410 research outputs found
Peak-to-peak exponential direct learning of continuous-time recurrent neural network models: a matrix inequality approach
Population Pharmacokinetic Modelling of FE 999049, a Recombinant Human Follicle-Stimulating Hormone, in Healthy Women After Single Ascending Doses
OBJECTIVE: The purpose of this analysis was to develop a population pharmacokinetic model for a novel recombinant human follicle-stimulating hormone (FSH) (FE 999049) expressed from a human cell line of foetal retinal origin (PER.C6(®)) developed for controlled ovarian stimulation prior to assisted reproductive technologies.METHODS: Serum FSH levels were measured following a single subcutaneous FE 999049 injection of 37.5, 75, 150, 225 or 450 IU in 27 pituitary-suppressed healthy female subjects participating in this first-in-human single ascending dose trial. Data was analysed by nonlinear mixed effects population pharmacokinetic modelling in NONMEM 7.2.0.RESULTS: A one-compartment model with first-order absorption and elimination rates was found to best describe the data. A transit model was introduced to describe a delay in the absorption process. The apparent clearance (CL/F) and apparent volume of distribution (V/F) estimates were found to increase with body weight. Body weight was included as an allometrically scaled covariate with a power exponent of 0.75 for CL/F and 1 for V/F.CONCLUSIONS: The single-dose pharmacokinetics of FE 999049 were adequately described by a population pharmacokinetic model. The average drug concentration at steady state is expected to be reduced with increasing body weight
Identification of Coevolving Residues and Coevolution Potentials Emphasizing Structure, Bond Formation and Catalytic Coordination in Protein Evolution
The structure and function of a protein is dependent on coordinated interactions between its residues. The selective pressures associated with a mutation at one site should therefore depend on the amino acid identity of interacting sites. Mutual information has previously been applied to multiple sequence alignments as a means of detecting coevolutionary interactions. Here, we introduce a refinement of the mutual information method that: 1) removes a significant, non-coevolutionary bias and 2) accounts for heteroscedasticity. Using a large, non-overlapping database of protein alignments, we demonstrate that predicted coevolving residue-pairs tend to lie in close physical proximity. We introduce coevolution potentials as a novel measure of the propensity for the 20 amino acids to pair amongst predicted coevolutionary interactions. Ionic, hydrogen, and disulfide bond-forming pairs exhibited the highest potentials. Finally, we demonstrate that pairs of catalytic residues have a significantly increased likelihood to be identified as coevolving. These correlations to distinct protein features verify the accuracy of our algorithm and are consistent with a model of coevolution in which selective pressures towards preserving residue interactions act to shape the mutational landscape of a protein by restricting the set of admissible neutral mutations
The Mildly Elevated Serum Bilirubin Level is Negatively Associated with the Incidence of End Stage Renal Disease in Patients with IgA Nephropathy
Oxidative stress plays various roles in the development and progression of IgA nephropathy, while bilirubin is known as a potent antioxidant. We therefore hypothesized that serum bilirubin would be associated with renal prognosis in IgA nephropathy. The study subjects comprised 1,458 adult patients with primary IgA nephropathy in Korea. We grouped patients according to the following quartile levels of bilirubin: <0.4 mg/dL (Q1), 0.4-0.5 mg/dL (Q2), 0.6-0.7 mg/dL (Q3), and >0.8 mg/dL (Q4). The outcome data were obtained from the Korean Registry of end-stage renal disease (ESRD). Eighty patients (5.5%) contracted ESRD during a mean follow-up period of 44.9 months. The ESRD incidences were 10.7% in Q1, 8.2% in Q2, 2.8% in Q3, and 2.8% in Q4 (p<0.001). The relative risk of ESRD compared to that in Q1 was 0.307 (95% confidence interval [CI], 0.126-0.751) in Q3 and 0.315 (95% CI, 0.130-0.765) in Q4. The differences of ESRD incidence were greater in subgroups of males and of patients aged 35 yr or more, with serum albumin 4.0 g/dL or more, with normotension, with eGFR 60 mL/min/1.73 m2 or more, and with proteinuria less then 3+ by dipstick test. In conclusion, higher bilirubin level was negatively associated with ESRD incidence in IgA nephropathy
Population Pharmacokinetics of Inhaled Fluticasone Furoate and Vilanterol in Subjects with Chronic Obstructive Pulmonary Disease
Author Correction: Comprehensive molecular characterization of mitochondrial genomes in human cancers
Correction to: Nature Genetics, published online 05 February 2020. In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium were listed in the Supplementary Information; however, these members should have been included in the main paper. The original Article has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper
Directed Mammalian Gene Regulatory Networks Using Expression and Comparative Genomic Hybridization Microarray Data from Radiation Hybrids
Meiotic mapping of quantitative trait loci regulating expression (eQTLs) has allowed the construction of gene networks. However, the limited mapping resolution of these studies has meant that genotype data are largely ignored, leading to undirected networks that fail to capture regulatory hierarchies. Here we use high resolution mapping of copy number eQTLs (ceQTLs) in a mouse-hamster radiation hybrid (RH) panel to construct directed genetic networks in the mammalian cell. The RH network covering 20,145 mouse genes had significant overlap with, and similar topological structures to, existing biological networks. Upregulated edges in the RH network had significantly more overlap than downregulated. This suggests repressive relationships between genes are missed by existing approaches, perhaps because the corresponding proteins are not present in the cell at the same time and therefore unlikely to interact. Gene essentiality was positively correlated with connectivity and betweenness centrality in the RH network, strengthening the centrality-lethality principle in mammals. Consistent with their regulatory role, transcription factors had significantly more outgoing edges (regulating) than incoming (regulated) in the RH network, a feature hidden by conventional undirected networks. Directed RH genetic networks thus showed concordance with pre-existing networks while also yielding information inaccessible to current undirected approaches
Organogenesis relies on SoxC transcription factors for the survival of neural and mesenchymal progenitors
During organogenesis, neural and mesenchymal progenitor cells give rise to many cell lineages, but their molecular requirements for self-renewal and lineage decisions are incompletely understood. In this study, we show that their survival critically relies on the redundantly acting SoxC transcription factors Sox4, Sox11 and Sox12. The more SoxC alleles that are deleted in mouse embryos, the more severe and widespread organ hypoplasia is. SoxC triple-null embryos die at midgestation unturned and tiny, with normal patterning and lineage specification, but with massively dying neural and mesenchymal progenitor cells. Specific inactivation of SoxC genes in neural and mesenchymal cells leads to selective apoptosis of these cells, suggesting SoxC cell-autonomous roles. Tead2 functionally interacts with SoxC genes in embryonic development, and is a direct target of SoxC proteins. SoxC genes therefore ensure neural and mesenchymal progenitor cell survival, and function in part by activating this transcriptional mediator of the Hippo signalling pathway
Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment : a review
Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.The authors acknowledge the financial support to the project PTDC/EBB-EBI/103147/2008 and the grant SFRH/BPD/48962/2008 provided by Fundacao para a Ciencia e Tecnologia (Portugal)
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