BackgroundAcute disseminated encephalomyelitis (ADEM) is an autoimmune disease that typically follows a monophasic course and may affect any age group. The precise population-based incidence of ADEM is still unknown in most countries. In China, there is no ADEM surveillance system. The exact incidence of ADEM is difficult to estimate, and other epidemiological characteristics of ADEM are unknown. The purpose of this study is to investigate the epidemiological characteristics of ADEM in Nanchang, China.MethodsA retrospective investigation was conducted with ADEM patients admitted to second-level and third-level hospitals in Nanchang from 2008 to 2010, aiming to analyse the epidemiologic characteristics of ADEM in the population in Nanchang. ADEM patients, defined as patients who were diagnosed according to the consensus definition of ADEM provided by the International Pediatric MS Study Group, were enrolled in the study. The data were extracted from the ADEM patients’ medical records.ResultsForty-seven ADEM patients were investigated. The average annual incidence was 0.31/100,000; the incidence among males (0.31/100,000) was nearly equal to that among females (0.31/100,000). The median age of onset was 25.97 years old, and the peak incidence was observed in the 5- to 9-year-old age group (0.75/100,000), followed by the over-60 age group (0.55/100,000). ADEM occurs throughout the year, but it occurs most frequently in March (n = 7) and least frequently in April and July (both n = 2). The patient numbers are roughly even in the other months. In the 2 months before the onset of ADEM, 15 patients presented with a preceding infection, but none of the patients received a vaccination. An increased number of vaccination was not accompanied by a corresponding increased number of cases of ADEM.ConclusionsThe average annual incidence of ADEM was 0.31/100,000 in Nanchang. The incidence among males was nearly equal to that among females. The peak age of onset was 5–9 years old. The peak season of onset was not apparent. There was no evidence of an association between increased number of vaccines administered and number of cases of ADEM in Nanchang, China.

Background: Identifying unrecognized, potentially modifiable risk factors is essential for heart failure (HF) management.Methods: The Atherosclerosis Risk in Communities (ARIC) study was used for machine learning (ML) to establish the top 20 important variables as potential risk factors for HF. Multivariable Cox regression analysis was performed in an explorative manner to find independent factors for HF and Mendelian randomization (MR) analysis to address causality.Results: Of the 14,842 participants included in the ARIC analysis, 20.4% of participants (3,028) were identified as HF. The 20 variables with the highest importance selected by ML were creatinine, glucose, age, previous coronary artery disease (CAD), systolic blood pressure, fibrinogen, albumin, income, diabetes, magnesium, insulin, white blood cell, hemoglobin, sodium, education, phosphorus, diastolic blood pressure, protein-c, heart rate and body mass index (BMI). Cox regression analysis demonstrated 19 independently associated variables except sodium. MR analysis provided evidence supporting that genetically determined BMI, CAD, diabetes and education was causally associated with HF.Conclusions: The ML plus MR framework was useful in identifying important causal factors of HF. BMI, CAD, diabetes, and education not only served as excellent prognostic factors for HF, but therapeutics targeted at these factors were likely to prevent HF effectively.

Background: Circadian clock plays a critical role in synchronizing the inner molecular, metabolic and physiological processes to the environmental cues with a period of 24 h. Misalignment in the circadian rhythms leads to decreased adaptation and performance and increased risk of associated disorders. The non-24-h schedules and shift schedules are commonly used in maritime operations, both of which could result in disturbance of circadian rhythms.Methods: In this study, we recruited volunteers and conducted two experiments: in one experiment 15 subjects followed an 8-h on and 4-h off schedule (non-24-h schedule), and in the second experiment 12 subjects followed a 3-d rotary schedule with consecutive shift in sleep time (phase-changing schedule). The serum/blood biochemical variables were measured and the serum miRNAs of the volunteers in the second experiment were subjected to transcriptomic miRNA sequencing.Results: The results show both of the schedules caused comprehensive changes in the blood/serum biochemical variables. Notably, significant elevation in serum phosphate was observed in both experiments: 1.210 ± 0.141 in control and 1.330 ± 0.117 in recovery (P = 0.014) in the first experiment and 1.193 ± 0.152 in control and 1.343 ± 0.099 in recovery (P = 0.007) in the second experiment. In addition, a subset of serum miRNAs targeting genes involved in circadian rhythms, sleep homeostasis, phosphate metabolism and multiple critical physiological processes or pathways were identified in the second experiments.Conclusions: This study reveals that non-24-h and shift schedules lead to changes in a large spectrum of blood/serum biochemical variables due to circadian misalignment. Schedules with frequent shift may cause remarkable changes in serum miRNAs which are involved in multiple physiological pathways. These findings would help understand the deleterious effects of shift schedules and develop optimized strategy to enhance welfare and performance of the shift workers.

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BackgroundLittle is known about how the residential distance to the coast is associated with incident myocardial infarction (MI) and which mechanisms may explain the association. We aim to explore this association using data from a prospective, population-based cohort with unprecedented sample size and broad geographical coverage.MethodsThree hundred seventy-seven thousand three hundred forty participants from the UK Biobank were included. Results4,059 MI occurred during median 8.0 years follow-up. Using group (<1 km) as reference, group (20-50 km) was associated with a lower risk of MI (hazard ratio, HR 0.79, 95% CI 0.64-0.98) and a U-shaped relation between distance to the coast and MI was shown with the low-risk interval between 32 km and 64 km (Pnonlinear=0.0012). Using participants of the intermediate region (32-64 km) as a reference, participants of the offshore region (<32 km) and inland region (>64 km) were both associated with a higher risk of incident MI (HR 1.12, 95% CI 1.04-1.21 and HR 1.09, 95% CI 1.01-1.18, respectively). HR for offshore region (<32 km) was larger in subgroup with low total physical activity (<24 hours/week) (HR 1.24, 95% CI 1.09-1.42, Pinteraction= 0.043). HR for inland region (>64 km) was larger in subgroup in urban area (HR 1.12, 95% CI 1.03-1.22, Pinteraction=0.065) and in subgroup of high nitrogen dioxide air pollution (HR 1.29, 95% CI 1.11-1.50, Pinteraction=0.021).ConclusionWe found a U-shaped association between residential distance to the coast and incident MI, and the association was modified by physical activity, population density, and air pollution.