Early Detection Strategies Research Articles

The association between health literacy and colorectal cancer screening uptake in Taiwan

Abstract Background Population-based cancer screening programs have been confirmed as a cost-effective strategy for early detection of colorectal cancer, leading to reduced mortality and morbidity. In Taiwan, the government has provided an immunochemical fecal occult blood test (iFOBT) every two years to all citizens aged 50 to 74 years since 2013. The study aims to determine the association between iFOBT uptake and health literacy (HL). Methods Data from the National Health Interview Survey (NHIS), a population-based cross-sectional survey conducted in 2021-22 in Taiwan, were applied. The European Health Literacy Survey Short Form (HLS-EU-Q16), self-reported iFOBT participation within the past 2 years, and covariates assessed by face-to-face interview. The present analysis included those age-eligible for screening (n = 3,871) and applied the survey-weighted multivariable logistic regression to estimate odds of iFOBT uptake between HL skill levels, controlling for age, education attainment, socioeconomic status, health status, and household urbanicity level. Results In general, 44.6% of participants had utilized the iFOBT, and 79.9% had adequate HL skills which reported higher iFOBT uptake rates (45.9%) than their counterparts (39.4%). Multivariable analysis showed that having adequate HL was associated with greater odds of iFOBT utilization (adjusted odds ratio [aOR] = 1.79; 95% CI: 1.29-2.49). Additionally, compared to those households registered in the township, participants in higher urbanicity levels had lower iFOBT uptake: city (aOR = 0.62; 95% CI: 0.47-0.82). Other predictors that contributed significantly were participants’ gender and having 2 or more chronic diseases. Conclusions Inadequate HL skills and urban residency may reduce participation in the CRC screening program, despite its free availability. More efforts should include literacy-friendly designed materials and the provision of tailored support in urban settings. Key messages • HL skills are significantly associated with the CRC screening uptake in Taiwan. Improving HL could have positive effects on people’s participation. • Urbanicity levels are also predictors associated with screening utilization. Disseminating health service information in localized ways should be a potential option.

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.

Follow-up strategy for early detection of delayed pseudoaneurysms in patients with blunt traumatic spleen injury: A single-center retrospective study

Follow-up strategy for early detection of delayed pseudoaneurysms in patients with blunt traumatic spleen injury: A single-center retrospective study

Sleep quality and associated factors in older outpatients with hypertension in Vietnam: A cross-sectional study

Background & Aim: Sleep plays a crucial role in controlling blood pressure. Older adults commonly suffer from poor sleep quality which results in several negative health outcomes, such as cognitive impairment, depression, and increased risk of falling. However, limited research exists on sleep quality in older Vietnamese adults. This study aimed to investigate sleep quality and its associated factors in older adults with hypertension in Central Vietnam. Methods & Materials: A cross-sectional study was conducted at a tertiary hospital in Central Vietnam with 235 outpatients who were aged 60 years or older, diagnosed with hypertension, and without cognitive impairment. The Pittsburgh Sleep Quality Index was utilized to assess the participants' sleep quality. Multiple binary logistic regression was computed to identify factors associated with sleep quality with a P value less than 0.05. Results: The mean sleep quality score was 8.2 (±3.9), with 71.9% of participants reporting poor sleep quality. Participants with a high school education or less were more likely to report poor sleep quality than those with higher education (OR = 1.91; 95% CI: 1.05 - 3.46; p= 0.034). Additionally, the presence of musculoskeletal disease increased the risk of poor sleep quality (OR= 2.26; 95% CI: 1.04 - 4.87; p= 0.038). Conclusion: The majority of participants suffered from poor sleep quality, which was strongly associated with educational level and the presence of musculoskeletal diseases. Strategies for early detection, prevention, and treatment of poor sleep quality are essential for improving health outcomes in this population.

Development and Initial Evaluation of a Digital Phenotype Collection System for Adolescents: Proof-of-Concept Study.

