Screening computational

BACKGROUND: We aimed to improve the image quality (IQ) of sparse-view computed tomography (CT) images using a U-Net for lung metastasis detection and determine the best tradeoff between number of views, IQ, and diagnostic confidence. METHODS: CT images from 41 subjects aged 62.8 ± 10.6 years (mean ± standard deviation, 23 men), 34 with lung metastasis, 7 healthy, were retrospectively selected (2016-2018) and forward projected onto 2,048-view sinograms...

Utilization of optimization technique is a must in the design of contemporary antenna systems. Often, global search methods are necessary, which are associated with high computational costs when conducted at the level of full-wave electromagnetic (EM) models. In this study, we introduce an innovative method for globally optimizing reflection responses of multi-band antennas. Our approach uses surrogates constructed based on response features, smoothing the objective function landscape processed by the algorithm...

BACKGROUND: Transcatheter mitral valve replacement (TMVR) is an alternative to conventional surgery to treat severe mitral disease but its use is limited by the risk of left ventricular outflow tract obstruction (LVOTO). Screening depends on ECG-gated computed tomography (CT) that is not widely available and requires contrast. We developed and validated a transthoracic echocardiographic (TTE) method to assess the risk of LVOTO after TMVR with the Tendyne System. METHODS: We measured the LVOT longitudinal area on preoperative TTE dataset of patients screened for TMVR...

Co-milling is an effective technique for improving dissolution rate limited absorption characteristics of poorly water soluble drugs. However, there is a scarcity of models available to forecast the magnitude of dissolution rate improvement caused by co-milling. Therefore, this study endeavoured to quantitatively predict the increase in dissolution by co-milling based on drug properties. Using a biorelevant dissolution setup, a series of 29 structurally diverse and crystalline drugs were screened in co-milled and physically blended mixtures with Polyvinylpyrrolidone K25...

Allergic rhinitis is a common allergic disease with a complex pathogenesis and many unresolved issues. Studies have shown that the incidence of allergic rhinitis is closely related to genetic factors, and research on the related genes could help further understand its pathogenesis and develop new treatment methods. In this study, 446 allergic rhinitis-related genes were obtained on the basis of the DisGeNET database. The protein-protein interaction network was searched using the random-walk-with-restart algorithm with these 446 genes as seed nodes to assess the linkages between other genes and allergic rhinitis...

PURPOSE: Breast arterial calcification (BAC) refers to medial calcium deposition in breast arteries and is detectable via mammography. Sarcopenia, which is characterised by low skeletal muscle mass and quality, is associated with several serious clinical conditions, increased morbidity, and mortality. Both BAC and sarcopenia share common pathologic pathways, including ageing, diabetes, and chronic kidney disease. Therefore, this study evaluated the relationship between BAC and sarcopenia as a potential indicator of sarcopenia...

The development of novel topoisomerase I (TOP1) inhibitors is crucial for overcoming the drawbacks and limitations of current TOP1 poisons. Here, we identified two potential TOP1 inhibitors, namely, FTY720 (a sphingosine 1-phosphate antagonist) and COH29 (a ribonucleotide reductase inhibitor), through experimental screening of known active compounds. Biological experiments verified that FTY720 and COH29 were nonintercalative TOP1 catalytic inhibitors that did not induce the formation of DNA-TOP1 covalent complexes...

The prolonged intravitreal administration of anti-vascular endothelial growth factor (VEGF) drugs is prone to inducing aberrant retinal vascular development and causing damage to retinal neurons. Hence, we have taken an alternative approach by designing and synthesizing a series of cyclic peptides targeting CC motif chemokine receptor 3 (CCR3). Based on the binding mode of the N-terminal region in CCR3 protein to CCL11, we used computer-aided identification of key amino acid sequence, conformational restriction through different cyclization methods, designed and synthesized a series of target cyclic peptides, and screened the preferred compound IB-2 through affinity...

Nondestructive plant phenotyping forms a key technique for unraveling molecular processes underlying plant development and response to the environment. While the emergence of high-throughput phenotyping facilities can further our understanding of plant development and stress responses, their high costs greatly hinder scientific progress. To democratize high-throughput plant phenotyping, we developed sets of low-cost image- and weight-based devices to monitor plant shoot growth and evapotranspiration. We paired these devices to a suite of computational pipelines for integrated and straightforward data analysis...

The binding affinity of nicotinoids to the binding residues of the α4 β2 variant of the nicotinic acetylcholine receptor (nAChR) was identified as a strong predictor of the nicotinoid's addictive character. Using ab initio calculations for model binding pockets of increasing size composed of 3, 6, and 14 amino acids (3AA, 6AA, and 14AA) that are derived from the crystal structure, the differences in binding affinity of 6 nicotinoids, namely, nicotine (NIC), nornicotine (NOR), anabasine (ANB), anatabine (ANT), myosmine (MYO), and cotinine (COT) were correlated to their previously reported doses required for increases in intracranial self-stimulation (ICSS) thresholds, a metric for their addictive function...

