Group B<i>Streptococcus</i>Induces a Robust IFN-<i>γ</i>Response by CD4<sup>+</sup>T Cells in an<i>In Vitro</i>and<i>In Vivo</i>Model
Bibliographic record
Abstract
Group B Streptococcus (GBS) serotype III causes life-threatening infections. Cytokines have emerged as important players for the control of disease, particularly IFN-γ. Although potential sources of this cytokine have been proposed, no specific cell line has ever been described as a leading contributor. In this study, CD4(+) T cell activation profiles in response to GBS were evaluated through in vivo, ex vivo, and in vitro approaches. Total splenocytes readily produce a type 1 proinflammatory response by releasing IFN-γ, TNF-α, and IL-6 and actively recruit T cells via chemokines like CXCL9, CXCL10, and CCL3. Responding CD4(+) T cells differentiate into Th1 cells producing large amounts of IFN-γ, TNF-α, and IL-2. In vitro studies using dendritic cell and CD4(+) T cell cocultures infected with wild-type GBS or a nonencapsulated mutant suggested that GBS capsular polysaccharide, one of the major bacterial virulence factors, differentially modulates surface expression of CD69 and IFN-γ production. Overall, CD4(+) T cells are important producers of IFN-γ and might thus influence the course of GBS infection through the expression balance of this cytokine.
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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) | 0.000 | 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".