Measures of preoperative anxiety: Part two.

The current literature indicates that routine evaluation of preoperative anxiety, its determinants, and patient-specific concerns is universally advocated. This aligns with the increasingly acknowledged importance of prehabilitation - a comprehensive process preparing patients for surgery. A crucial component of prehabilitation is assessing patients' mental health.

Computationally restoring the potency of a clinical antibody against Omicron.

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs and revealed how quickly viral escape can curtail effective options. When the SARS-CoV-2 Omicron variant emerged in 2021, many antibody drug products lost potency, including Evusheld and its constituent, cilgavimab. Cilgavimab, like its progenitor COV2-2130, is a class 3 antibody that is compatible with other antibodies in combination and is challenging to replace with existing approaches.

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method.

Protein-ligand interactions are essential to drug discovery and drug development efforts. Desirable on-target or multitarget interactions are the first step in finding an effective therapeutic, while undesirable off-target interactions are the first step in assessing safety. In this work, we introduce a novel ligand-based featurization and mapping of human protein pockets to identify closely related protein targets and to project novel drugs into a hybrid protein-ligand feature space to identify their likely protein interactions.

A Computational Pipeline to Identify and Characterize Binding Sites and Interacting Chemotypes in SARS-CoV-2.

Minimizing the human and economic costs of the COVID-19 pandemic and future pandemics requires the ability to develop and deploy effective treatments for novel pathogens as soon as possible after they emerge. To this end, we introduce a new computational pipeline for the rapid identification and characterization of binding sites in viral proteins along with the key chemical features, which we call chemotypes, of the compounds predicted to interact with those same sites. The composition of source organisms for the structural models associated with an individual binding site is used to assess the site's degree of structural conservation across different species, including other viruses and humans.

Computationally restoring the potency of a clinical antibody against SARS-CoV-2 Omicron subvariants.

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs, but also revealed how quickly viral escape can curtail effective options. With the emergence of the SARS-CoV-2 Omicron variant in late 2021, many clinically used antibody drug products lost potency, including Evusheld and its constituent, cilgavimab. Cilgavimab, like its progenitor COV2-2130, is a class 3 antibody that is compatible with other antibodies in combination and is challenging to replace with existing approaches.

PDBspheres: a method for finding 3D similarities in local regions in proteins.

We present a structure-based method for finding and evaluating structural similarities in protein regions relevant to ligand binding. PDBspheres comprises an exhaustive library of protein structure regions ('spheres') adjacent to complexed ligands derived from the Protein Data Bank (PDB), along with methods to find and evaluate structural matches between a protein of interest and spheres in the library. PDBspheres uses the LGA (Local-Global Alignment) structure alignment algorithm as the main engine for detecting structural similarities between the protein of interest and template spheres from the library, which currently contains >2 million spheres.

Large-scale application of free energy perturbation calculations for antibody design.

Alchemical free energy perturbation (FEP) is a rigorous and powerful technique to calculate the free energy difference between distinct chemical systems. Here we report our implementation of automated large-scale FEP calculations, using the Amber software package, to facilitate antibody design and evaluation. In combination with Hamiltonian replica exchange, our FEP simulations aim to predict the effect of mutations on both the binding affinity and the structural stability.

Discovery of Small-Molecule Inhibitors of SARS-CoV-2 Proteins Using a Computational and Experimental Pipeline.

A rapid response is necessary to contain emergent biological outbreaks before they can become pandemics. The novel coronavirus (SARS-CoV-2) that causes COVID-19 was first reported in December of 2019 in Wuhan, China and reached most corners of the globe in less than two months. In just over a year since the initial infections, COVID-19 infected almost 100 million people worldwide.

Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference.

Predicting accurate protein-ligand binding affinities is an important task in drug discovery but remains a challenge even with computationally expensive biophysics-based energy scoring methods and state-of-the-art deep learning approaches. Despite the recent advances in the application of deep convolutional and graph neural network-based approaches, it remains unclear what the relative advantages of each approach are and how they compare with physics-based methodologies that have found more mainstream success in virtual screening pipelines. We present fusion models that combine features and inference from complementary representations to improve binding affinity prediction.

Single Amino Acid Mutations Affect Zika Virus Replication In Vitro and Virulence In Vivo.

The 2014-2016 Zika virus (ZIKV) epidemic in the Americas resulted in large deposits of next-generation sequencing data from clinical samples. This resource was mined to identify emerging mutations and trends in mutations as the outbreak progressed over time. Information on transmission dynamics, prevalence, and persistence of intra-host mutants, and the position of a mutation on a protein were then used to prioritize 544 reported mutations based on their ability to impact ZIKV phenotype.

Factors Associated with High Preoperative Anxiety: Results from Cluster Analysis.

