bta-miR-29b attenuates apoptosis by directly targeting caspase-7 and NAIF1 and suppresses bovine viral diarrhea virus replication in MDBK cells
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small, endogenous, noncoding RNA molecules that serve as powerful regulators of multiple cellular processes, including apoptosis, differentiation, growth, and proliferation. Bovine viral diarrhea virus (BVDV) contributes significantly to health-related economic losses in the beef and dairy industries. Although BVDV-induced apoptosis correlates with increased intracellular viral RNA accumulation and with bta-miR-29b (miR-29b) expression upregulation in Madin-Darby bovine kidney (MDBK) cells infected with BVDV strain NADL, the role of miR-29b in regulating BVDV-infection-related apoptosis remains unexplored. Here, we report that miR-29b serves as a new miRNA regulating apoptosis. We showed that miR-29b target sequences were present in the 3' untranslated regions of 2 key apoptosis regulators mRNAs, cysteine aspartases-7 (caspase-7) and nuclear apoptosis-inducing factor 1 (NAIF1). Indeed, upon miRNA overexpression, both mRNA and protein levels of caspase-7 and NAIF1 were decreased. We further found that miR-29b attenuated apoptosis by directly regulating intracellular levels of caspase-7 and NAIF1. Moreover, apoptosis blockage by miR-29b was rescued upon co-infection of MDBK cells with lentiviruses expressing caspase-7 and NAIF1. Importantly, miR-29b decreased BVDV NADL envelope glycoprotein E1 mRNA levels and suppressed viral replication. These studies advance our understanding of the mechanisms of miRNAs in mediating the cells combating viral infections.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".