Early Prevention Research Articles

The Influence of Regional Specialization in Agriculture on Farmers’ Pest Control Behaviors Based on a Dual Examination of Control Strategies and Control Costs

The pest control behaviors of agricultural producers are crucial not only for effectively managing pests and diseases but also for ensuring the sustainable development of agricultural production and the environment. Regional specialization in agriculture, as a typical method to optimize planting structure, influences farmers’ control behaviors through dual mechanisms. However, existing research has largely overlooked this issue. This paper systematically examines the influence and mechanisms of agricultural regional specialization on farmers’ pest control strategies and costs. Using village tracking research data and farmer data from the Jiangsu, Sichuan, and Jilin provinces of China over 15 years, the study employs fixed-effects models and the instrumental variable method to provide empirical evidence. The research results indicate that by reducing biological diversity, which exacerbates the occurrence and damage of pests and diseases, and increasing the homogeneity of cropping structures, the development of regional specialization in agriculture prompts farmers to shift their control strategy from “ex post treatment” to “ex ante prevention” and has increased the control costs. The policy implication is that farmers should be encouraged to practice moderate crop rotation in rapidly increasing regional specialization. Additionally, strengthening real-time monitoring of pest and disease dynamics is essential to guide farmers in early prevention and timely control.

Screening for mitochondrial tRNA variants in 200 patients with systemic lupus erythematosus

Introduction: Systemic lupus erythematosus (SLE) is a common autoimmune disease with unknown etiology. Recently, a growing number of evidence suggested that mitochondrial dysfunctions played active roles in the pathogenesis of SLE, but its detailed mechanism remains largely undetermined. The aim of this study was to analysis the frequencies of mitochondrial tRNA (mt-tRNA) variants in Chinese individuals with SLE. Methods: We carried out a mutational screening of mt-tRNA variants in a cohort of 200 patients with SLE and 200 control subjects by PCR-Sanger sequencing. The potential pathogenicity of mt-tRNA variants were evaluated by phylogenetic conservation and haplogroup analyses. In addition, trans-mitochondrial cybrid cell lines were established, mitochondrial functions including ATP, reactive oxygen species (ROS), mitochondrial DNA (mtDNA) copy number, mitochondrial membrane potential (MMP), superoxide dismutase (SOD) and mt-RNA transcription were analyzed in cybrids with and without these putative pathogenic mt-tRNA variants. Results: We identified five possible pathogenic variants: tRNAVal G1606A, tRNALeu(UUR) A3243G, tRNAIle A4295G, tRNAGly T9997C, and tRNAThr A15924G that only found in SLE patients but were absent in controls. Interestingly, these variants were located at extremely conserved nucleotides of the corresponding tRNAs and may alter tRNAs’ structure and function. Furthermore, cells carrying these tRNA variants had much lower levels of ATP, mtDNA copy number, MMP and SOD than controls, by contrast, the levels of ROS increased significantly (p<0.05 for all). Furthermore, a significantly reductions in mt-ND1, ND2, ND3, ND5 and A6 mRNA expression were observed in cells with these mt-tRNA variants, while compared with controls. Thus, failures in tRNAs metabolism caused by these variants would impair mitochondrial translation, and subsequently lead to mitochondrial dysfunction that was involved in the progression and pathogenesis of SLE. Conclusions: Our study suggested that mt-tRNA variants were important causes for SLE, screening for mt-tRNA pathogenic variants was recommended for early detection and prevention for this disorder.

OGC SO02 - Analysis of routine upper gastrointestinal endoscopy referrals and outcomes in a single tertiary service

Abstract Background Routine (category 3/4) upper gastrointestinal endoscopies (UGIE) constitute a significant proportion of endoscopy workload in the National Health Service. Referrals are varied and there are opportunities for service improvement to reduce clinician burden and improve patient outcomes. This is of particular relevance to the early detection and prevention of cancer. This work aimed to analyse routine UGIE referrals and subsequent endoscopies in a large tertiary service to identify quality improvement opportunities within the health board. Method Referral indications for all males over 50 years awaiting routine UGIE in the health board on 02/03/2023 were reviewed. Referrals were categorised into 7 groups based on primary presentation and indication for UGIE; “Liver/variceal”, “Gastric”, “Oesophageal”, “Anaemia”, “Dysphagia”, “Tissue transglutaminase (TTG) positive” or “Other”. Data on findings, biopsy, and follow-up were gathered where UGIE was subsequently performed. To analyse routine cases only, patients referred for anaemia or dysphagia were excluded from final analysis. Results 471 records were reviewed and 332 patients included in final analysis; 210 had undergone UGIE at assessment point (3 records unavailable), with 99 waiting and 23 died/did not attend/declined. The most common referral indications were “Gastric” (41.6%), “Liver” (29.2%), and “Oesophageal” (21.4%) (n=207). 84 were excluded due to anaemia/dysphagia. At UGIE, 6.3% identified Barrett's oesophagus/malignancy across all groups with 1 case of new malignancy. 80.2% received medical/conservative management following their scope. Conclusion While pathology was identified at routine UGIE, a large number of procedures were required to identify this and there was no Barrett's oesophagus rich group. We have identified opportunities for improvement in the delivery of routine UGIE service in the health board which may reflect nationally. These include altered vetting practices and potential UGIE-saving procedures including cytosponge.

