GBP1 exerts inhibitory effects on acute viral myocarditis by inhibiting the inflammatory response of macrophages in mice
Post-publication record
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Bibliographic record
Abstract
Viral myocarditis (VMC) is a condition that could potentially progress to dilated cardiomyopathy or congestive heart failure, making it the leading cause of the untimely death in young adults. Interferon-induced GBP1 encodes much of the GTPase induced by interferon gamma in many eukaryotic cells. However, little is known regarding the effect of GBP1 on acute VMC (AVMC). Hence, this aim of this study was to assess the effect of GBP1 on AVMC. Once the AVMC mouse models were established, the functional role of GBP1 was determined in AVMC. Serum levels of IL-6, TNF-α, and TGF-β, and expression levels of GBP1, MIF, iNOS, and COX-2 were detected, together with the viability and apoptosis of cardiomyocytes. AVMC mice presented with increased levels of TGF-β, IL-6, TNF-α, MIF, iNOS, and COX-2, as well as cell apoptosis, but lower expression of GBP1 and viability of cardiomyocytes. Restored GBP1 or depleted macrophages resulted in decreased levels of TGF-β, IL-6, TNF-α, MIF, iNOS, and COX-2, as well as cardiomyocyte apoptosis, while increasing cardiomyocyte viability. In conclusion, our results highlight the potential role of GBP1 in inhibiting AVMC development. The experimental results indicate that GBP1 up-regulation and macrophage depletion can alleviate AVMC-related cardial damage by inhibiting inflammatory responses and cardiomyocyte apoptosis while increasing cardiomyocyte viability.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".