Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy
Bibliographic record
Abstract
Inosine modulates antitumor immunity Checkpoint blockade immunotherapy harnesses the immune system to kill cancer cells and has been used with great success to treat certain tumors, but not all cancer patients respond. The efficacy of checkpoint blockade immunotherapy has been shown to depend on the presence of distinct, beneficial bacteria residing in the gut of patients, but how the microbiome mediates such beneficial effects is unclear. Mager et al. found that specific bacteria produce a metabolite called inosine that enhances the effect of checkpoint blockade immunotherapy (see the Perspective by Shaikh and Sears). In mouse models, inosine, together with proinflammatory stimuli and immunotherapy, strongly enhanced the antitumor capacities of T cells in multiple tumor types, including colorectal cancer, bladder cancer, and melanoma. Science , this issue p. 1481 ; see also p. 1427
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".