The growing concern on adolescent mental health calls for proactive early detection and intervention strategies. There is a recognition of the link between digital phenotypes and mental health, drawing attention to their potential use. However, the process of collecting digital phenotype data presents challenges despite its promising prospects. This study aims to develop and validate system concepts for collecting adolescent digital phenotypes that effectively manage inherent challenges in the process. In a formative investigation (N=34), we observed adolescent self-recording behaviors and conducted interviews to develop design goals. These goals were then translated into system concepts, which included planners resembling interfaces, simplified data input with tags, visual reports on behaviors and moods, and supportive ecological momentary assessment (EMA) prompts. A proof-of-concept study was conducted over 2 weeks (n=16), using tools that simulated the concepts to record daily activities and complete EMA surveys. The effectiveness of the system was evaluated through semistructured interviews, supplemented by an analysis of the frequency of records and responses. The interview findings revealed overall satisfaction with the system concepts, emphasizing strong support for self-recording. Participants consistently maintained daily records throughout the study period, with no missing data. They particularly valued the recording procedures that aligned well with their self-recording goal of time management, facilitated by the interface design and simplified recording procedures. Visualizations during recording and subsequent report viewing further enhanced engagement by identifying missing data and encouraging deeper self-reflection. The average EMA compliance reached 72%, attributed to a design that faithfully reflected adolescents' lives, with surveys scheduled at convenient times and supportive messages tailored to their daily routines. The high compliance rates observed and positive feedback from participants underscore the potential of our approach in addressing the challenges of collecting digital phenotypes among adolescents. Integrating observations of adolescents' recording behavior into the design process proved to be beneficial for developing an effective and highly compliant digital phenotype collection system.

A dual-mode strategy for early detection of sugarcane pokkah boeng disease pathogen: A portable sensing device based on Cross-N DNA framework and MoS2@GDY

Sucrose, a common sugar primarily derived from sugarcane, is a crucial national strategic resource. However, its yield is significantly affected by various serious diseases, with pokkah boeng disease being one of the most damaging. Therefore, developing a sensitive method for the accurate detection of the pokkah boeng disease pathogen is crucial for ensuring the safety of sugar. This work presents a portable dual-modal detection device, assisted by a smartphone, which is based on MoS2@GDY, Mn3O4@Au nanomenzyme, cross-N DNA framework and Exo III exonuclease-assisted CHA signal amplification technology. The cross-N DNA framework provides many binding sites and is not restricted by AuNPs scattering positions, enhancing the signal output strength of the sensor. Additionally, the detection system incorporates a high-power-density capacitor to further amplify the electrochemical detection signal, increasing sensitivity by 9.1 times. Moreover, the use of electrochemical and colorimetric dual-mode detection effectively avoids mutual interference, reducing the likelihood of false positives from a single signal. Under optimized conditions, the proposed method has a linear range of 0.0001–10,000 pM, and with a detection limit of 6.1 aM (S/N=3). This high-sensitivity, high-reliability portable sensing method shows significant potential for the early detection and real-time on-site monitoring of the pokkah boeng disease pathogen.

Emerging strategies to investigate the biology of early cancer.

Early detection and intervention of cancer or precancerous lesions hold great promise to improve patient survival. However, the processes of cancer initiation and the normal-precancer-cancer progression within a non-cancerous tissue context remain poorly understood. This is, in part, due to the scarcity of early-stage clinical samples or suitable models to study early cancer. In this Review, we introduce clinical samples and model systems, such as autochthonous mice and organoid-derived or stem cell-derived models that allow longitudinal analysis of early cancer development. We also present the emerging techniques and computational tools that enhance our understanding of cancer initiation and early progression, including direct imaging, lineage tracing, single-cell and spatial multi-omics, and artificial intelligence models. Together, these models and techniques facilitate a more comprehensive understanding of the poorly characterized early malignant transformation cascade, holding great potential to unveil key drivers and early biomarkers for cancer development. Finally, we discuss how these new insights can potentially be translated into mechanism-based strategies for early cancer detection and prevention.

