OrthologAL: A Shiny application for quality-aware humanization of non-human pre-clinical high-dimensional gene expression data.

Single-cell and spatial transcriptomics provide unprecedented insight into the inner workings of disease. Pharmacotranscriptomic approaches are powerful tools that leverage gene expression data for drug repurposing and treatment discovery in many diseases. Multiple databases attempt to connect human cellular transcriptional responses to small molecules for use in transcriptome-based drug discovery efforts.

Identifiable Historic and Observable Factors May Predict Progression to Exfoliation Glaucoma in Newly Diagnosed Exfoliation Patients.

Objective: To identify clinical factors associated with conversion to exfoliation glaucoma (XFG) in exfoliation syndrome (XFS) patients who are most at risk of progression to XFG within 3 years for increased surveillance and early preventive interventions.

Design: A retrospective patient cohort study design was employed.

Subjects: A source population of XFS patients ≥ 50 years was identified from electronic medical records in the Utah Population Database.

Big data and electronic health records for glaucoma research.

The digitization of health records through electronic health records (EHRs) has transformed the landscape of ophthalmic research, particularly in the study of glaucoma. EHRs offer a wealth of structured and unstructured data, allowing for comprehensive analyses of patient characteristics, treatment histories, and outcomes. This review comprehensively discusses different EHR data sources, their strengths, limitations, and applicability towards glaucoma research.

Race, Social Determinants of Health, and the Quality of Diabetic Eye Care.

Importance: Besides race, little is known about how other social determinants of health (SDOH) affect quality of diabetic eye care.

Objective: To evaluate the association between multiple SDOH and monitoring for diabetic retinopathy (DR) in accordance with clinical practice guidelines (CPGs).

Design, Setting, And Participants: This cohort study was conducted in 11 US medical centers and included adult patients (18-75 years old) with diabetes.

Comparison of Diagnosis Codes to Clinical Notes in Classifying Patients with Diabetic Retinopathy.

Purpose: Electronic health records (EHRs) contain a vast amount of clinical data. Improved automated classification approaches have the potential to accurately and efficiently identify patient cohorts for research. We evaluated if a rule-based natural language processing (NLP) algorithm using clinical notes performed better for classifying proliferative diabetic retinopathy (PDR) and nonproliferative diabetic retinopathy (NPDR) severity compared with International Classification of Diseases, ninth edition (ICD-9) or 10th edition (ICD-10) codes.

Demographic and Metabolic Risk Factors Associated with Development of Diabetic Macular Edema among Persons with Diabetes Mellitus.

Purpose: Diabetic macular edema (DME), a leading cause of visual impairment, can occur regardless of diabetic retinopathy (DR) stage. Poor metabolic control is hypothesized to contribute to DME development, although large-scale studies have yet to identify such an association. This study aims to determine whether measurable markers of dysmetabolism are associated with DME development in persons with diabetes.

Gap Analysis of Glaucoma Examination Concept Representations within Standard Systemized Nomenclature of Medicine - Clinical Terms.

Objective/purpose: Standardization of eye care data is important for clinical interoperability and research. We aimed to address gaps in the representations of glaucoma examination concepts within Systemized Nomenclature of Medicine - Clinical Terms (SNOMED-CT), the preferred terminology of the American Academy of Ophthalmology.

Design: Study of data elements.

Incidence of Acute Cystoid Macular Edema after Starting a Prostaglandin Analog Compared with Other Classes of Glaucoma Medications.

Purpose: There is a longstanding belief that prostaglandin analogs (PGAs) may predispose patients with glaucoma to develop acute cystoid macular edema (CME). However, there is little solid evidence supporting this notion. The purpose of this study is to compare CME incidence rates among patients initiating treatment with different glaucoma medication classes.

Assessment of Social Vulnerabilities of Care and Prognosis in Adult Ocular Melanomas in the US.

Background: Prior works have studied the impact of social determinants on various cancers but there is limited analysis on eye-orbit cancers. Current literature tends to focus on socioeconomic status and race, with sparse analysis of interdisciplinary contributions. We examined social determinants as measured by the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI), quantifying eye and orbit melanoma disparities across the United States.

Enhancing CAR Macrophage Efferocytosis Via Surface Engineered Lipid Nanoparticles Targeting LXR Signaling.

