TCR+/BCR+ dual-expressing cells and their associated public BCR clonotype are not enriched in type 1 diabetes.

Ahmed and colleagues recently described a novel hybrid lymphocyte expressing both a B and T cell receptor, termed double expresser (DE) cells. DE cells in blood of type 1 diabetes (T1D) subjects were present at increased numbers and enriched for a public B cell clonotype. Here, we attempted to reproduce these findings. While we could identify DE cells by flow cytometry, we found no association between DE cell frequency and T1D status. We were unable to identify the reported public B cell clone, or any similar clone, in bulk B cells or sorted DE cells from T1D subjects or controls. We also did not observe increased usage of the public clone VH or DH genes in B cells or in sorted DE cells. Taken together, our findings suggest that DE cells and their alleged public clonotype are not enriched in T1D. This Matters Arising paper is in response to Ahmed et al. (2019), published in Cell. See also the response by Ahmed et al. (2021), published in this issue.

Single-Cell Analysis of Crohn's Disease Lesions Identifies a Pathogenic Cellular Module Associated with Resistance to Anti-TNF Therapy.

Clinical benefits of cytokine blockade in ileal Crohn's disease (iCD) are limited to a subset of patients. Here, we applied single-cell technologies to iCD lesions to address whether cellular heterogeneity contributes to treatment resistance. We found that a subset of patients expressed a unique cellular module in inflamed tissues that consisted of IgG plasma cells, inflammatory mononuclear phagocytes, activated T cells, and stromal cells, which we named the GIMATS module. Analysis of ligand-receptor interaction pairs identified a distinct network connectivity that likely drives the GIMATS module. Strikingly, the GIMATS module was also present in a subset of patients in four independent iCD cohorts (n = 441), and its presence at diagnosis correlated with failure to achieve durable corticosteroid-free remission upon anti-TNF therapy. These results emphasize the limitations of current diagnostic assays and the potential for single-cell mapping tools to identify novel biomarkers of treatment response and tailored therapeutic opportunities.

The olivary input to the cerebellum dissociates sensory events from movement plans.

Neurons in the inferior olive are thought to anatomically organize the Purkinje cells (P-cells) of the cerebellum into computational modules, but what is computed by each module? Here, we designed a saccade task in marmosets that dissociated sensory events from motor events and then recorded the complex and simple spikes of hundreds of P-cells. We found that when a visual target was presented at a random location, the olive reported the direction of that sensory event to one group of P-cells, but not to a second group. However, just before movement onset, it reported the direction of the planned movement to both groups, even if that movement was not toward the target. At the end of the movement if the subject experienced an error but chose to withhold the corrective movement, only the first group received information about the sensory prediction error. We organized the P-cells based on the information content of their olivary input and found that in the group that received sensory information, the simple spikes were suppressed during fixation, then produced a burst before saccade onset in a direction consistent with assisting the movement. In the second group, the simple spikes were not suppressed during fixation but burst near saccade deceleration in a direction consistent with stopping the movement. Thus, the olive differentiated the P-cells based on whether they would receive sensory or motor information, and this defined their contributions to control of movements as well as holding still.

Early Restrictive or Liberal Fluid Management for Sepsis-Induced Hypotension.

