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An 8-year-old, male Rhesus macaque (Macaca mulatta), previously used for dengue virus (DENV) vaccine research with viral challenge, was presented with adult-onset, chronic, cyclic thrombocytopenia. Platelet number, morphology, and function were evaluated by automated hematology, peripheral blood smears, electron microscopy, flow cytometry, and impedance aggregometry. Bone marrow was evaluated by cytology. Both serum anti-dengue nonstructural protein 1 (NS1) antibodies and anti-platelet antibodies were detected by ELISA. Platelet characterization showed a lack of aggregation to all agonists (ADP, ASP, and collagen), increased activation with increased expression of surface marker (HLA-ABC), and an absence of surface receptor GPIX during clinical episodes of petechiae and ecchymoses, even in the presence of normal platelet counts. Bone marrow aspirates identified potential mild megakaryocytic hypoplasia. All platelet functions and morphologic attributes were within normal limits during clinically normal phases. Presence of anti-dengue NS1 serum antibodies confirmed a positive DENV titer 8 years postvaccination. Based on the history and clinical findings, a primary differential diagnosis for this chronic, cyclic platelet pathology was autoimmune platelet destruction with potential bone marrow involvement.

To stimulate progress in automating the reconstruction of neural circuits, we organized the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain. Participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with a consensus of human expert annotations. The winning team had no prior experience with EM images, and employed a convolutional network. This “deep learning” approach has since become accepted as a standard for segmentation of EM images. The challenge has continued to accept submissions, and the best so far has resulted from cooperation between two teams. The challenge has probably saturated, as algorithms cannot progress beyond limits set by ambiguities inherent in 2D scoring and the size of the test dataset. Retrospective evaluation of the challenge scoring system reveals that it was not sufficiently robust to variations in the widths of neurite borders. We propose a solution to this problem, which should be useful for a future 3D segmentation challenge.

Synthetic biology is increasingly used to develop sophisticated living devices for basic and applied research. Many of these genetic devices are engineered using multi-copy plasmids, but as the field progresses from proof-of-principle demonstrations to practical applications, it is important to develop single-copy synthetic modules that minimize consumption of cellular resources and can be stably maintained as genomic integrants. Here we use empirical design, mathematical modeling, and iterative construction and testing to build single-copy, bistable toggle switches with improved performance and reduced metabolic load that can be stably integrated into the host genome. Deterministic and stochastic models led us to focus on basal transcription to optimize circuit performance and helped to explain the resulting circuit robustness across a large range of component expression levels. The design parameters developed here provide important guidance for future efforts to convert functional multi-copy gene circuits into optimized single-copy circuits for practical, real-world use., Defense Threat Reduction Agency (DTRA) (Grant HDTRA1-14-1-006), United States. Air Force Office of Scientific Research (Grant FA9550-14-1-0060), United States. Defense Advanced Research Projects Agency (Grant N66001-11-C-4203), United States. Office of Naval Research (Grant N000141110725), National Institutes of Health (U.S.) (Grant P50 GM098792)

Synthetic biology has focused on engineering microbes to synthesize useful products or to serve as living diagnostics and therapeutics. Here we utilize a host-derived Escherichia coli strain engineered with a genetic toggle switch as a research tool to examine in vivo replicative states in a mouse model of chronic infection, and to compare in vivo and in vitro bacterial behavior. In contrast to the effect of antibiotics in vitro, we find that the fraction of actively dividing bacteria remains relatively high throughout the course of a chronic infection in vivo and increases in response to antibiotics. Moreover, the presence of non-dividing bacteria in vivo does not necessarily lead to an antibiotic-tolerant infection, in contrast to expectations from in vitro experiments. These results demonstrate the utility of engineered bacteria for querying pathogen behavior in vivo, and the importance of validating in vitro studies of antibiotic effects with in vivo models. Using Escherichia coli engineered with a genetic toggle switch, Certain et al. demonstrate ongoing bacterial replication in a mouse model of chronic infection, even with antibiotic treatment. This finding runs contrary to the expectation that antibiotics preferentially eliminate actively dividing bacteria and highlights the in vivo utility of synthetic biology., Defense Threat Reduction Agency (DTRA) (Grant HDTRA1-15-1-0051)

Time series are an important data class that includes recordings ranging from radio emissions, seismic activity, global positioning data, and stock prices to EEG measurements, vital signs, and voice recordings. Rapid growth in sensor and recording technologies is increasing the production of time series data and the importance of rapid, accurate analyses. Time series data are commonly analyzed using time-varying spectral methods to characterize their nonstationary and often oscillatory structure. Current methods provide local estimates of data features. However, they do not offer a statistical inference framework that applies to the entire time series. The important advances that we report are state-space multitaper (SS-MT) methods, which provide a statistical inference framework for time-varying spectral analysis of nonstationary time series. We model nonstationary time series as a sequence of second-order stationary Gaussian processes defined on nonoverlapping intervals. We use a frequency-domain random-walk model to relate the spectral representations of the Gaussian processes across intervals. The SS-MT algorithm efficiently computes spectral updates using parallel 1D complex Kalman filters. An expectation–maximization algorithm computes static and dynamic model parameter estimates. We test the framework in time-varying spectral analyses of simulated time series and EEG recordings from patients receiving general anesthesia. Relative to standard multitaper (MT), SS-MT gave enhanced spectral resolution and noise reduction (>10 dB) and allowed statistical comparisons of spectral properties among arbitrary time series segments. SS-MT also extracts time-domain estimates of signal components. The SS-MT paradigm is a broadly applicable, empirical Bayes’ framework for statistical inference that can help ensure accurate, reproducible findings from nonstationary time series analyses. Keywords: nonparametric spectral analysis; spectral representation theorem; complex Kalma, National Institutes of Health (U.S.) (Award R01-GM104948), National Institutes of Health (U.S.) (Award P01-GM118629)

