Process Intensification of the Continuous Synthesis of Bio-Derived Monomers for Sustainable Coatings Using a Taylor Vortex Flow Reactor.

We describe the optimization and scale-up of two consecutive reaction steps in the synthesis of bio-derived alkoxybutenolide monomers that have been reported as potential replacements for acrylate-based coatings (Sci. Adv.2020, 6, eabe0026).

Electrochemical Benzylic C(sp)-H Direct Amidation.

Amide bonds are ubiquitous and found in a myriad of functional molecules. Although formed in a reliable and robust fashion, alternative amide bond disconnections provide flexibility and synthetic control. Herein we describe an electrochemical method to form the non-amide C-N bond from direct benzylic C(sp)-H amidation.

Perioperative Botulinum Toxin A in the Surgical Management of Seizure-Related Shoulder Instability: A Case Report.

Case: A 20-year-old woman presented with recurrent bilateral shoulder instability concurrent with severe, treatment-refractory epilepsy. Imaging revealed glenoid bone loss of 25% to 28% and large Hill-Sachs defects bilaterally. Bone graft augmentation of the glenoid and infill of the Hill-Sachs defects was performed bilaterally.

A holistic approach for suppression of COVID-19 spread in workplaces and universities.

As society has moved past the initial phase of the COVID-19 crisis that relied on broad-spectrum shutdowns as a stopgap method, industries and institutions have faced the daunting question of how to return to a stabilized state of activities and more fully reopen the economy. A core problem is how to return people to their workplaces and educational institutions in a manner that is safe, ethical, grounded in science, and takes into account the unique factors and needs of each organization and community. In this paper, we introduce an epidemiological model (the "Community-Workplace" model) that accounts for SARS-CoV-2 transmission within the workplace, within the surrounding community, and between them.

Toward a Mobile Platform for Real-world Digital Measurement of Depression: User-Centered Design, Data Quality, and Behavioral and Clinical Modeling.

Background: Although effective mental health treatments exist, the ability to match individuals to optimal treatments is poor, and timely assessment of response is difficult. One reason for these challenges is the lack of objective measurement of psychiatric symptoms. Sensors and active tasks recorded by smartphones provide a low-burden, low-cost, and scalable way to capture real-world data from patients that could augment clinical decision-making and move the field of mental health closer to measurement-based care.

Author Correction: Determination of RNA structural diversity and its role in HIV-1 RNA splicing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Determination of RNA structural diversity and its role in HIV-1 RNA splicing.

Human immunodeficiency virus 1 (HIV-1) is a retrovirus with a ten-kilobase single-stranded RNA genome. HIV-1 must express all of its gene products from a single primary transcript, which undergoes alternative splicing to produce diverse protein products that include structural proteins and regulatory factors. Despite the critical role of alternative splicing, the mechanisms that drive the choice of splice site are poorly understood.

Effect of Adductor Canal Block Versus Femoral Nerve Block on Quadriceps Strength, Function, and Postoperative Pain After Anterior Cruciate Ligament Reconstruction: A Systematic Review of Level 1 Studies.

Background: Femoral nerve block (FNB) is a popular technique for reducing postoperative pain in patients with anterior cruciate ligament reconstruction (ACLR), but it is also linked to a number of adverse effects, such as quadriceps weakness, antalgic ambulation, and increased fall risk. Adductor canal block (ACB) has been offered as a motor nerve-sparing alternative to FNB.

Purpose: To evaluate available literature that compares the effects of ACB and FNB on functional outcomes after arthroscopic ACLR.

Accurate eQTL prioritization with an ensemble-based framework.

We present a novel ensemble-based computational framework, EnsembleExpr, that achieved the best performance in the Fourth Critical Assessment of Genome Interpretation expression quantitative trait locus "(eQTL)-causal SNPs" challenge for identifying eQTLs and prioritizing their gene expression effects. eQTLs are genome sequence variants that result in gene expression changes and are thus prime suspects in the search for contributions to the causality of complex traits. When EnsembleExpr is trained on data from massively parallel reporter assays, it accurately predicts reporter expression levels from unseen regulatory sequences and identifies sequence variants that exhibit significant changes in reporter expression.

Predicting gene expression in massively parallel reporter assays: A comparative study.

In many human diseases, associated genetic changes tend to occur within noncoding regions, whose effect might be related to transcriptional control. A central goal in human genetics is to understand the function of such noncoding regions: given a region that is statistically associated with changes in gene expression (expression quantitative trait locus [eQTL]), does it in fact play a regulatory role? And if so, how is this role "coded" in its sequence? These questions were the subject of the Critical Assessment of Genome Interpretation eQTL challenge. Participants were given a set of sequences that flank eQTLs in humans and were asked to predict whether these are capable of regulating transcription (as evaluated by massively parallel reporter assays), and whether this capability changes between alternative alleles.

Convolutional neural network architectures for predicting DNA-protein binding.

Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA-protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications.

High-throughput mapping of regulatory DNA.

Quantifying the effects of cis-regulatory DNA on gene expression is a major challenge. Here, we present the multiplexed editing regulatory assay (MERA), a high-throughput CRISPR-Cas9-based approach that analyzes the functional impact of the regulatory genome in its native context. MERA tiles thousands of mutations across ∼40 kb of cis-regulatory genomic space and uses knock-in green fluorescent protein (GFP) reporters to read out gene activity.

Interactions between chromosomal and nonchromosomal elements reveal missing heritability.

The measurement of any nonchromosomal genetic contribution to the heritability of a trait is often confounded by the inability to control both the chromosomal and nonchromosomal information in a population. We have designed a unique system in yeast where we can control both sources of information so that the phenotype of a single chromosomal polymorphism can be measured in the presence of different cytoplasmic elements. With this system, we have shown that both the source of the mitochondrial genome and the presence or absence of a dsRNA virus influence the phenotype of chromosomal variants that affect the growth of yeast.

An integrated model of multiple-condition ChIP-Seq data reveals predeterminants of Cdx2 binding.

Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery.

Universal count correction for high-throughput sequencing.

We show that existing RNA-seq, DNase-seq, and ChIP-seq data exhibit overdispersed per-base read count distributions that are not matched to existing computational method assumptions. To compensate for this overdispersion we introduce a nonparametric and universal method for processing per-base sequencing read count data called FIXSEQ. We demonstrate that FIXSEQ substantially improves the performance of existing RNA-seq, DNase-seq, and ChIP-seq analysis tools when compared with existing alternatives.

High-resolution genetic mapping with pooled sequencing.

Background: Modern genetics has been transformed by high-throughput sequencing. New experimental designs in model organisms involve analyzing many individuals, pooled and sequenced in groups for increased efficiency. However, the uncertainty from pooling and the challenge of noisy sequencing data demand advanced computational methods.