Transforming Growth Factor- <i>β</i> Inhibits Coxsackievirus-Mediated Autoimmune Myocarditis
Bibliographic record
Abstract
Clinical myocarditis is a precursor to dilated cardiomyopathy and a principal cause of heart failure. Nearly 30% of all recently diagnosed cases of myocarditis are attributable to infection with coxsackie B virus (CBV), the most frequently associated pathogen. CBV initially replicates in the pancreas and quickly spreads to the heart, inducing chronic autoimmunity. To determine whether immunosuppressive cytokines could act to limit the extent of autoimmunity to the heart, we infected transgenic mice that express immunosuppressive cytokines in the pancreas. Herein, we demonstrate that transgenic expression of transforming growth factor-beta (1) (TGF-beta) within the pancreatic beta cells prevented mice from developing autoimmune myocarditis after CBV infection. In contrast, transgenic expression of interleukin-4 did not inhibit virus-mediated heart disease. Furthermore, we show that TGF-beta expression reduced viral replication while promoting the recruitment of macrophages into the pancreas. These results illustrate the benefit of TGF-beta in controlling not only viral replication, but also CBV-mediated autoimmunity.
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 | 0.000 | 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".