BACKGROUND: Intravenous fluids and vasopressor agents are commonly used in early resuscitation of patients with sepsis, but comparative data for prioritizing their delivery are limited. METHODS: In an unblinded superiority trial conducted at 60 U.S. centers, we randomly assigned patients to either a restrictive fluid strategy (prioritizing vasopressors and lower intravenous fluid volumes) or a liberal fluid strategy (prioritizing higher volumes of intravenous fluids before vasopressor use) for a 24-hour period. Randomization occurred within 4 hours after a patient met the criteria for sepsis-induced hypotension refractory to initial treatment with 1 to 3 liters of intravenous fluid. We hypothesized that all-cause mortality before discharge home by day 90 (primary outcome) would be lower with a restrictive fluid strategy than with a liberal fluid strategy. Safety was also assessed. RESULTS: A total of 1563 patients were enrolled, with 782 assigned to the restrictive fluid group and 781 to the liberal fluid group. Resuscitation therapies that were administered during the 24-hour protocol period differed between the two groups; less intravenous fluid was administered in the restrictive fluid group than in the liberal fluid group (difference of medians, -2134 ml; 95% confidence interval [CI], -2318 to -1949), whereas the restrictive fluid group had earlier, more prevalent, and longer duration of vasopressor use. Death from any cause before discharge home by day 90 occurred in 109 patients (14.0%) in the restrictive fluid group and in 116 patients (14.9%) in the liberal fluid group (estimated difference, -0.9 percentage points; 95% CI, -4.4 to 2.6; P = 0.61); 5 patients in the restrictive fluid group and 4 patients in the liberal fluid group had their data censored (lost to follow-up). The number of reported serious adverse events was similar in the two groups. CONCLUSIONS: Among patients with sepsis-induced hypotension, the restrictive fluid strategy that was used in this trial did not result in significantly lower (or higher) mortality before discharge home by day 90 than the liberal fluid strategy. (Funded by the National Heart, Lung, and Blood Institute; CLOVERS ClinicalTrials.gov number, NCT03434028.).

Synthesis of geometrically realistic and watertight neuronal ultrastructure manifolds for in silico modeling.

Understanding the intracellular dynamics of brain cells entails performing three-dimensional molecular simulations incorporating ultrastructural models that can capture cellular membrane geometries at nanometer scales. While there is an abundance of neuronal morphologies available online, e.g. from NeuroMorpho.Org, converting those fairly abstract point-and-diameter representations into geometrically realistic and simulation-ready, i.e. watertight, manifolds is challenging. Many neuronal mesh reconstruction methods have been proposed; however, their resulting meshes are either biologically unplausible or non-watertight. We present an effective and unconditionally robust method capable of generating geometrically realistic and watertight surface manifolds of spiny cortical neurons from their morphological descriptions. The robustness of our method is assessed based on a mixed dataset of cortical neurons with a wide variety of morphological classes. The implementation is seamlessly extended and applied to synthetic astrocytic morphologies that are also plausibly biological in detail. Resulting meshes are ultimately used to create volumetric meshes with tetrahedral domains to perform scalable in silico reaction-diffusion simulations for revealing cellular structure-function relationships. Availability and implementation: Our method is implemented in NeuroMorphoVis, a neuroscience-specific open source Blender add-on, making it freely accessible for neuroscience researchers.

Early Outpatient Treatment for Covid-19 with Convalescent Plasma.

BACKGROUND: Polyclonal convalescent plasma may be obtained from donors who have recovered from coronavirus disease 2019 (Covid-19). The efficacy of this plasma in preventing serious complications in outpatients with recent-onset Covid-19 is uncertain. METHODS: In this multicenter, double-blind, randomized, controlled trial, we evaluated the efficacy and safety of Covid-19 convalescent plasma, as compared with control plasma, in symptomatic adults (≥18 years of age) who had tested positive for severe acute respiratory syndrome coronavirus 2, regardless of their risk factors for disease progression or vaccination status. Participants were enrolled within 8 days after symptom onset and received a transfusion within 1 day after randomization. The primary outcome was Covid-19-related hospitalization within 28 days after transfusion. RESULTS: Participants were enrolled from June 3, 2020, through October 1, 2021. A total of 1225 participants underwent randomization, and 1181 received a transfusion. In the prespecified modified intention-to-treat analysis that included only participants who received a transfusion, the primary outcome occurred in 17 of 592 participants (2.9%) who received convalescent plasma and 37 of 589 participants (6.3%) who received control plasma (absolute risk reduction, 3.4 percentage points; 95% confidence interval, 1.0 to 5.8; P = 0.005), which corresponded to a relative risk reduction of 54%. Evidence of efficacy in vaccinated participants cannot be inferred from these data because 53 of the 54 participants with Covid-19 who were hospitalized were unvaccinated and 1 participant was partially vaccinated. A total of 16 grade 3 or 4 adverse events (7 in the convalescent-plasma group and 9 in the control-plasma group) occurred in participants who were not hospitalized. CONCLUSIONS: In participants with Covid-19, most of whom were unvaccinated, the administration of convalescent plasma within 9 days after the onset of symptoms reduced the risk of disease progression leading to hospitalization. (Funded by the Department of Defense and others; CSSC-004 ClinicalTrials.gov number, NCT04373460.).

Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience.

Ultraliser is a neuroscience-specific software framework capable of creating accurate and biologically realistic 3D models of complex neuroscientific structures at intracellular (e.g. mitochondria and endoplasmic reticula), cellular (e.g. neurons and glia) and even multicellular scales of resolution (e.g. cerebral vasculature and minicolumns). Resulting models are exported as triangulated surface meshes and annotated volumes for multiple applications in in silico neuroscience, allowing scalable supercomputer simulations that can unravel intricate cellular structure-function relationships. Ultraliser implements a high-performance and unconditionally robust voxelization engine adapted to create optimized watertight surface meshes and annotated voxel grids from arbitrary non-watertight triangular soups, digitized morphological skeletons or binary volumetric masks. The framework represents a major leap forward in simulation-based neuroscience, making it possible to employ high-resolution 3D structural models for quantification of surface areas and volumes, which are of the utmost importance for cellular and system simulations. The power of Ultraliser is demonstrated with several use cases in which hundreds of models are created for potential application in diverse types of simulations. Ultraliser is publicly released under the GNU GPL3 license on GitHub (BlueBrain/Ultraliser). SIGNIFICANCE: There is crystal clear evidence on the impact of cell shape on its signaling mechanisms. Structural models can therefore be insightful to realize the function; the more realistic the structure can be, the further we get insights into the function. Creating realistic structural models from existing ones is challenging, particularly when needed for detailed subcellular simulations. We present Ultraliser, a neuroscience-dedicated framework capable of building these structural models with realistic and detailed cellular geometries that can be used for simulations.

The final piece of the Triangle of U: Evolution of the tetraploid Brassica carinata genome.

Ethiopian mustard (Brassica carinata) is an ancient crop with remarkable stress resilience and a desirable seed fatty acid profile for biofuel uses. Brassica carinata is one of six Brassica species that share three major genomes from three diploid species (AA, BB, and CC) that spontaneously hybridized in a pairwise manner to form three allotetraploid species (AABB, AACC, and BBCC). Of the genomes of these species, that of B. carinata is the least understood. Here, we report a chromosome scale 1.31-Gbp genome assembly with 156.9-fold sequencing coverage for B. carinata, completing the reference genomes comprising the classic Triangle of U, a classical theory of the evolutionary relationships among these six species. Our assembly provides insights into the hybridization event that led to the current B. carinata genome and the genomic features that gave rise to the superior agronomic traits of B. carinata. Notably, we identified an expansion of transcription factor networks and agronomically important gene families. Completion of the Triangle of U comparative genomics platform has allowed us to examine the dynamics of polyploid evolution and the role of subgenome dominance in the domestication and continuing agronomic improvement of B. carinata and other Brassica species.

Synchronous spiking of cerebellar Purkinje cells during control of movements.

SignificanceThe information that one region of the brain transmits to another is usually viewed through the lens of firing rates. However, if the output neurons could vary the timing of their spikes, then, through synchronization, they would spotlight information that may be critical for control of behavior. Here we report that, in the cerebellum, Purkinje cell populations that share a preference for error convey, to the nucleus, when to decelerate the movement, by reducing their firing rates and temporally synchronizing the remaining spikes.

Impact of lowering fine particulate matter from major emission sources on mortality in Canada: A nationwide causal analysis.