The roles of the gut microbiota, metabolites, and epigenetics in the effects of maternal exercise on offspring metabolism

Metabolic diseases, including obesity, dyslipidemia, and type 2 diabetes, have become severe challenges worldwide. The developmental origins of health and disease (DOHaD) hypothesis suggests that an adverse intrauterine environment can increase the risk of metabolic disorders in offspring. Studies have demonstrated that maternal exercise is an effective intervention for improving the offspring metabolic health. However, the pathways through which exercise works are unclear. It has been reported that the gut microbiota mediates the effect of maternal exercise on offspring metabolism, and epigenetic modifications have also been proposed to be important molecular mechanisms. Microbial metabolites can influence epigenetics by providing substrates for DNA or histone modifications, binding to G-protein coupled receptors to affect downstream pathways, or regulating the activity of epigenetic modifying enzymes. This review aims to summarize the intergenerational effect of maternal exercise and proposes that gut microbiota-metabolites-epigenetic regulation is an important mechanism by which maternal exercise improves offspring metabolism, which may yield novel targets for the early prevention and intervention of metabolic diseases.

Assessment of potential drug-drug interactions in hospitalized patients with infectious diseases: an experience from a secondary care hospital

Background Polypharmacy is common among hospitalized patients with infectious infections owing to comorbidities or concomitant illnesses. This raises the likelihood of drug-drug interactions and creates uncertainty for healthcare providers. This study aimed to assess the potential drug-drug interactions (pDDIs) among hospitalized patients with infectious diseases in a secondary care hospital. Methods A prospective observational study was conducted in the internal medicine ward for six months after the ethics committee’s approval. Data were collected from patient case records, and prescriptions were screened for pDDIs from a portable electronic physician information database (PEPID) resource analyzed using SPSS, version 27.0. Results In total, 148 patient case records were analyzed, and 549 pDDIs were identified, with 66.8% having at least one or more DDIs. The mean number of drug interactions was 3.70 ± 4.58 per prescription. The most frequently encountered drug interactions were drug combinations such as bisoprolol with atorvastatin and aspirin with tazobactam/piperacillin. Bivariate analysis showed that age, comorbidities, length of hospital stay, and the number of drugs prescribed were risk factors associated with DDIs (p<0.05). In the multiple binary logistic regression analysis, DDIs were significantly associated with comorbidities and the number of prescribed medications (p<0.0001). Conclusions This study observed the prevalence of DDIs in hospitalized patients with infectious diseases of ‘moderate’ severity. Prescription screening using a drug information database assists in early identification and prevention of DDIs, enhancing drug safety and quality of patient-centered care.

Abstract 4131796: Non-Contact Biometric System for Early Detection of Hypertension and Diabetes Using AI and RGB Imaging

Introduction: In recent years, the development of wearable devices and bioinformation analysis applications utilizing smartphone sensors has seen significant advancements. Despite these technological strides, their adoption and sustained use remain limited to health-conscious individuals. The general populace, particularly those indifferent to health management, stands to miss out on the potential benefits of wearable technologies due to a lack of engagement. This disconnect underscores the necessity for more accessible health monitoring solutions. Research Questions and Goals: This study aims to bridge the gap in health monitoring accessibility by introducing a system capable of non-invasive, non-contact acquisition of biometric information. Such a system seeks to democratize the early detection and prevention of diseases across various demographics. Methods and Results: A prospective cohort clinical study was conducted in a hospital setting with approximately 200 consenting patients and healthy controls. Images of the subjects' faces and hands were captured with a high-speed camera, and blood pressure measurements were taken simultaneously for correlation. A machine learning algorithm was developed to analyze skin blood flow and spectral features from these images to identify potential diseases. The study specifically focused on early detection of hypertension and diabetes. Hypertension was categorized for individuals with systolic blood pressure ≥115 mmHg or diastolic blood pressure ≥75 mmHg. Diabetes was identified in subjects with HbA1c levels ≥6.5 or those previously diagnosed. The algorithm's performance in detecting hypertension showed a 94.2% in alignment with the AHA guidelines for stage1 hypertension, based on pulse wave features. For a subset including 40% early hypertension cases, accuracy rates were 86.2% for 30-second data segments and 80.9% for 5-second segments. For diabetes detection, the application of the algorithm to video data achieved a 75.3%, utilizing blood flow patterns as markers. Hypertension and diabetes were analyzed using different features. Conclusions: The integration of AI algorithms with video data analysis of skin and blood vessels demonstrates a promising avenue for the non-contact, early detection of hypertension and diabetes. This approach not only offers a viable non-contact monitoring technology, but also represents a significant leap towards inclusive, accessible health care prevention and management strategies.

