Anifrolumab Study for Treatment Effectiveness in the Real World (ASTER) among patients with systemic lupus erythematosus: protocol for an international observational effectiveness study.

Introduction: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with a diverse clinical presentation that involves multiple organ systems and may lead to organ damage and increased risk of mortality. SLE is associated with a high burden of disease that can include loss of productivity and employment and reduced health-related quality of life. The current standard of care for SLE is primarily based on immunosuppression and glucocorticoids and is associated with risk of toxicities and poor tolerability.

The phage shock protein (PSP) envelope stress response: discovery of novel partners and evolutionary history.

Bacterial phage shock protein (PSP) systems stabilize the bacterial cell membrane and protect against envelope stress. These systems have been associated with virulence, but despite their critical roles, PSP components are not well characterized outside proteobacteria. Using comparative genomics and protein sequence-structure-function analyses, we systematically identified and analyzed PSP homologs, phyletic patterns, domain architectures, and gene neighborhoods.

Materials design for hypersonics.

Hypersonic vehicles must withstand extreme conditions during flights that exceed five times the speed of sound. These systems have the potential to facilitate rapid access to space, bolster defense capabilities, and create a new paradigm for transcontinental earth-to-earth travel. However, extreme aerothermal environments create significant challenges for vehicle materials and structures.

Cellular mechanotransduction of human osteoblasts in microgravity.

Astronauts experience significant and rapid bone loss as a result of an extended stay in space, making the International Space Station (ISS) the perfect laboratory for studying osteoporosis due to the accelerated nature of bone loss on the ISS. This prompts the question, how does the lack of load due to zero-gravity propagate to bone-forming cells, human fetal osteoblasts (hFOBs), altering their maturation to mineralization? Here, we aim to study the mechanotransduction mechanisms by which bone loss occurs in microgravity. Two automated experiments, microfluidic chips capable of measuring single-cell mechanics via aspiration and cell spheroids incubated in pressure-controlled chambers, were each integrated into a CubeLab deployed to the ISS National Laboratory.

Cellular mechanotransduction of human osteoblasts in microgravity.

Astronauts experience significant and rapid bone loss as a result of an extended stay in space, making the International Space Station (ISS) the perfect laboratory for studying osteoporosis due to the accelerated nature of bone loss on the ISS. This prompts the question, how does the lack of load due to zero-gravity propagate to bone-forming cells, human fetal osteoblasts (hFOBs), altering their maturation to mineralization? Here, we aim to study the mechanotransduction mechanisms by which bone loss occurs in microgravity. Two automated experiments, 4 microfluidic chips capable of measuring single-cell mechanics of hFOBs via aspiration and cell spheroids incubated in pressure-controlled chambers, were each integrated into a CubeLab deployed to the ISS National Laboratory.

An Op-Ed Writing Curriculum for Medical Students to Engage in Advocacy Through Public Writing.

Background: Op-ed writing can be a powerful and accessible advocacy tool for physicians, but training is lacking in undergraduate medical education.

Aim: To train and engage first-year medical students in op-ed writing.

Setting: Midwestern research-intensive medical school.

Optimizing quantum noise-induced reservoir computing for nonlinear and chaotic time series prediction.

Quantum reservoir computing is strongly emerging for sequential and time series data prediction in quantum machine learning. We make advancements to the quantum noise-induced reservoir, in which reservoir noise is used as a resource to generate expressive, nonlinear signals that are efficiently learned with a single linear output layer. We address the need for quantum reservoir tuning with a novel and generally applicable approach to quantum circuit parameterization, in which tunable noise models are programmed to the quantum reservoir circuit to be fully controlled for effective optimization.

Technique and Outcomes of Concomitant Aortic and Caval Resection and Reconstruction for Retroperitoneal Tumors.

Background: Major vascular involvement is often considered a contraindication to resection of malignant tumors, but in highly selected patients, it can be performed safely, with results that are highly dependent upon the tumor biology. Resection of both the aorta and inferior vena cava (IVC) is a rare undertaking, requiring both favorable tumor biology and a patient fit for a substantial surgical insult; nevertheless, it provides the possibility of a cure.

Methods: Patients requiring resection and reconstruction of both the aorta and IVC from 2009 through 2019 at 2 university medical centers were included.

Matrix confinement modulates 3D spheroid sorting and burst-like collective migration.

While it is known that cells with differential adhesion tend to segregate and preferentially sort, the physical forces governing sorting and invasion in heterogeneous tumors remain poorly understood. To investigate this, we tune matrix confinement, mimicking changes in the stiffness and confinement of the tumor microenvironment, to explore how physical confinement influences individual and collective cell migration in 3D spheroids. High levels of confinement lead to cell sorting while reducing matrix confinement triggers the collective fluidization of cell motion.

Development of mechanosensitive synthetic cells for biomedical applications.

The ability of cells to sense and respond to their physical environment plays a fundamental role in a broad spectrum of biological processes. As one of the most essential molecular force sensors and transducers found in cell membranes, mechanosensitive (MS) ion channels can convert mechanical inputs into biochemical or electrical signals to mediate a variety of sensations. The bottom-up construction of cell-sized compartments displaying cell-like organization, behaviors, and complexity, also known as synthetic cells, has gained popularity as an experimental platform to characterize biological functions in isolation.

