T peripheral helper (Tph) cells, a marker of immune activation in cancer and autoimmune disorders
Bibliographic record
Abstract
T peripheral helper (Tph) cells are a newly discovered subtype of CD4+ T cells that have emerged as the counterpart of T follicular helper (Tfh) cells in the peripheral tissues. These two cell types share some common characteristics, such as high levels of PD1 and CXCL13 expression, but differ in the expression of transcription factors and chemokine receptors. Tph cells have been studied in relation to B cells' effector functions, including cytokines production and antibody-mediated immune responses. However, their role in the inflammatory-mediated development of malignancies remains poorly understood. Tph cells were initially identified in the synovium of rheumatoid arthritis patients and have since been found to be expanded in several autoimmune diseases. They have been linked to a worse prognosis in autoimmune conditions, but intriguingly, their presence has been correlated with better outcomes in certain types of cancer. The functions of Tph cells are still being investigated, but recent data suggests their involvement in the assembly of tertiary lymphoid structures (TLS). Furthermore, their interaction with B cells, which have been mainly described as possessing a memory phenotype, promotes their development. In this review, we explore the role of Tph cells in peripheral immune responses during cancer and autoimmune disorders.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".