Transcriptomics of Hirschsprung disease patient-derived enteric neural crest cells reveals a role for oxidative phosphorylation
Bibliographic record
Abstract
Hirschsprung disease is characterized by the absence of enteric neurons caused by the defects of enteric neural crest cells, leading to intestinal obstruction. Here, using induced pluripotent stem cell-based models of Hirschsprung and single-cell transcriptomic analysis, we identify a gene set of 118 genes commonly dysregulated in all patient enteric neural crest cells, and suggest HDAC1 may be a key regulator of these genes. Furthermore, upregulation of RNA splicing mediators and enhanced alternative splicing events are associated with severe form of Hirschsprung. In particular, the higher inclusion rate of exon 9 in PTBP1 and the perturbed expression of a PTBP1-target, PKM, are significantly enriched in these patient cells, and associated with the defective oxidative phosphorylation and impaired neurogenesis. Hedgehog-induced oxidative phosphorylation significantly enhances the survival and differentiation capacity of patient cells. In sum, we define various factors associated with Hirschsprung pathogenesis and demonstrate the implications of oxidative phosphorylation in enteric neural crest development and HSCR pathogenesis.
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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) | 0.001 | 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".