Calcium-triggered DNA-mediated membrane fusion in synthetic cells.

In cells, membrane fusion is mediated by SNARE proteins, whose activities are calcium-dependent. While several non-native membrane fusion mechanisms have been demonstrated, few can respond to external stimuli. Here, we develop a calcium-triggered DNA-mediated membrane fusion strategy where fusion is regulated using surface-bound PEG chains that are cleavable by the calcium-activated protease calpain-1.

Calcium-triggered DNA-mediated membrane fusion in synthetic cells.

In cells, membrane fusion is mediated by SNARE proteins, whose activities are calcium-dependent. While several non-native membrane fusion mechanisms have been demonstrated, few can respond to external stimuli. Here, we develop a calcium-triggered DNA-mediated membrane fusion strategy where fusion is regulated using surface-bound PEG chains that are cleavable by the calcium-activated protease calpain-1.

Comparing genomic and epigenomic features across species using the WashU Comparative Epigenome Browser.

Genome browsers have become an intuitive and critical tool to visualize and analyze genomic features and data. Conventional genome browsers display data/annotations on a single reference genome/assembly; there are also genomic alignment viewer/browsers that help users visualize alignment, mismatch, and rearrangement between syntenic regions. However, there is a growing need for a comparative epigenome browser that can display genomic and epigenomic data sets across different species and enable users to compare them between syntenic regions.

BrainGENIE: The Brain Gene Expression and Network Imputation Engine.

In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood-brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles.

"I am not a junkie": Social categorization and differentiation among people who use drugs.

Background: Substance use stigma is a form of group-based exclusion, and delineating pathways from stigma to poor health requires a deeper understanding of the social dynamics of people who use drugs (PWUD). Outside of recovery, scant research has examined the role of social identity in addiction. Framed by Social Identity Theory/Self-Categorization Theory, this qualitative study investigated strategies of within-group categorization and differentiation among PWUD and the roles these social categories may play in shaping intragroup attitudes, perceptions, and behaviors.

Quantum machine learning with differential privacy.

Quantum machine learning (QML) can complement the growing trend of using learned models for a myriad of classification tasks, from image recognition to natural speech processing. There exists the potential for a quantum advantage due to the intractability of quantum operations on a classical computer. Many datasets used in machine learning are crowd sourced or contain some private information, but to the best of our knowledge, no current QML models are equipped with privacy-preserving features.

Quality of care and prescription patterns among patients with diabetic kidney disease-a large-scale cohort study from Taiwanese clinics.

Aims: To investigate the quality of care and prescription patterns of patients with diabetic kidney disease (DKD) receiving primary care at local clinics in Taiwan.

Methods: A retrospective chart review was conducted in 43 primary care clinics in Taiwan. The patients' baseline characteristics, laboratory tests, presence of complications and antidiabetic agents prescribed were analyzed.

Management of acute aortoiliac arterial thrombosis in patients with the novel coronavirus disease 2019: A case series and systematic review of the literature.

Objectives: Venous thrombosis has been widely described in the setting of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection; however, arterial thrombosis has rarely been reported. This study aims to assess the incidence, risk factors, interventions, and outcomes of acute aortoiliac arterial thrombosis in patients with active SARS-CoV-2 infections.

Methods: We present seven SARS-CoV-2-positive patients from our institution who acutely developed thrombi in the aortoiliac arterial system (7/2020-1/2021).

WashU Epigenome Browser update 2022.

WashU Epigenome Browser (https://epigenomegateway.wustl.edu/browser/) is a web-based genomic data exploration tool that provides visualization, integration, and analysis of epigenomic datasets.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.

Summix: A method for detecting and adjusting for population structure in genetic summary data.

Publicly available genetic summary data have high utility in research and the clinic, including prioritizing putative causal variants, polygenic scoring, and leveraging common controls. However, summarizing individual-level data can mask population structure, resulting in confounding, reduced power, and incorrect prioritization of putative causal variants. This limits the utility of publicly available data, especially for understudied or admixed populations where additional research and resources are most needed.

A seq2seq model to forecast the COVID-19 cases, deaths and reproductive R numbers in US counties.

The global pandemic of coronavirus disease 2019 (COVID-19) has killed almost two million people worldwide and over 400 thousand in the United States (US). As the pandemic evolves, informed policy-making and strategic resource allocation relies on accurate forecasts. To predict the spread of the virus within US counties, we curated an array of county-level demographic and COVID-19-relevant health risk factors.

Federated Quantum Machine Learning.

Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet.

Lipidomics-Based Comparison of Molecular Compositions of Green, Yellow, and Red Bell Peppers.

Identifying and annotating the molecular composition of individual foods will improve scientific understanding of how foods impact human health and how much variation exists in the molecular composition of foods of the same species. The complexity of this task includes distinct varieties and variations in natural occurring pigments of foods. Lipidomics, a sub-field of metabolomics, has emerged as an effective tool to help decipher the molecular composition of foods.