Understanding inhibitory receptor function in neutrophils through the lens of <scp>CLEC12A</scp>
Bibliographic record
Abstract
Neutrophils are the first leukocytes recruited from the circulation in response to invading pathogens or injured cells. To eradicate pathogens and contribute to tissue repair, recruited neutrophils generate and release a host of toxic chemicals that can also damage normal cells. To avoid collateral damage leading to tissue injury and organ dysfunction, molecular mechanisms evolved that tightly control neutrophil response threshold to activating signals, the strength and location of the response, and the timing of response termination. One mechanism of response control is interruption of activating intracellular signaling pathways by the 20 inhibitory receptors expressed by neutrophils. The two inhibitory C-type lectin receptors expressed by neutrophils, CLEC12A and DCIR, exhibit both common and distinct molecular and functional mechanisms, and they are associated with different diseases. In this review, we use studies on CLEC12A as a model of inhibitory receptor regulation of neutrophil function and participation in disease. Understanding the molecular mechanisms leading to inhibitory receptor specificity offers the possibility of using physiologic control of neutrophil functions as a pharmacologic tool to control inflammatory diseases.
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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 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".