The role of autonomic efferents and uncoupling protein 1 in the glucose-lowering effect of leptin therapy
Bibliographic record
Abstract
OBJECTIVE: Leptin reverses hyperglycemia in rodent models of type 1 diabetes (T1D). Direct application of leptin to the brain can lower blood glucose in diabetic rodents, and can activate autonomic efferents and non-shivering thermogenesis in brown adipose tissue (BAT). We investigated whether leptin reverses hyperglycemia through a mechanism that requires autonomic innervation, or uncoupling protein 1 (UCP1)-mediated thermogenesis. METHODS: To examine the role of parasympathetic and sympathetic efferents in the glucose-lowering action of leptin, mice with a subdiaphragmatic vagotomy or 6-hydroxydopamine induced chemical sympathectomy were injected with streptozotocin (STZ) to induce hyperglycemia, and subsequently leptin treated. To test whether the glucose-lowering action of leptin requires activation of UCP1-mediated thermogenesis in BAT, we administered leptin in STZ-diabetic Ucp1 knockout (Ucp1 (-/-)) mice and wildtype controls. RESULTS: Leptin ameliorated STZ-induced hyperglycemia in both intact and vagotomised mice. Similarly, mice with a partial chemical sympathectomy did not have an attenuated response to leptin-mediated glucose lowering relative to sham controls, and showed intact leptin-induced Ucp1 expression in BAT. Although leptin activated BAT thermogenesis in STZ-diabetic mice, the anti-diabetic effect of leptin was not blunted in Ucp1 (-/-) mice. CONCLUSIONS: These results suggest that leptin lowers blood glucose in insulin-deficient diabetes through a manner that does not require parasympathetic or sympathetic innervation, and thus imply that leptin lowers blood glucose through an alternative CNS-mediated mechanism or redundant target tissues. Furthermore, we conclude that the glucose lowering action of leptin is independent of UCP1-dependent thermogenesis.
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 | 0.001 | 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 | 0.000 |
| 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".