Eosinophil Knockout Humans: Uncovering the Role of Eosinophils Through Eosinophil-Directed Biological Therapies
Bibliographic record
Abstract
The enigmatic eosinophil has emerged as an exciting component of the immune system, involved in a plethora of homeostatic and inflammatory responses. Substantial progress has been achieved through experimental systems manipulating eosinophils in vivo, initially in mice and more recently in humans. Researchers using eosinophil knockout mice have identified a contributory role for eosinophils in basal and inflammatory processes and protective immunity. Primarily fueled by the purported proinflammatory role of eosinophils in eosinophil-associated diseases, a series of anti-eosinophil therapeutics have emerged as a new class of drugs. These agents, which dramatically deplete eosinophils, provide a valuable opportunity to characterize the consequences of eosinophil knockout humans. Herein, we comparatively describe mouse and human eosinophil knockouts. We put forth the view that human eosinophils negatively contribute to a variety of diseases and, unlike mouse eosinophils, do not yet have an identified role in physiological health; thus, clarifying all roles of eosinophils remains an ongoing pursuit.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".