Emissions of fine particulate matter (PM2.5) from human activities have been linked to substantial disease burdens, but evidence regarding how reducing PM2.5 at its sources would improve public health is sparse. We followed a population-based cohort of 2.7 million adults across Canada from 2007 through 2016. For each participant, we estimated annual mean concentrations of PM2.5 and the fractional contributions to PM2.5 from the five leading anthropogenic sources at their residential address using satellite observations in combination with a global atmospheric chemistry transport model. For each source, we estimated the causal effects of six hypothetical interventions on 10-y nonaccidental mortality risk using the parametric g-formula, a structural causal model. We conducted stratified analyses by age, sex, and income. This cohort would have experienced tangible health gains had contributions to PM2.5 from any of the five sources been reduced. Compared with no intervention, a 10% annual reduction in PM2.5 contributions from transportation and power generation, Canada's largest and fifth-largest anthropogenic sources, would have prevented approximately 175 (95%CI: 123-226) and 90 (95%CI: 63-117) deaths per million by 2016, respectively. A more intensive 50% reduction per year in PM2.5 contributions from the two sources would have averted 360 and 185 deaths per million, respectively, by 2016. The potential health benefits were greater among men, older adults, and low-income earners. In Canada, where PM2.5 levels are among the lowest worldwide, reducing PM2.5 contributions from anthropogenic sources by as little as 10% annually would yield meaningful health gains.

Chronic kidney disease in type 1 diabetes: translation of novel type 2 diabetes therapeutics to individuals with type 1 diabetes.

Current management of chronic kidney disease (CKD) in type 1 diabetes centres on glycaemic control, renin-angiotensin system inhibition and optimisation of risk factors including blood pressure, lipids and body weight. While these therapeutic approaches have significantly improved outcomes among people with type 1 diabetes and CKD, this population remains at substantial elevated risk for adverse kidney and cardiovascular events, with limited improvements over the last few decades. The significant burden of CKD and CVD in type 1 diabetes populations highlights the need to identify novel therapies with the potential for heart and kidney protection. Over the last decade, sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide 1 receptor agonists and non-steroidal mineralocorticoid receptor antagonists have emerged as potent kidney-protective and/or cardioprotective agents in type 2 diabetes. The consistent, substantial kidney and cardiovascular benefits of these agents has led to their incorporation into professional guidelines as foundational care for type 2 diabetes. Furthermore, introduction of these agents into clinical practice has been accompanied by a shift in the focus of diabetes care from a 'glucose-centric' to a 'cardiorenal risk-centric' approach. In this review, we evaluate the potential translation of novel type 2 diabetes therapeutics to individuals with type 1 diabetes with the lens of preventing the development and progression of CKD.

Vaccine Effectiveness Against Influenza A-Associated Hospitalization, Organ Failure, and Death: United States, 2022-2023.

BACKGROUND: Influenza circulation during the 2022-2023 season in the United States largely returned to pre-coronavirus disease 2019 (COVID-19)-pandemic patterns and levels. Influenza A(H3N2) viruses were detected most frequently this season, predominately clade 3C.2a1b.2a, a close antigenic match to the vaccine strain. METHODS: To understand effectiveness of the 2022-2023 influenza vaccine against influenza-associated hospitalization, organ failure, and death, a multicenter sentinel surveillance network in the United States prospectively enrolled adults hospitalized with acute respiratory illness between 1 October 2022, and 28 February 2023. Using the test-negative design, vaccine effectiveness (VE) estimates against influenza-associated hospitalization, organ failures, and death were measured by comparing the odds of current-season influenza vaccination in influenza-positive case-patients and influenza-negative, SARS-CoV-2-negative control-patients. RESULTS: A total of 3707 patients, including 714 influenza cases (33% vaccinated) and 2993 influenza- and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-negative controls (49% vaccinated) were analyzed. VE against influenza-associated hospitalization was 37% (95% confidence interval [CI]: 27%-46%) and varied by age (18-64 years: 47% [30%-60%]; ≥65 years: 28% [10%-43%]), and virus (A[H3N2]: 29% [6%-46%], A[H1N1]: 47% [23%-64%]). VE against more severe influenza-associated outcomes included: 41% (29%-50%) against influenza with hypoxemia treated with supplemental oxygen; 65% (56%-72%) against influenza with respiratory, cardiovascular, or renal failure treated with organ support; and 66% (40%-81%) against influenza with respiratory failure treated with invasive mechanical ventilation. CONCLUSIONS: During an early 2022-2023 influenza season with a well-matched influenza vaccine, vaccination was associated with reduced risk of influenza-associated hospitalization and organ failure.

Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccination Against SARS-CoV-2 Omicron XBB and BA.2.86/JN.1 Lineage Hospitalization and a Comparison of Clinical Severity-IVY Network, 26 Hospitals, October 18, 2023-March 9, 2024.

BACKGROUND: Assessing variant-specific COVID-19 vaccine effectiveness (VE) and severity can inform public health risk assessments and decisions about vaccine composition. BA.2.86 and its descendants, including JN.1 (referred to collectively as "JN lineages"), emerged in late 2023 and exhibited substantial divergence from co-circulating XBB lineages. METHODS: We analyzed patients hospitalized with COVID-19-like illness at 26 hospitals in 20 U.S. states admitted October 18, 2023-March 9, 2024. Using a test-negative, case-control design, we estimated effectiveness of an updated 2023-2024 (Monovalent XBB.1.5) COVID-19 vaccine dose against sequence-confirmed XBB and JN lineage hospitalization using logistic regression. Odds of severe outcomes, including intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) or death, were compared for JN versus XBB lineage hospitalizations using logistic regression. RESULTS: 585 case-patients with XBB lineages, 397 case-patients with JN lineages, and 4,580 control-patients were included. VE in the first 7-89 days after receipt of an updated dose was 54.2% (95% CI = 36.1%-67.1%) against XBB lineage hospitalization and 32.7% (95% CI = 1.9%-53.8%) against JN lineage hospitalization. Odds of ICU admission (adjusted odds ratio [aOR] 0.80; 95% CI = 0.46-1.38) and IMV or death (aOR 0.69; 95% CI = 0.34-1.40) were not significantly different among JN compared to XBB lineage hospitalizations. CONCLUSIONS: Updated 2023-2024 COVID-19 vaccination provided protection against both XBB and JN lineage hospitalization, but protection against the latter may be attenuated by immune escape. Clinical severity of JN lineage hospitalizations was not higher relative to XBB.

Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows.

BACKGROUND: Heat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses. RESULTS: A total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively. CONCLUSIONS: Physiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.

Development of High-Throughput Experimentation Approaches for Rapid Radiochemical Exploration.

Positron emission tomography is a widely used imaging platform for studying physiological processes. Despite the proliferation of modern synthetic methodologies for radiolabeling, the optimization of these reactions still primarily relies on inefficient one-factor-at-a-time approaches. High-throughput experimentation (HTE) has proven to be a powerful approach for optimizing reactions in many areas of chemical synthesis. However, to date, HTE has rarely been applied to radiochemistry. This is largely because of the short lifetime of common radioisotopes, which presents major challenges for efficient parallel reaction setup and analysis using standard equipment and workflows. Herein, we demonstrate an effective HTE workflow and apply it to the optimization of copper-mediated radiofluorination of pharmaceutically relevant boronate ester substrates. The workflow utilizes commercial equipment and allows for rapid analysis of reactions for optimizing reactions, exploring chemical space using pharmaceutically relevant aryl boronates for radiofluorinations, and constructing large radiochemistry data sets.

Data-Driven Simulations to Assess the Impact of Study Imperfections in Time-to-Event Analyses.