Abstract 4141446: Sodium Glucose Co-transporter 2 (SGLT2) Inhibitors Promote Resiliency to High Pressure Stress in the Human Microvasculature

Emerging evidence suggests that vascular stress from cardiovascular-related co-morbidities promotes microvascular dysfunction, a key component in the development of heart failure with preserved ejection fraction. The sodium glucose co-transporter 2 (SGLT2) inhibitor empagliflozin has been shown to reduce both morbidity and mortality associated with heart failure with preserved ejection fraction, however the full scope of influence of this therapy on human microvascular function remains unknown. We hypothesized that pre-treatment of isolated human microvessels with empagliflozin will prevent stress-induced endothelial dysfunction as evidenced by preserving both the magnitude of flow-induced dilation (FID) as well as the ability to dilate to nitric oxide. Human resistance arterioles (80-250µm) from healthy adults (defined as patients with ≤1 risk factor for cardiovascular disease) were dissected from discarded surgical adipose tissue and treated with empagliflozin (1µM), or vehicle control (ethanol) for 16-20 hours prior to the flow experiment. Vessels were cannulated for videomicroscopy and subjected to high intraluminal pressure (150mmHg, 30 min), an acute stress known to induce endothelial dysfunction. Vessels were pre-constricted with endothelin-1 prior to initiation of flow. A nonlinear logistic regression was used to determine differences between curves. Compared to vehicle control, vessels pre-treated with empagliflozin (1µM ) exhibited nitric oxide-dependent FID as dilation was impaired in the presence of the nitric oxide synthase inhibitor L-NAME (EC50 Control: 10.7 vs L-NAME 83.45, p=0.0107). This data suggests that empagliflozin, an SGLT2 inhibitor, promotes microvascular resilience to stress via preservation of nitric oxide-mediated FID. The ability to elicit stress resilience may explain in part some of the cardiovascular benefits associated with SGLT2 inhibitors and may offer unique opportunities for early intervention or prevention of microvascular dysfunction associated with comorbidities that contribute to heart failure with preserved ejection fraction.

The Impact of Childhood Maltreatment Timing on Adolescents’ Depression and Anxiety

This study examined the relationship between the timing of childhood maltreatment and depression and anxiety in adolescents. Using prospective data from 867 children and their caregivers from the Longitudinal Study of Child Abuse and Neglect (LONGSCAN), the effects of early childhood maltreatment (ages 0–5.99) and middle childhood maltreatment (ages 6–11.99) on depression and anxiety at age 16 were compared. Early childhood and middle childhood maltreatment were measured in three ways, including latent class analysis. Findings from multiple regression analysis revealed that only early childhood maltreatment significantly increased adolescents’ depression and anxiety, even after controlling for multiple covariates such as negative life events, social support, and caregiver depression. Strategies to improve early childhood maltreatment prevention and reduce adolescents’ depression/anxiety are also discussed.

