Screening For Disease Research Articles

Screening for chronic kidney disease among health workers in a tertiary hospital in North Central Nigeria

Screening for chronic kidney disease among health workers in a tertiary hospital in North Central Nigeria

Deep learning radiomics based on ultrasound images for the assisted diagnosis of chronic kidney disease.

This study aimed to explore the value of ultrasound (US) images in chronic kidney disease (CKD) screening by constructing a CKD screening model based on grey-scale US images. According to the CKD diagnostic criteria, 1049 patients from Tongde Hospital of Zhejiang Province were retrospectively enrolled in the study. A total of 4365 renal US images were collected from these patients. Convolutional neural networks were used for feature extractions and a screening model was constructed by fusing ResNet34 and texture features to identify CKD and its stage. A comparative analysis was performed to compare the diagnosis results of the model with physicians. When diagnosing CKD or non-CKD, the receiver operating characteristic curve (AUC) of our model was 0.918 and that of the senior physician group was 0.869 (p < .05). For the diagnosis of CKD stage, the AUC of our model for CKD G1-G3 was 0.781, 0.880, and 0.905, respectively, while the AUC of the senior physician group for CKD G1-G3 was 0.506, 0.586, and 0.796, respectively; all differences were statistically significant (p < .05). The diagnostic efficiency of our model for CKD G4 and G5 reached the level of the senior physicians group. Specifically, the AUC of our model for CKD G4-G5 was 0.867 and 0.931, respectively, while the AUC of the senior physician group for CKD G4-G5 was 0.838 and 0.963, respectively (all p > .05). Our deep learning radiomics model is more effective than senior physicians in the diagnosis of early CKD.

Metadata-enhanced contrastive learning from retinal optical coherence tomography images

Deep learning has potential to automate screening, monitoring and grading of disease in medical images. Pretraining with contrastive learning enables models to extract robust and generalisable features from natural image datasets, facilitating label-efficient downstream image analysis. However, the direct application of conventional contrastive methods to medical datasets introduces two domain-specific issues. Firstly, several image transformations which have been shown to be crucial for effective contrastive learning do not translate from the natural image to the medical image domain. Secondly, the assumption made by conventional methods, that any two images are dissimilar, is systematically misleading in medical datasets depicting the same anatomy and disease. This is exacerbated in longitudinal image datasets that repeatedly image the same patient cohort to monitor their disease progression over time. In this paper we tackle these issues by extending conventional contrastive frameworks with a novel metadata-enhanced strategy. Our approach employs widely available patient metadata to approximate the true set of inter-image contrastive relationships. To this end we employ records for patient identity, eye position (i.e. left or right) and time series information. In experiments using two large longitudinal datasets containing 170,427 retinal optical coherence tomography (OCT) images of 7912 patients with age-related macular degeneration (AMD), we evaluate the utility of using metadata to incorporate the temporal dynamics of disease progression into pretraining. Our metadata-enhanced approach outperforms both standard contrastive methods and a retinal image foundation model in five out of six image-level downstream tasks related to AMD. We find benefits in both a low-data and high-data regime across tasks ranging from AMD stage and type classification to prediction of visual acuity. Due to its modularity, our method can be quickly and cost-effectively tested to establish the potential benefits of including available metadata in contrastive pretraining.

Strategies for scaling up pre-ART advanced HIV disease screening at a secondary referral hospital—Malawi: a qualitative study

