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Protocols for Isolation and Characterization of Human Corneal Epithelial and Conjunctival Epithelial Cells

2025· book-chapter· en· W4413229200 on OpenAlex
H.R. Krishna Rao, Najam A. Sharif

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBENTHAM SCIENCE PUBLISHERS eBooks · 2025
Typebook-chapter
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsMcMaster University
Fundersnot available
KeywordsConjunctivaCorneaMedicineCorneal epitheliumImmunologyBiologyPathologyCell biologyOphthalmology

Abstract

fetched live from OpenAlex

The eye is a specialized organ composed of many types of tissues and cells. Since the ocular surface is the first point of contact with light entering the eye, environmental airborne materials, and topically applied medications, it is important to understand the features of these cells and their physiopathology. Furthermore, such characteristics and receptor/enzyme/transporter profiles of the cells can serve as targets for drug discovery and development to treat such eye disorders and/or to show the potential risks of ocular irritation and inflammation associated with certain medications. This is particularly important with respect to corneal and conjunctival epithelial cells and mast cells, which are involved in the disease mechanisms associated with dry eye syndrome, ocular allergies, and ocular surface pain. The isolated cells can also be used to study the mechanisms of actions of certain drugs such as antihistamines, mast cell stabilizers, and steroids. This chapter aims to provide protocols to isolate, propagate, and study cells obtained from human cadaveric donor tissues. Potential ways to immortalize human corneal epithelial cells will also be described.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.273
Teacher spread0.252 · 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