Response to Comment on “Hepatitis C Virus-Specific Th17 Cells Are Suppressed by Virus-Induced TGF-β”
Bibliographic record
Abstract
The Journal of Immunology (1).The authors reported for the first time that Ag-specific Th17 cells were induced in patients infected by the hepatitis C virus (HCV).They also indicated that TGF- and IL-10, which are induced by the viral nonstructural protein 4 (NS4), suppressed Th1 and Th17 responses in HCV-infected patients.Previously, several groups recognized that a combination of IL-6 and TGF- was necessary for the differentiation of naive T cells into Th17 cells (2-4).It is very interesting that in HCV-infected patients TGF- is a potent regulatory cytokine with inhibitory effects on the Th17 response.We would like to draw attention to other studies that have identified two additional cytokines involved in the induction of Th17 response: IL-23, an essential factor for maintaining the differentiated Th17 cells through its phenotype stabilization (5-7), and IL-21, which plays a role in amplification of the Th17 response (8 -9).The Rowan group's work indicates the potential of further research into the influence of viral NS4 in HCV-infected patients on IL-6, IL-21, and IL-23 expression.One such study might investigate whether suppression of Th17 response in this patient population may be associated with influencing viral NS4 on IL-6, IL-21, and IL-23 levels in addition to its demonstrated role in suppressing the influence of TGF- and IL-10 on Th17 response.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.027 | 0.032 |
| Insufficient payload (model declined to judge) | 0.018 | 0.018 |
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".