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Mesenchymal stem cells are multipotent adult stem cells capable of generating bone, cartilage and fat, and are thus currently being exploited for regenerative medicine. When considering osteogenesis, developments have been made with regards to chemical induction (e.g. differentiation media) and physical induction (e.g. material stiffness, nanotopography), targeting established early transcription factors or regulators such as runx2 or bone morphogenic proteins and promoting increased numbers of cells committing to osteo-specific differentiation. Recent research highlighted the involvement of microRNAs in lineage commitment and terminal differentiation. Herein, gold nanoparticles that confer stability to short single stranded RNAs were used to deliver MiR-31 antagomiRs to both pre-osteoblastic cells and primary human MSCs in vitro. Results showed that blocking miR-31 led to an increase in osterix protein in both cell types at day 7, with an increase in osteocalcin at day 21, suggesting MSC osteogenesis. In addition, it was noted that antagomiR sequence direction was important, with the 5 prime reading direction proving more effective than the 3 prime. This study highlights the potential that miRNA antagomiR-Tagged nanoparticles offer as novel therapeutics in regenerative medicine.

Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology; stem cell biology; metabolism; genome-scale modeling; pluripotency; histone methylation; naive (ground) state; primed state; cell fate; metabolic network

The gut microbial community is dynamic during the first 3 years of life, before stabilizing to an adult-like state. However, little is known about the impact of environmental factors on the developing human gut microbiome. We report a longitudinal study of the gut microbiome based on DNA sequence analysis of monthly stool samples and clinical information from 39 children, about half of whom received multiple courses of antibiotics during the first 3 years of life. Whereas the gut microbiome of most children born by vaginal delivery was dominated by Bacteroides species, the four children born by cesarean section and about 20% of vaginally born children lacked Bacteroides in the first 6 to 18 months of life. Longitudinal sampling, coupled with whole-genome shotgun sequencing, allowed detection of strain-level variation as well as the abundance of antibiotic resistance genes. The microbiota of antibiotic-treated children was less diverse in terms of both bacterial species and strains, with some species often dominated by single strains. In addition, we observed short-term composition changes between consecutive samples from children treated with antibiotics. Antibiotic resistance genes carried on microbial chromosomes showed a peak in abundance after antibiotic treatment followed by a sharp decline, whereas some genes carried on mobile elements persisted longer after antibiotic therapy ended. Our results highlight the value of high-density longitudinal sampling studies with high-resolution strain profiling for studying the establishment and response to perturbation of the infant gut microbiome., National Human Genome Research Institute (U.S.) (grant 2U54HG003067-10), Juvenile Diabetes Research Foundation International, National Institutes of Health (U.S.) (grant U54 DK102557), National Institutes of Health (U.S.) (grant R01 DK092405), National Institutes of Health (U.S.) (grant P30 DK043351), Leona M. and Harry B. Helmsley Charitable Trust, Crohn's and Colitis Foundation of America

Inertial measurement units (IMUs) have been demonstrated to reliably measure human joint angles—an essential quantity in the study of biomechanics. However, most previous literature proposed IMU-based joint angle measurement systems that required manual alignment or prescribed calibration motions. This paper presents a simple, physically-intuitive method for IMU-based measurement of the knee flexion/extension angle in gait without requiring alignment or discrete calibration, based on computationally-efficient and easy-to-implement Principle Component Analysis (PCA). The method is compared against an optical motion capture knee flexion/extension angle modeled through OpenSim. The method is evaluated using both measured and simulated IMU data in an observational study (n = 15) with an absolute root-mean-square-error (RMSE) of 9.24 and a zero-mean RMSE of 3.49. Variation in error across subjects was found, made emergent by the larger subject population than previous literature considers. Finally, the paper presents an explanatory model of RMSE on IMU mounting location. The observational data suggest that RMSE of the method is a function of thigh IMU perturbation and axis estimation quality. However, the effect size for these parameters is small in comparison to potential gains from improved IMU orientation estimations. Results also highlight the need to set relevant datums from which to interpret joint angles for both truth references and estimated data., National Science Foundation (U.S.) (GRFP), National Science Foundation (U.S.) (IIS-1453141)

