Jagiellonian University

About: Jagiellonian University is a education organization based out in Krakow, Poland. It is known for research contribution in the topics: Population & Catalysis. The organization has 17438 authors who have published 44092 publications receiving 862633 citations. The organization is also known as: Academia Cracoviensis & Akademia Krakowska.

CABS-flex 2.0: a web server for fast simulations of flexibility of protein structures.

Abstract: Classical simulations of protein flexibility remain computationally expensive, especially for large proteins. A few years ago, we developed a fast method for predicting protein structure fluctuations that uses a single protein model as the input. The method has been made available as the CABS-flex web server and applied in numerous studies of protein structure-function relationships. Here, we present a major update of the CABS-flex web server to version 2.0. The new features include: extension of the method to significantly larger and multimeric proteins, customizable distance restraints and simulation parameters, contact maps and a new, enhanced web server interface. CABS-flex 2.0 is freely available at http://biocomp.chem.uw.edu.pl/CABSflex2.

Modified valence indices from the two-particle density matrix

Abstract: The modified ionic and covalent valence indices are introduced, defined in the framework of the two-particle density matrix, with respect to the reference state of separated atoms or ions (SAL). They include only quadratic contributions in changes of the molecular charge-and-bond order matrix elements, relative to the SAL. General properties of the modified valence indices are examined and illustrative qualitative results for model systems are presented. Numerical UHF SCF MO valence data for selected diatomic and triatomic molecules are reported and interpreted in terms of the valence saturation effect and the ionic vs. covalent valence competition. A three-orbital valence model of a symmetric transition state of the bond-forming–bond-breaking reaction supports the BEBO model postulate of preservation of the total “bond order.” The model predictions are compared with the UHF numerical values. © 1994 John Wiley & Sons, Inc.

Search for high-mass diboson resonances with boson-tagged jets in proton-proton collisions at √s=8 TeV with the ATLAS detector

Abstract: A search is performed for narrow resonances decaying into WW, WZ, or ZZ boson pairs using 20.3 fb(-1) of proton-proton collision data at a centre-of-mass energy of root s = TeV recorded with the AT ...

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics

Abstract: Background Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. Objectives We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. Methods Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. Results Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. Conclusion Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.