Disease Risk Assessment Research Articles

Waist-to-hip ratio as a contributor associated with higher atherosclerotic cardiovascular disease risk assessment in patients with diabetes: a cross-sectional study

IntroductionThis study aimed to identify the factors most strongly associated with an increased atherosclerotic cardiovascular disease (ASCVD) risk score in patients with type 2 diabetes (T2D).MethodsThis cross-sectional study included 4698 patients with T2D over an 11-year period (2010–2021). Patients were categorized into four groups based on their 10-year ASCVD risk score (< 5%, 5–7.5%, 7.5–20%, and > 20%). Multinominal regression analysis was used to evaluate the association between various modifiable and non-modifiable risk factors and the ASCVD risk score.ResultsOf the patients, 35.9% had a 10-year ASCVD risk score below 5%, 12.6% had a score between 5% and 7.5%, 30.8% had a score between 7.5% and 20%, and 19.7% had a score above 20%. Higher ASCVD risk scores were significantly associated with elevated waist-to-hip ratio (WHR > 0.93), pulse pressure, uric acid, triglycerides, and decreased glomerular filtration rate (all p-values < 0.05). WHR demonstrated the strongest association with higher ASCVD risk scores (OR: 4.55, 95% CI: 2.94–7.03, p < 0.001) when comparing patients with ASCVD scores > 5% to those with scores < 5%.ConclusionWHR was independently associated with higher ASCVD risk scores in patients with T2D. Incorporating WHR, along with traditional risk factors, could improve ASCVD risk assessments in this population.

Research progress on the application of virtual artificial intelligence in risk assessment and diagnosis of periodontal disease

Periodontal disease is a common and frequently-occurring disease in China. Early detection, diagnosis, and treatment of periodontal disease are of great significance for achieving universal oral health and even systemic health. Artificial intelligence endows machines with the ability to mimic human intelligent behavior, and is commonly used in medical field with both physical and virtual forms. Virtual artificial intelligence empowers traditional experience in the application of periodontal disease risk assessment and diagnosis, with the potential to develop a variety of oral health screening tools. It helps to provide new evidence for the prognosis of periodontal disease, improve the accuracy and efficiency of diagnosis, reduce technical sensitivity and further promote the periodontal treatment transformation from "treatment-oriented" to "prevention-oriented". This paper reviews the current applications and progresses of virtual artificial intelligence in periodontal risk assessment and diagnosis, as well as its limitations, providing ideas for future researches on the application of virtual artificial intelligence in this field.

Biomarker identification and risk assessment of cardiovascular disease based on untargeted metabolomics and machine learning

Cardiovascular disease (CVD) is the leading cause of mortality, disability, and healthcare costs, with a significant impact on the elderly and contributing to premature deaths across various age groups, including those below age 70. Despite decades of transformative discoveries and clinical efforts, the challenges of diagnosis, prevention, and treatment of CVD persist on a massive scale. This study aimed to unravel potential CVD-associated biomarkers and establish a machine learning model for the risk assessment of CVD. Untargeted metabolic assay with ultra-high performance liquid chromatography-tandem mass spectrometry and routine clinical biochemistry test were undertaken on the fasting venous blood specimens from 57 subjects. Four relevant clinical traits and 164 CVD-associated metabolites were identified, especially those related to glycerophospholipid metabolism and biosynthesis of unsaturated fatty acids. The machine learning model achieved from an integrated biomarker panel of palmitic amide, oleic acid, 138-pos (the 138th detected metabolomic feature in positive ion mode), phosphatidylcholine, linoleic acid, age, direct bilirubin, and inorganic phosphate, was able to improve the accuracy of CVD risk assessment up to a high satisfactory value of 0.91. The findings indicate that disorders in the metabolic processes of biological membranes and energy are significantly associated with increased risk of vascular damage in CVD patients. With machine learning methods, the pivotal metabolites and clinical biomarkers offer a promising potential for the efficient risk assessment and diagnosis of CVD.

