Anti-FGA polyclonal antibody [HRP]

Background Although several genetic risk factors for deep vein thrombosis (DVT) are known, almost all related to hemostasis, a large genetic component remains unexplained. Objectives To identify novel genetic determinants by using targeted DNA sequencing. Patients/Methods We included 899 DVT patients and 599 controls from three case-control studies (DVT-Milan, Multiple Environmental and Genetic Assessment of risk factors for venous thrombosis [MEGA], and the Thrombophilia, Hypercoagulability and Environmental Risks in Venous Thromboembolism [THE-VTE] study) for sequencing of the coding regions of 734 genes involved in hemostasis or related pathways. We performed single-variant association tests for common variants (minor allele frequency [MAF] >= 1%) and gene-based tests for rare variants (MAF <= 1%), accounting for multiple testing by use of the false discovery rate (FDR). Results Sixty-two of 3617 common variants were associated with DVT risk (FDR < 0.10). Most of these mapped to F5,ABO,FGA-FGG, and CYP4V2-KLKB1-F11. The lead variant at F5 was rs6672595 (odds ratio [OR] 1.58, 95% confidence interval [CI] 1.29-1.92), in moderate linkage with the known variant rs4524. Reciprocal conditional analyses suggested that intronic variation might drive this association. We also observed a secondary association at the F11 region: missense KLKB1 variant rs3733402 remained associated conditional on known variants rs2039614 and rs2289252 (OR 1.36, 95% CI 1.10-1.69). Two novel variant associations were observed, in CBS and MASP1, but these were not replicated in the meta-analysis data from the International Network against Thrombosis (INVENT) consortium. There was no support for a burden of rare variants contributing to DVT risk (FDR > 0.2). Conclusions We confirmed associations between DVT and common variants in F5,ABO,FGA-FGG, and CYP4V2-KLKB1-F11, and observed secondary signals in F5 and CYP4V2-KLKB1-F11 that warrant replication and fine-mapping in larger studies.

The Green-Ampt (GA) model, which assumes a rectangular saturated piston flow and homogeneous isotropic soil with uniform initial water content, is one of the most widely used models for describing infiltration processes. However, these assumptions severely limit the applications of the model. Thus, a modified GA model has long been a topic of interest. This study mainly investigates the effects of the broken-line wetting profile and dynamic capillary pressure on the GA model of a horizontal soil column. The aim is to provide a reasonable correction term for the hydraulic conductivity and suction head. The correction term is considered to be 0.4 when the dynamic capillary pressure (CGA model) is neglected. When the dynamic capillary pressure is taken into account, the correction term is a special function (FGA model). Moreover, the results of the CGA model, FGA model, Richards equation, and Mao model are compared with respect to the measured data for sandy loam, silt loam, and silty clay loam. Richards equation cannot accurately describe the infiltration of water into silt loam, and part of the reason is the high infiltration velocity. Although the Mao model can perfectly simulate the infiltration process in a short time (approximately 50 min in this study), its results gradually deviate from the actual situation after 50 min. The CGA model can predict the entire infiltration processes relatively accurately except in the dry sand with zero water content. However, as in the traditional GA model, small errors can still occur during the early infiltration stage. The FGA model is considered to be the most suitable approach for describing infiltration processes. In this paper, the characteristics of these models are explained, and the parameters of the FGA model are discussed in detail.