People classified by a priori definitions as having metabolically healthy obesity have frequently been found to be at increased risk of mortality, compared with individuals with metabolically healthy normal weight, suggesting these definitions may be insufficient.

To systematically derive a new definition of metabolic health (MH) and investigate its association with cardiovascular disease (CVD) mortality and total mortality.

In a cohort study using data from the third National Health and Nutrition Examination Survey (NHANES-III), a representative survey using complex multistage probability sampling, anthropometric factors, biomarkers, and blood pressure (BP) associated with total and CVD mortality among participants with obesity were identified with Cox proportional hazards regression. Area under the receiver operating characteristic was calculated to identify predictive factors for mortality to be used to define MH, cutoff levels were determined by the Youden index, and the findings were validated throed risks.

This newly proposed definition of MH may identify a subgroup of people with obesity without increased risk of mortality and stratify risks in people who are overweight or normal weight.
This newly proposed definition of MH may identify a subgroup of people with obesity without increased risk of mortality and stratify risks in people who are overweight or normal weight.Nasal swabs collected from 40 wild ruminants in Namibia were analyzed by PCR for the presence of lumpy skin disease virus (LSDV) DNA. One sample from an asymptomatic eland (Taurotragus oryx) tested positive, providing the first evidence of the presence of LSDV DNA in an eland.Oil spills represent a continued threat to marine wildlife. Although the public expects, and the State of California, US requires, oiled animals to be rescued for rehabilitation and release, scientists have questioned the welfare and conservation value of capture and rehabilitation of oiled wildlife, based on poor postrelease survival documented in the few available studies. In May 2015, Plains Pipeline 901 spilled >100,000 gallons of oil near Refugio State Beach, California. Many California Brown Pelicans (Pelecanus occidentalis californicus) were oiled; capture and rehabilitation efforts began within 1 d. Ultimately, 65 live birds were captured, including 50 pelicans. Forty-six pelicans survived and were released. Of these, 12 adults (six male, six female) were fitted with solar-powered GPS satellite Platform Terminal Transmitters (PTT) and released in June 2015. In early July, we captured eight adult (three male, four female, one unknown), unoiled pelicans from the Ventura, California area. These control birds were similarly instrumented and released immediately. At 6 mo after release, PTTs from nine of 12 oiled pelicans and six of eight control pelicans were still transmitting; at 1 yr, those numbers decreased to two of 12 and two of eight, respectively. Survival analysis revealed no difference in survival between oiled and control birds. Although our sample size is limited, these data demonstrate that most oiled and rehabilitated pelicans can survive for 6 mo following release, and some individuals can survive over 1 yr.
Visualization is a powerful tool to analyze, understand and present big data. Computational biology, bioinformatics, and molecular modeling require dedicated tools, tailored to very complex, highly multidimensional data. Over the recent years, numerous tools have been developed for online presentation, but new challenges like the COVID-19 pandemic require new libraries which will guarantee fast development of online tools for a better understanding of biomedical data/results.

VisuaLife is a Python library that provides a new approach to visualization in a web browser. It offers 2D and 3D plotting capabilities as well as widgets designed to display the most common biological data types nucleotide or protein sequences, 3D biomolecular structures and multiple sequence alignments. https://www.selleckchem.com/products/PCI-24781.html Components provided by the VisuaLife library can be assembled into a web application to create an analysis tool tailored to provide multi-dimensional analysis of a specific research problem. VisuaLife, to our best knowledge, is the most modern solution that allows one to implement such a client-side interactivity in Python.

The git repository of the library is hosted at BitBucket https//bitbucket.org/dgront/visualife/. PyPI distribution is also provided for MacOS and Linux. While basic examples are provided in the supporting materials, the full documentation is available at ReadTheDocs website https//visualife.readthedocs.io/.
The git repository of the library is hosted at BitBucket https//bitbucket.org/dgront/visualife/. PyPI distribution is also provided for MacOS and Linux. While basic examples are provided in the supporting materials, the full documentation is available at ReadTheDocs website https//visualife.readthedocs.io/.
Healthcare quality assessment is being conducted in many countries. Although improving health equity is one of the major objectives of medical quality assessment, it is not clear whether different socio-economic statuses show the same health outcomes even in the same medical quality hospitals. No study has directly compared the health outcomes of different socio-economic statuses in the same hospitals nationwide.

To determine whether the mortality rate of acute stroke patients differs according to socioeconomic status.

This study was a retrospective, observational study of patients who were subject to acute stroke quality assessment in 2013. A total of 10 399 stroke cases were included in the study. When evaluating the mortality rate, the researchers analysed 10 228 cases, after excluding 171 cases that were measured twice for the same person. The levels of socio-economic status were divided according to the use of medical benefits, either National Health Insurance (NHI) for general population or Medicaomic status in stroke patients in Korea. Efforts to improve equity are needed, including the development and monitoring of equality indicators and developing policies for healthcare equity.