Acceleration without Disruption: DFT Software as a Service.

Density functional theory (DFT) has been a cornerstone in computational chemistry, physics, and materials science for decades, benefiting from advancements in computational power and theoretical methods. This paper introduces a novel, cloud-native application, Accelerated DFT, which offers an order of magnitude acceleration in DFT simulations. By integrating state-of-the-art cloud infrastructure and redesigning algorithms for graphic processing units (GPUs), Accelerated DFT achieves high-speed calculations without sacrificing accuracy.

A framework for translating tauopathy therapeutics: Drug discovery to clinical trials.

The tauopathies are defined by pathological tau protein aggregates within a spectrum of clinically heterogeneous neurodegenerative diseases. The primary tauopathies meet the definition of rare diseases in the United States. There is no approved treatment for primary tauopathies.

Accelerating Computational Materials Discovery with Machine Learning and Cloud High-Performance Computing: from Large-Scale Screening to Experimental Validation.

High-throughput computational materials discovery has promised significant acceleration of the design and discovery of new materials for many years. Despite a surge in interest and activity, the constraints imposed by large-scale computational resources present a significant bottleneck. Furthermore, examples of very large-scale computational discovery carried out through experimental validation remain scarce, especially for materials with product applicability.

Evaluation of a pharmacist-led personal continuous glucose monitor workflow to improve glycemic management in an internal medicine clinic.

Background: The use of personal continuous glucose monitors (CGMs) in patients with diabetes has increased substantially and is expected to continue to increase as CGMs become more affordable and insurance plans improve coverage. The utilization of CGMs has improved diabetes management and reduced hypoglycemic events.

Objectives: To create pharmacist-led personal CGM workflow and evaluate its impact on glycemic management in patients with diabetes.

Clinical effectiveness of coronavirus disease 2019 vaccination in patients with multiple sclerosis stratified by disease-modifying treatment.

Background And Purpose: Coronavirus disease 2019 (COVID-19) vaccination has been associated with a dampened humoral and/or cellular immune response in patients with multiple sclerosis (MS) who were concurrently on disease-modifying treatment (DMT) with B-cell depleting agents or sphingosine-1-phosphate receptor modulators (S1PRMs). Our main goal was to investigate the impact of these DMT classes on the clinical effectiveness of COVID-19 vaccination.

Methods: Since March 2020, demographics and clinical data of patients with MS who developed COVID-19 have been collected at the Belgian National MS Centre in Melsbroek.

Nuances of knowing: Brain potentials reveal implicit effects of domain knowledge on word processing in the absence of sentence-level knowledge.

In previous work investigating the relationship between domain knowledge (of the fictional world of Harry Potter) and sentence comprehension, domain knowledge had a greater impact on electrical brain potentials to words which completed sentences about fictional "facts" participants reported they did not know compared to facts they did. This suggests that individuals use domain knowledge continuously to activate relevant/related concepts as they process sentences, even with only partial knowledge. As that study relied on subjective reports, it may have resulted in response bias related to an individual's overall domain knowledge.

Investigating the Extent to which Distributional Semantic Models Capture a Broad Range of Semantic Relations.

Distributional semantic models (DSMs) are a primary method for distilling semantic information from corpora. However, a key question remains: What types of semantic relations among words do DSMs detect? Prior work typically has addressed this question using limited human data that are restricted to semantic similarity and/or general semantic relatedness. We tested eight DSMs that are popular in current cognitive and psycholinguistic research (positive pointwise mutual information; global vectors; and three variations each of Skip-gram and continuous bag of words (CBOW) using word, context, and mean embeddings) on a theoretically motivated, rich set of semantic relations involving words from multiple syntactic classes and spanning the abstract-concrete continuum (19 sets of ratings).

A leucine-rich repeat kinase 2 (LRRK2) pathway biomarker characterization study in patients with Parkinson's disease with and without LRRK2 mutations and healthy controls.

Increased leucine-rich repeat kinase 2 (LRRK2) kinase activity is an established risk factor for Parkinson's disease (PD), and several LRRK2 kinase inhibitors are in clinical development as potential novel disease-modifying therapeutics. This biomarker characterization study explored within- and between-subject variability of multiple LRRK2 pathway biomarkers (total LRRK2 [tLRRK2], phosphorylation of the serine 935 (Ser935) residue on LRRK2 [pS935], phosphorylation of Rab10 [pRab10], and total Rab10 [tRab10]) in different biological sources (whole blood, peripheral blood mononuclear cells [PBMCs], neutrophils) as candidate human target engagement and pharmacodynamic biomarkers for implementation in phase I/II pharmacological studies of LRRK2 inhibitors. PD patients with a LRRK2 mutation (n = 6), idiopathic PD patients (n = 6), and healthy matched control subjects (n = 10) were recruited for repeated blood and cerebrospinal fluid (CSF) sampling split over 2 days.

