Faculty Opinions recommendation of Irx3 and Irx5 in Ins2-Cre+ cells regulate hypothalamic postnatal neurogenesis and leptin response.
Bibliographic record
Abstract
Obesity is mainly due to excessive food intake. IRX3 and IRX5 have been suggested as determinants of obesity in connection with the intronic variants of FTO, but how these genes contribute to obesity via changes in food intake remains unclear. Here, we show that mice doubly heterozygous for Irx3 and Irx5 mutations exhibit lower food intake with enhanced hypothalamic leptin response. By lineage tracing and single-cell RNA sequencing using the Ins2-Cre system, we identify a previously unreported radial glia-like neural stem cell population with high Irx3 and Irx5 expression in early postnatal hypothalamus and demonstrate that reduced dosage of Irx3 and Irx5 promotes neurogenesis in postnatal hypothalamus leading to elevated numbers of leptin-sensing arcuate neurons. Furthermore, we find that mice with deletion of Irx3 in these cells also exhibit a similar food intake and hypothalamic phenotype. Our results illustrate that Irx3 and Irx5 play a regulatory role in hypothalamic postnatal neurogenesis and leptin response. PMID: 33859429 Funding information This work was supported by: Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada), Grant ID: MOP-136821 Diabetes Canada (DC), Grant ID: NOD_PF-3-15-4739-JS
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.273 | 0.112 |
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".