Rat F1+2(Prothrombin Fragment 1+2) ELISA Kit

BACKGROUND & AIMS: Alcohol-related liver disease (ALD) causes chronic liver disease. We investigated how information on patients' drinking history and amount, stage of liver disease, and demographic feature can be used to determine risk of disease progression. METHODS: We collected data from 2334 heavy drinkers (50 g/day or more) with persistently abnormal results from liver tests who had been admitted to a hepato-gastroenterology unit in France from January 1982 through December 1997; patients with a recorded duration of alcohol abuse were assigned to the development cohort (n=1599; 75% men) or the validation cohort (n=735; 75% men), based on presence of a liver biopsy. We collected data from both cohorts on patient history and disease stage at the time of hospitalization. For the development cohort, severity of the disease was scored by the METAVIR (due to the availability of liver histology reports); in the validation cohort only the presence of liver complications was assessed. We developed a model of ALD progression and occurrence of liver complications (hepatocellular carcinoma and/or liver decompensation) in association with exposure to alcohol, age at the onset of heavy drinking, amount of alcohol intake, sex and body mass index. The model was fitted to the development cohort and then evaluated in the validation cohort. We then tested the ability of the model to predict disease progression for any patient profile (baseline evaluation). Patients with a 5-y weighted risk of liver complications greater than 5% were considered at high risk for disease progression. RESULTS: Model results are given for the following patient profiles: men and women, 40 y old, who started drinking at an age of 25 y, drank 150 g/day, and had a body mass index of 22 kg/m(2) according to the disease severity at baseline evaluation. For men with baseline F0-F2 fibrosis, the model estimated the probabilities of normal liver, steatosis, or steatohepatitis at baseline to be 31.8%, 61.5% and 6.7%, respectively. The 5-y weighted risk of liver complications was 1.9%, ranging from 0.2% for men with normal liver at baseline evaluation to 10.3% for patients with steatohepatitis at baseline. For women with baseline F0-F2 fibrosis, probabilities of normal liver, steatosis, or steatohepatitis at baseline were 25.1%, 66.5% and 8.4%, respectively; the 5-y weighted risk of liver complications was 3.2%, ranging from 0.5% for women with normal liver at baseline to 14.7% for patients with steatohepatitis at baseline. Based on the model, men with F3-F4 fibrosis at baseline have a 24.5% 5-y weighted risk of complications (ranging from 20.2% to 34.5%) and women have a 30.1% 5-y weighted risk of complications (ranging from 24.7% to 41.0%). CONCLUSIONS: We developed a Markov model that integrates data on level and duration of alcohol use to identify patients at high risk of liver disease progression. This model might be used to adapt patient care pathways.

Understanding the structure of hybrid zones provides valuable insights about species boundaries and speciation, such as the evolution of barriers to gene flow and the strength of selection. In river networks, studying evolutionary processes in hybrid zones can be especially challenging, given the influence of past and current river properties along with biological species-specific traits. Here, we suggest that a natural hybrid zone between two divergent lineages of the sexually dimorphic Neotropical fishNematocharax venustuswas probably established by secondary contact as a result of a river capture event between the Contas and Pardo river basins. This putative river capture is supported by hydrogeological evidence of elbows of capture, wind gaps and geological faults. The morphological (colour pattern) and genetic (mtDNA and RADseq) variation reveal a clinal transition between parental lineages along the main river, with predominance of F2 hybrids at the centre of the hybrid zone, absence of early generation backcrosses and different levels of hybridization in the tributaries. We highlight that different sources of information are crucial for understanding how the riverscape spatial history influences the connectivity between and within river systems and, consequently, the dynamics of gene flow between freshwater lineages/species.