Effectiveness of two scrub methods with different chlorhexidine combinations for surgical field antisepsis in cats.

Objective: Assessing effectiveness of circular (CM) and linear (LM) scrub methods using 3 different combinations of chlorhexidine in surgical field antisepsis in cats. Animals and procedure: Surgical field antisepsis was applied with 2 scrub methods (CM and LM) and 3 different chlorhexidine combinations (A1, A2, and A3) in 51 female cats undergoing ovariectomy. Sterile swabs collected from the surgical field pre- and post-antisepsis were inoculated in the laboratory and colony-forming units (CFU/mL) were quantified. Results: Following the application of antisepsis, the number of positive samples decreased in all groups (P < 0.05) when using both CM and LM, except for CM in the A1 group (P = 0.063). The CFU/mL counts also decreased after antisepsis with both CM and LM in all groups (P < 0.05). A high reduction in CFU/mL counts was observed after antisepsis with both CM and LM in all groups, but no significant differences were observed between the 2 scrub methods (P > 0.05). Conclusion and clinical relevance: Surgical field antisepsis in cats with CM and LM scrub methods, using 2% chlorhexidine combined with 70% ethyl or 70% isopropyl alcohol, or 1% chlorhexidine combined with 70% ethyl alcohol, can effectively reduce the bacterial load on the skin.

Efficacité de deux méthodes de désinfection avec différentes combinaisons de chlorhexidine pour l'antisepsie du champ opératoire chez le chat. Objectif: Évaluation de l'efficacité des méthodes de désinfection par mouvements circulaires (CM) et linéaires (LM) utilisant 3 combinaisons différentes de chlorhexidine dans l'antisepsie du champ opératoire chez le chat. Animaux et procédure: Une antisepsie chirurgicale sur le terrain a été appliquée avec 2 méthodes de désinfection (CM et LM) et 3 combinaisons différentes de chlorhexidine (A1, A2 et A3) chez 51 chattes subissant une ovariectomie. Des écouvillons stériles prélevés sur le champ opératoire avant et après l'antisepsie ont été inoculés en laboratoire et les unités formant des colonies (UFC/mL) ont été quantifiées. Résultats: À la suite de l'application de l'antisepsie, le nombre d'échantillons positifs a diminué dans tous les groupes (P < 0,05) lors de l'utilisation à la fois de CM et de LM, à l'exception du CM dans le groupe A1 (P = 0,063). Le nombre d'UFC/mL a également diminué après antisepsie avec CM et LM dans tous les groupes (P < 0,05). Une forte réduction du nombre d'UFC/mL a été observée après antisepsie avec CM et LM dans tous les groupes, mais aucune différence significative n'a été observée entre les 2 méthodes de désinfection (P > 0,05). Conclusion et pertinence clinique: L'antisepsie chirurgicale sur le terrain chez les chats avec les méthodes de désinfection CM et LM, utilisant 2 % de chlorhexidine combinée à 70 % d'alcool éthylique ou 70 % d'alcool isopropylique, ou 1 % de chlorhexidine combinée à 70 % d'alcool éthylique, peut réduire efficacement la charge bactérienne sur la peau.(Traduit par Dr Serge Messier).

FRETpredict: a Python package for FRET efficiency predictions using rotamer libraries.

Förster resonance energy transfer (FRET) is a widely-used and versatile technique for the structural characterization of biomolecules. Here, we introduce FRETpredict, an easy-to-use Python software to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses a rotamer library approach to describe the FRET probes covalently bound to the protein. The software efficiently and flexibly operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We provide access to rotamer libraries for many commonly used dyes and linkers and describe a general methodology to generate new rotamer libraries for FRET probes. We demonstrate the performance and accuracy of the software for different types of systems: a rigid peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict .

Austropuccinia licaniae, first congeneric with the myrtle rust pathogen A. psidii.

In 1895 and 2001, rust fungi affecting Licania trees (Chrysobalanchaceae) in Brazil were described as Uredo licaniae by Hennings in the state of Goiás and as Phakopsora tomentosae by Ferreira et al. in the state of Amazonas, respectively. Recently, a Licania rust fungus collected close to the Amazonian type location sharing symptoms with the former two species was subjected to morphological examinations and molecular phylogenetic analyses using 28S nuc rDNA (ITS2-28S) and cytochrome c oxidase subunit III (CO3) gene sequences. Since the original type specimen of Ph. tomentosae is considered lost, we carefully reviewed the type description and questioned the identity of the telium, which justified the description of the fungus as a Phakopsora species. Furthermore, the additional revision of the type material described by Hennings revealed that Ph. tomentosae is a synonym of U. licaniae. Based on the morphological examinations, disease symptoms, and shared hosts, we concluded that the newly collected material is conspecific with U. licaniae. However, the phylogenetic analyses rejected allocation in Phakopsora and instead assigned the Licania rust fungus in a sister relationship with Austropuccinia psidii (Sphaerophragmiaceae), the causal agent of the globally invasive myrtle rust pathogen. We therefore favored a recombination of U. licaniae (syn. Ph. tomentosae) into Austropuccinia and proposed the new name Austropuccina licaniae for the second species now identified for this genus. The fungus shares conspicuous symptoms with A. psidii, causing often severe infections of growing leaves and shoots that lead to leaf necrosis, leaf shedding, and eventually to the dieback of entire shoots. In view of the very similar symptoms of its aggressively invasive sister species, we briefly discuss the current state of knowledge about A. licaniae and the potential risks, and the opportunity of its identification.

