Identification of Competing Endogenous RNA Regulatory Networks in Vitamin A Deficiency-Induced Congenital Scoliosis by Transcriptome Sequencing Analysis
Bibliographic record
Abstract
BACKGROUND/AIMS: Congenital scoliosis (CS) is a result of anomalous development of vertebrae and is frequently associated with somitogenesis malformation. Although noncoding RNAs (ncRNAs) have been recently determined to be involved in the pathogenesis of CS, the competing endogenous RNA (ceRNA) regulatory networks in CS remain largely unknown. METHODS: Sequencing was conducted to explore the ncRNA expression profiles in rat embryos (gestation day 9) following vitamin A deficiency (VAD) (n = 9 for the vitamin A deficiency-induced congenital scoliosis (VAD-CS) group and n = 4 for the control group). Real-time reverse transcriptase polymerase chain reaction (RT-PCR) was conducted to verify the expression levels of selected mRNAs, long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs). Bioinformatics analysis was used to discover the possible relationships and functions of the ceRNAs. RESULTS: A total of 749 mRNAs, 56 miRNAs, 685 lncRNAs, and 70 circRNAs were identified to have significantly different expression levels in the two groups. Wnt, PI3K-ATK, FoxO, EGFR, and mTOR were found to be the most significant pathways involved in VAD-CS pathogenesis. The circRNA/miRNA/mRNA and lncRNA/miRNA/mRNA networks of CS were built, and the gene expression mechanisms regulated by ncRNAs were unveiled via the ceRNA regulatory networks. CONCLUSION: We comprehensively identified ceRNA regulatory networks of embryonic somite development in VAD-CS as well as revealed the contribution of different ncRNA expression profiles. Our data demonstrate the association between mRNAs and ncRNAs in the pathogenic mechanism of CS.
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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 | 0.001 |
| 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".