Effect of ethnicity and other sociodemographic factors on attendance at ophthalmology appointments following referral from a Diabetic Eye Screening Programme: a retrospective cohort study.

Background/aims: To examine the association between sociodemographic characteristics and attendance at Hospital Eye Service (HES) referrals from the Diabetic Eye Screening Programme (DESP), in a large, ethnically diverse urban population.

Methods: Retrospective cohort study (4 January 2016-12 August 2019) of people with diabetic retinopathy (DR) referred from an English DESP to a tertiary referral eye hospital. We conducted a multivariable logistic regression with attendance as the primary outcome, controlling for age, sex, ethnicity, Index of Multiple Deprivation, best eye visual acuity and baseline DR grade.

Targeting necroptosis in MCF-7 breast cancer cells: In Silico insights into 8,12-dimethoxysanguinarine from Eomecon Chionantha through molecular docking, dynamics, DFT, and MEP studies.

Breast cancer remains a significant challenge in oncology, highlighting the need for alternative therapeutic strategies that target necroptosis to overcome resistance to conventional therapies. Recent investigations into natural compounds have identified 8,12-dimethoxysanguinarine (SG-A) from Eomecon chionantha as a potential necroptosis inducer. This study presents the first computational exploration of SG-A interactions with key necroptotic proteins-RIPK1, RIPK3, and MLKL-through molecular docking, molecular dynamics (MD), density functional theory (DFT), and molecular electrostatic potential (MEP) analyses.

Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.

Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with researchers often using ethnicity as a surrogate marker for biological variability. We derived a continuous, measured metric, the retinal pigment score (RPS), that quantifies the degree of pigmentation from a colour fundus photograph of the eye. RPS was validated using two large epidemiological studies with demographic and genetic data (UK Biobank and EPIC-Norfolk Study) and reproduced in a Tanzanian, an Australian, and a Chinese dataset.

Therapeutic potential inhibitor for dipeptidyl peptidase IV in diabetic type 2: in silico approaches.

Diabetes mellitus (DM) is a metabolic disease marked by an excessive rise in blood sugar (glucose) levels caused by a partial or total absence of insulin production, combined with alterations in the metabolism of proteins, lipids, and carbohydrates. The International Diabetes Federation estimates that 425 million individuals globally had diabetes in 2017 which will be 629 million by 2045. Several medications are used to treat DM, but they have limitations and side effects including weight gain, nausea, vomiting, and damage to blood vessels and kidneys.

Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programme.

Aims: Automated retinal image analysis using Artificial Intelligence (AI) can detect diabetic retinopathy as accurately as human graders, but it is not yet licensed in the NHS Diabetic Eye Screening Programme (DESP) in England. This study aims to assess perceptions of People Living with Diabetes (PLD) and Healthcare Practitioners (HCP) towards AI's introduction in DESP.

Methods: Two online surveys were co-developed with PLD and HCP from a diverse DESP in North East London.