Optical technologies are essential for the rapid and efficient delivery of health care to patients. Efforts have begun to implement these technologies in miniature devices that are implantable in patients for continuous or chronic uses. In this review, we discuss guidelines for biomaterials suitable for use in vivo. Basic optical functions such as focusing, reflection, and diffraction have been realized with biopolymers. Biocompatible optical fibers can deliver sensing or therapeutic-inducing light into tissues and enable optical communications with implanted photonic devices. Wirelessly powered, light-emitting diodes (LEDs) and miniature lasers made of biocompatible materials may offer new approaches in optical sensing and therapy. Advances in biotechnologies, such as optogenetics, enable more sophisticated photonic devices with a high level of integration with neurological or physiological circuits. With further innovations and translational development, implantable photonic devices offer a pathway to improve health monitoring, diagnostics, and light-activated therapies. Keywords: biomaterials; biocompatible; biodegradable; optics; photonics, United States. Department of Defense (Award FA9550-13-1-0068), National Institutes of Health (U.S.) (Award P41-EB015903), National Institutes of Health (U.S.) (Award R01-CA192878), National Science Foundation (U.S.) (Award CBET-1264356), National Science Foundation (U.S.) (Award ECCS-1505569)

microRNAs (miRNAs) show high potential for cancer treatment, however one of the most significant bottlenecks in enabling miRNA effect is the need for an efficient vehicle capable of selective targeting to tumor cells without disrupting normal cells. Even more challenging is the ability to detect and silence multiple targets simultaneously with high sensitivity while precluding resistance to the therapeutic agents. Focusing on the pervasive role of miRNAs, herein we review the multiple nanomaterial-based systems that encapsulate DNA/RNA for miRNA sensing and inhibition in cancer therapy. Understanding the potential of miRNA detection and silencing while overcoming existing limitations will be critical to the optimization and clinical utilization of this technology. Keywords: microRNA; RNAi; Nanomaterials; Surface modification; Biosensors; Cancer; Nanotheranostics; Translational medicine

Physiologic and environmental factors can modulate antibiotic activity and thus pose a significant challenge to antibiotic treatment. The quinolone class of antibiotics, which targets bacterial topoisomerases, fails to kill bacteria that have grown to high density; however, the mechanistic basis for this persistence is unclear. Here, we show that exhaustion of the metabolic inputs that couple carbon catabolism to oxidative phosphorylation is a primary cause of growth phase-dependent persistence to quinolone antibiotics. Supplementation of stationary-phase cultures with glucose and a suitable terminal electron acceptor to stimulate respiratory metabolism is sufficient to sensitize cells to quinolone killing. Using this approach, we successfully sensitize high-density populations of Escherichia coli, Staphylococcus aureus, and Mycobacterium smegmatis to quinolone antibiotics. Our findings link growth-dependent quinolone persistence to discrete impairments in respiratory metabolism and identify a strategy to kill non-dividing bacteria. Gutierrez et al. show that activation of cellular respiration is sufficient to sensitize antibiotic refractory bacteria at high densities to drugs targeting DNA topoisomerases. This suggests that the nutrient environment and metabolic state are key components of bacterial persistence phenotypes. Keywords: quinolones; drug persistence; antibiotic; oxidative phosphorylation, Defense Threat Reduction Agency (DTRA) (Grant HDTRA1-15-1-0051)

HIV is a highly mutable virus, and over 30 years after its discovery, a vaccine or cure is still not available. The isolation of broadly neutralizing antibodies (bnAbs) from HIV-infected patients has led to renewed hope for a prophylactic vaccine capable of combating the scourge of HIV. A major challenge is the design of immunogens and vaccination protocols that can elicit bnAbs that target regions of the virus’s spike proteins where the likelihood of mutational escape is low due to the high fitness cost of mutations. Related challenges include the choice of combinations of bnAbs for therapy. An accurate representation of viral fitness as a function of its protein sequences (a fitness landscape), with explicit accounting of the effects of coupling between mutations, could help address these challenges. We describe a computational approach that has allowed us to infer a fitness landscape for gp160, the HIV polyprotein that comprises the viral spike that is targeted by antibodies. We validate the inferred landscape through comparisons with experimental fitness measurements, and various other metrics. We show that an effective antibody that prevents immune escape must selectively bind to high escape cost residues that are surrounded by those where mutations incur a low fitness cost, motivating future applications of our landscape for immunogen design. Keywords: HIV; fitness landscape; envelope protein; statistical inference; broadly neutralizing antibodies

Fecal microbiota transplantation is a highly effective intervention for patients suffering from recurrent Clostridium difficile, a common hospital-acquired infection. Fecal microbiota transplantation’s success as a therapy for C. difficile has inspired interest in performing clinical trials that experiment with fecal microbiota transplantation as a therapy for other conditions like inflammatory bowel disease, obesity, diabetes, and Parkinson’s disease. Results from clinical trials that use fecal microbiota transplantation to treat inflammatory bowel disease suggest that, for at least one condition beyond C. difficile, most fecal microbiota transplantation donors produce stool that is not efficacious. The optimal strategies for identifying and using efficacious donors have not been investigated. We therefore examined the optimal Bayesian response-adaptive strategy for allocating patients to donors and formulated a computationally tractable myopic heuristic. This heuristic computes the probability that a donor is efficacious by updating prior expectations about the efficacy of fecal microbiota transplantation, the placebo rate, and the fraction of donors that produce efficacious stool. In simulations designed to mimic a recent fecal microbiota transplantation clinical trial, for which traditional power calculations predict ∼100% statistical power, we found that accounting for differences in donor stool efficacy reduced the predicted statistical power to ∼9%. For these simulations, using the heuristic Bayesian allocation strategy more than quadrupled the statistical power to ∼39%. We use the results of similar simulations to make recommendations about the number of patients, the number of donors, and the choice of clinical endpoint that clinical trials should use to optimize their ability to detect if fecal microbiota transplantation is effective for treating a condition.