BackgroundImplementation of the World Health Organization (WHO) recommended Advanced HIV Disease screening package, remains poor in most settings with limited resources. More than 50% of newly diagnosed-HIV clients are missed on screening as a result of implementation barriers. It is important to mitigate the existing barriers and leverage enablers’ inorder to maximize uptake of the advanced HIV disease screening. This study aimed to identify strategies for scaling up implementation of advanced HIV disease screening among newly HIV-diagnosed clients in pre-ART phase using a Consolidated Framework for Implementation Research-Expert Recommendation for Implementing Change (CFIR-ERIC) guiding tool.MethodsA qualitative study was conducted at Rumphi district hospital in Malawi (August – September, 2023). Two sessions of Focus group discussions (FDGs) involving key stakeholders were facilitated to identify specific strategies following the initial study on exploration of barriers and facilitators of advanced HIV disease screening package. Participants comprised healthcare providers, purposively selected from key hospital departments. A deductive approach was used to analyze FDG transcripts where emerging themes were mapped with ERIC list of strategies. CFIR-ERIC Matching tool version 1.0, was used to generate an output of the most to least expert-endorsed Level 1 and Level 2 strategies.FindingsAbout 25 key healthcare workers participated in FDGs. Overall, 6 Level 1 strategies (≥ 50% expert endorsement score) and 4 Level 2 strategies (≥ 20%, ≤ 49% expert endorsement score) were identified, targeting barriers associated with availability of resources, intervention complexity, access to knowledge and information, communication; and implementation leads. Most of the reported strategies were cross-cutting and aimed at enhancing clinical knowledge of the intervention (distributing training materials, educational meetings), developing stakeholders’ interrelations (network weaving) as well as improving clinical workflow (environmental restructuring). Use of evaluative and iterative strategies such as monthly data collection for evaluation were also recommended as part of continuous improvement while an AHD coordinator was recommended to be formally appointed inorder to spearhead coordination of AHD screening services.ConclusionThrough the involvement of key stakeholders and the use of CFIR-ERIC matching tool, this study has identified cross-cutting strategies that if well implemented, can help to mitigate contextual barriers and leverage enablers for an improved delivery of AHD screening package.

Chagas Disease: Epidemiology, Diagnosis, and Treatment.

This review seeks to describe the updates in the literature - particularly with regards to the epidemiology and diagnosis of Chagas disease. Additionally, this paper describes updates to the antiparasitic treatment for Chagas disease. With regards to changing epidemiology, autochthonous cases are being found within the USA in addition to Latin America. Additionally, there appears to be more intermixing of discrete typing units-meaning, they are not confined to specific geographic regions. Screening for Chagas disease is recommended in persons who lived in areas with endemic Chagas, persons wtih family member diagnosed with Chagas Disease, persons who have lived in homes of natural material in Latin America, and persons with history of kissing bug bites. Treatment for the parasitic infection remains limited to benznidazole and nifurtimox, and the role of these treatments in Chagas cardiomyopathy has not yet been definitively defined. Finally, indications for and management of heart transplant in the setting of Chagas disease are discussed. Use of antiparasitics during chronic chagas disease should be further explored. Additionally, future research identifying other markers of infection would be valuable to defining cure from infection.

Automated Fibrosis-4 Index: Simplifying Non-Alcoholic Fatty Liver Disease for Diabetologists.

Background and Objectives: Patients with type 2 diabetes (T2D) have a high prevalence of non-alcoholic fatty liver disease (NAFLD) (55%) and are at increased risk for developing non-alcoholic steatohepatitis, a severe form of NAFLD. Early detection of advanced fibrosis in patients with T2D and NAFLD is crucial and can prevent progression to chronic liver disease, cirrhosis, and hepatocellular carcinoma. However, screening for liver disease and risk-stratification pathways are not established in patients with T2D. We evaluated the efficacy of using the automated fibrosis-4 (FIB-4) index in routine clinical settings to identify patients requiring further specialist evaluation. Materials and Methods: In this prospective cohort study, individuals diagnosed with T2D were recruited from diabetes clinics at a tertiary university hospital. Demographic, clinical, and laboratory data were comprehensively collected. The FIB-4 index was automatically calculated and integrated into the hospital's electronic medical records (EMRs), which were then stratified by age. Patients with advanced fibrosis (FIB-4 index ≥ 1.3) were referred to a specialist. Student's t-test or the Mann-Whitney U test was used to analyze variables associated with advanced fibrosis. Logistic regression was used to identify predictors of advanced fibrosis. Results: Among the 318 patients with T2D, 9.7% had advanced fibrosis. The majority were females (54.7%) and Saudi nationals (89.6%). Several factors, including age, platelet count, total bilirubin, serum albumin, total cholesterol, low-density lipoprotein, transaminases, and gamma-glutamyl transferase (GGT), showed significant associations with advanced fibrosis (all p < 0.05). Older age, elevated total bilirubin and GGT levels, and prolonged international normalized ratio emerged as independent predictors of advanced fibrosis. Conclusions: Integrating the FIB-4 index into the EMR during the routine care of patients with T2D proved to be a valuable tool in effectively identifying individuals at risk of advanced fibrosis. Our findings emphasize the need for further research to refine screening strategies in this high-risk population.