High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation.

Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases.

LRRK2 Inhibition by BIIB122 in Healthy Participants and Patients with Parkinson's Disease.

Background: Leucine-rich repeat kinase 2 (LRRK2) inhibition is a promising therapeutic approach for the treatment of Parkinson's disease (PD).

Objective: The aim of this study was to evaluate the safety, tolerability, pharmacokinetics, and pharmacodynamics of the potent, selective, CNS-penetrant LRRK2 inhibitor BIIB122 (DNL151) in healthy participants and patients with PD.

Methods: Two randomized, double-blind, placebo-controlled studies were completed.

A fast MR fingerprinting simulator for direct error estimation and sequence optimization.

Magnetic resonance fingerprinting (MRF) is a novel quantitative MR technique that simultaneously provides multiple tissue property maps. When optimizing MRF scans, modeling undersampling errors and field imperfections in cost functions for direct measurement of quantitative errors will make the optimization results more practical and robust. However, optimizing such cost function is computationally expensive and impractical for MRF optimization with tens of thousands of iterations.

Risk for excessive anticoagulation during hemodialysis is associated with type of vascular access and bedside coagulation testing: Results of a cross-sectional study.

Background: Recommendations and practice patterns for heparin dosing during hemodialysis show substantial heterogeneity and are scantly supported by evidence. This study assessed the variability in unfractionated heparin (UFH) dosing during hemodialysis and its clinical and biological anticoagulatory effects, and identified explanatory factors of heparin dosing.

Methods: Cross-sectional study assessing UFH dosing, coagulation tests - activated partial thromboplastin time (aPTT) and activated clotting time (ACT) before dialysis start, 1 h after start and at treatment end (4 h) - and measurement of residual blood compartment volume of used dialyzers.

Patterns of hemispheric asymmetry provide evidence dissociating the semantic and syntactic P600.

To understand how neural networks in the left (LH) and right (RH) cerebral hemispheres contribute to different aspects of language comprehension, in two experiments we measured event-related potentials (ERPs) as right-handed participants read sentences, some of which contained morphosyntactic and thematic role violations. Replicating prior work (Kuperberg et al., 2006), in Experiment 1 thematic role violations elicited both an N400 and a (semantic) P600 effect.

Practical quantum advantage in quantum simulation.

The development of quantum computing across several technologies and platforms has reached the point of having an advantage over classical computers for an artificial problem, a point known as 'quantum advantage'. As a next step along the development of this technology, it is now important to discuss 'practical quantum advantage', the point at which quantum devices will solve problems of practical interest that are not tractable for traditional supercomputers. Many of the most promising short-term applications of quantum computers fall under the umbrella of quantum simulation: modelling the quantum properties of microscopic particles that are directly relevant to modern materials science, high-energy physics and quantum chemistry.

Preclinical and clinical evaluation of the LRRK2 inhibitor DNL201 for Parkinson's disease.

Mutations in leucine-rich repeat kinase 2 () are the most common genetic risk factors for Parkinson's disease (PD). Increased LRRK2 kinase activity is thought to impair lysosomal function and may contribute to the pathogenesis of PD. Thus, inhibition of LRRK2 is a potential disease-modifying therapeutic strategy for PD.

Safety, pharmacokinetics and target engagement of novel RIPK1 inhibitor SAR443060 (DNL747) for neurodegenerative disorders: Randomized, placebo-controlled, double-blind phase I/Ib studies in healthy subjects and patients.

RIPK1 is a master regulator of inflammatory signaling and cell death and increased RIPK1 activity is observed in human diseases, including Alzheimer's disease (AD) and amyotrophic lateral sclerosis (ALS). RIPK1 inhibition has been shown to protect against cell death in a range of preclinical cellular and animal models of diseases. SAR443060 (previously DNL747) is a selective, orally bioavailable, central nervous system (CNS)-penetrant, small-molecule, reversible inhibitor of RIPK1.

Wrong or right? Brain potentials reveal hemispheric asymmetries to semantic relations during word-by-word sentence reading as a function of (fictional) knowledge.