Backyard flock sampling and artificial intelligence: A dual strategy for early detection of Avian Influenza and Newcastle Disease

Avian Influenza (AI) and Newcastle Disease (ND) are significant avian diseases that pose substantial threats to the commercial poultry industry due to their high contagion rates and potential for severe outcomes. Recent shifts in the epidemiology and ecology of both viruses have led to devastating impacts on wild bird and poultry populations, as well as farms and communities worldwide. These challenges underscore the necessity for One Health approaches to pandemic prevention and preparedness, emphasizing the need for multisectoral collaboration among animal, environmental, and public health sectors. To mitigate future pandemic risks, it is essential to control the transmission of AI and ND viruses among domestic and wild animals as well as humans. This involves addressing the upstream drivers of outbreaks, ensuring rapid response mechanisms, and conducting thorough risk assessments for zoonotic diseases. Effective implementation and maintenance of prevention programs, surveillance, and outbreak responses require strong political commitment and sustainable funding. A robust combination of active and passive surveillance strategies should be applied to monitor and control them. In addition, the integration of modern technologies, such as artificial intelligence and big data analytics, can enhance both active and passive surveillance efforts by improving the accuracy and speed of data collection, analysis, and reporting. The use of backyard flocks as an early warning system for avian diseases represents a proactive approach to understanding and managing the risks associated with AI and ND through targeted surveillance and timely interventions. In response to these challenges, the EpirORNIS Project aimed to leverage these sentinel backyard flocks for early detection of AI and ND, thereby enhancing surveillance and control strategies.

Cardiovascular diseases risk assessment: the Italian Health Examination Survey 2023 - CUORE Project

Abstract Background The reduction of NCDs premature mortality is pursued by the WHO; risk conditions targets are recommended as well as population-level monitoring of cardiovascular disease (CVD) risk. The Italian Ministry of Health (MoH) has strengthened prevention/health promotion and supported periodic CVD risk assessment through national health examination surveys (HESs), funded by the MoH-CCM and conducted within the CUORE Project. Methods In 2023 a new HES started including the 10-year fatal and non-fatal CVD risk assessment based on knowledge of sex, age, smoking habit, measured systolic blood pressure and fasting total and HDL serum cholesterol, and presence of diabetes (on measured fasting serum glycemia and/or treatment) and anti-hypertensive therapy. Up to now, data from random samples of residents in 7 Regions (of 20 regions) distributed in North, Centre and South of Italy, aged 35-69 years, without previous CVD, are available (585 men, 617 women). Determinations were assayed by a central lab. CUORE Project functions developed on and for the Italian adults were used. Results Mean values of the CVD risk assessment resulted 6.9% (95% CI: 6.3-7.4) in men and 2.3% (2.1-2.5) in women. For men aged 35-44 years risk was 1.6% (1.5-1.8), for 45-54 years 3.8% (3.5-4.2), for 55-64 years 10.0% (9.0-10.9), for 65-69 years 17.6% (16.4-18.9); for women was 0.5% (0.4-0.6), 1.0% (0.9-1.1), 3.3% (2.9-3.7) and 6.0% (5.5-6.6) respectively. Prevalence of CVD risk less than 5% was 57% (49-64) in men and 88% (84-93) in women, of 10-15% risk were 22% (15-28) of men and 9% (5-14) of women, of 15-20% risk were 5% (1.6-8.0) of men and 0% of women, of over 20% risk were 2% (0-3.6) of men and 0% of women. Conclusions Compared to 2008, these data showed stable mean levels of CVD risk both in men and women at any age-classes and stable prevalence of CVD risk classes. CVD risk perception represents a challenge in primary prevention especially for young age groups and women. Key messages • In the Italian general population, CVD risk assessment remained stable compared to 15 years ago. • CVD risk perception represents a challenge in primary prevention.