Prevalence of Adverse Childhood Experiences in Child Population Samples

ImportanceExposure to adverse childhood experiences (ACEs) before the age of 18 years is a major contributor to the global burden of disease and disability.ObjectiveTo meta-analyze data from samples with children 18 years or younger to estimate the average prevalence of ACEs, identify characteristics and contexts associated with higher or lower ACE exposure, and explore methodological factors that might influence these prevalence estimates.Design, Setting, and ParticipantsStudies that were published between January 1, 1998 and February 19, 2024, were sourced from MEDLINE, PsycINFO, CINHAL, and Embase. Inclusion criteria required studies to report the prevalence of 0, 1, 2, 3, or 4 or more ACEs using an 8- or 10-item ACEs questionnaire (plus or minus 2 items), include population samples of children 18 years or younger, and be published in English. Data from 65 studies, representing 490 423 children from 18 countries, were extracted and synthesized using a multicategory prevalence meta-analysis. These data were analyzed from February 20, 2024, through May 17, 2024.Main Outcomes and MeasuresACEs.ResultsThe mean age of children across studies was 11.9 (SD, 4.3) years, the age range across samples was 0 to 18 years, and 50.5% were female. The estimated mean prevalences were 42.3% for 0 ACEs (95% CI, 25.3%-52.7%), 22.0% for 1 ACE (95% CI, 9.9%-32.7%), 12.7% for 2 ACEs (95% CI, 3.8%-22.3%), 8.1% for 3 ACEs (95% CI, 1.4%-16.8%), and 14.8% for 4 or more ACEs (95% CI, 5.1%-24.8%). The prevalence of 4 or more ACEs was higher among adolescents vs children (prevalence ratio, 1.16; 95% CI, 1.04-1.30), children in residential care (1.26; 95% CI, 1.10-1.43), with a history of juvenile offending (95% CI, 1.29; 1.24-1.34), and in Indigenous peoples (1.63; 95% CI, 1.28-2.08), as well as in studies where file review was the primary assessment method (1.29; 95% CI, 1.23-1.34). The prevalence of 0 ACEs was lower in questionnaire-based studies where children vs parents were informants (0.85; 95% CI, 0.80-0.90).ConclusionsIn this study, ACEs were prevalent among children with notable disparities across participant demographic characteristics and contexts. As principal antecedent threats to child and adolescent well-being that can affect later life prospects, ACEs represent a pressing global social issue. Effective early identification and prevention strategies, including targeted codesigned community interventions, can reduce the prevalence of ACEs and mitigate their severe effects, thereby minimizing the harmful health consequences of childhood adversity in future generations.

EPCO-56. INHERITED PREDISPOSITION TO ADULT GLIOMAS: OVERVIEW OF THE CURRENT CLINICAL PRACTICE AND FUTURE RECOMMENDATIONS

Abstract Gliomas are the most common adult primary malignant brain tumor and occur in ages 45-65 years old. While most gliomas are sporadic in nature, a small portion is related to cancer predisposition syndromes (CPS), such as Li Fraumeni or Lynch syndromes. Given that 5–10% of patients will have a family history of glioma, there is currently an effort in identifying germline variants associated with gliomas. Additionally, with the advent of somatic tumor testing, it is possible to pick up suspected germline mutations in genes that cause CPS. Our experience includes a 32-year-old patient diagnosed with astrocytoma IDH mutant, Grade 2 who was found to have a BRAC1 mutation on somatic brain tumor testing. 10 years later, the patient was found with metastatic ovarian cancer and a germline BRAC1 mutation. Early identification of CPS can lead to early detection or prevention of malignancies in affected patients and relatives. However, gliomas are rarely the primary or presenting tumor of CPS, and guidance of CPS screening for these individuals is still lacking. Due to the increasing interest and importance of CPS testing in patients with glioma we have developed a collaborative protocol between our neuro-oncologists and genetic counselors aso that patients have access to germline testing. We propose that all patients with glioma at age of 50 or under, patients with strong family history of cancer including gliomas, and patients with suspected germline mutations based on tumoral somatic mutational profile should be referred to the genetic counselors. Our preliminary findings include 8 patients who completed germline genetic testing. Of these, one patient tested positive for a BRCA1 pathogenic variant. We are planning to continue to collect this data to better inform clinical practice.

The Emergence of Saliva as a Diagnostic and Prognostic Tool for Viral Infections

Saliva has emerged as a promising diagnostic fluid for viral infections, enabling the direct analysis of viral genetic material and the detection of infection markers such as proteins, metabolites, microRNAs, and immunoglobulins. This comprehensive review aimed to explore the use of saliva as a diagnostic tool for viral infections, emphasizing its advantages and limitations. Saliva stands out due to its simplicity and safety in collection, along with the convenience of self-collection without the need for healthcare supervision, while potentially being comparable to urine and blood in terms of effectiveness. Herein, we highlighted the significant potential of saliva in assessing viral loads and diagnosing viral infections, such as herpesviruses, HPV, PyV, TTV, SARS-CoV-2, and MPXV. The detection of viral shedding in saliva underscores its utility in early diagnosis, the monitoring of infection progression, and evaluating treatment responses. The non-invasive nature of saliva collection makes it an appealing alternative to more invasive methods, promoting better patient compliance and facilitating large-scale screening and surveillance. As such, we further highlight current evidence on the use of saliva as a prognostic tool. Although a significant amount of data is already available, further investigations are warranted to more comprehensively assess the added benefit from the utilization of salivary biomarkers in the clinics. Salivary biomarkers show great promise for the early detection and prevention of viral infection complications, potentially improving disease management and control at the population level. Integrating these non-invasive tools into routine clinical practice could enhance personalized healthcare strategies and patient outcomes. Future studies should focus on establishing standardization protocols, validating the accuracy of salivary diagnostics, and expanding clinical research to enhance the diagnostic and monitoring capabilities of salivary biomarkers.