Novel flexible magnetoelastic biosensor based on PDMS/FeSiB/QD composite film for the detection of African swine fever virus P72 protein.

African swine fever (ASF) is a highly contagious and severe hemorrhagic disease caused by the African swine fever virus (ASFV). The continuous spread of ASFV affects the safety of the global meat supply; therefore, the establishment of sensitive and specific detection methods for ASFV has become an important hot spot in food safety. Herein, we developed a flexible magnetoelastic (ME) biosensor based on PDMS/FeSiB/QDs composite films for the detection of ASFV P72 protein. Based on the high luminescence performance of CsPbBr3 quantum dots and the excellent magnetoelastic effect of FeSiB, flexible ME biosensors convert stress signals generated by antibody-antigen-specific binding into optical and electromagnetic signals. The nanostructures covalently linked by quantum dots and PDMS provide biomodification sites for ASFV P72 antibodies, simplifying the functionalization modification process compared to the case of conventional biosensors. The deformation of the PDMS film is amplified, and the conversion of surface stress signals to electrical signals is enhanced by exposing the biosensor to a uniform magnetic field. The experimental results proved that the flexible ME biosensor has a wide linear range of 10 ng mL-1-100 μg mL-1, and the detection limit is as low as 0.079 ng mL-1. Moreover, the flexible ME biosensor also shows good stability, sensitivity and specificity, confirming the potential for early disease screening.

Multimorbidity in people living with HIV and cancer in Mexico.

The proportion of older people living with HIV (PLWH) has increased. Non-communicable diseases occur earlier in PLWH than in the general population. The goal of this study was to estimate the prevalence of comorbidities in PLWH and cancer in a tertiary referral center in Mexico City. In this retrospective study, we included PLWH > 40 years with a history of cancer, coming to Instituto Nacional de Cancerologia from 2010 through 2019. All patients needed to be on antiretrovirals for at least six months. Data collected included cancer type, comorbidities, frequency of polypharmacy, FRAX score and 10-year cardiovascular risk. Patients were evaluated for depression with the Beck Inventory Depression-II Scale. Variables associated to multimorbidity (2 or more comorbidities) were evaluated. Of 125 patients, 69% had at least one comorbidity; 32% had ≥ 2. Common comorbidities were dyslipidemia (54%), hypertension (19%), obesity (14%) and Diabetes (12%). In patients ≥ 50 years, 29 (62%) already undergone a densitometry and 9 (31%) had osteoporosis; 56 depression questionnaires were used: 30% had mild-to-severe depression. Being ≥ 50 years was associated with multimorbidity (aOR 2.57 (1.18-5.58), p = 0.017). A high prevalence of multimorbidity and poor screening of bone disease and mental health is reported in patients with PLWH and cancer. A holistic approach to the PLWH in the Infectious Diseases consultation is needed to improve the detection and management of non-communicable diseases, to go beyond viral suppression and towards an improved quality of life.

Multimorbidity in people living with HIV and cancer in Mexico.