Comparison of cardiovascular disease risk assessment tools in primary prevention patients with raised lipoprotein(a)

Abstract Background Genetically inherited lipoprotein (a) (lp(a)) is an independent cardiac risk factor. The approach to cardiovascular disease (CVD) risk modification is, however, uncertain. Current CVD risk calculators do not take lp(a) into account and guidance suggests binary treatment decisions based on presentation of lp(a) without considering other risk factors. A new CVD risk assessment tool has been developed which includes lp(a) concentration, Lp(a) Clinical Guidance (lpaclinicalguidance.com). Purpose The aim was to compare the CVD risk estimations and management impact, over both 10 years and lifetime, using the HEART UK consensus statement, QRISK3, Lp(a) Score, Score-2, Score-2 OP, and LIFE-CVD assessment tools in 20 primary prevention patients with raised lp(a). Methods This was a retrospective analysis from an existing database, recruited through lipid and cardiology outpatient services, with raised lp(a), and no history of CVD. A random selection with a broad range of lp(a) concentrations were chosen. The 10-year risk threshold to treat was based on current NICE guidance at 10% and, in the absence of consensus, a lifetime risk threshold of 25%. Lp(a) was measured by a reference clinical laboratory using a Roche platform (Denka Seiken reagent, isoform insensitive). Results The subset (n=20) included patients with lp(a) ranging from 64 nmol/L to &amp;gt;720 nmol/L, aged 20 to 78 (12 females). Risk assessment tool age restrictions prohibited risk estimation in all patients (explaining the variation in denominator below). Figure 1 shows a comparison of 10-year risk assessment tools, figure 2 lifetime risk. HEART UK guidance would indicate 90% of patients (18/20) were eligible to commence lipid lowering therapy, however, all patients would have treatment indicated based on Lp(a) Score (16/16). Using Score-2, no patients would have treatment indicated (0/6). Only 25% of patients (1/4) would have treatment indicated using Score-2 OP despite a minimum age criterion that alone introduces a major CVD risk factor. Of the remaining risk estimation tools: LIFE-CVD, QRISK3 lifetime risk, and QRISK3 10-year risk indicated 85% (11/13), 50% (8/16), and 38% (6/16) of patients, respectively, would have treatment indicated. Conclusions In primary prevention patients with raised lp(a), CVD risk estimation and decision-making is impaired by discrepancies in risk assessment tools. There may be underestimation in CVD risk, and subsequently under-treatment, with principal use of QRISK3 10-year risk to guide lipid lowering therapy. Lifetime CVD risk may be underestimated by QRISK and LIFE-CVD proportionally to the degree of elevation of lp(a). Risk assessment is imperfect; population data can only provide limited information when applied to an individual and the wide discrepancy found here calls into question the validity of risk estimation formulae in this population, or alternatively provides a range of tools for clinicians to select to suit the question asked.

Office-based risk equation of Globorisk for prediction of ten-years cardiovascular risk among Iranian population: findings from Fasa PERSIAN cohort study

