Generation of neuropeptidergic hypothalamic neurons from human pluripotent stem cells
Bibliographic record
Abstract
Hypothalamic neurons orchestrate many essential physiological and behavioral processes via secreted neuropeptides, and are relevant to human diseases such as obesity, narcolepsy and infertility. We report the differentiation of human pluripotent stem cells into many of the major types of neuropeptidergic hypothalamic neurons, including those producing pro-opiolemelanocortin, agouti-related peptide, hypocretin/orexin, melanin-concentrating hormone, oxytocin, arginine vasopressin, corticotropin-releasing hormone (CRH) or thyrotropin-releasing hormone. Hypothalamic neurons can be generated using a 'self-patterning' strategy that yields a broad array of cell types, or via a more reproducible directed differentiation approach. Stem cell-derived human hypothalamic neurons share characteristic morphological properties and gene expression patterns with their counterparts in vivo, and are able to integrate into the mouse brain. These neurons could form the basis of cellular models, chemical screens or cellular therapies to study and treat common human diseases.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".