Hands-on demonstrations greatly enhance the teaching of science, technology, engineering, and mathematics (STEM) concepts and foster engagement and exploration in the sciences. While numerous chemistry and physics classroom demonstrations exist, few biology demonstrations are practical and accessible due to the challenges and concerns of growing living cells in classrooms. We introduce BioBits™ Explorer, a synthetic biology educational kit based on shelf-stable, freeze-dried, cell-free (FD-CF) reactions, which are activated by simply adding water. The FD-CF reactions engage the senses of sight, smell, and touch with outputs that produce fluorescence, fragrances, and hydrogels, respectively. We introduce components that can teach tunable protein expression, enzymatic reactions, biomaterial formation, and biosensors using RNA switches, some of which represent original FD-CF outputs that expand the toolbox of cell-free synthetic biology. The BioBits™ Explorer kit enables hands-on demonstrations of cutting-edge science that are inexpensive and easy to use, circumventing many current barriers for implementing exploratory biology experiments in classrooms.

Nanoparticle (NP) carriers provide new opportunities for controlled delivery of drugs, and have potential to address challenges such as effective oral delivery of insulin. However, due to the difficulty of efficiently loading insulin and other proteins inside polymeric NPs, their use has been mostly restricted to the encapsulation of small molecules. To better understand the processes involved in encapsulation of proteins in NPs, we study how buffer conditions, ionic chelation, and preparation methods influence insulin loading in poly(lactic-co-glycolic acid)-b-poly(ethylene glycol) (PLGA-PEG) NPs. We report that, although insulin is weakly bound and easily released from the NPs in the presence of buffer ions, insulin loading can be increased by over 10-fold with the use of chelating zinc ions and by the optimization of the pH during nanoprecipitation. We further provide ways of changing synthesis parameters to control NP size while maintaining high insulin loading. These results provide a simple method to enhance insulin loading of PLGA-PEG NPs and provide insights that may extend to other protein drug delivery systems that are subject to limited loading., National Science Foundation (U.S.) (award number DMR-0819762), Canadian Institutes of Health Research (postdoctoral fellowship), National Institutes of Health (U.S.) (Grant R01 EB015419)

There is a need for large-scale, longitudinal studies to determine the mechanisms by which the gut microbiome and its interactions with the host affect human health and disease. Current methods for profiling the microbiome typically utilize next-generation sequencing applications that are expensive, slow, and complex. Here, we present a synthetic biology platform for affordable, on-demand, and simple analysis of microbiome samples using RNA toehold switch sensors in paper-based, cell-free reactions. We demonstrate species-specific detection of mRNAs from 10 different bacteria that affect human health and four clinically relevant host biomarkers. We develop a method to quantify mRNA using our toehold sensors and validate our platform on clinical stool samples by comparison to RT-qPCR. We further highlight the potential clinical utility of the platform by showing that it can be used to rapidly and inexpensively detect toxin mRNA in the diagnosis of Clostridium difficile infections., National Institutes of Health (U.S.) (Grant T32-DK007191)

Upper-extremity exoskeletons have demonstrated potential as augmentative, assistive, and rehabilitative devices. Typical control of upper-extremity exoskeletons have relied on switches, force/torque sensors, and surface electromyography (sEMG), but these systems are usually reactionary, and/or rely on entirely hand-tuned parameters. sEMG-based systems may be able to provide anticipatory control, since they interface directly with muscle signals, but typically require expert placement of sensors on muscle bodies. We present an implementation of an adaptive sEMG-based exoskeleton controller that learns a mapping between muscle activation and the desired system state during interaction with a user, generating a personalized sEMG feature classifier to allow for anticipatory control. This system is robust to novice placement of sEMG sensors, as well as subdermal muscle shifts. We validate this method with 18 subjects using a thumb exoskeleton to complete a book-placement task. This learning-from-demonstration system for exoskeleton control allows for very short training times, as well as the potential for improvement in intent recognition over time, and adaptation to physiological changes in the user, such as those due to fatigue., Jeptha H. and Emily V. Wade Fund

Protein-DNA interactions are critical for the successful functioning of all natural systems. The key role in these interactions is played by processes of protein search for specific sites on DNA. Although it has been studied for many years, only recently microscopic aspects of these processes became more clear. In this work, we present a review on current theoretical understanding of the molecular mechanisms of the protein target search. A comprehensive discrete-state stochastic method to explain the dynamics of the protein search phenomena is introduced and explained. Our theoretical approach utilizes a first-passage analysis and it takes into account the most relevant physical-chemical processes. It is able to describe many fascinating features of the protein search, including unusually high effective association rates, high selectivity and specificity, and the robustness in the presence of crowders and sequence heterogeneity., National Science Foundation (U.S.) (Grant CHE-1664218), National Science Foundation (U.S.) (Grant PHY-1427654), Robert A. Welch Foundation (Grant C-1559)

In 1985, the serendipitous discovery of fullerene triggered the research of carbon structures into the world of symmetric nanomaterials. Consequently, Robert F. Curl, Harold W. Kroto and Richard E. Smalley were awarded the Noble prize in chemistry for their discovery of the buckminsterfullerene (C[subscript 60] with a cage-like fused-ring structure). Fullerene, as the first symmetric nanostructure in carbon nanomaterials family, opened up new perspectives in nanomaterials field leading to discovery and research on other symmetric carbon nanomaterials like carbon nanotubes and two-dimensional graphene which put fullerenes in the shade, while fullerene as the most symmetrical molecule in the world with incredible properties deserves more attention in nanomaterials studies. Buckyball with its unique structure consisting of sp[superscript 2] carbons which form a high symmetric cage with different sizes (C[subscript 60], C[subscript 70] and so on); however, the most abundant among them is C[subscript 60] which possesses 60 carbon atoms. The combination of unique properties of this molecule extends its applications in divergent areas of science, especially those related to biomedical engineering. This review aims to be a comprehensive review with a broad interest to the biomedical engineering community, being a substantial overview of the most recent advances on fullerenes in biomedical applications that have not been exhaustively and critically reviewed in the past few years.

