Decreased levels of miR-28-5p and miR-361-3p and increased levels of insulin-like growth factor 1 mRNA in mononuclear cells from patients with hereditary hemorrhagic telangiectasia
Bibliographic record
Abstract
Hereditary hemorrhagic telangiectasia (HHT) is a rare vascular disorder inherited in an autosomal dominant manner. Patients with HHT can develop vascular dysplasias called telangiectasias and arteriovenous malformations (AVMs). Our objective was to profile and characterize micro-RNAs (miRNAs), short noncoding RNAs that regulate gene expression posttranscriptionally, in HHT patient-derived peripheral blood mononuclear cells (PBMCs). PBMCs, comprised mostly of lymphocytes and monocytes, have been reported to be dysfunctional in HHT. A total of 40 clinically confirmed HHT patients and 22 controls were enrolled in this study. PBMCs were isolated from 16 mL of peripheral blood and purified for total RNA. MiRNA expression profiling was conducted with a human miRNA array analysis. Select dysregulated miRNAs and miRNA targets were validated with reverse transcription-quantitative polymerase chain reaction. Of the 377 miRNAs screened, 41 dysregulated miRNAs were identified. Both miR-28-5p and miR-361-3p, known to target insulin-like growth factor 1 (IGF1), a potent angiogenic growth factor, were found to be significantly downregulated in HHT patients. Consequently, IGF1 mRNA levels were found to be significantly elevated. Our research successfully identified miRNA dysregulation and elevated IGF1 mRNA levels in PBMCs from HHT patients. This novel discovery represents a potential pathogenic mechanism that could be targeted to alleviate clinical manifestations of HHT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".