Differential up-regulation of CXCR3 on effector CD4+Foxp3- T cells and regulatory CD4+Foxp3+ T cells during blood-stage <i>Plasmodium chabaudi</i> AS infection (149.5)
Bibliographic record
Abstract
Abstract The chemokine receptor CXCR3 and its ligands CXCL9 and CXCL10 are critical for trafficking of pathogenic CD8+ T cells to the brain during experimental cerebral malaria in Plasmodium berghei ANKA infected mice. We investigated the role of chemokines and their receptors during blood-stage P. chabaudi AS infection in C57BL/6 (B6) mice which control and resolve the infection with a peak of parasitemia at days 8-9 post infection (p.i.). Real-time PCR analysis revealed significantly increased CXCL9 mRNA expression in spleen cells at days 6, 8 and 11 p.i. while FACS analysis showed significantly increased CXCR3 expression on splenic CD4+ T cells at days 8 and 11 p.i. compared to naïve mice. To determine if CD4+ T cell populations differentially expressed CXCR3 during P. chabaudi AS infection, we examined CXCR3 expression on splenic CD4+Foxp3- T cells (Teffs) compared to CD4+Foxp3+ T cells (Tregs). In naïve mice, 15% of Tregs and 15% of Teffs were CXCR3+, at day 8 p.i., 30% of Tregs vs 45% of Teffs were CXCR3+, and at day 11 p.i., CXCR3+ Tregs were still 30% while CXCR3+ Teffs were 55%. Increased CXCR3 expression on Teffs correlated with increased protective CD4+Tbet+IFNγ+ Th1 cells in the spleen. These findings indicate that CXCR3 expression is up-regulated on both Teffs and Tregs during blood-stage malaria. Higher expression of CXCR3 on Teffs might allow these cells to migrate more efficiently to the spleen, the critical tissue for immune control and resolution of the 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 | 0.000 | 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) | 0.002 | 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".