Microbiome-producing SCFAs are associated with preterm birth via trophoblast function modulation

ABSTRACT Although preterm birth (PTB) is one of the major causes of perinatal mortality and neonatal morbidity, little is known about its complex etiology. An abnormal cervicovaginal microbiome during pregnancy is associated with an increased risk of PTB. The cervicovaginal microbiota and its active metabolites, such as short-chain fatty acids (SCFAs), might be effectively used to predict and diagnose PTB. However, the roles of these proteins and the underlying mechanisms involved remain elusive. We conducted 16S rRNA gene sequencing and used a targeted metabolomics approach to study cervicovaginal swabs obtained from 51 singleton pregnancies and 52 twin pregnancies in the second trimester. Next, functional in vitro experiments were performed to investigate the roles and mechanisms of SCFAs in placental trophoblast cells (HTR8/SVneo cells). Significant cervicovaginal microbiome dysbiosis, characterized by a substantial reduction in the abundance of lactobacilli and overgrowth of anaerobes, was revealed in the second trimester and was strongly associated with subsequent PTB ( P = 0.036). Among the paired samples ( n = 103), acetic acid was significantly greater in the preterm group than in the term group ( P = 0.047). Data obtained from integrated gas chromatography‒mass spectrometry and 16S RNA studies revealed metabolites that were distinctly associated with particular microbial communities. Gardnerella vaginalis was the species most positively associated with acetic acid content. In addition, we identified a marker set consisting of the pregnancy type, acetic acid concentration, and community state type to accurately diagnose PTB. Acetate was associated with increased interleukin (IL)-8 and IL-6 levels and extravillous trophoblast cell migration and invasion through the activation of the extracellular signal-regulated kinase 1/2 signaling pathway in HTR8/SVneo cells. Cervicovaginal microbiota dysbiosis is an important etiological factor of PTB. The cervicovaginal microbiota and its active metabolites can be efficiently used to predict and diagnose PTB. Our findings enrich the microbiota–placenta axis theory and contribute to the development of microecological products for pregnancy. IMPORTANCE Preterm birth (PTB) is a leading cause of infant mortality and long-term health issues, affecting millions of families worldwide. Despite its prevalence, the exact causes of PTB remain unclear. Our study reveals that certain bacteria and their metabolic byproducts in the cervicovaginal environment, specifically short-chain fatty acids (SCFAs), are linked to the risk of preterm birth. By analyzing samples from pregnant women, we found that an imbalance in the vaginal microbiota and increased levels of SCFAs are associated with changes in cells that can lead to early labor. This research provides new insights into how the microbiome influences pregnancy outcomes and highlights potential biomarkers for predicting preterm birth. Understanding these microbial influences could lead to innovative strategies for early diagnosis and prevention, ultimately improving maternal and infant health.

A Narrative Review of Ethical Issues in the Use of Artificial Intelligence Enabled Diagnostics for Diabetic Retinopathy

ABSTRACTIntroductionDiabetic retinopathy is one of the leading causes of avoidable blindness among adults globally, and screening programmes can enable early diagnosis and prevention of progression. Artificial intelligence (AI) diagnostic solutions have been developed to diagnose diabetic retinopathy. The aim of this review is to identify ethical concerns related to AI‐enabled diabetic retinopathy diagnostics and enable future research to explore these issues further.MethodsThis is a narrative review that uses thematic analysis methods to develop key findings. We searched two databases, PubMed and Scopus, for papers focused on the intersection of AI, diagnostics, ethics, and diabetic retinopathy and conducted a citation search. Primary research articles published in English between 1 January 2013 and 14 June 2024 were included. From the 1878 papers that were screened, nine papers met inclusion and exclusion criteria and were selected for analysis.ResultsWe found that existing literature highlights ensuring patient data has appropriate protection and ownership, that bias in algorithm training data is minimised, informed patient decision‐making is encouraged, and negative consequences in the context of clinical practice are mitigated.ConclusionsWhile the technical developments in AI‐enabled diabetic retinopathy diagnostics receive the bulk of the research focus, we found that insufficient attention is paid to how this technology is accessed equitably in different settings and which safeguards are needed against exploitative practices. Such ethical issues merit additional exploration and practical problem‐solving through primary research. AI‐enabled diabetic retinopathy screening has the potential to enable screening at a scale that was previously not possible and could contribute to reducing preventable blindness. It will only achieve this if ethical issues are emphasised, understood, and addressed throughout the translation of this technology to clinical practice.