SARS-CoV-2 infections in animals have been reported globally. However, the understanding of the complete spectrum of animals susceptible to SARS-CoV-2 remains limited. The virus's dynamic nature and its potential to infect a wide range of animals are crucial considerations for a One Health approach that integrates both human and animal health. This study introduces a bioinformatic approach to predict potential susceptibility to SARS-CoV-2 in both domestic and wild animals. By examining genomic sequencing, we establish phylogenetic relationships between the virus and its potential hosts...

Recent advances in computational methods provide the promise of dramatically accelerating drug discovery. While mathematical modeling and machine learning have become vital in predicting drug-target interactions and properties, there is untapped potential in computational drug discovery due to the vast and complex chemical space. This paper builds on our recently published computational fragment-based drug discovery (FBDD) method called fragment databases from screened ligand drug discovery (FDSL-DD). FDSL-DD uses in silico screening to identify ligands from a vast library, fragmenting them while attaching specific attributes based on predicted binding affinity and interaction with the target subdomain...

IMPORTANCE: The National Cancer Institute comprehensive cancer centers (CCCs) lack spatial and temporal evaluation of their self-designated catchment areas. OBJECTIVE: To identify disparities in cancer stage at diagnosis within and outside a CCC's catchment area across a 10-year period using spatial and statistical analyses. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional, population-based study conducted between 2010 and 2019 utilized cancer registry data for the Johns Hopkins Sidney Kimmel CCC (SKCCC)...

The pursuit of efficient photocatalysts toward photocatalytic water splitting has attracted wide attention. However, the low efficiency of photocatalytic reactions due to the rapid electron-hole recombination and the time-consuming searching process hinder the development of high-performance photocatalysts. Here, we proposed a data-driven screening procedure for covalent organic frameworks (COFs) as overall solar water-splitting photocatalysts. Based on a COF database through assembling different Cores and Linkers , three COFs are predicted to be efficient photocatalysts for overall solar water splitting after high-throughput computational screening...

Due to the magnitude of chemical space, the discovery of novel substrates in energy transfer (EnT) catalysis remains a daunting task. Experimental and computational strategies to identify compounds that successfully undergo EnT-mediated reactions are limited by their time and cost efficiency. To accelerate the discovery process in EnT catalysis, we herein present the EnTdecker platform, which facilitates the large-scale virtual screening of potential substrates using machine-learning (ML) based predictions of their excited state properties...

Bimetallic nanoparticles (NPs) with peroxidase-like (POD-like) activity play a crucial role in biosensing, disease treatment, environmental management, and other fields. However, their development is impeded by a vast range of tunable properties in components and structures, making the establishment of structure-effect relationships and the discovery of active materials challenging. Addressing this, we established robust scaling relationships by meticulously analyzing the catalytic reaction networks of pure metal NPs, which laid the volcano-shaped correlation between the activity and O* adsorption energy...

Small molecule drugs can be used to target nucleic acids (NA) to regulate biological processes. Computational modeling methods, such as molecular docking or scoring functions, are commonly employed to facilitate drug design. However, the accuracy of the scoring function in predicting the closest-to-native docking pose is often suboptimal. To overcome this problem, a machine learning model, RmsdXNA, was developed to predict the root-mean-square-deviation (RMSD) of ligand docking poses in NA complexes. The versatility of RmsdXNA has been demonstrated by its successful application to various complexes involving different types of NA receptors and ligands, including metal complexes and short peptides...

OBJECTIVE: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy...

INTRODUCTION: Appendiceal signet-ring cell adenocarcinoma (ASCA) is rare and more aggressive in malignant appendiceal neoplasms. The presentation can be appendicitis, which is lack of specific symptom and makes early diagnosis difficult. There is no effective surveillance. Prognosis largely relies on timely detection. We report a case of ASCA incidentally diagnosed through pathological examination after appendectomy for appendicitis. CASE PRESENTATION: The patient presented to our department with a progressive right lower quadrant abdominal pain lasting for 3 days...

Computer vision syndrome (CVS) refers to a set of eye-related symptoms that arise from prolonged computer usage. A survey was conducted to investigate the demographic characteristics, factors contributing to, and preventive measures against CVS. Out of 159 participants, 31.0% experienced seven or more symptoms, indicating a notable prevalence. The study found no significant correlation between age or academic years and CVS occurrence ( P values of 0.481 and 0.392, respectively). However, gender exhibited a statistically significant relationship, with females students showing a higher prevalence than males ( P =0...