-
Russo McGrath posted an update 5 months, 4 weeks ago
To investigate the effect of myocardial injury on the prognosis of patients with severe or critical coronavirus disease 2019 (COVID-19).
Between February 10, 2020 and March 31, 2020, data of severe and critical COVID-19 patients were collected and retrospectively analyzed. Admission data included age, heart rates, mean arterial pressure, and myocardial injury markers including creatine kinase isoenzyme-MB (CK-MB), myoglobin, N-terminal pro-B-type natriuretic peptide (NT-proBNP), and interleukin-6. The endpoints included mortality, the incidence of malignant arrhythmia, and mechanical ventilation time. Univariate regression analysis, multivariate linear regression analysis, and binary logistic analysis were performed to develop the risk predictors in myocardial injury to the prognosis of severe and critical COVID-19 patients.
Seventy-four COVID-19 patients were included (mean age of 67.2 ± 14.6 years, male of 66.2%), including 42 severe and 32 critical cases. The mortality was 62.2% (n = 46). CK-MB (odds was observed. Increases of CK-MB, myoglobin, NT-proBNP, interleukin-6, and age were independently associated with poor prognosis including increased ventilation duration, the incidence of malignant arrhythmia, and mortality.
This study aims to evaluate the trends and geographic variations of incident diabetes as well as the corresponding sex differences in China.
The open cohort study derived data of 16,610 individuals from the China Health and Nutrition Survey 1997-2015. Direct standardisation was employed to calculate the age-standardised diabetes incidence. Mixed effects logistic regression models with interaction terms were performed to examine variations in incident diabetes. Socio-demographic (age, sex, marital status, racial compositions and educational attainment) and lifestyle attributes (smoking history, BMI and waist circumference) were sequentially included as covariates.
Overall age-standardised diabetes incidence increased from 2.94 per 1000 person-years (95% CI, 2.44-3.44) in 1997-2004 to 5.54 (95% CI, 4.94-6.14) in 2009-2015. Models with interaction terms suggest that the increase among men was higher than that among women (wave 2006-2009 × Female OR=0.45, 95% CI 0.28-0.72). Age-standardised incidence of diabetes varied across regions, ranging from 5.67 (95% CI, 4.95-6.40) in Eastern China to 2.69 (95% CI 2.19-3.19) in Western China. Subsequent modelling analyses suggest that the geographic variations could be mostly explained by the variations in the BMI and waist circumference across regions.
Results suggest that the incidence of self-reported diabetes approximately doubled during the study period. The increase among men was steeper than that among women. Public interventions reducing the population’s obesity level hold promise to alleviate geographic variations and flatten the growth curve.
Results suggest that the incidence of self-reported diabetes approximately doubled during the study period. The increase among men was steeper than that among women. Public interventions reducing the population’s obesity level hold promise to alleviate geographic variations and flatten the growth curve.’Omics’ technologies have facilitated the identification of hundreds to thousands of tick molecules that mediate tick feeding and play a role in the transmission of tick-borne diseases. Deep sequencing methodologies have played a key role in this knowledge accumulation, profoundly facilitating the study of the biology of disease vectors lacking reference genomes. For example, the nucleotide sequences of the entire set of tick salivary effectors, the so-called tick ‘sialome’, now contain at least one order of magnitude more transcript sequences compared to similar projects based on Sanger sequencing. MeclofenamateSodium Tick feeding is a complex and dynamic process, and while the dynamic ‘sialome’ is thought to mediate tick feeding success, exactly how transcriptome dynamics relate to tick-host-pathogen interactions is still largely unknown. The identification and, importantly, the functional analysis of the tick ‘sialome’ is expected to shed light on this ‘black box’. This information will be crucial for developing strategies to block pathogen transmission, not only for anti-tick vaccine development but also the discovery and development of new, pharmacologically active compounds for human diseases.Multi-hazard coupling disasters, in which multiple hazards occur simultaneously and interact to compound the consequences, are a common phenomenon. The assessment of the individual risk in multi-hazard coupling disasters faces several difficulties due to the nonlinear additivity of risks from multiple hazards. This article presents the Choquet integral multiple linear regression model as a method of overcoming the problems of nonlinear additivity. Using this method, the nonlinear additive individual risks of multi-hazard coupling disasters can be superposed with the nonadditivity of the fuzzy measure during the Choquet integral and the nonlinearity of the Choquet integral itself. This method also takes into account the effects of magnification on the severity of disasters and the vulnerability of victims in multi-hazard disasters. It provides the magnification coefficients to quantitatively calculate the risks of all disasters. To examine the efficacy of the risk-assessment measure, this article uses as a case study the severe fire and explosion disaster that occurred in a port at Tianjin, China, in 2015. From this case study, it can be concluded that the composite individual risk of multi-hazard coupling disasters is greater than that of the simple addition of the risk of each hazard. This finding indicates that multi-hazard coupling disasters are more severe than disasters involving single hazards. Moreover, this risk-assessment method provides guidance in preventing, estimating, and dealing with multi-hazard coupling disasters. It can also provide solutions to complex risk-analysis problems in fields, such as finance, economics, and information science.Members of the POU4F/Brn3 transcription factor family have an established role in the development of retinal ganglion cell (RGCs) types, the main transducers of visual information from the mammalian eye to the brain. Our previous work using sparse random recombination of a conditional knock-in reporter allele expressing alkaline phosphatase (AP) and intersectional genetics had identified three types of Brn3c positive (Brn3c+ ) RGCs. Here, we describe a novel Brn3cCre mouse allele generated by serial Dre to Cre recombination and use it to explore the expression overlap of Brn3c with Brn3a and Brn3b and the dendritic arbor morphologies and visual stimulus response properties of Brn3c+ RGC types. Furthermore, we explore brain nuclei that express Brn3c or receive input from Brn3c+ neurons. Our analysis reveals a much larger number of Brn3c+ RGCs and more diverse set of RGC types than previously reported. Most RGCs expressing Brn3c during development are still Brn3c positive in the adult, and all express Brn3a while only about half express Brn3b.