Complexity of Host Micro-RNA Response to Cytomegalovirus Reactivation After Organ Transplantation
Bibliographic record
Abstract
Human (Homo sapiens) micro-RNAs (hsa-miRNAs) regulate virus and host-gene translation, but the biological impact in patients with human cytomegalovirus (hCMV) infection is not well defined in a clinically relevant model. First, we compared hsa-miRNA expression profiles in peripheral blood mononuclear cells from 35 transplant recipients with and without CMV viremia by using a microarray chip covering 847 hsa-miRNAs. This approach demonstrated a set of 142 differentially expressed hsa-miRNAs. Next, we examined the effect of each of these miRNAs on viral growth by using human fibroblasts (human foreskin fibroblast-1) infected with the hCMV Towne strain, identifying a subset of proviral and antiviral hsa-miRNAs. miRNA-target prediction software indicated potential binding sites within the hCMV genome (e.g., hCMV-UL52 and -UL100 [UL = unique long]) and host-genes (e.g., interleukin-1 receptor, IRF1). Luciferase-expressing plasmid constructs and immunoblotting confirmed several predicted miRNA targets. Finally, we determined the expression of selected proviral and antiviral hsa-miRNAs in 242 transplant recipients with hCMV-viremia. We measured hsa-miRNAs before and after antiviral therapy and correlated hsa-miRNA expression levels to hCMV-replication dynamics. One of six antiviral hsa-miRNAs showed a significant increase during treatment, concurrent with viral decline. In contrast, six of eight proviral hsa-miRNAs showed a decrease during viral decline. Our results indicate that a complex and multitargeted hsa-miRNA response occurs during CMV replication in immunosuppressed patients. This study provides mechanistic insight and potential novel biomarkers for CMV replication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".