Neutrophil and T-Cell Homeostasis in the Closed Eye
Why this work is in the frame
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Bibliographic record
Abstract
Purpose: This study sought to examine the changes and phenotype of the tear neutrophil and T-cell populations between early eyelid closure and after a full night of sleep. Methods: Fourteen healthy participants were recruited and trained to wash the ocular surface with PBS for at-home self-collection of ocular surface and tear leukocytes following up to 1 hour of sleep and a full night of sleep (average 7 hours), on separate days. Cells were isolated, counted, and incubated with fluorescently labeled antibodies to identify neutrophils, monocytes, and T cells. For neutrophil analysis, samples were stimulated with lipopolysaccharide (LPS) or calcium ionophore (CaI) before antibody incubation. Flow cytometry was performed. Results: Following up to 1 hour of sleep, numerous leukocytes were collected (2.6 × 105 ± 3.0 × 105 cells), although significantly (P < 0.005) more accumulated with 7 hours of sleep (9.9 × 105 ± 1.2× 106 cells). Neutrophils (65%), T cells (3%), and monocytes (1%) were identified as part of the closed eye leukocyte infiltration following 7 hours of sleep. Th17 cells represented 22% of the total CD4+ population at the 7-hour time point. Neutrophil phenotype changed with increasing sleep, with a downregulation of membrane receptors CD16, CD11b, CD14, and CD15, indicating a loss in the phagocytic capability of neutrophils. Conclusions: Neutrophils begin accumulating in the closed eye conjunctival sac much earlier than previously demonstrated. The closed eye tears are also populated with T cells, including a subset of Th17 cells. The closed eye environment is more inflammatory than previously thought and is relevant to understanding ocular homeostasis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it