Synthetic gene expression is highly sensitive to intragenic compositional context (promoter structure, spacing regions between promoter and coding sequences, and ribosome binding sites). However, much less is known about the effects of intergenic compositional context (spatial arrangement and orientation of entire genes on DNA) on expression levels in synthetic gene networks. We compare expression of induced genes arranged in convergent, divergent, or tandem orientations. Induction of convergent genes yielded up to 400% higher expression, greater ultrasensitivity, and dynamic range than divergent- or tandem-oriented genes. Orientation affects gene expression whether one or both genes are induced. We postulate that transcriptional interference in divergent and tandem genes, mediated by supercoiling, can explain differences in expression and validate this hypothesis through modeling and in vitro supercoiling relaxation experiments. Treatment with gyrase abrogated intergenic context effects, bringing expression levels within 30% of each other. We rebuilt the toggle switch with convergent genes, taking advantage of supercoiling effects to improve threshold detection and switch stability.

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. In vehicle dynamics, it is commonly understood that there is an inverse relationship between stability and maneuverability. However, animal studies have found that stability and maneuverability can coincide. In this study, we examine humans running a reactive agility obstacle and consider the relationship between observational perceived agility and balance, as well as the relationship between quantified surrogates of agility and balance. Recreational athletes (n = 18) completed the agility task while wearing inertial measurement units (IMUs) on their body. The task was also video-recorded. An observational study was completed by a separate group of adults (n = 33) that were asked to view the videos and score each athlete on a Likert scale for balance and for agility. The data from the body-worn IMUs were used to estimate quantified surrogate measures for agility and balance, and to assess if the relationship between the quantified agility and balance was in the same direction as the perceived relationship from the Likert scale responses. Results indicate that athletes that were given a higher Likert agility score were also given a higher balance score (rs= 0.75,p < 0.001). Quantitative surrogates of agility and balance also showed this same relationship. Additional insights on technique for this reactive agility task were informed by the quantitative surrogates. We observed the importance of stepping technique in achieving the faster completion times. The fast performing athletes spent a greater proportion of the task in double support and lower overall time in single support indicating increased periods of static stability. The fast performing athletes did not have a higher body speed, but performed the task with a more efficient tec

HIV-1–specific broadly neutralizing antibodies (bnAbs) typically develop in individuals with continuous high-level viral replication and increased immune activation, conditions that cannot be reproduced during prophylactic immunization. Understanding mechanisms supporting bnAb development in the absence of high-level viremia may be important for designing bnAb-inducing immunogens. Here, we show that the breadth of neutralizing antibody responses in HIV-1 controllers was associated with a relative enrichment of circulating CXCR5[superscript +]CXCR3[superscript +]PD-1[superscript lo] CD4[superscript +] T cells. These CXCR3[superscript +]PD-1[superscript lo] Tfh-like cells were preferentially induced in vitro by functionally superior dendritic cells from controller neutralizers, and able to secrete IL-21 and support B cells. In addition, these CXCR3[superscript +]PD-1[superscript lo] Tfh-like cells contained higher proportions of stem cell–like memory T cells, and upon antigenic stimulation differentiated into PD-1[superscript hi ]Tfh-like cells in a Notch-dependent manner. Together, these data suggest that CXCR5[superscript +]CXCR3[superscript +]PD-1[superscript lo] cells represent a dendritic cell–primed precursor cell population for PD-1hi Tfh-like cells that may contribute to the generation of bnAbs in the absence of high-level viremia.

We demonstrate a quantitative X-ray phase contrast imaging (XPCI) technique derived from propagation dependent phase change. We assume that the absorption and phase components are correlated and solve the Transport of Intensity Equation (TIE). The experimental setup is simple compared to other XPCI techniques; the only requirements are a micro-focus X-ray source with sufficient temporal coherence and an X-ray detector of sufficient spatial resolution. This method was demonstrated in three scenarios, the first of which entails identification of an index-matched sphere. A rubber and nylon sphere were immersed in water and imaged. While the rubber sphere could be plainly seen on a radiograph, the nylon sphere was only visible in the phase reconstruction. Next, the technique was applied to differentiating liquid samples. In this scenario, three liquid samples (acetone, water, and hydrogen peroxide) were analyzed using both conventional computed tomography (CT) and phase contrast CT. While conventional CT was capable of differentiating between acetone and the other two liquids, it failed to distinguish between water and hydrogen peroxide; only phase CT was capable of differentiating all three samples. Finally, the technique was applied to CT imaging of a human artery specimen with extensive atherosclerotic plaque. This scenario demonstrated the increased sensitivity to soft tissue compared to conventional CT; it also uncovered some drawbacks of the method, which will be the target of future work. In all cases, the signal-to-noise ratio of phase contrast was greatly enhanced relative to conventional attenuation-based imaging. Keywords: Phase retrieval, transport of intensity, X-ray imaging, United States. Department of Homeland Security (Contract HSHQDC-11-C-00083)

Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our ‘ribocomputing’ systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings., National Institutes of Health (U.S.) (Grant 1DP2OD007292), National Institutes of Health (U.S.) (Grant 1R01EB018659), United States. Office of Naval Research (Award N000141110914), United States. Office of Naval Research (Grant N000141010827), United States. Office of Naval Research (Grant N000141310593), United States. Office of Naval Research (Grant N000141410610), United States. Office of Naval Research (Grant N000141612410), National Science Foundation (U.S.) (Grant CCF1054898), National Science Foundation (U.S.) (Grant CCF1317291), National Science Foundation (U.S.) (Grant CCF1162459), United States. Defense Advanced Research Projects Agency (Grant HR001112C0061), Defense Threat Reduction Agency (DTRA) (Grant HDTRA1-15-1-0040)

X-ray phase imaging utilizes a variety of techniques to render phase information as intensity contrast and these intensity images can in some cases be processed to retrieve quantitative phase. A subset of these techniques use free space propagation to generate phase contrast and phase can be recovered by inverting differential equations governing propagation. Two techniques to generate quantitative phase reconstructions from a single phase contrast image are described in detail, along with regularization techniques to reduce the inuence of noise. Lastly, a recently developed technique utilizing a binary-amplitude grid to enhance signal strength in propagation-based techniques is described., United States. Department of Homeland Security. Science and Technology Directorate (Contract HSHQDC-11-C-00083), National Institutes of Health (U.S.) (R01EB009715)

Deep learning has been proven to achieve ground-breaking accuracy in various tasks. In this paper, we implemented a deep neural network (DNN) to achieve phase retrieval in a wide-field microscope. Our DNN utilized the residual neural network (ResNet) architecture and was trained using the data generated by a phase SLM. The results showed that our DNN was able to reconstruct the profile of the phase target qualitatively. In the meantime, large error still existed, which indicated that our approach still need to be improved., Singapore-MIT Alliance for Research and Technology (SMART), United States. Department of Energy. Computational Science Graduate Fellowship Program (DE-FG02-97ER25308), United States. Intelligence Advanced Research Projects Activity

We present a novel and time-efficient method for intracoronary lumen detection, which produces three-dimensional (3-D) coronary arteries using optical coherence tomographic (OCT) images. OCT images are acquired for multiple patients and longitudinal cross-section (LOCS) images are reconstructed using different acquisition angles. The lumen contours for each LOCS image are extracted and translated to 2-D cross-sectional images. Using two angiographic projections, the centerline of the coronary vessel is reconstructed in 3-D, and the detected 2-D contours are transformed to 3-D and placed perpendicular to the centerline. To validate the proposed method, 613 manual annotations from medical experts were used as gold standard. The 2-D detected contours were compared with the annotated contours, and the 3-D reconstructed models produced using the detected contours were compared to the models produced by the annotated contours. Wall shear stress (WSS), as dominant hemodynamics factor, was calculated using computational fluid dynamics and 844 consecutive 2-mm segments of the 3-D models were extracted and compared with each other. High Pearson's correlation coefficients were obtained for the lumen area (r = 0.98) and local WSS (r = 0.97) measurements, while no significant bias with good limits of agreement was shown in the Bland-Altman analysis. The overlapping and nonoverlapping areas ratio between experts' annotations and presented method was 0.92 and 0.14, respectively. The proposed computer-aided lumen extraction and 3-D vessel reconstruction method is fast, accurate, and likely to assist in a number of research and clinical applications.

Contemporary endovascular stents are the product of an iterative design and development process that leverages evolving concepts in vascular biology and engineering. This article reviews how insights into vascular pathophysiology, materials science, and design mechanics drive stent design and explain modes of stent failure. Current knowledge of pathologic processes is providing a more complete picture of the factors mediating stent failure. Further evolution of endovascular stents includes bioresorbable platforms tailored to treat plaques acutely and to then disappear after lesion pacification. Ongoing refinement of stent technology will continue to require insights from pathology to understand adverse events, refine clinical protocols, and drive innovation. Keywords: Coronary artery disease; Pathology; Bare metal stent; Drug-eluting stent; In-stent restenosis; In-stent thrombosis; Atherosclerosis; Neoatherosclerosis, National Institutes of Health (U.S.) (Grant R01 GM-49039)

Vaccines remain the most effective tool to prevent infectious diseases. Here, we introduce an in vitro booster vaccination approach that relies on antigen-dependent activation of human memory B cells in culture. This stimulation induces antigen- specific B cell proliferation, differentiation of B cells into plasma cells, and robust antibody secretion after a few days of culture. We validated this strategy using cells from healthy donors to retrieve human antibodies against tetanus toxoid and influenza hemagglutinin (HA) from H1N1 and newly emergent subtypes such as H5N1 and H7N9. Anti-HA antibodies were cross-reactive against multiple subtypes, and some showed neutralizing activity. Although these antibodies may have arisen as a result of previous influenza infection, we also obtained gp120-reactive antibodies from non-HIV-infected donors, indicating that we can generate antibodies without prior antigenic exposure. Overall, our novel approach can be used to rapidly produce therapeutic antibodies and has the potential to assess the immunogenicity of candidate antigens, which could be exploited in future vaccine development., National Institutes of Health (U.S.) (Award DP2 OD020839), National Institutes of Health (U.S.) (Award U24 AI11862-01), National Institutes of Health (U.S.) (Award P50 HG006193), Bill & Melinda Gates Foundation (Grant 03629000189)