Background: Preoperative anxiety is a common patients' reaction related to serious adverse events post-operatively. The aim was to explore the characteristics of cardiac surgery patients experiencing high preoperative anxiety.

Methods: A total of 127 patients (mean age 64.

Multiscale analysis for patterns of Zika virus genotype emergence, spread, and consequence.

The question of how Zika virus (ZIKV) changed from a seemingly mild virus to a human pathogen capable of microcephaly and sexual transmission remains unanswered. The unexpected emergence of ZIKV's pathogenicity and capacity for sexual transmission may be due to genetic changes, and future changes in phenotype may continue to occur as the virus expands its geographic range. Alternatively, the sheer size of the 2015-16 epidemic may have brought attention to a pre-existing virulent ZIKV phenotype in a highly susceptible population.

Measures of preoperative anxiety.

The evaluation of treatment from the patient's perspective (Patient Reported Outcomes, PROs) currently remains one of the most vibrant and dynamically developing fields of research. Among PROs, patient self-assessment of various symptoms, including one's psychological state, is of great importance. Anxiety is one of the most frequently observed psychological reactions among patients awaiting various surgeries, and may occur even in up to 80% of patients scheduled for high-risk surgical procedures.

Erratum to: Measurement of the boson polarisation in events from collisions at in the lepton + jets channel with ATLAS.

[This corrects the article DOI: 10.1140/epjc/s10052-017-4819-4.].

Measurement of the Soft-Drop Jet Mass in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector.

Jet substructure observables have significantly extended the search program for physics beyond the standard model at the Large Hadron Collider. The state-of-the-art tools have been motivated by theoretical calculations, but there has never been a direct comparison between data and calculations of jet substructure observables that are accurate beyond leading-logarithm approximation. Such observables are significant not only for probing the collinear regime of QCD that is largely unexplored at a hadron collider, but also for improving the understanding of jet substructure properties that are used in many studies at the Large Hadron Collider.

Predictors and prognostic implications of clinical decisions in patients with primary high-risk non-muscle-invasive bladder cancer - results of a cross country retrospective study.

Adjuvant diagnostic and therapeutic procedures are available to reduce the risk of recurrence or progression in patients with high-risk non-muscle-invasive bladder cancer (NMIBC). However, their indications and efficacy remain a matter of debate. The aim of this study was to analyze therapeutic decisions in patients with primary high-risk NMIBC and to analyze the adherence to clinical guidelines in this field.

Direct top-quark decay width measurement in the lepton+jets channel at with the ATLAS experiment.

This paper presents a direct measurement of the decay width of the top quark using events in the lepton+jets final state. The data sample was collected by the ATLAS detector at the LHC in proton-proton collisions at a centre-of-mass energy of 8 TeV and corresponds to an integrated luminosity of 20.2 fb .

Search for new phenomena in high-mass final states with a photon and a jet from collisions at = 13 TeV with the ATLAS detector.

A search is performed for new phenomena in events having a photon with high transverse momentum and a jet collected in of proton-proton collisions at a centre-of-mass energy of = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider. The invariant mass distribution of the leading photon and jet is examined to look for the resonant production of new particles or the presence of new high-mass states beyond the Standard Model. No significant deviation from the background-only hypothesis is observed and cross-section limits for generic Gaussian-shaped resonances are extracted.

Search for heavy resonances decaying into in the final state in collisions at with the ATLAS detector.

A search for neutral heavy resonances is performed in the decay channel using collision data corresponding to an integrated luminosity of , collected at a centre-of-mass energy of 13 by the ATLAS detector at the Large Hadron Collider. No evidence of such heavy resonances is found. In the search for production via the quark-antiquark annihilation or gluon-gluon fusion process, upper limits on as a function of the resonance mass are obtained in the mass range between 200 and up to 5 for various benchmark models: a Higgs-like scalar in different width scenarios, a two-Higgs-doublet model, a heavy vector triplet model, and a warped extra dimensions model.

Search for doubly charged Higgs boson production in multi-lepton final states with the ATLAS detector using proton-proton collisions at .

A search for doubly charged Higgs bosons with pairs of prompt, isolated, highly energetic leptons with the same electric charge is presented. The search uses a proton-proton collision data sample at a centre-of-mass energy of 13 TeV corresponding to 36.1 of integrated luminosity recorded in 2015 and 2016 by the ATLAS detector at the LHC.

Measurement of the -boson mass in pp collisions at with the ATLAS detector.

A measurement of the mass of the boson is presented based on proton-proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC, and corresponding to of integrated luminosity. The selected data sample consists of candidates in the channel and candidates in the channel. The -boson mass is obtained from template fits to the reconstructed distributions of the charged lepton transverse momentum and of the boson transverse mass in the electron and muon decay channels, yielding where the first uncertainty is statistical, the second corresponds to the experimental systematic uncertainty, and the third to the physics-modelling systematic uncertainty.