p38 MAPK Signaling Enhances Reovirus Replication by Facilitating Efficient Virus Entry, Virus Capsid Uncoating and Post-Uncoating Steps
Bibliographic record
Abstract
Abstract Mammalian orthoreovirus serotype 3 Dearing an orphan human virus currently being pursued as an oncolytic virus in multiple phase I/II clinical trials. Previous clinical trials have emphasized the importance of patient pre-screening for prognostic markers to improve therapeutic success. However, currently, only generic cancer markers such as EGFR, Hras, Kras, Nras, Braf and/or p53 are utilized and have exhibited limited benefit in predicting therapeutic efficacy. Utilization of more specific markers that influence specific steps during reovirus replication could prove beneficial as prognostic markers. This study delineated the role of p38 MAPK signaling during reovirus infection and illustrated a connection between specific p38 MAPK isoforms and reovirus infection. Using a panel of specific p38 MAPK inhibitors and an inactive inhibitor analogue, we demonstrated that p38 MAPK signaling is essential for establishment of reovirus infection by enhancing reovirus endocytosis, facilitating efficient reovirus uncoating at the endo-lysosomal stage, and augmenting post uncoating replication steps. Using a broad panel of human breast cancer cell lines, we observed susceptibility of reovirus infection corresponded with virus binding and uncoating efficiency, which was strongly correlated with status of the p38β isoform. Together, our study proposes p38β as a potential prognostic marker for early stages of reovirus infection that are crucial to establishment of successful reovirus infection.
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) | 0.001 | 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 | 0.000 |
| 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".