Machine learning-based identification and validation of immune-related biomarkers for early diagnosis and targeted therapy in diabetic retinopathy.

The early diagnosis of diabetic retinopathy (DR) is challenging, highlighting the urgent need to identify new biomarkers. Immune responses play a crucial role in DR, yet there are currently no reports of machine learning (ML) algorithms being utilized for the development of immune-related molecular markers in DR. Based on the datasets GSE102485 and GSE160306, differentially expressed genes (DEGs) were screened using Weighted Gene Co-expression Network Analysis (WGCNA).

Effects of atropine and tropicamide on ocular biological parameters in children: a prospective observational study.

Background: The effectiveness of cycloplegia in delaying the progression of myopia and its application in refractive examination in children have been extensively studied, but there are still few studies on the effects of atropine/tropicamide on ocular biological parameters. Therefore, the purpose of this study was to explore the effects of atropine/tropicamide on children's ocular biological parameters in different age groups and the differences between them.

Methods: This was a prospective observational study in which all school children were examined for dioptres and ocular biological parameters in the outpatient clinic, and 1% atropine or tropicamide was used for treatment.

Changes in ocular biological parameters after cycloplegia based on dioptre, age and sex.

The effects of cycloplegia on ocular biological parameters in children have been extensively studied, but few studies have compared these parameters between different refractive states, ages, and sexes. Therefore, the purpose of this study was to investigate the changes in ocular biometry before and after cycloplegia in different groups based on dioptre, age and sex. We examined a total of 2049 participants in this cross-sectional study.