Evaluating Tobacco Cessation Readiness in OPMD Patients Using the Transtheoretical Model in a tertiary care setting in Northeast India

Background: Oropharyngeal cancers pose significant global health challenges and addressing public awareness, early symptoms, and risk factors, alongside promoting tobacco cessation among individuals with potentially malignant oral disorders, is crucial for reducing the disease burden.Objective: Evaluating the degree of public knowledge of oral malignancy & OPMD, initial signs & risk factors amongst patients going to a dental college in North East India, as well as readiness to quit tobacco amongst OPMD patient.Methods: This cross-sectional investigation was undertaken at the Department of Public Health Dentistry, Tertiary care Hospital in Guwahati. 200 participants aged 15-65 years who consented were surveyed using a self-administered questionnaire. Collected data underwent thorough checks for completeness and accuracy. To determine the odd's ratio (OR) and to summarise the data, descriptive & inferential statistics were used. To test the relationship, data were dichotomised. Oral lesions present or absent; behavioural phases were divided into two categories: (preparation + action) & (precontemplation + contemplation). P < 0.05 was used as the statistical significance threshold.Results: Most participants were in the contemplation stage regarding tobacco's risks, neglecting other risk factors like alcohol & inadequate dental hygiene for oral malignancy/OPMD development.Conclusions: The lack of knowledge of oral malignancy & potentially malignant disorders (OPMDs) amongst North Eastern Indian communities, underscores the immediate demand for targeted education and health promotion campaigns. Emphasizing early symptom recognition, risk factors, and prevention measures, tailored to diverse communication preferences, is crucial.

Feasibility and challenges in sustaining a community based surveillance system in post-Ebola Sierra Leone

BackgroundIn outbreak-prone settings, community-based surveillance (CBS) systems can alert health authorities to respond in a timely manner where suspected cases of disease are being reported. After the 2014–2016 Ebola outbreak, the WHO and other stakeholders supported the establishment of CBS in Sierra Leone, for which community health workers (CHW) were trained to collect and report symptoms data of 11 priority health conditions in their communities. Our study objective was to assess feasibility and challenges to sustain CBS in a low resource setting as part of a World Bank evaluation of Sierra Leone’s Ministry of Health and Sanitation’s (MoHS) CBS and electronic Integrated Disease Surveillance & Response (eIDSR) systems.MethodsIn 2019 we conducted a mixed methods assessment consisting of a household incidence survey, health facility survey, household case verification survey, a costing analysis, and in-depth interviews and focus group discussions with key stakeholders of the CBS system in eight chiefdoms of 4 purposefully selected districts in Sierra Leone. The study period for primary data collection was February through April 2019. We also conducted secondary data analysis of surveillance data in DHIS2 of all 32 chiefdoms.ResultsIn districts where CBS was ‘fully functional’, the number and type of CBS alerts corresponded to the number and type of diseases reported through facility based eIDSR system in the same period. However under-reporting of diarrhea and measles suspects from the community still appeared to occur, and reporting deteriorated when primary health care staff including CHWs reported the stoppage of stipends. The annual budget impact for CBS was estimated at 4.4 million USD in 2018. The majority of costs were made at community level (73%) compared to regional (0.3%), primary health unit (21%), district (4%) and national (2%) level. The most important costs drivers were training of CHWs (59% of total costs) and salaries (including stipends of the CHWs) of human resources (15%). Barriers included sustainable financing of human resources, internet connectivity, as well as limited trainings and supportive supervision, and unsupported transportation costs for CHWs and peer supervisors (PS). CHWs and community members reported that communities are more willing to share information about health issues compared to the pre-CBS implementation period.ConclusionsThe similarity between CBS and IDSR reports support the possibility that CBS increases the sensitivity of disease surveillance to the level of the community, which would enable local authorities to take early prevention measures when and where impact will be the greatest. Qualitative interviews suggest that CBS has improved the interface between the community and primary level of the health system. However if the barriers to sustainability are left unaddressed, opportunities for CBS to prevent disease outbreaks will go unrealized.