BackgroundGloborisk is one of the prediction tools for 10-year risk assessment of cardiovascular disease, featuring an office-based (non-laboratory-based) version. This version does not require laboratory tests for determining the CVD risk. The present study aims to determine the 10-year CVD risk using the office-based Globorisk model and factors associated with the 10-year CVD risk.MethodsIn this study, baseline data from 6810 individuals participating in the Fasa cohort study, with no history of CVD or stroke, were utilized. The risk equation of the office-based Globorisk model incorporates age, sex, systolic blood pressure (SBP), body mass index (BMI), and smoking status. The Globorisk model categorizes the risk into three groups: low risk (< 10%), moderate risk (10% to < 20%), and high risk (≥ 20%). To identify factors associated with the 10-year CVD risk, the predicted risk was categorized into two groups: <10% and ≥ 10%. Multivariable logistic regression analysis was employed to determine factors associated with an increased CVD risk.ResultsAccording to the 10-year CVD risk categorization, 78.3%, 16.4%, and 5.3% of men were in the low, moderate, and high risk groups, respectively, while 85.8%, 10.0%, and 4.2%, of women were in the respective risk groups. Multivariable logistic regression results indicated that in men, the 10-year CVD risk decreases with being an opium user, and increases with being illiterate, having abdominal obesity, and low or moderate physical activity compared to high physical activity. In women, being married, and higher fiber consumption decrease the 10-year CVD risk, while being illiterate, low or moderate physical activity compared to high physical activity, having abdominal obesity, opium use, and being in wealth quintiles 1 to 4 compared to quintile 5 increase the risk.ConclusionsConsidering the factors associated with increased CVD risk, there is a need to enhance awareness and modify lifestyle to mitigate and reduce the risk of CVD. Additionally, early identification of individuals at moderate to high risk is essential for preventing disease progression. The use of the office-based Globorisk model can be beneficial in settings where resources are limited for determining the 10-year CVD risk.

Risk-enhancing factors and social determinants of health in risk assessment for atherosclerotic cardiovascular disease.

The Pooled Cohort Equations (PCEs) do not accurately estimate atherosclerotic cardiovascular disease (ASCVD) risk in certain populations. The 2018 AHA/ACC cholesterol guideline identified risk-enhancing factors as a supplement to PCEs-based risk assessment. However, the role of each risk-enhancing factor in ASCVD risk assessment has not been well quantified. Further, social determinants of health (SDOH) are not included in the PCEs nor considered as risk-enhancing factors in the US cholesterol guideline. We sought to evaluate ASCVD risk associated with each risk-enhancing factor and commonly collected SDOH including education, income, and employment status, and to assess if adding risk-enhancing factors and SDOH to the PCEs improve ASCVD risk prediction. We included individuals aged 40 to 75 years, without ASCVD or diabetes at baseline, and with low-density lipoprotein cholesterol 70-189 mg/dL from two contemporary prospective cohort studies (MESA and REGARDS) and from Kaiser Permanente Southern California (KPSC). The primary endpoint was incident ASCVD defined as nonfatal myocardial infarction, fatal coronary heart disease, or fatal or nonfatal stroke over a 10-year period (median follow-up 10 years). We used Cox proportional hazards models to estimate associations between risk-enhancing factors and SDOH with ASCVD. We also assessed changes in model performance after adding risk-enhancing factors and SDOH to the PCEs. We included 13,863 adults (mean age 60.7 years) from the prospective cohorts and 307,931 adults (mean age 54.8 years) from KPSC. Risk-enhancing factors including hypercholesterolemia, hypertriglyceridemia, metabolic syndrome, and chronic kidney disease were associated with a higher ASCVD risk, independent of 10-year risk estimated by the PCEs. Low education, low income, and unemployment were also associated with higher ASCVD risk. While adding individual risk-enhancing factors or SDOH to the PCEs had limited impact on model performance, adding multiple risk-enhancing factors and SDOH simultaneously led to modest improvements in discrimination (C-index increased by up to 0.07), calibration (integrated Brier score reduced by up to 2.3%), and net reclassification improvement up to 41.4%. These findings suggest including SDOH and risk-enhancing factors may improve ASCVD risk assessment.

Little disease but lots of bites: social, urbanistic, and entomological risk factors of human exposure to Aedes aegypti in South Texas, U.S.

