Hougaardnoer0784
Findings highlighted that obstetric triage is a process with a dual and dynamic nature. This process involves clinical decision making to prioritize the pregnant mother and her fetus based on the severity and acuity of the disease in order to allocate medical resources and care for providing appropriate treatment at the right time and place to the right patient. The results of this study could be used for the design and implementation of the obstetric triage system.
Findings highlighted that obstetric triage is a process with a dual and dynamic nature. This process involves clinical decision making to prioritize the pregnant mother and her fetus based on the severity and acuity of the disease in order to allocate medical resources and care for providing appropriate treatment at the right time and place to the right patient. The results of this study could be used for the design and implementation of the obstetric triage system.
Brachygnathia, cardiomegaly and renal hypoplasia syndrome (BCRHS, OMIA 001595-9940 ) is a previously reported recessively inherited disorder in Australian Poll Merino/Merino sheep. Affected lambs are stillborn with various congenital defects as reflected in the name of the disease, as well as short stature, a short and broad cranium, a small thoracic cavity, thin ribs and brachysternum. The BCRHS phenotype shows similarity to certain human short stature syndromes, in particular the human 3M syndrome-2. PHA-793887 mouse Here we report the identification of a likely disease-causing variant and propose an ovine model for human 3M syndrome-2.
Eight positional candidate genes were identified among the 39 genes in the approximately 1 Mb interval to which the disease was mapped previously. Obscurin like cytoskeletal adaptor 1 (OBSL1) was selected as a strong positional candidate gene based on gene function and the resulting phenotypes observed in humans with mutations in this gene. Whole genome sequencing of an affected lamb (BC promising given the availability of carrier ram semen for BCRHS.
Proso millet is a highly nutritious cereal considered an essential component of processed foods. It is also recognized with high water-use efficiency as well as short growing seasons. This research was primarily aimed at investigating the genetic diversity among genotypes based on evaluating those important traits proposed in previous researches under both normal and salinity- stress conditions. Use of Amplified fragment length polymorphism (AFLP) molecular markers as well as evaluating the association between markers and the investigated traits under both conditions was also another purpose of this research.
According to the phenotypic correlation coefficients, the seed yield had the highest correlation with the forage and biological yields under both conditions. By disintegrating those traits investigated under normal and salinity-stress conditions into principal component analysis, it was found that the first four principal components justified more than 59.94 and 62.48% of the whole variance, respectinotypic data, the wide germplasm of Iranian proso millet has significant variation in terms of measured traits. It can be concluded that markers showing strong associations with traits under salinity-stress conditions are suitable candidates to be used in future marker-assisted selection (MAS) studies to improve salinity-resistance genotypes of Panicum miliaceum in arid and semiarid areas.
According to the analysis of phenotypic data, the wide germplasm of Iranian proso millet has significant variation in terms of measured traits. It can be concluded that markers showing strong associations with traits under salinity-stress conditions are suitable candidates to be used in future marker-assisted selection (MAS) studies to improve salinity-resistance genotypes of Panicum miliaceum in arid and semiarid areas.
Although previous studies have shown that intra-network abnormalities in brain functional networks are correlated with clinical/cognitive impairment in multiple sclerosis (MS), there is little information regarding the pattern of causal interactions among cognition-related resting-state networks (RSNs) in different disease stages of relapsing-remitting MS (RRMS) patients. We hypothesized that abnormalities of causal interactions among RSNs occurred in RRMS patients in the acute and remitting phases.
Seventeen patients in the acute phases of RRMS, 24 patients in the remitting phases of RRMS, and 23 appropriately matched healthy controls participated in this study. First, we used group independent component analysis to extract the time courses of the spatially independent components from all the subjects. Then, the Granger causality analysis was used to investigate the causal relationships among RSNs in the spectral domain and to identify correlations with clinical indices.
Compared with the patients in twith the disease duration (mean disease duration less then 5 years) and relatively better clinical scores than those in the acute phase, abnormal connections, such as the information flow from the rECN to the aSN and the rECN to the visuospatial network, might provide adaptive compensation in the remitting phase of RRMS.
Statistical analyses of biological problems in life sciences often lead to high-dimensional linear models. To solve the corresponding system of equations, penalization approaches are often the methods of choice. They are especially useful in case of multicollinearity, which appears if the number of explanatory variables exceeds the number of observations or for some biological reason. Then, the model goodness of fit is penalized by some suitable function of interest. Prominent examples are the lasso, group lasso and sparse-group lasso. Here, we offer a fast and numerically cheap implementation of these operators via proximal gradient descent. The grid search for the penalty parameter is realized by warm starts. The step size between consecutive iterations is determined with backtracking line search. Finally, seagull -the R package presented here- produces complete regularization paths.
Publicly available high-dimensional methylation data are used to compare seagull to the established R package SGL. The results of both packages enabled a precise prediction of biological age from DNA methylation status.