Skeletal muscle reactive oxygen species and microvascular endothelial function in age‐related hypertension: a study protocol using a microdialysis technique

AbstractIncreased reactive oxygen species (ROS) generation and microvascular endothelial disruptions occur with natural ageing, but often transpire before the detection of cardiometabolic conditions including hypertension. Age‐related increases in blood pressure are driven by complex systemic changes with poorly understood integrated mechanisms. The deconditioning experienced by ageing skeletal muscle from mid‐life is associated with reduced microvascular blood flow and increased peripheral resistance, suggesting that vasodilatory decrements in the muscle may precede the age‐related increases in blood pressure. Structural and functional changes within the vascular and skeletal muscle systems with advancing age can influence redox homeostasis, and vice versa, further compounding microvascular endothelial dysfunction. Therefore, comparisons between the microvascular environments of healthy and hypertensive cohorts can provide insights into the changes that occur during significant periods of functional decline. This comprehensive study protocol describes a microdialysis technique to assess the interactions of microvascular health and functional changes in the muscle, which currently cannot be otherwise addressed. Here, we detail an experimental protocol to simultaneously detect skeletal muscle ROS (H2O2 and indirect O2−), determine nutritive blood flow and assess microvascular endothelial function in response to acetylcholine stimulation. We expect that healthy middle‐aged individuals should not have increased ROS generation in the muscle at rest, compared to their hypertensive or older counterparts, but may exhibit perturbed microvascular function. The described technique allows for intricate exploration of microvascular physiology that will provide a critically novel insight into benchmarking potential age‐related mechanisms involved in the development of age‐related hypertension, and aid in early identification and prevention. imageKey points Increased reactive oxygen species (ROS) production and microvascular endothelial dysfunction precede the onset of age‐related cardiometabolic and vascular conditions such as hypertension. The profound structural and functional changes that occur within the vasculature and in skeletal muscle from middle age prompt a need to mechanistically explore the microvascular environment in healthy and hypertensive individuals. Using a novel microdialysis technique, we detail an experimental protocol to simultaneously detect skeletal muscle ROS (H2O2 and indirect O2−), determine nutritive blood flow and assess microvascular endothelial function in response to acetylcholine stimulation. With this technique and study protocol, we can reveal functional insights into potential perturbations in ROS generation at rest and the microvascular endothelium, which play important roles in the development of age‐related hypertension.

Enhanced Fuzzy Score-Based Decision Support System for Early Stroke Prediction

According to the Global Health Observatory (GHO), stroke ranks second worldwide in causing dementia, right after Alzheimer's disease. The mortality rate linked to dementia resulting from stroke is high because symptoms are often recognized late, and stroke can be misinterpreted as other brain disorders. Early detection and diagnosis of stroke is crucial. Therefore, increasing awareness of stroke symptoms and implementing preventive measures becomes imperative. Prompt intervention by healthcare professionals can improve outcomes and reduce long-term complications of stroke. The research introduces an innovative approach for early stroke prediction using a fuzzy scoring-based Decision Support System. This approach encompasses three main modules: Mind-map based Data Modeling, Fuzzy scoring computing, and ML-based Decision System. By incorporating fuzzy logic, the approach extracts valuable knowledge from imprecise and uncertain data. Combining the fuzzy stroke risk model with a machine learning-based decision support system aims to enhance stroke prediction accuracy and improve preventive measures and patient outcomes. The approach's effectiveness was validated using real clinical data and tested with various machine learning classifiers, including K-Nearest Neighbour (KNN), Logistic Regression (LR), Decision Tree (DT), Artificial Neural Network (ANN), and Support Vector Machine (SVM). The results showed a strong correlation between stroke cases and computed risk-scoring values. In comparison to predictions without fuzzy scoring and other related works, the stroke risk prediction using the proposed approach demonstrated higher accuracy, making it a promising method for early stroke detection and prevention.

Lipid Accumulation Product and Cardiometabolic Index as Effective Tools for the Identification of Athletes at Risk for Metabolic Syndrome