Quantitative bias analysis (QBA) permits assessment of the expected impact of various imperfections of the available data on the results and conclusions of a particular real-world study. This article extends QBA methodology to multivariable time-to-event analyses with right-censored endpoints, possibly including time-varying exposures or covariates. The proposed approach employs data-driven simulations, which preserve important features of the data at hand while offering flexibility in controlling the parameters and assumptions that may affect the results. First, the steps required to perform data-driven simulations are described, and then two examples of real-world time-to-event analyses illustrate their implementation and the insights they may offer. The first example focuses on the omission of an important time-invariant predictor of the outcome in a prognostic study of cancer mortality, and permits separating the expected impact of confounding bias from non-collapsibility. The second example assesses how imprecise timing of an interval-censored event - ascertained only at sparse times of clinic visits - affects its estimated association with a time-varying drug exposure. The simulation results also provide a basis for comparing the performance of two alternative strategies for imputing the unknown event times in this setting. The R scripts that permit the reproduction of our examples are provided.

Improving the Sensitivity of Protein Quantification by Immunoaffinity Liquid Chromatography─Triple Quadrupole Mass Spectrometry Using an Iterative Transition Summing Technique.

The desire to reach ever-diminishing lower limits of quantification (LLOQ) to probe changes in low abundance protein targets has led to enormous progress in sample preparation and liquid chromatography-tandem mass spectrometry (LC-MS/MS) instrumentation. To maximize signal and reduce noise, many approaches have been employed, including specific immunoaffinity (IA) enrichment and reducing the LC flow to the nanoflow (nLC) level; however, additional sensitivity gains may still be required. Recently, a technique termed "echo summing" has been described for small-molecular-weight analytes on a triple quadrupole (QqQ) MS where multiple iterations of the same, single selected reaction monitoring (SRM) transition are collected, summed, and integrated, yielding significant analyte dependent signal-to-noise (S/N) improvements. Herein, the direct applicability of echo summing to protein quantification by sequential IA combined with nLC-MS/MS (IA-nLC-MS/MS) is described for a beta nerve growth factor (NGF) and a soluble asialoglycoprotein receptor (sASGPR) assay from human serum. Five iterations of echo summing outperformed traditional collection in relative average accuracy (-1.5 ± 7.7 vs -41.7 ± 10.7% bias) and precision (7.8 vs 18.4% coefficient of variation (CV)) of the low-end quality control (QC) sample (N = 4) for NGF and improved functional sensitivity of serially diluted serum QC samples (N = 5 each population) approximately 2-fold (1.96 and 2.00-fold) for two peptides of sASGPR. Echo summing also extended the minimum quantifiable QC level for sASGPR 4-fold lower. Similar gains are believed to be achievable for most protein IA-nLC-MS/MS assays.

Reducing Quantitative Uncertainty Caused by Data Processing in Untargeted Metabolomics.

Processing liquid chromatography-mass spectrometry-based metabolomics data using computational programs often introduces additional quantitative uncertainty, termed computational variation in a previous work. This work develops a computational solution to automatically recognize metabolic features with computational variation in a metabolomics data set. This tool, AVIR (short for "Accurate eValuation of alIgnment and integRation"), is a support vector machine-based machine learning strategy (https://github.com/HuanLab/AVIR). The rationale is that metabolic features with computational variation have a poor correlation between chromatographic peak area and peak height-based quantifications across the samples in a study. AVIR was trained on a set of 696 manually curated metabolic features and achieved an accuracy of 94% in a 10-fold cross-validation. When tested on various external data sets from public metabolomics repositories, AVIR demonstrated an accuracy range of 84%-97%. Finally, tested on a large-scale metabolomics study, AVIR clearly indicated features with computational variation and thus guided us to manually correct them. Our results show that 75.3% of the samples with computational variation had a relative intensity difference of over 20% after correction. This demonstrates the critical role of AVIR in reducing computational variation to improve quantitative certainty in untargeted metabolomics analysis.

Gamification-augmented home-based exercise for peripheral artery disease: Rationale and design of the GAMEPAD Study.

