Use of accounting concepts to study research: return on investment in XSEDE, a US cyberinfrastructure service.

This paper uses accounting concepts-particularly the concept of Return on Investment (ROI)-to reveal the quantitative value of scientific research pertaining to a major US cyberinfrastructure project (XSEDE-the eXtreme Science and Engineering Discovery Environment). XSEDE provides operational and support services for advanced information technology systems, cloud systems, and supercomputers supporting non-classified US research, with an average budget for XSEDE of US$20M+ per year over the period studied (2014-2021). To assess the financial effectiveness of these services, we calculated a proxy for ROI, and converted quantitative measures of XSEDE service delivery into financial values using costs for service from the US marketplace.

A comprehensive survey of coronaviral main protease active site diversity in 3D: Identifying and analyzing drug discovery targets in search of broad specificity inhibitors for the next coronavirus pandemic.

Although the rapid development of therapeutic responses to combat SARS-CoV-2 represents a great human achievement, it also demonstrates untapped potential for advanced pandemic preparedness. Cross-species efficacy against multiple human coronaviruses by the main protease (MPro) inhibitor nirmatrelvir raises the question of its breadth of inhibition and our preparedness against future coronaviral threats. Herein, we describe sequence and structural analyses of 346 unique MPro enzymes from all coronaviruses represented in the NCBI Virus database.

The scalable precision medicine open knowledge engine (SPOKE): a massive knowledge graph of biomedical information.

Motivation: Knowledge graphs (KGs) are being adopted in industry, commerce and academia. Biomedical KG presents a challenge due to the complexity, size and heterogeneity of the underlying information.

Results: In this work, we present the Scalable Precision Medicine Open Knowledge Engine (SPOKE), a biomedical KG connecting millions of concepts via semantically meaningful relationships.

Connecting the dots for fundamental understanding of structure-photophysics-property relationships of COFs, MOFs, and perovskites using a Multiparticle Holstein Formalism.

Photoactive organic and hybrid organic-inorganic materials such as conjugated polymers, covalent organic frameworks (COFs), metal-organic frameworks (MOFs), and layered perovskites, display intriguing photophysical signatures upon interaction with light. Elucidating structure-photophysics-property relationships across a broad range of functional materials is nontrivial and requires our fundamental understanding of the intricate interplay among excitons (electron-hole pair), polarons (charges), bipolarons, phonons (vibrations), inter-layer stacking interactions, and different forms of structural and conformational defects. In parallel with electronic structure modeling and data-driven science that are actively pursued to successfully accelerate materials discovery, an accurate, computationally inexpensive, and physically-motivated theoretical model, which consistently makes quantitative connections with conceptually complicated experimental observations, is equally important.

Introducing mirror-image discrimination capability to the TSR-based method for capturing stereo geometry and understanding hierarchical structure relationships of protein receptor family.

We have developed a Triangular Spatial Relationship (TSR)-based computational method for protein structure comparison and motif discovery that is both sequence and structure alignment-free. A protein 3D structure is modeled by all possible triangles that are constructed with every three C atoms of amino acids as vertices. Every triangle is represented using an integer (a key).

RCSB Protein Data Bank: Efficient Searching and Simultaneous Access to One Million Computed Structure Models Alongside the PDB Structures Enabled by Architectural Advances.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) provides open access to experimentally-determined three-dimensional (3D) structures of biomolecules. The RCSB PDB RCSB.org research-focused web portal is used annually by many millions of users around the world.

Quantum Mechanics/Molecular Mechanics Simulations on NVIDIA and AMD Graphics Processing Units.

We have ported and optimized the graphics processing unit (GPU)-accelerated QUICK and AMBER-based quantum mechanics/molecular mechanics (QM/MM) implementation on AMD GPUs. This encompasses the entire Fock matrix build and force calculation in QUICK including one-electron integrals, two-electron repulsion integrals, exchange-correlation quadrature, and linear algebra operations. General performance improvements to the QUICK GPU code are also presented.

Integrating plant physiology into simulation of fire behavior and effects.

Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine-scale models and do not capture variation in live fuel (i.

Emerging role of artificial intelligence in cardiac electrophysiology.

Artificial intelligence (AI) and machine learning (ML) have significantly impacted the field of cardiovascular medicine, especially cardiac electrophysiology (EP), on multiple fronts. The goal of this review is to familiarize readers with the field of AI and ML and their emerging role in EP. The current review is divided into 3 sections.

NMF Clustering: Accessible NMF-based Clustering Utilizing GPU Acceleration.

Non-negative Matrix Factorization (NMF) is an algorithm that can reduce high dimensional datasets of tens of thousands of genes to a handful of metagenes which are biologically easier to interpret. Application of NMF on gene expression data has been limited by its computationally intensive nature, which hinders its use on large datasets such as single-cell RNA sequencing (scRNA-seq) count matrices. We have implemented NMF based clustering to run on high performance GPU compute nodes using CuPy, a GPU backed python library, and the Message Passing Interface (MPI).

Estimating County-Level Overdose Rates Using Opioid-Related Twitter Data: Interdisciplinary Infodemiology Study.

Background: There were an estimated 100,306 drug overdose deaths between April 2020 and April 2021, a three-quarter increase from the prior 12-month period. There is an approximate 6-month reporting lag for provisional counts of drug overdose deaths from the National Vital Statistics System, and the highest level of geospatial resolution is at the state level. By contrast, public social media data are available close to real-time and are often accessible with precise coordinates.

