the hypothalamus to lower glucose production in high-fat–fed rodents in vivo .
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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) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".