Notice bibliographique
Résumé
INTRODUCTION Contact lens wear can cause corneal damage, which destabilizes the tear film that protects the ocular surface and may lead to Dry Eye Syndrome [1]. Contact lens-induced Dry Eye Syndrome causes significant discomfort and affects the quality of life of millions worldwide [2,3]. A possible cause of this discomfort is increased friction between ocular tissues [4]. Proteoglycan 4 (PRG4) is a mucin-like glycoprotein that was originally found in synovial fluid, but has also recently been discovered on the eye. It was shown to function as an effective boundary lubricant for the ocular surfaces [4], specifically between the cornea and eyelid or a contact lens [5]. However, these initial studies were not performed in the presence of tear film proteins, which can accumulate on contact lenses with wear causing discomfort [6]. The objectives of this project were to determine if PRG4 adheres to commercially available contact lenses, and to clarify whether PRG4 is able to maintain its boundary-lubricating ability at a cornea-contact lens biointerface in the presence of tear film proteins. METHODS A western blot was performed to measure adhesion of PRG4 on contact lenses. Samples were prepared by soaking commercial contact lenses Air Optix Aqua (AO), Acuvue Oasys (OAS), Acuvue 2 (Av2) in native bovine PRG4 overnight. The lenses were then rinsed three times in saline to remove excess PRG4, and then heated to 70°C to release PRG4 adhered to the lenses. These samples were loaded onto a gel and immunostained to test for presence of PRG4. The lubricity of commercially available contact lenses OAS and Acuvue TruEye (TE) was analyzed using a custom cornea-contact lens friction test. Lenses were soaked in an artificial tear solution (ATS) or ATS doped with PRG4 (ATS+PRG4), sent from collaborators at the University of Waterloo, to challenge the lenses to a proteinaceous condition. Friction tests measure axial load and torque to calculation friction coefficients for these lubrication conditions. RESULTS Figure 1. Image of a western blot membrane showing PRG4 adhesion of OAS, AO, and Av2 soaked in native PRG4. Western blots showed strong PRG4 adhesion (denoted by the density of the PRG4 bands) on silicone hydrogel contact lenses (OAS and AO), and little adhesion on a conventional hydrogel lens (Av2). AO clearly held onto PRG4 the best (Figure 1). Kinetic friction coefficients were not significantly different for the ATS and ATS+PRG4 conditions. Values of were higher for TE than OAS (0.35±0.18 TE; 0.28±0.14 OAS mean±SEM). DISCUSSION AND CONCLUSIONS PRG4 is known to have difficulty sticking to hydrophilic surfaces, such as Av2 conventional hydrogel lenses. Adding silicone to a lens makes it more hydrophobic, allowing PRG4 to better adhere to it [6]. PRG4 had no apparent effect in ATS, possibly due to PRG4 getting bound up in the hydrophobic lipids in ATS before adhering to the lens. Future experiments may examine soaking a contact lens in PRG4 first, before testing in ATS to prevent this, or testing a used contact lens.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».