An idea to explore: How an interdisciplinary undergraduate course exploring a global health challenge in molecular detail enabled science communication and collaboration in diverse audiences.

Communication and collaboration are key science competencies that support sharing of scientific knowledge with experts and non-experts alike. On the one hand, they facilitate interdisciplinary conversations between students, educators, and researchers, while on the other they improve public awareness, enable informed choices, and impact policy decisions. Herein, we describe an interdisciplinary undergraduate course focused on using data from various bioinformatics data resources to explore the molecular underpinnings of diabetes mellitus (Types 1 and 2) and introducing students to science communication.

Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future.

As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) "Resolution Revolution" made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps.

Repurposing of drugs for combined treatment of COVID-19 cytokine storm using machine learning.

Severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) induced cytokine storm is the major cause of COVID-19 related deaths. Patients have been treated with drugs that work by inhibiting a specific protein partly responsible for the cytokines production. This approach provided very limited success, since there are multiple proteins involved in the complex cell signaling disease mechanisms.

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents.

Effects of Microhydration on the Mechanisms of Hydrolysis and Cl Substitution in Reactions of N O and Seawater.

The reaction of N O at atmospheric interfaces has recently received considerable attention due to its importance in atmospheric chemistry. N O reacts preferentially with Cl to form ClNO /NO (Cl substitution), but can also react with H O to form 2HNO (hydrolysis). In this paper, we explore these competing reactions in a theoretical study of the clusters N O /Cl /nH O (n=2-5), resulting in the identification of three reaction motifs.

Changes in abdominal adipose tissue depots assessed by MRI correlate with hepatic histologic improvement in non-alcoholic steatohepatitis.

Background & Aims: Non-alcoholic steatohepatitis (NASH) is prevalent in adults with obesity and can progress to cirrhosis. In a secondary analysis of prospectively acquired data from the multicenter, randomized, placebo-controlled FLINT trial, we investigated the relationship between reduction in adipose tissue compartment volumes and hepatic histologic improvement.

Methods: Adult participants in the FLINT trial with paired liver biopsies and abdominal MRI exams at baseline and end-of-treatment (72 weeks) were included (n = 76).

NEMAR: an open access data, tools and compute resource operating on neuroelectromagnetic data.

To preserve scientific data created by publicly and/or philanthropically funded research projects and to make it ready for exploitation using recent and ongoing advances in advanced and large-scale computational modeling methods, publicly available data must use in common, now-evolving standards for formatting, identifying and annotating should share data. The OpenNeuro.org archive, built first as a repository for magnetic resonance imaging data based on the Brain Imaging Data Structure formatting standards, aims to house and share all types of human neuroimaging data.

Hydration Structure of Na and K Ions in Solution Predicted by Data-Driven Many-Body Potentials.

The hydration structure of Na and K ions in solution is systematically investigated using a hierarchy of molecular models that progressively include more accurate representations of many-body interactions. We found that a conventional empirical pairwise additive force field that is commonly used in biomolecular simulations is unable to reproduce the extended X-ray absorption fine structure (EXAFS) spectra for both ions. In contrast, progressive inclusion of many-body effects rigorously derived from the many-body expansion of the energy allows the MB-nrg potential energy functions (PEFs) to achieve nearly quantitative agreement with the experimental EXAFS spectra, thus enabling the development of a molecular-level picture of the hydration structure of both Na and K in solution.

Protein Data Bank: A Comprehensive Review of 3D Structure Holdings and Worldwide Utilization by Researchers, Educators, and Students.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive.

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D.

Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open-access global archive housing three-dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB.

Accurate Modeling of Bromide and Iodide Hydration with Data-Driven Many-Body Potentials.

Ion-water interactions play a central role in determining the properties of aqueous systems in a wide range of environments. However, a quantitative understanding of how the hydration properties of ions evolve from small aqueous clusters to bulk solutions and interfaces remains elusive. Here, we introduce the second generation of data-driven many-body energy (MB-nrg) potential energy functions (PEFs) representing bromide-water and iodide-water interactions.

Data-Driven Many-Body Potential Energy Functions for Generic Molecules: Linear Alkanes as a Proof-of-Concept Application.

We present a generalization of the many-body energy (MB-nrg) theoretical/computational framework that enables the development of data-driven potential energy functions (PEFs) for generic covalently bonded molecules, with arbitrary quantum mechanical accuracy. The "nearsightedness of electronic matter" is exploited to define monomers as "natural building blocks" on the basis of their distinct chemical identity. The energy of generic molecules is then expressed as a sum of individual many-body energies of incrementally larger subsystems.

Predictors of Time to Coronavirus Disease 2019 Infection in the National Basketball Association: A Retrospective Case-Control Study.

A case-control study was conducted between 1 December 2021 and 31 January 2022 to identify factors, which increase risk for coronavirus disease 2019 (COVID-19) among athletes in the National Basketball Association (NBA). Behavioral factors and stadium attendance significantly decreased time to COVID-19 infection, but local COVID-19 rates were not associated in a multivariable model.

A biomedical open knowledge network harnesses the power of AI to understand deep human biology.

Knowledge representation and reasoning (KR&R) has been successfully implemented in many fields to enable computers to solve complex problems with AI methods. However, its application to biomedicine has been lagging in part due to the daunting complexity of molecular and cellular pathways that govern human physiology and pathology. In this article we describe concrete uses of SPOKE, an open knowledge network that connects curated information from 37 specialized and human-curated databases into a single property graph, with 3 million nodes and 15 million edges to date.