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Record W3211125258 · doi:10.1097/iae.0000000000003320

LOW VULNERABILITY OF THE POSTERIOR EYE SEGMENT TO SARS-COV-2 INFECTION

2021· article· en· W3211125258 on OpenAlexaff
Steffen E. Künzel, Thore Bürgel, Sandrine H. Künzel, Dominika Pohlmann, Oliver Zeitz, Antonia M. Joussen, Alexandre Dubrac

Bibliographic record

VenueRetina · 2021
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsChoroidRetinaRetinalBiologyCellCoronavirus disease 2019 (COVID-19)BiomarkerCell typePathologyOphthalmologyMedicineGeneticsNeuroscience

Abstract

fetched live from OpenAlex

PURPOSE: Retinal manifestations have been described in COVID-19 patients, but it is unknown whether SARS-CoV-2, the causal agent in COVID-19, can directly infect posterior ocular tissues. Here, we investigate SARS-CoV-2 host factor gene expression levels and their distribution across retinal and choroidal cell types. METHODS: Query of single-cell RNA sequencing data from human retina and choroid. RESULTS: We find no relevant expression of two key genes involved in SARS-CoV-2 entry, ACE2 and TMPRSS2, in retinal cell types. By contrast, scarce expression levels could be detected in choroidal vascular cells. CONCLUSION: Given the current understanding of viral host cell entry, these findings suggest a low vulnerability of the posterior eye segment to SARS-CoV-2 with a potential weak spot in the vasculature, which could play a putative causative role in ocular lesions in COVID-19 patients. This may qualify the vasculature of the human posterior eye segment as an in vivo biomarker for life-threatening vascular occlusions in COVID-19 patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.315
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

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