The proportion of older people living with HIV (PLWH) has increased. Non-communicable diseases occur earlier in PLWH than in the general population. The goal of this study was to estimate the prevalence of comorbidities in PLWH and cancer in a tertiary referral center in Mexico City. In this retrospective study, we included PLWH > 40 years with a history of cancer, coming to Instituto Nacional de Cancerologia from 2010 through 2019. All patients needed to be on antiretrovirals for at least six months. Data collected included cancer type, comorbidities, frequency of polypharmacy, FRAX score and 10-year cardiovascular risk. Patients were evaluated for depression with the Beck Inventory Depression-II Scale. Variables associated to multimorbidity (2 or more comorbidities) were evaluated. Of 125 patients, 69% had at least one comorbidity; 32% had ≥ 2. Common comorbidities were dyslipidemia (54%), hypertension (19%), obesity (14%) and Diabetes (12%). In patients ≥ 50 years, 29 (62%) already undergone a densitometry and 9 (31%) had osteoporosis; 56 depression questionnaires were used: 30% had mild-to-severe depression. Being ≥ 50 years was associated with multimorbidity (aOR 2.57 (1.18-5.58), p = 0.017). A high prevalence of multimorbidity and poor screening of bone disease and mental health is reported in patients with PLWH and cancer. A holistic approach to the PLWH in the Infectious Diseases consultation is needed to improve the detection and management of non-communicable diseases, to go beyond viral suppression and towards an improved quality of life.

Enhancing the ophthalmic AI assessment with a fundus image quality classifier using local and global attention mechanisms.

The assessment of image quality (IQA) plays a pivotal role in the realm of image-based computer-aided diagnosis techniques, with fundus imaging standing as the primary method for the screening and diagnosis of ophthalmic diseases. Conventional studies on fundus IQA tend to rely on simplistic datasets for evaluation, predominantly focusing on either local or global information, rather than a synthesis of both. Moreover, the interpretability of these studies often lacks compelling evidence. In order to address these issues, this study introduces the Local and Global Attention Aggregated Deep Neural Network (LGAANet), an innovative approach that integrates both local and global information for enhanced analysis. The LGAANet was developed and validated using a Multi-Source Heterogeneous Fundus (MSHF) database, encompassing a diverse collection of images. This dataset includes 802 color fundus photography (CFP) images (302 from portable cameras), and 500 ultrawide-field (UWF) images from 904 patients with diabetic retinopathy (DR) and glaucoma, as well as healthy individuals. The assessment of image quality was meticulously carried out by a trio of ophthalmologists, leveraging the human visual system as a benchmark. Furthermore, the model employs attention mechanisms and saliency maps to bolster its interpretability. In testing with the CFP dataset, LGAANet demonstrated remarkable accuracy in three critical dimensions of image quality (illumination, clarity and contrast based on the characteristics of human visual system, and indicates the potential aspects to improve the image quality), recording scores of 0.947, 0.924, and 0.947, respectively. Similarly, when applied to the UWF dataset, the model achieved accuracies of 0.889, 0.913, and 0.923, respectively. These results underscore the efficacy of LGAANet in distinguishing between varying degrees of image quality with high precision. To our knowledge, LGAANet represents the inaugural algorithm trained on an MSHF dataset specifically for fundus IQA, marking a significant milestone in the advancement of computer-aided diagnosis in ophthalmology. This research significantly contributes to the field, offering a novel methodology for the assessment and interpretation of fundus images in the detection and diagnosis of ocular diseases.

Improving Clinician Awareness of and Screening for Chagas Disease with an Educational Intervention.

Chagas disease is an underrecognized, chronic, and potentially life-threatening disease caused by the parasite Trypanosoma cruzi. We aimed to improve awareness and screening for Chagas disease among patients from endemic areas using a large safety-net academic hospital system in the United States. We developed an educational intervention consisting of a case-based didactic session presented to physicians, trainees, and other healthcare providers at conferences across different departments. Performance on a knowledge assessment administered before and after the presentation was analyzed with paired Student's t-test for within-subject difference testing. Institutional testing rates for T. cruzi were evaluated for an equal time period (29 months) before and after the start of the intervention. Testing rates were compared by a Welch's unequal variances t-test and by interrupted time series based on multivariate linear regression. Eleven educational sessions were held over the intervention period, and 103 participants completed the pre- and post-presentation surveys. The mean survey scores were 59.2% before the presentation and 96.6% after presentation (P <0.001). Trypanosoma cruzi testing during the postintervention period was significantly higher than testing during the pre-intervention period (171 patients pre-intervention versus 378 patients postintervention [P = 0.015]). Notable increases in testing from the pre-intervention to postintervention periods occurred among midwives (1-68 patients tested) and trainees (57-133 patients tested). Overall, 56/537 (10.4%) nonduplicate T. cruzi commercial screening tests were positive. Testing increased over time, both at an institutional level and within targeted departments. In addition to the educational program, other factors likely influenced expanded testing.

