NK Cells in the Lymph Nodes and Their Role in Anti-Tumour Immunity
Bibliographic record
Abstract
The lymph nodes are vital to enable adaptive immune responses to infection. Natural killer (NK) cells are cytotoxic lymphocytes that directly kill cancer cells and modulate the activation of other immune cells during anti-tumour immune response. NK cells in the lymph nodes are involved in the regulation of T-cell and B-cell populations and the clearance of viral infections. In solid tumours, lymph nodes are a frequent site of metastasis and immune cell priming, whilst in haematological malignancies, tumour cells can proliferate in the lymph nodes. Thus, lymph nodes are an important site in anti-tumour immunity and therapy resistance. It is therefore crucial to identify strategies to increase recruitment and overcome suppression of NK cells in the lymph node microenvironment to improve tumour clearance. In this review, we summarise the literature interrogating NK cell phenotype and function in the lymph nodes in the context of infection and cancer and evaluate both current and potential strategies to mobilise and activate NK cells within the lymph nodes of cancer patients.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".