Deletions Rate-Limit Breast and Ovarian Cancer Initiation.

Optimizing prevention and early detection of cancer requires understanding the number, types and timing of driver mutations. To quantify this, we exploited the elevated cancer incidence and mutation rates in germline BRCA1 and BRCA2 (gBRCA1/2) carriers. Using novel statistical models, we identify genomic deletions as the likely rate-limiting mutational processes, with 1-3 deletions required to initiate breast and ovarian tumors. gBRCA1/2 -driven hereditary and sporadic tumors undergo convergent evolution to develop a similar set of driver deletions, and deletions explain the elevated cancer risk of gBRCA1/2 -carriers. Orthogonal mutation timing analysis identifies deletions of chromosome 17 and 13q as early, recurrent events. Single-cell analyses confirmed deletion rate differences in gBRCA1/2 vs. non-carrier tumors as well as cells engineered to harbor gBRCA1/2 . The centrality of deletion-associated chromosomal instability to tumorigenesis shapes interpretation of the somatic evolution of non-malignant tissue and guides strategies for precision prevention and early detection.

Innovative Biomedical Interventions for Cardiovascular Risk Reduction and Health Promotion: A Review Study

Cardiovascular diseases (CVD) remain the leading cause of mortality worldwide, with increasing prevalence in both developed and developing regions. The complexity of CVD necessitates innovative approaches that combine biomedical research with clinical practice for effective prevention, diagnosis, and treatment. This chapter explores cutting-edge biomedical interventions to reduce cardiovascular risk and promote heart health. It focuses on recent advancements in biomarker identification, gene therapy, nanotechnology, and regenerative medicine, offering new strategies for early detection and targeted treatment of cardiovascular conditions. Additionally, the chapter highlights the role of precision medicine and personalized healthcare approaches in managing individual risk factors, including hypertension, dyslipidemia, and diabetes, while addressing lifestyle influences like nutrition and physical activity. Public health initiatives are also discussed, examining how biomedical research has contributed to the development of population-level interventions, such as community-based screening programs and digital health tools for monitoring cardiovascular health. By integrating biomedical innovation with preventive healthcare strategies, this chapter provides a comprehensive overview of the future directions in cardiovascular risk reduction, underscoring the importance of a multi-disciplinary approach for enhancing patient outcomes and promoting long-term cardiovascular wellness.

Multi-scale asynchronous correlation and 2D convolutional autoencoder for adolescent health risk prediction with limited fMRI data.

Adolescence is a fundamental period of transformation, encompassing extensive physical, psychological, and behavioral changes. Effective health risk assessment during this stage is crucial for timely intervention, yet traditional methodologies often fail to accurately predict mental and behavioral health risks due to the intricacy of neural dynamics and the scarcity of quality-annotated fMRI datasets. This study introduces an innovative deep learning-based framework for health risk assessment in adolescents by employing a combination of a two-dimensional convolutional autoencoder (2DCNN-AE) with multi-sequence learning and multi-scale asynchronous correlation information extraction techniques. This approach facilitates the intricate analysis of spatial and temporal features within fMRI data, aiming to enhance the accuracy of the risk assessment process. Upon examination using the Adolescent Risk Behavior (AHRB) dataset, which includes fMRI scans from 174 individuals aged 17-22, the proposed methodology exhibited a significant improvement over conventional models. It attained a precision of 83.116%, a recall of 84.784%, and an F1-score of 83.942%, surpassing standard benchmarks in most pertinent evaluative measures. The results underscore the superior performance of the deep learning-based approach in understanding and predicting health-related risks in adolescents. It underscores the value of this methodology in advancing the precision of health risk assessments, offering an enhanced tool for early detection and potential intervention strategies in this sensitive developmental stage.

