B Cell Presentation of Chlamydia Antigen Selects Out Protective CD4γ13 T Cells: Implications for Genital Tract Tissue-Resident Memory Lymphocyte Clusters
Bibliographic record
Abstract
ABSTRACT Surveillance and defense of the enormous mucosal interface with the nonsterile world are critical to protecting the host from a wide range of pathogens. Chlamydia trachomatis is an intracellular bacterial pathogen that replicates almost exclusively in the epithelium of the reproductive tract. The fallopian tubes and vagina are poorly suited to surveillance and defense, with limited immune infrastructure positioned near the epithelium. However, a dynamic process during clearing primary infections leaves behind new lymphoid clusters immediately beneath the epithelium. These memory lymphocyte clusters (MLCs) harboring tissue-resident memory (Trm) T cells are presumed to play an important role in protection from subsequent infections. Histologically, human Chlamydia MLCs have prominent B cell populations. We investigated the status of genital tract B cells during C. muridarum infections and the nature of T cells recovered from immune mice using immune B cells as antigen-presenting cells (APCs). These studies revealed a genital tract plasma B cell population and a novel genital tract CD4 T cell subset producing both gamma interferon (IFN-γ) and interleukin-13 (IL-13). A panel of CD4 T cell clones and microarray analysis showed that the molecular fingerprint of CD4γ13 T cells includes a Trm-like transcriptome. Adoptive transfer of a Chlamydia -specific CD4γ13 T cell clone completely prevented oviduct immunopathology without accelerating bacterial clearance. Existence of a CD4γ13 T cell subset provides a plausible explanation for the observation that human peripheral blood mononuclear cell (PBMC) Chlamydia -specific IFN-γ and IL-13 responses predict resistance to reinfection.
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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) | 0.003 | 0.001 |
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".