Effectiveness of various atropine concentrations in myopia control for Asian children: a network meta-analysis.

Objectives: To assess the effectiveness of various atropine concentrations in managing myopia among children in East, South, and Southeast Asia, and to determine the most effective concentration.

Methods: A systematic literature review was conducted using PubMed, Web of Science, Cochrane Library, and EMBASE. The search was limited to articles published up to 1 June 2024, and included studies in Chinese or English.

Development and research status of intelligent ophthalmology in China.

This paper analyzes the current status, technological developments, academic exchange platforms, and future challenges and solutions in the field of intelligent ophthalmology (IO) in China. In terms of technology, significant progress has been made in various areas, including diabetic retinopathy, fundus image analysis, quality assessment of medical artificial intelligence products, clinical research methods, technical evaluation, and industry standards. Researchers continually enhance the safety and standardization of IO technology by formulating a series of clinical application guidelines and standards.

Artificial intelligence applications in ophthalmic optical coherence tomography: a 12-year bibliometric analysis.

Aim: To explore the current application and research frontiers of global ophthalmic optical coherence tomography (OCT) imaging artificial intelligence (AI) research.

Methods: The citation data were downloaded from the Web of Science Core Collection database (WoSCC) to evaluate the articles in application of AI in ophthalmic OCT published from January 1, 2012 to December 31, 2023. This information was analyzed using CiteSpace 6.

Mendelian randomization reveals that abnormal lipid metabolism mediates the causal relationship between body mass index and keratoconus.

Previous studies suggest that a high body mass index (BMI) may be a risk factor for keratoconus (KC), but the causal relationship remains unclear. This study used Mendelian randomization (MR) to investigate this connection and explore the mediating role of circulating serum metabolites and inflammatory factors in this association. Two-sample MR analysis was conducted to assess the relationship between BMI and KC.

Total outward leakage of face-worn products used by the general public for source control.

Background: During Coronavirus disease 2019 pandemic, the general public used any face-worn products they could get to overcome the shortage of N95 respirators and surgical masks. These products, often not meeting any standards, raised concerns about their effectiveness in reducing the spread of respiratory viruses.

Methods: This study quantified total outward leakage (TOL) of units from 9 face-worn product categories used by members of the general public.

Epidemiological characteristics of myopia among school-age children before, during, and after the COVID-19 pandemic: a cohort study in Shenzhen, China.

Objectives: To evaluate the epidemiological characteristics of myopia among school-aged children before, during, and after the coronavirus disease (COVID-19) pandemic.

Methods: A total of 848,697 students aged 6-15 years from 786 primary and secondary schools in Shenzhen, China, were randomly selected as research subjects. We conducted annual myopia screenings from 2019 to 2022.

Hierarchical structures and magnetism of Co clusters: a perspective from integration of deep learning and a hybrid differential evolution algorithm.

Theoretically determining the lowest-energy structure of a cluster has been a persistent challenge due to the inherent difficulty in accurate description of its potential energy surface (PES) and the exponentially increasing number of local minima on the PES with the cluster size. In this work, density-functional theory (DFT) calculations of Co clusters were performed to construct a dataset for training deep neural networks to deduce a deep potential (DP) model with near-DFT accuracy while significantly reducing computational consumption comparable to classic empirical potentials. Leveraging the DP model, a high-efficiency hybrid differential evolution (HDE) algorithm was employed to search for the lowest-energy structures of Co ( = 11-50) clusters.

Vessel-promoted OCT to OCTA image translation by heuristic contextual constraints.

Optical Coherence Tomography Angiography (OCTA) is a crucial tool in the clinical screening of retinal diseases, allowing for accurate 3D imaging of blood vessels through non-invasive scanning. However, the hardware-based approach for acquiring OCTA images presents challenges due to the need for specialized sensors and expensive devices. In this paper, we introduce a novel method called TransPro, which can translate the readily available 3D Optical Coherence Tomography (OCT) images into 3D OCTA images without requiring any additional hardware modifications.

Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters.

In medical image segmentation, it is often necessary to collect opinions from multiple experts to make the final decision. This clinical routine helps to mitigate individual bias. However, when data is annotated by multiple experts, standard deep learning models are often not applicable.

NCME-Net: Nuclear cataract mask encoder network for intelligent grading using self-supervised learning from anterior segment photographs.

Cataracts are a leading cause of blindness worldwide, making accurate diagnosis and effective surgical planning critical. However, grading the severity of the lens nucleus is challenging because deep learning (DL) models pretrained using ImageNet perform poorly when applied directly to medical data due to the limited availability of labeled medical images and high interclass similarity. Self-supervised pretraining offers a solution by circumventing the need for cost-intensive data annotations and bridging domain disparities.