Renal sympathetic denervation (RDN) is under investigation as a treatment option in patients with resistant hypertension (RH). Determinants of arterial compliance may, however, help to predict the BP response to therapy. Aortic distensibility (AD) is a well-established parameter of aortic stiffness and can reliably be obtained by CMR. This analysis sought to investigate the effects of RDN on AD and to assess the predictive value of pre-treatment AD for BP changes. We analyzed data of 65 patients with RH included in a multicenter trial. RDN was performed in all participants. A standardized CMR protocol was utilized at baseline and at 6-month follow-up. AD was determined as the change in cross-sectional aortic area per unit change in BP. Office BP decreased significantly from 173/92 ± 24/16 mmHg at baseline to 151/85 ± 24/17 mmHg (p < 0.001) 6 months after RDN. Maximum aortic areas increased from 604.7 ± 157.7 to 621.1 ± 157.3 mm[superscript 2] (p = 0.011). AD improved significantly by 33% from 1.52 ± 0.82 to 2.02 ± 0.93 × 10[superscript −3] mmHg[superscript −1] (p < 0.001). Increase of AD at follow-up was significantly more pronounced in younger patients (p = 0.005) and responders to RDN (p = 0.002). Patients with high-baseline AD were significantly younger (61.4 ± 10.1 vs. 67.1 ± 8.4 years, p = 0.022). However, there was no significant correlation of baseline AD to response to RDN. AD is improved after RDN across all age groups. Importantly, these improvements appear to be unrelated to observed BP changes, suggesting that RDN may have direct effects on the central vasculature. Keywords: Renal denervation, Aortic distensibility, Compliance, Vascular stiffness, Cardiovascular magnetic resonance, CMR, Resistant hypertension

Background: Despite the increasing recognition that microbial communities within the human body are linked to health, we have an incomplete understanding of the environmental and molecular interactions that shape the composition of these communities. Although host genetic factors play a role in these interactions, these factors have remained relatively unexplored given the requirement for large population-based cohorts in which both genotyping and microbiome characterization have been performed. Methods: We performed whole-genome sequencing of 298 donors from the Human Microbiome Project (HMP) healthy cohort study to accompany existing deep characterization of their microbiomes at various body sites. This analysis yielded an average sequencing depth of 32x, with which we identified 27 million (M) single nucleotide variants and 2.3 M insertions-deletions. Results: Taxonomic composition and functional potential of the microbiome covaried significantly with genetic principal components in the gastrointestinal tract and oral communities, but not in the nares or vaginal microbiota. Example associations included validation of known associations between FUT2 secretor status, as well as a variant conferring hypolactasia near the LCT gene, with Bifidobacterium longum abundance in stool. The associations of microbial features with both high-level genetic attributes and single variants were specific to particular body sites, highlighting the opportunity to find unique genetic mechanisms controlling microbiome properties in the microbial communities from multiple body sites. Conclusions: This study adds deep sequencing of host genomes to the body-wide microbiome sequences already extant from the HMP healthy cohort, creating a unique, versatile, and well-controlled reference for future studies seeking to identify host genetic modulators of the microbiome. Keywords: Human Microbiome Project, Microbiome and human genetics, Human genome sequence, Microbiome metagenome sequence, Ass, National Institutes of Health (U.S.) (Grant U54HG003067 ), National Institutes of Health (U.S.) (Grant U54DE023798), United States. Army Research Office (Grant W911NF-11-1-0429)

As our population ages, there is a greater need for a suitable supply of engineered tissues to address a range of debilitating ailments. Stem cell based therapies are envisioned to meet this emerging need. Despite significant progress in controlling stem cell differentiation, it is still difficult to engineer human tissue constructs for transplantation. Recent advances in micro- and nanofabrication techniques have enabled the design of more biomimetic biomaterials that may be used to direct the fate of stem cells. These biomaterials could have a significant impact on the next generation of stem cell based therapies. Here, we highlight the recent progress made by micro- and nanoengineering techniques in the biomaterials field in the context of directing stem cell differentiation. Particular attention is given to the effect of surface topography, chemistry, mechanics and micro- and nanopatterns on the differentiation of embryonic, mesenchymal and neural stem cells. Keywords: micro- and nanotopography; microwells; microarrays; embryonic and adult stem cells; stem cell therapy, National Institutes of Health (U.S.) (Grant HL092836), National Institutes of Health (U.S.) (Grant DE019024), National Institutes of Health (U.S.) (Grant EB008392), National Institutes of Health (U.S.) (Grant DE021468), National Institutes of Health (U.S.) (Grant AR05837), National Institutes of Health (U.S.) (Grant EB012597), National Institutes of Health (U.S.) (Grant HL099073), National Science Foundation (U.S.) (Award DMR 0847287)

