In the eye of the storm: <scp>SARS‐CoV‐2</scp> infection and replication at the ocular surface?
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first emerged in December 2019 and spread quickly causing the coronavirus disease 2019 (COVID-19) pandemic. Recent single cell RNA-Seq analyses have shown the presence of SARS-CoV-2 entry factors in the human corneal, limbal, and conjunctival superficial epithelium, leading to suggestions that the human ocular surface may serve as an additional entry gateway and infection hub for SARS-CoV-2. In this article, we review the ocular clinical presentations of COVID-19 and the features of the ocular surface that may underline the overall low ocular SARS-CoV-2 infection. We critically evaluate the studies performed in nonhuman primates, ex vivo organ culture ocular models, stem cell derived eye organoids and the differences in infection efficiency observed in different parts of human ocular surface epithelium. Finally, we highlight the additional work that needs to be carried out to understand the immune response of the ocular surface to SARS-CoV-2 infection, which can be translated into prophylactic treatments that may be applied to other organ systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".