Exploring the causal relationship between body mass index and keratoconus: a Mendelian randomization study.

Background: Despite reports suggesting a link between obesity and keratoconus, the causal relationship is not fully understood.

Methods: We used genome-wide association study (GWAS) data from public databases for a two-sample Mendelian randomization analysis to investigate the causal link between body mass index (BMI) and keratoconus. The primary method was inverse variance weighted (IVW), complemented by different analytical techniques and sensitivity analyses to ensure result robustness.

Diabetic retinopathy identification based on multi-source-free domain adaptation.

Aim: To address the challenges of data labeling difficulties, data privacy, and necessary large amount of labeled data for deep learning methods in diabetic retinopathy (DR) identification, the aim of this study is to develop a source-free domain adaptation (SFDA) method for efficient and effective DR identification from unlabeled data.

Methods: A multi-SFDA method was proposed for DR identification. This method integrates multiple source models, which are trained from the same source domain, to generate synthetic pseudo labels for the unlabeled target domain.

Unveiling the Evolution of Virtual Reality in Medicine: A Bibliometric Analysis of Research Hotspots and Trends over the Past 12 Years.

Background: Virtual reality (VR), widely used in the medical field, may affect future medical training and treatment. Therefore, this study examined VR's potential uses and research directions in medicine.

Methods: Citation data were downloaded from the Web of Science Core Collection database (WoSCC) to evaluate VR in medicine in articles published between 1 January 2012 and 31 December 2023.

Effect of composition and architecture on the thermodynamic behavior of AuCu nanoparticles.

The chemical and physical properties of nanomaterials ultimately rely on their crystal structures, chemical compositions and distributions. In this paper, a series of AuCu bimetallic nanoparticles with well-defined architectures and variable compositions has been addressed to explore their thermal stability and thermally driven behavior by molecular dynamics simulations. By combination of energy and Lindemann criteria, the solid-liquid transition and its critical temperature were accurately identified.

Inhibition of differentiation of monocyte-derived macrophages toward an M2-Like phenotype May Be a neglected mechanism of β-AR receptor blocker therapy for atherosclerosis.

The clinical efficacy of adrenergic β-receptor (β-AR) blockers in significantly stabilizing atherosclerotic plaques has been extensively supported by evidence-based medical research; however, the underlying mechanism remains unclear. Recent findings have highlighted the impact of lipid-induced aberrant polarization of macrophages during normal inflammatory-repair and regenerative processes on atherosclerosis formation and progression. In this review, we explore the relationship between macrophage polarization and atherosclerosis, as well as the influence of β-AR blockers on macrophage polarization.

The optimal atropine concentration for myopia control in Chinese children: a systematic review and network Meta-analysis.

Aim: To figure out whether various atropine dosages may slow the progression of myopia in Chinese kids and teenagers and to determine the optimal atropine concentration for effectively slowing the progression of myopia.

Methods: A systematic search was conducted across the Cochrane Library, PubMed, Web of Science, EMBASE, CNKI, CBM, VIP, and Wanfang database, encompassing literature on slowing progression of myopia with varying atropine concentrations from database inception to January 17, 2024. Data extraction and quality assessment were performed, and a network Meta-analysis was executed using Stata version 14.

Analysis of research hotspots and trends in pediatric ophthalmopathy based on 10 years of WoSCC literature.

Background: Ophthalmopathy occurring in childhood can easily lead to irreversible visual impairment, and therefore a great deal of clinical and fundamental researches have been conducted in pediatric ophthalmopathy. However, a few studies have been performed to analyze such large amounts of research using bibliometric methods. This study intended to apply bibliometric methods to analyze the research hotspots and trends in pediatric ophthalmopathy, providing a basis for clinical practice and scientific research to improve children's eye health.

Application and visualization study of an intelligence-assisted classification model for common eye diseases using B-mode ultrasound images.

Aim: Conventional approaches to diagnosing common eye diseases using B-mode ultrasonography are labor-intensive and time-consuming, must requiring expert intervention for accuracy. This study aims to address these challenges by proposing an intelligence-assisted analysis five-classification model for diagnosing common eye diseases using B-mode ultrasound images.

Methods: This research utilizes 2064 B-mode ultrasound images of the eye to train a novel model integrating artificial intelligence technology.

Bibliometric analysis of hotspots and trends of global myopia research.

Aim: To gain insights into the global research hotspots and trends of myopia.

Methods: Articles were downloaded from January 1, 2013 to December 31, 2022 from the Science Core Database website and were mainly statistically analyzed by bibliometrics software.

Results: A total of 444 institutions in 87 countries published 4124 articles.