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Record W4285104051 · doi:10.1097/ico.0000000000003030

Effect of Collagenase A on Descemet Membrane Endothelial Keratoplasty Scroll Tightness

2022· article· en· W4285104051 on OpenAlexaff
Luqmaan Moolla, Michael Mimouni, Nizar Din, Eyal Cohen‬‏, Allan R. Slomovic, David S. Rootman, Clara C. Chan

Bibliographic record

VenueCornea · 2022
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScrollCollagenaseScroll compressorOphthalmologyMedicineChemistryBiochemistryMechanical engineering

Abstract

fetched live from OpenAlex

PURPOSE: The scrolling properties of the Descemet membrane endothelial keratoplasty (DMEK) graft are essential for surgical success. Currently, there is limited knowledge on what dictates the tightness of the DMEK scroll. The purpose of this study was to determine the impact of temperature and protein digestion on DMEK graft scroll tightness. METHODS: For the temperature experiment, a total of 28 eyes were used for this study. Scrolls in the cold group were kept at 4°C while scrolls in the hot group were kept at 37°C. Scroll width was recorded at the 5-, 15-, and 30-minute mark. For the protein digestion experiment, a total of 18 eyes were exposed to collagenase A (10 CDU/mL) in Optisol solution. Scroll width was recorded at the time points of 1, 3, 5, 10, and 20 minutes. RESULTS: The results of the temperature experiment did not yield any statistically significant changes in the mean scroll width of the DMEK scrolls across both temperature ranges and observation times. For the protein digestion experiment, the mean scroll width grew from 1.85 mm to 2.13 mm from the beginning of the experiment until the final observation at 20 minutes. This is a 14.7% change over 20 minutes with a P value (<0.001), exemplifying a statistically significant change in scroll width. CONCLUSIONS: Temperature did not have any significant effect over scroll tightness, but scroll tightness decreased with collagenase exposure.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.379
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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