Cerradopsora, a new genus of neotropical rust fungi.

Two Cerrado rust fungi, Phakopsora rossmaniae and Aplopsora hennenii, described in 1993 and 1995 and originally assigned to families Phakopsoraceae and Ochropsoraceae, respectively, were subjected to molecular phylogenetic analyses using fragments of the nuc 28S and 18S rDNA and mitochondrial cytochrome c oxidase subunit 3 (CO3) gene. Although both taxa were morphologically well placed in their original genera, they were shown to belong in a strongly supported new lineage within the Raveneliineae distant from the Phakopsoraceae and Ochropsoraceae. Therefore, we properly treated this lineage as the new genus Cerradopsora now harboring C. rossmaniae (type species) and C. hennenii. However, this novel phakopsoroid genus remains in uncertain familial position without support to be included in any of the families that share space within the Raveneliineae.

FRETpredict: A Python package for FRET efficiency predictions using rotamer libraries.

Here, we introduce FRETpredict, a Python software program to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses an established Rotamer Library Approach to describe the FRET probes covalently bound to the protein. The software efficiently operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We demonstrate the performance and accuracy of the software for different types of systems: a relatively structured peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). We also describe a general approach to generate new rotamer libraries for FRET probes of interest. FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict.

A context-dependent and disordered ubiquitin-binding motif.

Ubiquitin is a small, globular protein that is conjugated to other proteins as a posttranslational event. A palette of small, folded domains recognizes and binds ubiquitin to translate and effectuate this posttranslational signal. Recent computational studies have suggested that protein regions can recognize ubiquitin via a process of folding upon binding. Using peptide binding arrays, bioinformatics, and NMR spectroscopy, we have uncovered a disordered ubiquitin-binding motif that likely remains disordered when bound and thus expands the palette of ubiquitin-binding proteins. We term this motif Disordered Ubiquitin-Binding Motif (DisUBM) and find it to be present in many proteins with known or predicted functions in degradation and transcription. We decompose the determinants of the motif showing it to rely on features of aromatic and negatively charged residues, and less so on distinct sequence positions in line with its disordered nature. We show that the affinity of the motif is low and moldable by the surrounding disordered chain, allowing for an enhanced interaction surface with ubiquitin, whereby the affinity increases ~ tenfold. Further affinity optimization using peptide arrays pushed the affinity into the low micromolar range, but compromised context dependence. Finally, we find that DisUBMs can emerge from unbiased screening of randomized peptide libraries, featuring in de novo cyclic peptides selected to bind ubiquitin chains. We suggest that naturally occurring DisUBMs can recognize ubiquitin as a posttranslational signal to act as affinity enhancers in IDPs that bind to folded and ubiquitylated binding partners.

DEER-PREdict: Software for efficient calculation of spin-labeling EPR and NMR data from conformational ensembles.

Owing to their plasticity, intrinsically disordered and multidomain proteins require descriptions based on multiple conformations, thus calling for techniques and analysis tools that are capable of dealing with conformational ensembles rather than a single protein structure. Here, we introduce DEER-PREdict, a software program to predict Double Electron-Electron Resonance distance distributions as well as Paramagnetic Relaxation Enhancement rates from ensembles of protein conformations. DEER-PREdict uses an established rotamer library approach to describe the paramagnetic probes which are bound covalently to the protein.DEER-PREdict has been designed to operate efficiently on large conformational ensembles, such as those generated by molecular dynamics simulation, to facilitate the validation or refinement of molecular models as well as the interpretation of experimental data. The performance and accuracy of the software is demonstrated with experimentally characterized protein systems: HIV-1 protease, T4 Lysozyme and Acyl-CoA-binding protein. DEER-PREdict is open source (GPLv3) and available at github.com/KULL-Centre/DEERpredict and as a Python PyPI package pypi.org/project/DEERPREdict.

The PCNA interaction motifs revisited: thinking outside the PIP-box.

