Progressive postnatal decline in leptin sensitivity of arcuate hypothalamic neurons in the<i>Magel2</i>-null mouse model of Prader–Willi syndrome
Bibliographic record
Abstract
Prader-Willi syndrome (PWS) is a multigene disorder associated with neonatal failure to thrive, developmental delay and endocrine abnormalities suggestive of hypothalamic dysfunction. Children with PWS typically develop overt hyperphagia and obesity ∼8 years of age, later than children with other genetic forms of obesity. This suggests a postnatal developmental or degenerative component to PWS-associated obesity. De novo inactivating mutations in one PWS candidate gene, MAGEL2, have been identified in children with features of PWS. Adult mice lacking Magel2 are insensitive to the anorexic effect of leptin treatment, and their hypothalamic pro-opiomelanocortin (POMC) neurons fail to depolarize in response to leptin. However, it is unclear whether this leptin insensitivity is congenital, or whether normal leptin sensitivity in neonatal Magel2-null mice is lost postnatally. We used in vitro cytosolic calcium imaging to follow the postnatal development of leptin responses in POMC neurons in these mice. Leptin caused an activation of POMC neurons in wild-type acute hypothalamic slice preparations at all ages, reflecting their normal leptin-invoked depolarization. Normal leptin responses were found in Magel2-null mice up to 4 weeks of age, but the proportion of leptin-responsive POMC neurons was reduced in 6-week-old Magel2-null mice. The number of α-melanocyte-stimulating hormone immunoreactive fibers in the paraventricular hypothalamic nucleus was also reduced in mutant mice at 6 weeks of age. A similar progressive loss of leptin sensitivity caused by loss of MAGEL2 in children with PWS could explain the delayed onset of increased appetite and weight gain in this complex disorder.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".