Estimation of burden of cancer incidence and mortality in India: based on global burden of disease study 1990–2021

BackgroundCancer poses a significant public health challenge in India, making it crucial to predict its future impact for effective healthcare planning. This study forecast cancer incidence, mortality, and disability-adjusted life years (DALYs) in India from 2022 to 2031.MethodsWe extracted age-standardized data on incidence, prevalence, DALYs, and mortality from 1990 to 2021 from the Global Burden of Disease (GBD) study. We used Decadal Average Percentage Change techniques to identify trends in cancer burden over decades and the Autoregressive Integrated Moving Average (ARIMA) method were used for forecasting. The ARIMA (2,2,2) model was identified as the best for predicting cancer incidence, ARIMA (0,3,3) for DALYs, and ARIMA (0,2,2) for mortality.ResultsThe cancer incidence rate is expected to rise from 529.40 (95% CI: 525.41-533.38) in 2022 to 549.17 (95% CI: 487.43-610.92) per 100,000 population in 2031. The DALYs rate is projected to decrease from 2001.53 (95% CI: 1964.24-2038.82) in 2022 to 1842.08 (95% CI: 1273.57-2410.60) per 100,000 population in 2031, indicating improvements in cancer burden management. Mortality rates are forecasted to increase slightly, from 71.52 (95% CI: 69.91–73.12) in 2022 to 73.00 (95% CI: 60.88–85.11) per 100,000 population in 2031. Overall, while incidence and mortality rates show a slight upward trend, the DALYs rate is projected to decrease, reflecting potential advancements in cancer management and treatment over the forecast period.ConclusionsOver the next decade, cancer incidence and mortality are expected to increase in India, highlighting the need for enhanced prevention, early detection, and proper treatment strategies. Despite these increases, the anticipated decrease in DALYs suggests potential advancements in cancer management, warranting further investigation into the drivers of this positive trend and measures to sustain it.

Advances in microRNAs as Emerging Biomarkers for Colorectal Cancer Early Detection and Diagnosis.

Colorectal cancer (CRC) remains the second most common cause of cancer-related mortality worldwide, necessitating advancements in early detection and innovative treatment strategies. MicroRNAs (miRNAs), small non-coding RNAs involved in gene regulation, have emerged as crucial players in the pathogenesis of CRC. This review synthesizes the latest findings on miRNA deregulated in precancerous lesions and in CRC. By examining the deregulation patterns of miRNAs across different stages of CRC development, this review highlights their potential as diagnostic tools. We specifically analyse the roles and diagnostic relevance of four miRNAs-miR-15b, miR-21, miR-31, and miR-146a-that consistently exhibit altered expression in CRC. The current knowledge of their role in key oncogenic pathways, drug resistance, and clinical relevance is discussed. Despite challenges posed by the heterogeneity of the research findings on miRNA deregulation and their role in CRC, integrating miRNA diagnostics into current screening methods holds promise for enhancing personalized medicine approaches. This review emphasizes the transformative potential of miRNAs in CRC diagnosis, paving the way for improved patient outcomes and novel therapeutic paradigms.

Expression of the large amino acid transporter SLC7A5/LAT1 on immune cells is enhanced in primary sclerosing cholangitis-associated cholangiocarcinoma and correlates with poor prognosis in cholangiocarcinoma