The removal of dying cells, or efferocytosis, is an indispensable part of resolving inflammation. However, the inflammatory microenvironment of the atherosclerotic plaque frequently affects the biology of both apoptotic cells and resident phagocytes, rendering efferocytosis dysfunctional. To overcome this problem, a chimeric antigen receptor (CAR) macrophage that can target and engulf phagocytosis-resistant apoptotic cells expressing CD47 is developed.

Prediction Models for Glaucoma in a Multicenter Electronic Health Records Consortium: The Sight Outcomes Research Collaborative.

Purpose: Advances in artificial intelligence have enabled the development of predictive models for glaucoma. However, most work is single-center and uncertainty exists regarding the generalizability of such models. The purpose of this study was to build and evaluate machine learning (ML) approaches to predict glaucoma progression requiring surgery using data from a large multicenter consortium of electronic health records (EHR).

Using Natural Language Processing to Identify Different Lens Pathology in Electronic Health Records.

Purpose: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may be used. We assessed whether natural language processing (NLP), as an alternative approach, could more accurately identify lens pathology.

Reliability of Intraocular Pressure Measurements in a Low-Contact Drive-Through Setting.

Prcis: Drive-through intraocular pressure (IOP) measurement using iCare tonometry is a promising method of low-contact, high-throughput IOP monitoring. However, owing to its vulnerability to variable measurement technique and local air currents, the iCare may overestimate IOPs.

Purpose: During the COVID-19 pandemic, a drive-through IOP measurement protocol using the iCare tonometer was established to facilitate low-contact monitoring of select glaucoma patients.

Robotic-Assisted Repair of a Ureterosciatic Hernia with Combined Ureteral Stenting.

Pelvic floor hernias represent a rare type of hernia and a rare etiology of pelvic symptoms. The rarest type of pelvic floor hernias are sciatic hernias, which present with a variety of symptoms depending on the hernia contents and location. Many different treatment approaches are described in the literature.

Nanotechnology Approaches for Prevention and Treatment of Chemotherapy-Induced Neurotoxicity, Neuropathy, and Cardiomyopathy in Breast and Ovarian Cancer Survivors.

Nanotechnology has emerged as a promising approach for the targeted delivery of therapeutic agents while improving their efficacy and safety. As a result, nanomaterial development for the selective targeting of cancers, with the possibility of treating off-target, detrimental sequelae caused by chemotherapy, is an important area of research. Breast and ovarian cancer are among the most common cancer types in women, and chemotherapy is an essential treatment modality for these diseases.

MAEPI and CIR: New Metrics for Robust Evaluation of the Prediction Performance of AI-Based IOL Formulas.

Purpose: To develop a class of new metrics for evaluating the performance of intraocular lens power calculation formulas robust to issues that can arise with AI-based methods.

Methods: The dataset consists of surgical information and biometry measurements of 6893 eyes of 5016 cataract patients who received Alcon SN60WF lenses at University of Michigan's Kellogg Eye Center. We designed two types of new metrics: the MAEPI (Mean Absolute Error in Prediction of Intraocular Lens [IOL]) and the CIR (Correct IOL Rate) and compared the new metrics with traditional metrics including the mean absolute error (MAE), median absolute error, and standard deviation.

Systematic User-centered Design of a Prototype Clinical Decision Support System for Glaucoma.

Purpose: To rigorously develop a prototype clinical decision support (CDS) system to help clinicians determine the appropriate timing for follow-up visual field testing for patients with glaucoma and to identify themes regarding the context of use for glaucoma CDS systems, design requirements, and design solutions to meet these requirements.

Design: Semistructured qualitative interviews and iterative design cycles.

Participants: Clinicians who care for patients with glaucoma, purposefully sampled to ensure a representation of a range of clinical specialties (glaucoma specialist, general ophthalmologist, optometrist) and years in clinical practice.

Environmental and health risks of perovskite solar modules: Case for better test standards and risk mitigation solutions.

Perovskite solar cells (PSCs) promise high efficiencies and low manufacturing costs. Most formulations, however, contain lead, which raises health and environmental concerns. In this review, we use a risk assessment approach to identify and evaluate the technology risks to the environment and human health.