BACKGROUND: Supervised exercise therapy improves walking performance, functional capacity, and quality of life in patients with peripheral artery disease (PAD). However, few patients with PAD are enrolled in supervised exercise programs, and there are a number of logistical and financial barriers to their participation. A home-based walking intervention is likely to be more accessible to patients with PAD, but no fully home-based walking program has demonstrated efficacy. Concepts from behavioral economics have been used to design scalable interventions that increase daily physical activity in patients with atherosclerotic vascular disease, but whether a similar program would be effective in patients with PAD is uncertain. STUDY DESIGN AND OBJECTIVES: GAMEPAD (NCT04536012) is a pragmatic, virtual, randomized controlled trial designed to evaluate the effectiveness of a gamification strategy informed by concepts from behavioral economics to increase daily physical activity in patients with PAD who are seen in cardiology and vascular surgery clinics affiliated with the University of Pennsylvania Health System. Patients are contacted by email or text message, and complete enrollment and informed consent on the Penn Way to Health online platform. A GAMEPAD substudy will evaluate the effectiveness of opt-in versus opt-out framing when approaching patients for study participation. Patients are then provided with a wearable fitness tracker, establish a baseline daily step count, set a goal to increase daily step count by 33%-50%, and are randomized 1:1 to the gamification or control arms. Interventions continue for 16 weeks, including a 4-week period during which goal step count is gradually increased in the gamification arm, with follow-up for an additional 8 weeks to evaluate the durability of behavior change. The trial has met its enrollment goal of 102 participants, with a primary endpoint of change from baseline in daily steps over the 16-week intervention period. Key secondary endpoints include change from baseline in daily steps over the 8-week postintervention follow-up period and changes in patient-reported measures of PAD symptoms and quality of life over the intervention and follow-up periods. CONCLUSIONS: GAMEPAD is a virtual, pragmatic randomized clinical trial of a novel, fully home-based walking intervention informed by concepts from behavioral economics to increase physical activity and PAD-specific quality of life in patients with PAD. Its results will have important implications for the application of behavioral economic concepts to scalable home-based strategies to promote physical activity in patients with PAD and other disease processes where physical activity is limited by exertional symptoms. CLINICAL TRIAL REGISTRATION: clinicaltrials.gov; NCT04536012.

Angiographic characteristics of patients with STEMI and COVID-19: Insights from NACMI registry.

BACKGROUND: To date, there has been no independent core lab angiographic analysis of patients with COVID-19 and STEMI. The study characterized the angiographic parameters of patients with COVID-19 and STEMI. METHODS: Angiograms of patients with COVID-19 and STEMI from the North American COVID-19 Myocardial Infarction (NACMI) Registry were sent to a Core Laboratory in Vancouver, Canada. Culprit lesion(s), Thrombolysis In Myocardial Infarction (TIMI) flow, Thrombus Grade Burden (TGB), and percutaneous coronary intervention (PCI) outcome were assessed. RESULTS: From 234 patients, 74% had one culprit lesion, 14% had multiple culprits and 12% had no culprit identified. Multivessel thrombotic disease and multivessel CAD were found in 27% and 53% of patients, respectively. Stent thrombosis accounted for 12% of the presentations and occurred in 55% of patients with previous coronary stents. Of the 182 who underwent PCI, 60 (33%) had unsuccessful PCI due to post-PCI TIMI flow <3 (43/60), residual high thrombus burden (41/60) and/or thrombus related complications (27/60). In-hospital mortality for successful, partially successful, and unsuccessful PCI was 14%, 13%, and 27%, respectively. Unsuccessful PCI was associated with increased risk of in-hospital mortality (risk ratio [RR] 1.96; 95% CI: 1.05-3.66, P = .03); in the adjusted model this estimate was attenuated (RR: 1.24; 95% CI: 0.65-2.34, P = .51). CONCLUSION: In patients with COVID-19 and STEMI, thrombus burden was pervasive with notable rates of multivessel thrombotic disease and stent thrombosis. Post-PCI, persistent thrombus and sub-optimal TIMI 3 flow rates led to one-third of the PCI's being unsuccessful, which decreased over time but remained an important predictor of in-hospital mortality.