How does individual-level variation in experience and knowledge influence neural mechanisms important for real-time language comprehension? We used event-related brain potentials (ERPs) combined with lateralized visual field (VF) presentation of sentence-final words to examine asymmetries in hemispheric processing as individuals who varied in their knowledge of the fictional world of Harry Potter (HP) read sentences about general topics and HP. HP sentence endings were either contextually supported, unrelated anomalies, or semantically related anomalies. Amongst HP experts, we observed contextual support effects with presentation to both left and right VFs, but related anomaly effects only with presentation to the left VF (right hemisphere).

Molecular architecture determines brain delivery of a transferrin receptor-targeted lysosomal enzyme.

Delivery of biotherapeutics across the blood-brain barrier (BBB) is a challenge. Many approaches fuse biotherapeutics to platforms that bind the transferrin receptor (TfR), a brain endothelial cell target, to facilitate receptor-mediated transcytosis across the BBB. Here, we characterized the pharmacological behavior of two distinct TfR-targeted platforms fused to iduronate 2-sulfatase (IDS), a lysosomal enzyme deficient in mucopolysaccharidosis type II (MPS II), and compared the relative brain exposures and functional activities of both approaches in mouse models.

Automated design of pulse sequences for magnetic resonance fingerprinting using physics-inspired optimization.

Magnetic resonance fingerprinting (MRF) is a method to extract quantitative tissue properties such as [Formula: see text] and [Formula: see text] relaxation rates from arbitrary pulse sequences using conventional MRI hardware. MRF pulse sequences have thousands of tunable parameters, which can be chosen to maximize precision and minimize scan time. Here, we perform de novo automated design of MRF pulse sequences by applying physics-inspired optimization heuristics.

Thematic and other semantic relations central to abstract (and concrete) concepts.

In this article, we discuss multiple types of meaningful (semantic) relations underlying abstract (as compared to concrete) concepts. We adopt the viewpoint that words act as cues to meaning (Elman in Ment Lexicon 6(1):1-34, 2011; Lupyan and Lewis in Lang Cogn Neurosci 34(10):1319-1337, 2019), which is dependent on the dynamic contents of a comprehender's mental model of the situation. This view foregrounds the importance of both linguistic and real-world context as individuals make sense of words, flexibly access relevant knowledge, and understand described events and situations.

To catch a Snitch: Brain potentials reveal variability in the functional organization of (fictional) world knowledge during reading.

We harnessed the temporal sensitivity of event-related brain potentials (ERPs) alongside individual differences in Harry Potter (HP) knowledge to investigate the extent to which the availability and timing of information relevant for real-time written word processing are influenced by variation in domain knowledge. We manipulated meaningful (category, event) relationships between sentence fragments about HP stories and their sentence final words. During word-by-word reading, N400 amplitudes to (a) linguistically supported and (b) unsupported but meaningfully related, but not to (c) unsupported, unrelated sentence endings varied with HP domain knowledge.

Band Structure Extraction at Hybrid Narrow-Gap Semiconductor-Metal Interfaces.

The design of epitaxial semiconductor-superconductor and semiconductor-metal quantum devices requires a detailed understanding of the interfacial electronic band structure. However, the band alignment of buried interfaces is difficult to predict theoretically and to measure experimentally. This work presents a procedure that allows to reliably determine critical parameters for engineering quantum devices; band offset, band bending profile, and number of occupied quantum well subbands of interfacial accumulation layers at semiconductor-metal interfaces.

Toward Quantum Computing for High-Energy Excited States in Molecular Systems: Quantum Phase Estimations of Core-Level States.

This paper explores the utility of the quantum phase estimation (QPE) algorithm in calculating high-energy excited states characterized by the promotion of electrons occupying core-level shells. These states have been intensively studied over the last few decades, especially in supporting the experimental effort at light sources. Results obtained with QPE are compared with various high-accuracy many-body techniques developed to describe core-level states.

Harry Potter and the Chamber of ?: The impact of what individuals know on word processing during reading.

During reading, effects of contextual support indexed by N400-a brain potential sensitive to semantic activation/retrieval-amplitude are presumably mediated by comprehenders' world knowledge. Moreover, variability in knowledge may influence the contents, timing, and mechanisms of what is brought to mind during real-time sentence processing. Since it is infeasible to assess the entirety of each individual's knowledge, we investigated a limited domain-the narrative world of Harry Potter (HP).