Introduction: Metabolic syndrome (MS) is a growing global public health concern that is associated with increased risk for cardiovascular events, even in athletes. The lipid accumulation product (LAP) index and cardiometabolic index (CMI) have been shown to be efficient markers of MS in the general population; its applicability in athletes has not been discussed yet. We aimed to assess the role of LAP and CMI in predicting MS in athletes. Methods: We retrospectively enrolled 793 Olympic athletes practicing different sporting disciplines (power, skill, endurance, and mixed), classified arbitrarily into no risk (NR), low risk (LR), high risk (HR), or MS if they had 0, 1, 2, or 3 criteria for MS, respectively. Evaluations included a calculation of the LAP index, CMI, anthropometric measurements, and clinical and laboratorial variables. Results: Among our population, only 0.8% reached the criteria for MS, 9.1% were at HR for MS, 37.8% were defined as LR, and 52.3% had NR. Significant differences in anthropometric parameters and the principal components of MS criteria (blood pressure, lipidic profile, glycemia) were reported predominantly in HR athletes and those with MS (p < 0.0001). LAP and CMI presented linearly increasing values from individuals with NR to those with MS (p < 0.0001). In addition, HR and MS athletes were classified as “likely MS” (9.8%) and LR and NR athletes as “unlikely MS” (90.2%). After adjusting for potential confounders, LAP ≥ 34.66 and CMI ≥ 0.776 emerged as independent predictors for MS in the overall cohort (Hazar Ratio (HR) 7.22 [3.75–13.89], p < 0.0001, and HR 5.37 [2.96–9.73], p < 0.0001, respectively). The ROC curve revealed that these cut-offs in the general population predict MS with an area under the curve (AUC) of 0.80 and 0.79, respectively, for LAP and CMI. However, gender-related cut-offs seem to be more precise in predicting MS (LAP ≥ 38.79 for male, LAP ≥ 14.16 for female, and CMI ≥ 0.881 for male and ≥0.965 for female). Conclusion: The ROC curve analyses of LAP and CMI showed good diagnostic accuracy in predicting MS among athletes, despite the low prevalence of MS in our sample. Thus, these indexes may be used to promote screening for primary prevention and early detection of athletes at risk for MS to establish an early prevention strategy. Larger prospective studies are necessary to validate their benefit in the general population.

Needs assessment for interprofessional education module on prevention and early detection of oral cancer among dental interns: a cross- sectional survey

BackgroundThe challenges associated with ensuring widespread system changes to enable early diagnosis and prevention of oral cancer could benefit from interprofessional practice. A needs assessment study was conducted to inform the Interprofessional Education and Collaborative Practice (IPECP) course related to oral cancer. The primary objectives of this study were 1) to establish a tool assess the knowledge attitude and practice (KAP) related to prevention and early detection of oral cancer of health professional students, and 2) to assess the same KAP of pre-licensure dental students. Additional objectives were to consider the possibility that dental students would demonstrate good scores related to early detection and prevention of oral cancer thus indicating their readiness for interprofessional learning and collaborative practice.MethodsTwo questionnaires were utilized for this study which included 1) Readiness for interprofessional learning was assessed using the pre- validated tool of Readiness for Interprofessional Learning Scale (RIPLS) 2) A questionnaire to assess the KAP related to early diagnosis and prevention of oral cancer which was developed, validated, and evaluated. Statistical analysis includes, descriptive statistics, Mann–Whitney U test, Ordered logistic regression and Probit analysis. p value was set at < 0.05.ResultsA total of 130 dental students (74.6% female) were included in the study. Mean scores related to KAP were 15.96 ± 1.394, 4.70 + 1.146, 7.02 ± 1.019 respectively. The mean score of RIPLS was 73.15 ± 15.961. The probability of overall samples to have good RIPLS scores was around 0.68 to 0.76 (Male 0.68—0.82 & Female 0.68 -0.74). The percentage of students having good knowledge score was 93.8%, good attitude score was around 54.6% and good practice score was around 90%.ConclusionKnowledge and practice related to prevention and early detection of oral cancer were scored highly. Attitude scores were lower in a relatively higher proportion of participants and needed to be addressed in the curriculum. RIPLS score indicates a positive attitude towards interprofessional learning.

Magnetoelastic Immunosensor for the Rapid Detection of SARS-CoV-2 in Bioaerosols.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a protein-coated, single-stranded RNA virus that parasitizes and infects primates, including humans. The current detection methods are mainly carried out using humans as a medium, such as a chest computed tomography (CT) examination, nucleic acid detection, antibody detection, and antigen detection. In addition, SARS-CoV-2 in bioaerosols is an important way of transmission and infection, which has attracted wide attention. In this paper, we simulate a sampling system of SARS-CoV-2 in bioaerosols and detect SARS-CoV-2 in bioaerosols by means of a magnetoelastic (ME) sensing device based on an Android intelligent terminal, which can directly detect SARS-CoV-2 in bioaerosols in a certain unit environment. This approach aims to achieve early detection and prevention. The experimental results show that the sampling system can successfully collect SARS-CoV-2 in bioaerosols. In the linear range of 5-20 ng/mL, the ME sensing detection system results closely match those of the calibration instrument (VNA), with goodness-of-fit values of 0.997 and 0.995, respectively. This work demonstrates that the ME sensing detection system proposed is stable, highly specific, real-time, rapid, and has certain reference values and feasibility.