Use of the Screening for Occult Renal Disease (SCORED) Questionnaire to Screen Diabetic Nephropathy in Asymptomatic Patients: A Cross-Sectional Study.

The 2007 Screening for Occult Renal Disease (SCORED)questionnaire accesses risk factors for chronic kidney disease (CKD) and makes it possible to screen high-risk patients, being adapted and validated for the Brazilian culture in 2012. The present study evaluated the questionnaire's ability to predict the occurrence of CKD in asymptomatic patients, as well as identify a high risk for developing the disease. This was an analytical observational study with a cross-sectional design carried out in two stages: answering the SCORED and performing fasting blood glucose and creatinine tests. The participants were patients at the Hospital das Clínicas of the Federal University of Minas Gerais (HC-UFMG) with scheduled creatinine and fasting blood glucose tests, respecting the inclusion and exclusion criteria defined for the study. SCORED was applied with questions covering gender, age, proteinuria, and diabetes, being classified as high or low risk for CKD. The data collected were height, weight, age, sex, diagnosis of diabetes mellitus, and fasting blood glucose. The sample space was 212 individuals, the majority of whom were female (N=130, 61.3%), with a median of 58 years of age. The prevalence of CKD was 15.6% (N=33) with a sensitivity of 90.9%, a specificity of 30.2%, a positive predictive value of 19.4%, a negative predictive value of 94.7%, and a diagnostic accuracy of 39.7%. We concluded that the SCORED questionnaire can be a useful tool for screening CKD in asymptomatic patients and also that there is a relationship was detected between glycemic changes and an increased risk for CKD.

Application of principles learned in a prevention-focused pediatric dental residency curriculum to professional practice.

This study examined whether pediatric dentists who participated in a pediatric dental residency program focusing on disease prevention and management training and screening for social determinants of health (SDOH) were applying these principles to their professional practice upon graduation. Using a cross-sectional study design, a one-time-only online survey was disseminated to 75 pediatric dentists who graduated from the University of California, Los Angeles's training program between 2012 and 2022. The 21-item survey included questions on demographics, patient population characteristics, and application of preventive dentistry and SDOH to their professional practice. Descriptive statistics and bivariate analyses were used to assess survey items. The survey response rate was 64%. Over two-thirds (67%) of alumni reported accepting Medicaid, 34% saw patients in a medically underserved area and all reported seeing children with special needs in their practice. Strategies used to address SDOH in their practice included providing anticipatory guidance (98%) and educating families on oral disease prevention and screening for SDOH (96%). Alumni accepting patients with Medicaid/public health insurance were more likely to address SDOH in their practice, such as assisting patients with filling out Medicaid paperwork (p<0.05), conducting outreach to underserved communities (p<0.05), and using interpreters in their practice (p<0.01) in comparison with alumni not accepting patients with Medicaid/public health insurance. This study demonstrated that a pediatric dental residency program may be successful in training residents to educate children, families, and special needs patients on disease prevention and management in an ethical and culturally sensitive manner and screen for SDOH during patient visits.

CffDNA screening for Niemann-pick disease, type C1: a case series.