Aedes aegypti presence, human-vector contact rates, and Aedes-borne virus transmission are highly variable through time and space. The Lower Rio Grande Valley (LRGV), Texas, is one of the few regions in the U.S. where local transmission of Aedes-borne viruses occurs, presenting an opportunity to evaluate social, urbanistic, entomological, and mobility-based factors that modulate human exposure to Ae. aegypti. Mosquitoes were collected using BG-Sentinel 2 traps during November 2021 as part of an intervention trial, with knowledge, attitudes, and practices (KAP) and housing quality surveys to gather environmental and demographic data. Human blood samples were taken from individuals and a Bitemark Assay (ELISA) was conducted to quantify human antibodies to the Ae. aegypti Nterm-34kDa salivary peptide as a measure of human exposure to bites. In total, 64 houses were surveyed with 142 blood samples collected. More than 80% of participants had knowledge of mosquito-borne diseases and believed mosquitoes to be a health risk in their community. Our best fit generalized linear mixed effects model found four fixed effects contributed significantly to explaining the variation in exposure to Ae. aegypti bites: higher annual household income, younger age, larger lot area, and higher female Ae. aegypti abundance per trap night averaged over 5 weeks prior to human blood sampling. Most surveyed residents recognized mosquitoes and the threat they pose to individual and public health. Urbanistic (i.e., lot size), social (i.e., income within a low-income community and age), and entomological (i.e., adult female Ae. aegypti abundance) factors modulate the risk of human exposure to Ae. aegypti bites. The use of serological biomarker assays, such as the Bitemark Assay, are valuable tools for surveillance and risk assessment of mosquito-borne disease, especially in areas like the LRGV where the transmission of target pathogens is low or intermittent.

Serious adverse events following immunization with COVID-19 vaccines in Lebanon: a retrospective analysis of the National Pharmacovigilance Database

Continuous surveillance and risk assessment of inactivated Coronavirus Disease 2019 (COVID-19)) vaccines provide an understanding of their safety profiles, guide vaccination strategy and public health policy. This study aims to analyze the characteristics and prevalence of officially reported serious adverse events following immunization (AEFIs) with inactivated COVID-19 vaccines by System Organ Class (SOC), age, and sex.To achieve this aim, a retrospective observational study was conducted between February 14th, 2021, and June 30th, 2022. Reported AEFIs were evaluated for data completeness. Causality assessment adhered to the World Health Organization guidelines.Findings revealed that the AEFIs occurrence did not significantly differ between vaccines used (ChAdOx1 vs. BNT162b2), sex, or SOC. The most prevalent AEFIs were vascular disorders (37%), followed by cardiac (25%) and nervous system disorders (14%). The adverse events were predominantly reported post-vaccination with the BNT162b2 vaccine, mainly after the first dose. The mean age was highest for miscellaneous disorders (70 ± 21.7 years) and the lowest for nervous system (46 ± 22 years) and immune system disorders (45 ± 19 years). Age differences were statistically different for vascular disorders (p = 0.003) and immune system disorders (p = 0.012).In conclusion, ongoing surveillance and risk assessment of the vaccine’s safety profile is crucial for detecting potential safety signals. Active surveillance of the reported serious AEFIs is highly needed to support evidence-based vaccination strategies and maintain public confidence in immunization programs,

Prevalence of Cardiovascular Disease and Comparison of Risk Category Predictions of Systemic Coronary Risk Evaluation Score-2 and 4 Other Cardiovascular Disease Risk Assessment Tools Among People Living with Human Immunodefficiency Virus in Türkiye.

Cardiovascular disease (CVD) is a major cause of mortality among people living with HIV (PLWH). We aimed to assess the prevalence of diagnosed CVD and the risk of CVD among PLWH using 5 different tools. This retrospective, cross-sectional study was conducted in 20 tertiary centers in Türkiye between October 2021 and March 2022, among 1425 PLWH aged 40-75 years. About 82.7% were male, with a median age of 51. Web-based tools for each score were used for CVD risk calculations. Of 1425 PLWH enrolled, 10.8% had confirmed CVD, and 1132 had their risk scores evaluated. Of those participants, 42.8% had a higher risk of CVD (10-year risk of atherosclerotic CVD risk score (ASCVD) above 7.5%), and according to the European Society of Cardiology systemic coronary risk evaluation 2 (SCORE2), 71.7% had a high- to very high-risk rate. The agreement between various CVD risk tools varied, with Framingham heart study risk score (FRS), modified FRS, data collection on adverse effects of anti-HIV drugs (DAD), and SCORE2 for high-risk countries showing overall agreement rates of 82%, 94%, 91%, and 36%, respectively, compared to ASCVD. According to the 2021 European and 2019 American Cardiology guidelines, 75.3% and 47.1% of PLWH would be eligible for lipid-lowering agents, respectively. The diagnosed CVD prevalence highlighted the importance of monitoring cardiovascular health and comorbidities in this population. SCORE2 identified a greater number of individuals at high/very high risk compared to other prediction tools. The implementation of CVD prevention through lipid-lowering therapy was far from desired levels in our cohort.