Proliferating cell nuclear antigen (PCNA) is a cellular hub in DNA metabolism and a potential drug target. Its binding partners carry a short linear motif (SLiM) known as the PCNA-interacting protein-box (PIP-box), but sequence-divergent motifs have been reported to bind to the same binding pocket. To investigate how PCNA accommodates motif diversity, we assembled a set of 77 experimentally confirmed PCNA-binding proteins and analyzed features underlying their binding affinity. Combining NMR spectroscopy, affinity measurements and computational analyses, we corroborate that most PCNA-binding motifs reside in intrinsically disordered regions, that structure preformation is unrelated to affinity, and that the sequence-patterns that encode binding affinity extend substantially beyond the boundaries of the PIP-box. Our systematic multidisciplinary approach expands current views on PCNA interactions and reveals that the PIP-box affinity can be modulated over four orders of magnitude by positive charges in the flanking regions. Including the flanking regions as part of the motif is expected to have broad implications, particularly for interpretation of disease-causing mutations and drug-design, targeting DNA-replication and -repair.

A new scoring function for protein-protein docking that identifies native structures with unprecedented accuracy.

Protein-protein (P-P) 3D structures are fundamental to structural biology and drug discovery. However, most of them have never been determined. Many docking algorithms were developed for that purpose, but they have a very limited accuracy in generating native-like structures and identifying the most correct one, in particular when a single answer is asked for. With such a low success rate it is difficult to point out one docked structure as being native-like. Here we present a new, high accuracy, scoring method to identify the 3D structure of P-P complexes among a set of trial poses. It incorporates alanine scanning mutagenesis experimental data that need to be obtained a priori. The scoring scheme works by matching the computational and the experimental alanine scanning mutagenesis results. The size of the trial P-P interface area is also taken into account. We show that the method ranks the trial structures and identifies the native-like structures with unprecedented accuracy (∼94%), providing the correct P-P 3D structures that biochemists and molecular biologists need to pursue their studies. With such a success rate, the bottleneck of protein-protein docking moves from the scoring to searching algorithms.

Solvent-accessible surface area: How well can be applied to hot-spot detection?

A detailed comprehension of protein-based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA-based features for their ability to correlate and differentiate hot- and null-spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot- and null-spots, while presenting low correlations. Residue standardization such as rel SASAi or rel/res SASAi , improved the features as a tool to predict ΔΔGbinding values. A new method using support machine learning algorithms was developed: SBHD (Sasa-Based Hot-spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set.

Perfil de risco de reestenose em pacientes submetidos a implante de stents coronarianos convencionais / Restenosis risk profile of patients submitted to coronary bare-metal stent implantation

Introdução: O perfil de risco de reestenose de populações tratadas com implante de stents coronarianos em nosso meio não é conhecido. Essa informação tem importância na decisão de incorporar uma estratégia seletiva de implante de stents farmacológicos pelo sistema público de saúde. Objetivos: Avaliar o risco de reestenose antes do procedimento de uma população de pacientes tratados com stents coronarianos convencionais. Método: Estudo observacional de corte transversal, com 4.482 pacientes tratados com 5.336 stents , no período de janeiro de 2000 a dezembro de 2007. O risco de reestenose foi avaliado conforme escore previamente validado, com pontuação de 0 a 5 conforme a presença de diabetes melito (1 ponto), o diâmetro de referência do vaso tratado (menor 3 mm igual 2 pontos, 3-3,5 mm igual 0) e a extensão da lesão (maior 20 mm igual 2 pontos, 10-20 mm igual 1, e menor 10 mm igual 0. Resultados: A média de idade foi de 60,6 mais ou menos 10,6 anos e 32 por cento dos pacientes eram do sexo feminino. O diâmetro de referência do vaso tratado foi de 3,10 maior e menor 0,51 mm, a extensão da lesão foi de 13,2 maior ou menor 5,9 mm e 20 por cento dos pacientes apresentavam diabetes melito. A distribuição dos pacientes conforme os pontos no escore de reestenose...

Background: The restenosis risk of patient populations treated with coronary stent implantation is not well studied. This information has a potential impact on the decision of incorporating a selective strategy of drug-eluting stent implantation by the public health system. Our objective was to evaluate the restenosis risk of a population of patients (pts) treated with bare-metal stents. Methods: Observational study with 4,482 pts treated with 5,336 stents, between January 2000 and December 2007. The restenosis risk was assessed according to a previous validated risk score. Points in the score ranged from 0 to 5 according to diabetes mellitus (1 point), reference vessel diameter (< 3 mm = 2 points, 3-3.5 mm = 1, and > 3.5 mm = 0), and the lesion length (> 20 mm = 2 points, 10-20 mm = 1, and < 10 mm = 0). Results: The mean age was 60.6 ± 10.6 years of age, and 32% were female. The mean reference vessel diameter was 3.10 mm ± 0.51mm, the lesion length was 13.2 mm ± 5.9 mm, and 20% of the pts were diabetics. The distribution of pts according to points in the risk score was the following: score 0 = 4% of the pts; score 1 = 22%; 2 = 34%; 3 = 29%; 4 = 9%; and score 5 = 1% of the pts. Conclusions: The majority of pts presented low or intermediate restenosis risk. The adoption of a selectivestrategy of drug-eluting stent implantation only in those at higher restenosis risk would represent its use in no more than 20% of the procedures.