Tissue Resident Memory Cells: Friend or Foe?
Bibliographic record
Abstract
ABSTRACT Tissue‐resident memory T (T RM ) cells are a specialised subset of immune cells that remain within tissues, playing a vital role in localised immune defence and long‐term immunity. Unlike circulating memory T cells, T RM cells do not recirculate to provide rapid and effective responses against previously encountered pathogens at the tissue level. The formation of T RM cells is driven by tissue‐specific cues, guiding their differentiation and retention within organs such as the skin, lungs and gut. They are characterised by the expression of unique markers, including CD69 and CD103, which facilitate their retention and longevity in tissues. T RM cells are essential for immune surveillance, effectively detecting and responding to different infections and contributing to tumour suppression. However, T RM cells are also implicated in chronic inflammatory and autoimmune diseases, where persistent activation by resident and autoantigens can lead to tissue damage. This pathogenic role is evident in chronic inflammatory conditions such as psoriasis, vitiligo and inflammatory bowel disease (IBD), where T RM cells may drive persistent localised inflammation and contribute to disease progression and severity. Emerging therapeutic strategies seek to modulate T RM cells to balance their protective and pathogenic roles in these inflammatory diseases. Approaches such as checkpoint inhibitors, cytokine modulation and cell‐depletion therapies aim to enhance T RM cells' beneficial immune functions while minimising their role in autoimmunity. A deeper understanding of T RM cell development, maintenance and functional diversity is critical for advancing treatments for infectious diseases, chronic inflammation, autoimmune conditions and cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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; both teacher heads agree on what is shown here.
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".