Ultrastructural Identification of Exocytosis of Granules from Human Gut Eosinophils in vivo
Bibliographic record
Abstract
Twenty-two percent of 117 biopsies of human intestinal tissues had ultrastructural images of classical regulated secretion from eosinophils in vivo i.e. eosinophil granule extrusion (EGE). Replicate intestinal biopsies that were positive for bacteria had EGE more often than not (p < 0.05); 77% of the isolates were Staphylococci. Some of the intestinal biopsies also had damaged nerves; all that had EGE and damaged enteric nerves also had positive bacterial cultures. The EGE that we observed could not account for all enteric nerve damage, suggesting multifactorial mechanisms for nerve damage in gut tissues. Among the possibilities are release of neurotoxic eosinophil granule proteins by an alternate secretory route, i.e., piecemeal degranulation, direct toxicity of tissue invasive bacteria and/or damaged nerves of unknown etiology such as those that are regularly present in uninvolved tissues of patients with Crohn's disease.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".