STAT1 and STAT3 α/β splice form activation predicts host responses in mouse hepatitis virus type 3 infection
Bibliographic record
Abstract
Signal transducer and activator of transcription 1alpha (STAT1 alpha) is reported to be essential for IFN-gamma and IFN-alpha regulated gene expression, while STAT1 beta, an alternate splice-form, mediates only IFN-alpha-dependent gene expression. STAT3 alpha and STAT3 beta splice forms are also differentially activated in response to cytokines including IL-6 and IL-10. The aim of this study was to investigate whether the STAT activation will predict the host immune response to viral infection and possibly a therapeutic target for the treatment of viral infection. Mouse hepatitis virus type 3 (MHV-3) resistant strain (A/J) and sensitive mouse strains (BalB/cJ) were infected intraperitoneally (i.p.) with 100 plaque form units (pfu) of MHV-3. The mice were sacrificed at the indicated times, and livers and spleens were immediately frozen in liquid nitrogen. Nuclear extracts proteins were detected by immunoblotting. STAT1 and STAT3 activation in spleen increased 24 to 72 hr following MHV-3 infections in both sensitive and resistant mouse strains. However, over this time period, the ratio of activated alpha to beta splice-form for STAT1 and STAT3 increased above 1.0 in resistant A/J mice, while the ratio fell to <0.3 in MHV-3 sensitive Balb/cJ and C3H/HeJ strains. Activated STAT1 alpha/beta and STAT3 alpha/beta ratio in liver were similar in resistant and sensitive mouse strains. Treatment of sensitive Balb/cJ mice with neutralizing anti-TGF-beta antibody could increase the STAT1 alpha/beta ratio to <1.0 in spleens, predicting enhanced rates of survival. These results suggested that ratio of activated STAT1 alpha/beta and STAT3 alpha/beta in mixed leukocytes from spleen predict the outcome to MHV-3 infection, and may be an important marker and therapeutic target for modification of host immune response to virus infection.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".