Cell-free fetal DNA (cffDNA) screening is a valuable tool in clinical practice for detecting chromosomal abnormalities and autosomal dominant (AD) conditions. This study introduces a novel proof-of-concept assay designed for autosomal recessive (AR) cffDNA screening, focusing on cases involving the NPC1 gene. We aim to illustrate the significant benefits of AR cffDNA screening in managing high-risk pregnancies, specifically where biallelic pathogenic variants in NPC1 cause Niemann-Pick disease, type C1 (NPC), a disorder marked by progressive neurodegeneration. Three participants for this study were recruited and gave consent to a hospital in Saudi Arabia. These participants were either carriers of NPC or had a first- or second-degree relative affected by the disorder. No specific criteria were set for the age of the participants. All were between 15 and 18 weeks of gestation. Using amplicon-based next-generation sequencing (NGS), we analyzed the zygosity and variants in cffDNA extracted from maternal peripheral blood. After amplicon NGS, analysis was completed by a custom data analysis pipeline that included in-house-built data processing scripts and commonly used software packages. Importantly, the results were not disclosed to the patients. Our findings showed that in all three cases, AR cffDNA screening results were consistent with standard invasive diagnostic testing. This screening method offers several advantages: it provides critical information to families earlier in the pregnancy compared to invasive diagnostic tests, and it helps to alleviate parental anxiety. Moreover, this non-invasive method can determine pregnancy status in the first trimester for known familial variants. Future research may extend this approach to screen for known disease-causing variants in common AR conditions.

Research Progress in the Construction and Application of In Vitro Vascular Models

The vascular system maintains cellular homeostasis by transporting oxygen, nutrients, and metabolic waste products. The vascular system is involved in a variety of fundamental physiological phenomena and is closely associated with human vascular diseases. Additionally, the stability of drugs in the vasculature affects their efficacy. Therefore, researchers have used vascular models to study vascular diseases, assess drug stability, and screen drugs. However, there are many shortcomings in the animal models and in vitro two-dimensional vascular models that have been extensively developed. In this paper, we specifically review the construction methods of in vitro vascular models and classify the specific methods into photolithography, soft lithography, self-assembly, template, 3D bioprinting, and laser degradation/cavitation. The first two are microfluidics-based methods and the last three are non-microfluidics-based methods. The vascular model construction methods reviewed in this paper overcome the shortcomings of traditional models—which cannot accurately reproduce the human vascular microenvironment—and can assist in the construction of in vitro 3D vascular models and tissue engineering vascularization. These models can be reused by perfusion devices, and the cells within the channels reside on biocompatible materials that are used to simulate the microenvironment and 3D cellular organization of the vasculature in vivo. In addition, these models are reproducible in shape and length, allowing experiments to be repeated, which is difficult to do with natural vessels. In vitro vascular models are widely used in research and drug screening for diseases associated with endothelial dysfunction, cancer, and other vascular abnormalities.

Abstract Mo105: End Systolic Pressure and Ejection Timing Correlate with Impaired Relaxation

Impaired relaxation is a common feature in most cases of diastolic dysfunction, including heart failure with preserved ejection fraction. Isovolumetric relaxation is typically characterized by τ, an exponential time constant, but may be broken into relaxation and stiffness-like parameters (µ and Ek). Recent in vitro work suggests that strain during late systole (protodiastolic period) modifies relaxation. We hypothesize that late systolic pressure and time indexes correlate with myocardial relaxation. Thirty-four (34) simultaneous aortic and left ventricular micromanometric (Millar) pressure traces were obtained from a comprehensive database of clinical cardiac catheterization patients. These patients underwent coronary artery disease screening and presented but did not have arterial blockages. Pressure and time parameters were calculated over a five-minute interval. Relaxation rate (1/τ), and stiffness (Ek) correlated to end systolic parameters in an orthogonal pattern to relaxation (µ). 1/τ showed strong correlations with time from peak pressure to aortic valve divided by ejection time (t54/t52, r = .675, p &lt; .01) and moderate correlation to the pressure decline after peak pressure to aortic valve pressure divided by the pulse pressure (P45/P42, r = .577, p &lt; .01). In parallel Ek showed moderate correlation with t54/t52 (r = .592, p &lt; .01), and a moderate correlation with P45/P42 (r = .470, p &lt; .01), the pressure at aortic valve closure (r = -.420, p &lt; .05), and aortic augmentation index (AIx, r = -.360, p &lt; .05). Finally, µ presented a moderate correlation to P45/P42 (r = .501, p &lt; .05), the pressure at aortic valve closure (r = .404, p &lt; .05), and AIx (r = -.357, p &lt; .05). As predicted, ventricular relaxation in patients correlates with late systolic hemodynamics. Parameters or combinations of parameters may predict relaxation rates or correlate to in vivo late systolic strain. Prospective studies evaluating end systolic strain and relaxation merit consideration. Overall, these observations are consistent with in vitro studies that suggest that impaired cessation of contraction is a regulator of relaxation.