Reporting a Rare HLA Allele with Sequence Analysis Prevents Potentially Lethal Allopurinol Hypersensitivity Reaction

Abstract Introduction/Objective In addition to their essential role in histocompatibility testing, human leukocyte antigen (HLA) alleles have informative pharmacogenomic and disease associations. For example, HLA-B*58:01 carriers have 100- fold greater risk of allopurinol hypersensitivity syndrome (AHS), a lethal T-cell mediated Type IV reaction with a 20- 25% mortality rate. To prevent AHS, patients are tested for carrier status before treatment. Methods/Case Report Patient presented for workup of intermittently flaring right knee pain and uricemia. Uric acid is elevated, plain film imaging is ordered, arthrocentesis is planned, and HLA testing is performed to inform uricemia treatment. Next generation sequencing (NGS) typing reveals the patient carries HLA-B*58:11. Sequence analysis demonstrates the allele’s open reading frame differs from HLA-B*58:01 by a single I194V substitution. Amino acid sequences of peptide binding regions (PBR) encoded by these alleles are identical. Presentation of allopurinol/oxypurinol peptides to T-cells by B*58:01 is the putative mechanism underlying AHS pathogenesis. Identical protein sequence in the PBR of B*58:11 favors similar function. Findings are reported and treatment with allopurinol foregone. Results (if a Case Study enter NA) NA Conclusion High resolution HLA testing is essential to appropriately interpret and report results for disease risk and pharmacogenomics assessments. However, NGS detects rare alleles that have yet to be associated with a disease process. When pathogenesis is thought to be linked to the PBR, rare HLA alleles with identical or similar PBR to disease associated alleles may confer similar risk. In this case, NGS identified PBR similarity between the patient’s allele and an established AHS risk allele. Although B*58:11 has not been shown to be associated with AHS, likely due to low prevalence, the risk was deemed sufficient to select an alternative therapy and potentially prevent a lethal drug reaction.

High-Sensitivity Cardiac Troponin [hs-cTn] as a Valuable Biomarker for Pulmonary Hypertension Risk Stratification: A Contemporary Review of the Literature.

Background: Pulmonary hypertension (PH) can lead to cardiac failure, thereby significantly affecting life expectancy and quality of life. Due to inadequate disease surveillance and risk assessment, clinical challenges persist despite advances in diagnosis and treatment. We aimed to review the potential of high-sensitivity cardiac troponin (hs-cTn) as a biomarker for predicting outcomes in PH patients. Methods: A thorough examination of the PubMed and Google Scholar databases was conducted through March 2023. Studies involving adult PH patients and hsTn as a prognostic indicator of outcomes such as mortality, hospitalization, and disease progression were included, after screening their titles and abstracts. Two independent evaluators extracted data, with the quality assessed using the JBI critical appraisal tool. Results: This review uncovered eight studies that examined the prognostic value of hs-cTn in PH patients. Higher hs-cTn levels were associated with increased mortality and hospitalization rates, according to the studies. The severity of PH, cardiac dysfunction, right ventricular function, and systolic dysfunction were associated with hs-cTn. Multiple studies have demonstrated that hsTn has the potential to identify high-risk PH patients who could benefit from targeted therapies and increased clinical monitoring. Conclusions: This review suggests that hsTn may be a biomarker for PH risk stratification and prognosis. Across PH subtypes, elevated hsTn levels predict poor outcomes. However, large-scale prospective studies are needed to confirm hs-cTn's function in diagnosing pulmonary hypertension and determine its potential value in treatment.

