Activation of Central Lactate Metabolism Lowers Glucose Production in Uncontrolled Diabetes and Diet-Induced Insulin Resistance
Bibliographic record
Abstract
OBJECTIVE: Hypothalamic lactate metabolism lowers hepatic glucose production and plasma glucose levels in normal rodents. However, it remains unknown whether activation of hypothalamic lactate metabolism lowers glucose production and plasma glucose levels in rodents with diabetes and obesity. RESEARCH DESIGN AND METHODS: We performed intracerebroventricular (ICV) administration of lactate to enhance central lactate metabolism in 1) early-onset streptozotocin-induced uncontrolled diabetic rodents, 2) experimentally induced hypoinsulinemic normal rodents, and 3) early-onset diet-induced insulin-resistant rodents. Tracer-dilution methodology was used to assess the impact of ICV lactate on the rate of glucose production in all three models. RESULTS: We first report that in the absence of insulin treatment, ICV lactate administration lowered glucose production and glucose levels in rodents with uncontrolled diabetes. Second, ICV lactate administration lowered glucose production and glucose levels in normal rodents with experimentally induced hypoinsulinemia. Third, and finally, ICV lactate administration lowered glucose production in normal rodents with diet-induced insulin resistance. CONCLUSIONS: Central lactate metabolism lowered glucose production in uncontrolled diabetic and normal rodents with hypoinsulinemia and in rodents with diet-induced insulin resistance. These data suggest that insulin signaling is not required for central lactate to lower glucose production and that the activation of hypothalamic lactate metabolism could consequently bypass insulin resistance and lower glucose levels in early-onset diabetes and obesity.
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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 | 0.000 |
| 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".