Biliary tract cancers (BTC) are rare lethal malignancies arising along the biliary tree. Unfortunately, effective therapeutics are lacking and the prognosis remains dismal even for patients eligible for surgical resection. Therefore, novel therapeutic approaches along with early detection strategies and prognostic markers are urgently needed. Primary sclerosing cholangitis (PSC) is a chronic disease of the bile ducts leading to fibrosis and ultimately cirrhosis. Patients with PSC have a 5–20% lifetime risk of developing BTC; yet the molecular mechanisms that underpin the development of PSC- associated biliary tract cancer (PSC-BTC) have not been fully elucidated. SLC7A5/LAT1, a large amino acid transporter, has been shown to modulate cell growth and proliferation as well as other intracellular processes in solid tumors. In this study, we evaluated SLC7A5 expression in PSC-BTC and in sporadic BTC (sBTC) and its role as a prognostic factor. Analysis of the TGCA cohort showed a significantly higher expression of SLC7A5 in tumor tissue compared with adjacent normal tissue (p = 0.0002) in BTC. In our cohort (comprised of 69 BTC patients including 16 PSC-BTC), SLC7A5/LAT1 expression was observed in both tumor and intratumoral immune cells. A significantly higher percentage of SLC7A5/LAT1 positive intratumoral immune cells was observed in PSC-BTC compared with sBTC (p = 0.004). Multiplex immunofluorescence co-detection by indexing (CODEX) analysis identified CD4+ regulatory T lymphocytes and CD68+ macrophages as the largest immune cell populations expressing LAT1.SLC7A5/LAT1 expression as well as a higher intratumoral infiltration of SLC7A5/LAT1-positive immune cells (≥2%) were associated with a shorter overall survival in our cohort (LogRank test, p = 0.04 and p = 0.008; respectively). SLC7A5/LAT1 expressing tumors are higher staged tumors (pT3/4 versus pT1/2, p = 0.048).These results underline the potential use of SLC7A5/LAT1 as a prognostic marker in BTC. Furthermore, the higher frequency of SLC7A5/LAT1 positive immune cells in PSC-BTC compared to sBTC may hint at the potential role of SLC7A5/LAT1 in inflammation-driven carcinogenesis.

Proteomic and metabolomic profiles of plasma-derived Extracellular Vesicles differentiate melanoma patients from healthy controls

BackgroundPlasma-derived Extracellular Vesicles (EVs) have been suggested as novel biomarkers in melanoma, due to their ability to reflect the cell of origin and ease of collection. This study aimed to identify novel EV biomarkers that can discriminate between disease stages. This was achieved by characterising the plasma-derived EVs of patients with melanoma, and comparing their proteomic and metabolomic profile to those from healthy controls. MethodsEVs were isolated from the plasma of 36 patients with melanoma and 13 healthy controls using Size Exclusion Chromatography. Proteomic and Metabolomic Analyses were performed, and machine learning algorithms were used to identify potential proteins and metabolites to differentiate the plasma-derived EVs from melanoma patients of different disease stages. ResultsThe concentration and size of the EV population isolated was similar between groups. Proteins (APOC4, PRG4, PLG, TNC, VWF and SERPIND1) and metabolites (lyso PC a C18:2, PC ae C44:3) previously associated with melanoma pathogenesis were identified as relevant in differentiating between disease stages. ConclusionThe results further support the continued investigation of circulating plasma-derived EVs as biomarkers in melanoma. Furthermore, the potential of combined proteo-metabolomic signatures for differentiation between disease stages may provide valuable insights into early detection, prognosis, and personalised treatment strategies.

Hepatocellular Carcinoma Situation in Indonesia: A Systematic Review of Clinical Staging and Histological Characteristics at the Time of Diagnosis

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. However, systematic data on HCC characteristics in Indonesia are limited. Objective: To summarize the body of literature on the characteristics of HCC in Indonesia. Methods: A comprehensive search was conducted in MEDLINE, ScienceDirect, Scopus, Web of Science, and Google Scholar databases without date restrictions. Clinical studies investigating the characteristics of HCC exclusively in Indonesia were eligible for inclusion. Risk-of-bias assessments were conducted, and results were presented descriptively. Results: Ten studies comprising 1,389 HCC patients were included. The Barcelona Clinic Liver Cancer (BCLC) staging system, reported in 5 studies, revealed a predominance of intermediate to advanced stages (B and C) at diagnosis. Child-Pugh scores, available for 7 studies, indicated variability in liver function, with Child-Pugh A ranging from 12.0% to 85.7%. Hepatitis B virus (HBV) infection was the primary etiological factor, with prevalence ranging from 53.8% to 84.0%. Hepatitis C virus (HCV) infection was less common (1.0% to 25.21%). Non-viral etiologies represented a substantial proportion, reaching up to 37.4% of cases. The mean age at diagnosis ranged from 52.43 to 63.1 years. Conclusion: This review highlights the late-stage presentation of HCC in Indonesia, the predominance of HBV as an etiological factor, and a significant burden of non-viral HCC. The findings underscore the need for improved early detection strategies, strengthened HBV prevention efforts, and increased attention to metabolic risk factors. Regional variations in HCC characteristics suggest the need for tailored approaches to HCC management across different parts of Indonesia.