Calling for Action: The Need of Large-Scale Cohorts to Uncover the Cardiovascular Risk in Non-Sleepy Obstructive Sleep Apnea.

Since randomized clinical trials currently do not support continuous positive airway pressure treatment of asymptomatic obstructive sleep apnea (OSA) we proposed the Obesity, Symptoms, and CARdiovascular assessment (OSCAR) algorithm to aid clinicians in the management of asymptomatic low-risk moderate-severe OSA, focusing on weight loss, symptoms and cardiovascular disease (CVD) risk assessment. Exploiting the data of the Sleep Heart Health Study we selected subjects with a body mass index (BMI) < 30 Kg/m2, no history of CVD or sleepiness and compared 552 patients with moderate-severe OSA (OSCAR(-)) to 916 individuals without OSA (No-OSA). After adjusting for age, gender, and BMI, there was no significant difference in the risk of major adverse cardiovascular events (MACE) between OSCAR(-) and No-OSA (1.05; 95%CI 0.81-1.37). The study suggests that low-risk moderate-severe OSA patients may not have a greater risk of MACE compared to those without OSA and highlights the need for further research on this topic.

Risk assessment of non-communicable diseases (NCDs) in rural Maharashtra, India

The research question I addressed was - “To what extent do socioeconomic factors influence the risk of developing lifestyle diseases such as Obesity, Hypertension and Type II Diabetes Mellitus in Rural and Urban Indian women aged 35-55 years?”. Having lived in the urban parts of India for the majority of my life, this opportunity exposed me to healthcare in rural India and language barriers due to the diversity of subIndian cultures.

Discovery of prognostic lncRNAs in colorectal cancer using spatial transcriptomics

Colorectal cancer (CRC) exhibits significant genetic and epigenetic diversity, evolving into sub-clonal populations with varied metastatic potentials and treatment responses. Predicting metastatic disease in CRC patients remains challenging, underscoring the need for reliable biomarkers. While most research on therapeutic targets and biomarkers has focused on proteins, non-coding RNAs such as long non-coding RNAs (lncRNAs) comprise most of the transcriptome and demonstrate superior tissue- and cancer-specific expression. We utilised spatial transcriptomics to investigate lncRNAs in CRC tumours, offering more precise cell-type-specific expression data compared to bulk RNA sequencing. Our analysis identified 301 lncRNAs linked to malignant CRC regions, which we validated with public data. Further validation using RNA–FISH revealed three lncRNAs (LINC01978, PLAC4, and LINC01303) that are detectable in stage II tumours but not in normal epithelium and are upregulated in metastatic tissues. These lncRNAs hold potential as biomarkers for early risk assessment of metastatic disease.

One-step TaqMan® RT-qPCR detection of sugar beet-infecting poleroviruses in Myzus persicae from yellow water pan traps opens up new possibilities for early risk assessment of virus yellows disease

Virus yellows disease (VY) is a major threat to sugar beet production in Europe. Beet chlorosis virus (BChV) and beet mild yellowing virus (BMYV) are of particular economic importance and are both persistently transmitted by the aphid vector Myzus persicae. As part of integrated pest management strategies, M. persicae influx into sugar beet fields is recorded weekly using yellow water pan traps. To date, only ELISA and RT-PCR assays have been described for BChV and BMYV detection in individual aphids.In this study, we describe for the first time two one-step TaqMan® RT-qPCR assays designed for the specific detection of BChV and BMYV in M. persicae after 7d incubation in water pan trap medium. Both viruses were reproducibly detected in individual aphids. After 7d incubation in trap medium, both viruses were reproducibly detected in individual aphids, as well as in one viruliferous aphid in a pool of 99 non-viruliferous aphids. Significant correlations can be shown between different mixing ratios of viruliferous to non-viruliferous aphids and Ct values of total RNA templates, allowing the percentage of viruliferous aphids in yellow water pan traps to be estimated using a standard curve.The described methodology provides a high sensitivity combined with a high sample throughput and can be used, after evaluation in the field, for practical monitoring, risk modelling and development of decision support systems for VY.

