Human microRNA responses predict cytomegalovirus replication following solid organ transplantation
Bibliographic record
Abstract
Background: Homo sapiens mature micro-ribonucleic acid (miRNA)-200b-3p and 200c-3p are predicted to bind to 3' untranslated region of mRNA encoding human cytomegalovirus (HCMV) immediate early protein 2 (IE2). We hypothesized that expression of these miRNAs pretransplant could predict HCMV replication after solid organ transplantation (SOT). Methods: A total of 272 SOT recipients were HCMV-seropositive pretransplant and were managed using preemptive therapy. Pretransplant peripheral blood mononuclear cells were stimulated with HCMV followed by collection of RNA 1 day poststimulation. The miRNAs were quantified using real-time reverse transcription-polymerase chain reaction. Human foreskin fibroblasts were transfected with 200b-3p and 200c-3p and infected with HCMV 1 hour post-transfection. Protein was collected at 3 days postinfection (dpi) and 7 dpi underwent immunoblotting for IE2. Results: Medians of 200b-3p and 200c-3p were significantly lower in recipients with HCMV replication (n = 144) (361.6 vs 552.6, P = .035; 3586.8 vs 12986.8 copies/μL, P = .03, respectively). Multivariate regression revealed that 200b-3p ≥100 copies/μL (odds ratio [OR]: 0.53; P = .02), was associated with less HCMV replication. Transfection with 200b-3p resulted in 2.7- and 2.5-fold decreased IE2 at 3 dpi and 7 dpi, respectively, compared to mock cells. Conclusions: MicroRNAs may play a biologically relevant role in controlling HCMV replication post-transplant.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".