Aberrant Expressions and Variant Screening of SEMA3D in Indonesian Hirschsprung Patients
Bibliographic record
Abstract
Background: The semaphorin 3D (SEMA3D) gene has been implicated in the pathogenesis of Hirschsprung disease (HSCR), a complex genetic disorder characterized by the loss of ganglion cells in varying lengths of gastrointestinal tract. We wished to investigate the role of SEMA3D variants, both rare and common variants, as well as its mRNA expression in Indonesian HSCR patients. Methods: Sanger sequencing was performed in 54 HSCR patients to find a pathogenic variant in SEMA3D. Next, we determined SEMA3D expression in 18 HSCR patients and 13 anorectal malformation colons as controls by quantitative real-time polymerase chain reaction (qPCR). Results: No rare variant was found in the SEMA3D gene, but one common variant in exon 17, p.Lys701Gln (rs7800072). The risk allele (C) frequency at rs7800072 among HSCR patients (23%) was similar to those reported for the 1000 Genomes (27%) and ExAC (28%) East Asian ancestry controls (p=0.49 and 0.41, respectively). A significant different of SEMA3D expression was observed between groups (p=0.04). Furthermore, qPCR revealed that SEMA3D expression was strongly up-regulated (5.5-fold) in the ganglionic colon of HSCR patients compared to control colon (CT 10.8 ± 2.1 vs. 13.3 ± 3.9; p=0.025). Conclusions: We report the first study of aberrant SEMA3D expressions in HSCR patients and suggest further understanding into the contribution of aberrant SEMA3D expression in the development of HSCR. In addition, this study is the first comprehensive analysis of SEMA3D variants in the Asian ancestry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".