Screening Strategies and Methodologies.

While glaucoma is a leading cause of irreversible vision loss, it presents technical challenges in the design and implementation of screening. New technologies such as PRS and AI offer potential improvements in our ability to identify people at high risk of sight loss from glaucoma and may improve the viability of screening for this important disease. To review the current evidence and concepts around screening for glaucoma. A group of glaucoma-focused clinician scientists drew on knowledge and experience around glaucoma, its etiology, and the options for screening. Glaucoma is a chronic progressive optic neuropathy affecting around 76 million individuals worldwide and is the leading cause of irreversible blindness globally. Early stages of the disease are asymptomatic meaning a substantial proportion of cases remain undiagnosed. Early detection and timely intervention reduce the risk of glaucoma-related visual morbidity. However, imperfect tests and a relatively low prevalence currently limit the viability of population-based screening approaches. The diagnostic yield of opportunistic screening strategies, relying on the identification of disease during unrelated health care encounters, such as cataract clinics and diabetic retinopathy screening programs, focusing on older people and/or those with a family history, are hindered by a large number of false-positive and false-negative results. Polygenic risk scores (PRS) offer personalized risk assessment for adult-onset glaucoma. In addition, artificial intelligence (AI) algorithms have shown impressive performance, comparable to expert humans, in discriminating between potentially glaucomatous and non-glaucomatous eyes. These emerging technologies may offer a meaningful improvement in diagnostic yield in glaucoma screening. While glaucoma is a leading cause of irreversible vision loss, it presents technical challenges in the design and implementation of screening. New technologies such as PRS and AI offer potential improvements in our ability to identify people at high risk of sight loss from glaucoma and may improve the viability of screening for this important disease.

Oculomics: a window to the health of the body

In 2023 medical tech firm Occuity won a business start-up award from the Institute of Physics for its ground-breaking ophthalmic and disease-screening technologies. Alistair Bounds explores the power of the eye in screening for diseases and introduces the company’s work developing advanced methods to detect chronic diseases.

Prediction of resistance, virulence, and host-by-pathogen interactions using dual-genome prediction models

Key messageIntegrating disease screening data and genomic data for host and pathogen populations into prediction models provides breeders and pathologists with a unified framework to develop disease resistance.Developing disease resistance in crops typically consists of exposing breeding populations to a virulent strain of the pathogen that is causing disease. While including a diverse set of pathogens in the experiments would be desirable for developing broad and durable disease resistance, it is logistically complex and uncommon, and limits our capacity to implement dual (host-by-pathogen)-genome prediction models. Data from an alternative disease screening system that challenges a diverse sweet corn population with a diverse set of pathogen isolates are provided to demonstrate the changes in genetic parameter estimates that result from using genomic data to provide connectivity across sparsely tested experimental treatments. An inflation in genetic variance estimates was observed when among isolate relatedness estimates were included in prediction models, which was moderated when host-by-pathogen interaction effects were incorporated into models. The complete model that included genomic similarity matrices for host, pathogen, and interaction effects indicated that the proportion of phenotypic variation in lesion size that is attributable to host, pathogen, and interaction effects was similar. Estimates of the stability of lesion size predictions for host varieties inoculated with different isolates and the stability of isolates used to inoculate different hosts were also similar. In this pathosystem, genetic parameter estimates indicate that host, pathogen, and host-by-pathogen interaction predictions may be used to identify crop varieties that are resistant to specific virulence mechanisms and to guide the deployment of these sources of resistance into pathogen populations where they will be more effective.

Autoimmune diseases, autoantibody status and silicosis in a cohort of 1238 workers from the artificial stone benchtop industry

ObjectivesAutoimmune disorders are multifactorial but occupational exposures have long been implicated, including respirable crystalline silica (RCS). A modern epidemic of silicosis is emerging internationally, associated with dry processing of engineered...