External Validation of the American Heart Association PREVENT Cardiovascular Disease Risk Equations

The American Heart Association's Predicting Risk of Cardiovascular Disease Events (PREVENT) equations were developed to extend and improve on previous cardiovascular disease (CVD) risk assessments for the purpose of treatment initiation and patient-clinician communication. To assess prognostic capabilities, calibration, and discrimination of the PREVENT equations in a study sample representative of the noninstitutionalized, US general population. This prognostic study used data from the National Health and Nutrition Examination Survey (NHANES) 1999 to 2010 data cycles. Participants included adults for whom 10-year follow-up data were available. Data curation and analyses took place from December 2023 through May 2024. Primary measures were risk estimated by the PREVENT equations, as well as risk estimates from the previous Pooled Cohort Equations (PCEs). The primary outcome was composite CVD-related mortality at 10 years of follow-up. Additional analyses compared the PREVENT equations against the PCEs. Model discrimination was assessed with receiver-operator characteristic curves and Harrell C statistic from proportional hazard regression; model calibration was determined as the slope of predicted versus observed risk. The study cohort, accounting for NHANES complex survey design, consisted of 172.9 million participants (mean age, 45.0 years [95% CI, 44.6-45.4 years]; 52.1% women [95% CI, 51.5%-52.6%]). In analyses adjusted for the NHANES survey design, a 1% increase in PREVENT risk estimates was statistically significantly associated with increased CVD mortality risk (hazard ratio, 1.090; 95% CI, 1.087-1.094). PREVENT risk scores demonstrated excellent discrimination (C statistic, 0.890; 95% CI, 0.881-0.898) but moderate underfitting of the model (calibration slope, 1.13; 95% CI, 1.06-1.21). PREVENT risk models performed statistically significantly better than the PCEs, as assessed by the net reclassification index (0.093; 95% CI, 0.073-0.115). In this prognostic study of the PREVENT equations, PREVENT risk estimates demonstrated excellent discrimination and only modest discrepancies in calibration. These findings provided evidence supporting utilization of the PREVENT equations for application in the intended population as suggested by the American Heart Association.

A Big Data Intelligent Evaluation System for Sports Knowledge

The rapid evolution of computer technology has significantly impacted the field of medicine, particularly in the utilization of information and image evidence. In the realm of sports medicine, this technological advancement plays a crucial role in ensuring sports safety, especially in the context of injury recovery following sports-related activities. The necessity to interpret and utilize a vast amount of sports medical data effectively has emerged as a pivotal research avenue. This paper delves into the challenges associated with extracting, studying, and the accuracy training of complex algorithms essential for analyzing critical sporting medical data.Central to this discussion is introducing an Optimized Convolutional Neural Network (OCNN) model, which is based on deep learning principles. This model is designed to enhance the detection and risk assessment of diseases related to sport medicine. It incorporates a novel Self-Adjustment Resizing algorithm (SAR), augmented by a self-coding method of convolution (SCM). The proposed OCNN model comprises two convolutional layers, two pooling layers, a fully connected layer, and a SoftMax structure. This architecture is tailored for the classification and analysis of sport-related medical data.

5037 Coronary artery disease risk assessment by coronary artery calcium scoring in asymptomatic Thai people with diabetes mellitus

5037 Coronary artery disease risk assessment by coronary artery calcium scoring in asymptomatic Thai people with diabetes mellitus