Role of myeloid cell leptin signaling in the regulation of glucose metabolism
Bibliographic record
Abstract
Abstract Although innate immunity is linked to metabolic health, the effect of leptin signaling in cells from the innate immune system on glucose homeostasis has not been thoroughly investigated. We generated two mouse models using Cre-lox methodology to determine the effect of myeloid cell-specific leptin receptor (Lepr) reconstitution and Lepr knockdown on in vivo glucose metabolism. Male mice with myeloid cell-specific Lepr reconstitution (Lyz2Cre+LeprloxTB/loxTB) had better glycemic control as they aged compared to male mice with whole-body transcriptional blockade of Lepr (Lyz2Cre−LeprloxTB/loxTB). In contrast, Lyz2Cre+LeprloxTB/loxTB females only had a trend for diminished hyperglycemia after a prolonged fast. During glucose tolerance tests, Lyz2Cre+LeprloxTB/loxTB males had a mildly improved plasma glucose profile compared to Cre− controls while Lyz2Cre+LeprloxTB/loxTB females had a similar glucose excursion to their Cre− controls. Myeloid cell-specific Lepr knockdown (Lyz2Cre+Leprflox/flox) did not significantly alter body weight, blood glucose, insulin sensitivity, or glucose tolerance in males or females. Expression of the cytokine interleukin 10 (anti-inflammatory) tended to be higher in adipose tissue of male Lyz2Cre+LeprloxTB/loxTB mice (p = 0.0774) while interleukin 6 (pro-inflammatory) was lower in male Lyz2Cre+Leprflox/flox mice (p < 0.05) vs. their respective controls. In conclusion, reconstitution of Lepr in cells of myeloid lineage has beneficial effects on glucose metabolism in male mice.
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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".