Customs Intelligence Strategy Encountering Smuggling Threats in a Changing World

This research analyzes the intelligence strategies employed by the Directorate General of Customs and Excise (DGCE) in Indonesia to combat the evolving landscape of smuggling in the era of Industry 4.0. The study aims to identify and analyze current intelligence practices and subsequently formulate effective strategies for early detection, prevention, and suppression of smuggling activities. Employing a qualitative research methodology, the study utilizes NVivo 14 software to analyze data gathered from relevant sources. The findings reveal a significant increase in the complexity of smuggling operations, characterized by the involvement of transnational organized crime syndicates, sophisticated trade-based money laundering schemes, and the exploitation of electronic commerce (e-commerce) platforms. Despite these challenges, the research indicates that customs intelligence has not been fully maximized as a tool for economic security. Therefore, this study proposes the adoption of a dynamic and adaptive customs intelligence strategy. This strategy encompasses crucial aspects such as strengthening legal frameworks, optimizing organizational structure, enhancing human resource capabilities, and modernizing intelligence facilities and infrastructure. With implementing these recommendations, the DGCE can optimize the role of customs intelligence in safeguarding national economic security and effectively enforcing customs and excise laws in the face of increasingly sophisticated smuggling threats.

Inflammation in Chemotherapy-Induced Cardiotoxicity.

In this review we describe the role of inflammation in chemotherapy-induced cardiotoxicity with a particular focus on anthracycline-induced cardiomyopathy (AIC). First, we discuss inflammation associated with anthracyclines at a cellular level. Next, we discuss the clinical implications of these inflammatory mechanisms for early detection and cardioprotective strategies in patients undergoing anthracycline treatment. Key inflammatory pathways identified in AIC include cytokine release, upregulation of the innate immune system via toll-like receptors, and activation of the inflammasome. Emerging evidence suggests a role for inflammatory biomarkers in detecting subclinical AIC. Advanced imaging techniques, such as cardiac PET with novel tracers targeting inflammation, may enhance early detection. Both traditional cardioprotective strategies and novel anti-inflammatory therapies show potential in preventing and treating AIC. Understanding the inflammatory mechanisms involved in AIC provides new opportunities for early detection and targeted cardioprotective strategies in patients undergoing anthracycline treatment and informs our understanding of other forms of chemotherapy-induced cardiotoxicity.

Nonlinear association of sex hormone-binding globulin levels and chronic kidney disease, an analysis based on the National Health and Nutrition Examination Survey (NHANES) 2013–2016

Studies on the relationship between serum sex hormone-binding globulin (SHBG) levels and chronic kidney disease (CKD) remain limited and inconclusive. Therefore, this study aims to evaluate the effects of SHBG on CKD in a nationally representative population. We included a total of 7713 adults from the National Health and Nutrition Examination Survey (NHANES) conducted between 2013 and 2016. Multivariate logistic regression models were utilized to evaluate the association between SHBG levels and CKD, and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Additionally, we employed a restricted cubic-spline regression model to explore potential dose-response associations. Among the participants, 4030 (52.2%) were women, and CKD was observed in 13.50% (1043/7713). After adjusting for various variables, SHBG levels were found to be associated with the risk of CKD (OR: 1.24; 95% CI: 1.11–1.38), indicating a 24% higher risk of CKD for SHBG levels (log2-transformed). A comparison between the highest quartile (Q4) and the lowest quartile (Q1) of SHBG levels revealed an OR of 1.51 (95% CI: 1.17–1.95) for CKD prevalence. Notably, while the association between SHBG and the risk of CKD disappeared when SHBG levels were <46.1 nmol/l, it existed when SHBG levels exceeded 46.1 nmol/l. Taken together, these findings indicate nonlinear correlations between serum SHBG levels and CKD, with the inflection point occurring at approximately 46.1 nmol/l, which suggest that SHBG levels could serve as a useful marker for assessing CKD risk, with potential applications in early detection and management strategies.

