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Record W1029058984 · doi:10.3791/54261

Impression Cytology of the Lid Wiper Area

2016· article· en· W1029058984 on OpenAlexaff
Alex Müntz, Kevin van Doorn, Lakshman N. Subbaraman, Lyndon Jones

Bibliographic record

VenueJournal of Visualized Experiments · 2016
Typearticle
Languageen
FieldHealth Professions
TopicNeonatal skin health care
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsImpressionCytologyArtMedicineComputer sciencePathologyWorld Wide Web

Abstract

fetched live from OpenAlex

Few reports on the cellular anatomy of the lid wiper (LW) area of the inner eyelid exist and only one report makes use of cytological methods. The optimization of a method of collecting, staining and imaging cells from the LW region using impression cytology (IC) is described in this study. Cells are collected from the inner surface of the upper eyelid of human subjects using hydrophilic polytetrafluoroethylene (PTFE) membranes, and stained with cytological dyes to reveal the presence of goblet cells, mucins, cell nuclei and various degrees of pre- and para-keratinization. Immunocytochemical dyes show cell esterase activity and compromised cell membranes by the use of a confocal scanning laser microscope. Up to 100 microscopic digital images are captured for each sample and stitched into a high-resolution, large scale image of the entire IC span. We demonstrate a higher sensitivity of IC than reported before, appropriate for identifying cellular morphologies and metabolic activity in the LW area. To our knowledge, this is the first time this selection of fluorescent dyes was used to image LW IC membranes. This protocol will be effective in future studies to reveal undocumented details of the LW area, such as assessing cellular particularities of contact lens wearers or patients with dry eye or lid wiper epitheliopathy.

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)0.001
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 score0.154
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.087
GPT teacher head0.555
Teacher spread0.469 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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