Reassessment of arterial versus venous perfusion of diabetic retinal neovascularization using ultrawide-field fluorescein angiography.

The purpose of this study was to assess whether diabetic NV is perfused by the arterial or the venous circulation. This is a retrospective, consecutive case series evaluating patients with proliferative diabetic retinopathy (PDR) imaged with ultrawide-field (UWF) fluorescein angiography (FA). Areas of neovascularization elsewhere (NVE) and neovascularization of the disc (NVD) were assessed. Perfusion was defined as arterial, arteriovenous, or venous if the area of diabetic neovascularization (NV) began to hyperfluoresce either prior, during, or after laminar venous flow, respectively. A total of 180 eyes from 176 patients with 928 NV were identified (830 NVE, 98 NVD). Of those, 5.1% of NVE were classified as arterial and 58.2% of NVD were classified as arterial. The remaining NV were classified as arteriovenous except for a small subset (6.1%) which were indeterminate. None of the NV were classified as venous. Noteworthy examples demonstrated NV that nearly fully perfused prior to any detectable fluorescence within nearby veins as well as clear shunting of blood from a feeding artery to a draining vein. UWF FA images suggest that some NV is perfused by retinal arteries. This may be useful in devising strategies for early detection and treatment of NV precursors. What is known • Diabetic retinal neovascularization has long been thought to be perfused by the retinal venous circulation. • Vascular endothelial growth factor has been shown to play key roles in both angiogenesis and arteriogenesis. What is new • Ultrawide-field fluorescein angiography demonstrates that at least some diabetic neovascularization is perfused by the retinal arterial circulation. • This supports the hypothesis that diabetic neovascularization may arise from arterially-perfused intraretinal microvascular abnormalities in the capillary bed.

The development of Liver Research Cymru, a new partnership to increase hepatology research activity in Wales

Background The incidence and severity of liver disease in the United Kingdom have increased over the last 20 years. Many patients present with advanced disease with limited treatment options and subsequently high morbidity and mortality. There was also a significant correlation with deprivation. Strategies that support the earlier detection of liver disease are paramount to reverse this trend. Despite significant progress in terms of novel pathways, the optimal strategy for early detection of liver disease remains unknown. Novel ways to tackle the deprivation gradient and reduce health inequalities are urgently required. Methods Clinical research has an enormous role to play both in terms of identifying the true scale of this challenge, where current gaps exist, and to identify the optimal early detection strategies and their implementation. WE therefore established Liver Rsearch Cymru (LRC) a multi-disciplinary collaboration that seeks to maximise the benefits from our existing data sources and clinical networks and increase the output of hepatology research in Wales. Results LRC has developed the first Wales wide research collaborative. We have successfully collaborated with the Secure Anonymised Information Linkage (SAIL) data resource to develop a greater understanding of liver disease burdens through comprehensive analysis of primary and secondary care data. We are now using this information to evaluate the effectiveness of local early detection pathways and to identify the scale of delays in diagnosis with a view to addressing this important care gap. Conclusion LRC has successfully brought together patients. Hepatologists and population/primary care academics to better understand current discrepancies in the early diagnosis of liver disease in Wales. In addition, it has laid a foundation for future research work based both on our preliminary findings and allowed us to collaborate with other more established liver disease research groups.