Ras proteins are highly conserved signaling molecules that exhibit regulated, nucleotide-dependent switching between active and inactive states. The high conservation of Ras requires mechanistic explanation, especially given the general mutational tolerance of proteins. Here, we use deep mutational scanning, biochemical analysis and molecular simulations to understand constraints on Ras sequence. Ras exhibits global sensitivity to mutation when regulated by a GTPase activating protein and a nucleotide exchange factor. Removing the regulators shifts the distribution of mutational effects to be largely neutral, and reveals hotspots of activating mutations in residues that restrain Ras dynamics and promote the inactive state. Evolutionary analysis, combined with structural and mutational data, argue that Ras has co-evolved with its regulators in the vertebrate lineage. Overall, our results show that sequence conservation in Ras depends strongly on the biochemical network in which it operates, providing a framework for understanding the origin of global selection pressures on proteins., National Institutes of Health (U.S.) (Grant PO1 AI091580)

Demand for clinical decision support systems in medicine and self-diagnostic symptom checkers has substantially increased in recent years. Existing platforms rely on knowledge bases manually compiled through a labor-intensive process or automatically derived using simple pairwise statistics. This study explored an automated process to learn high quality knowledge bases linking diseases and symptoms directly from electronic medical records. Medical concepts were extracted from 273,174 de-identified patient records and maximum likelihood estimation of three probabilistic models was used to automatically construct knowledge graphs: logistic regression, naive Bayes classifier and a Bayesian network using noisy OR gates. A graph of disease-symptom relationships was elicited from the learned parameters and the constructed knowledge graphs were evaluated and validated, with permission, against Google’s manually-constructed knowledge graph and against expert physician opinions. Our study shows that direct and automated construction of high quality health knowledge graphs from medical records using rudimentary concept extraction is feasible. The noisy OR model produces a high quality knowledge graph reaching precision of 0.85 for a recall of 0.6 in the clinical evaluation. Noisy OR significantly outperforms all tested models across evaluation frameworks (p < 0.01)., Google (Firm)

All rights reserved. Recent advances in cellular profiling have demonstrated substantial heterogeneity in the behaviour of cells once deemed 'identical', challenging fundamental notions of cell 'type' and 'state'. Not surprisingly, these findings have elicited substantial interest in deeply characterizing the diversity, interrelationships and plasticity among cellular phenotypes. To explore these questions, experimental platforms are needed that can extensively and controllably profile many individual cells. Here, microfluidic structures-whether valve-, droplet- or nanowell-based-have an important role because they can facilitate easy capture and processing of single cells and their components, reducing labour and costs relative to conventional plate-based methods while also improving consistency. In this article, we review the current state-of-the-art methodologies with respect to microfluidics for mammalian single-cell 'omics' and discuss challenges and future opportunities., National Institutes of Health (U.S.) (Award DP2OD020839), National Institutes of Health (U.S.) (Grant U24AI118672), National Institutes of Health (U.S.) (Grant P50HG006193)

The cell fate decision between interferon-producing plasmacytoid DC (pDC) and antigen-presenting classical DC (cDC) is controlled by the E protein transcription factor TCF4 (E2-2). We report that TCF4 comprises two transcriptional isoforms, both of which are required for optimal pDC development in vitro. The long Tcf4 isoform is expressed specifically in pDCs, and its deletion in mice impaired pDCs development and led to the expansion of non-canonical CD8⁺ cDCs. The expression of Tcf4 commenced in progenitors and was further upregulated in pDCs, correlating with stage-specific activity of multiple enhancer elements. A conserved enhancer downstream of Tcf4 was required for its upregulation during pDC differentiation, revealing a positive feedback loop. The expression of Tcf4 and the resulting pDC differentiation were selectively sensitive to the inhibition of enhancer-binding BET protein activity. Thus, lineage-specifying function of E proteins is facilitated by lineage-specific isoform expression and by BET-dependent feedback regulation through distal regulatory elements.

Background: In-stent hyperplasia (ISH) may develop in regions of low endothelial shear stress (ESS), but the relationship between the magnitude of low ESS, the extent of ISH, and subsequent clinical events has not been investigated. Methods and Results: We assessed the association of poststent ESS with neointimal ISH and clinical outcomes in patients treated with percutaneous coronary interventions (PCI). Three-dimensional coronary reconstruction was performed in 374 post-PCI patients at baseline and 6 to 10 months follow-up as part of the PREDICTION Study. Each vessel was divided into 1.5-mm-long segments, and we calculated the local ESS within each stented segment at baseline. At follow-up, we assessed ISH and the occurrence of a clinically indicated repeat PCI for in-stent restenosis. In 246 total stents (54 overlapping), 100 (40.7%) were bare-metal stents (BMS), 104 (42.3%) sirolimus-eluting stents, and 42 (17.1%) paclitaxel-eluting stents. In BMS, low ESS post-PCI at baseline was independently associated with ISH (β=1.47 mm 2 per 1-Pa decrease; 95% CI, 0.38-2.56; P < 0.01). ISH was minimal in drug-eluting stents. During follow-up, repeat PCI in BMS was performed in 21 stents (8.5%). There was no significant association between post-PCI ESS and in-stent restenosis requiring PCI. Conclusions: Low ESS after BMS implantation is associated with subsequent ISH. ISH is strongly inhibited by drug-eluting stents. Post-PCI ESS is not associated with in-stent restenosis requiring repeat PCI. ESS is an important determinant of ISH in BMS, but ISH of large magnitude to require PCI for in-stent restenosis is likely attributed to factors other than ESS within the stent., Hellenic Cardiological Society, Schaubert Family, George D. Behrakis Cardiovascular Research Fellowship

RNA-centric biochemical purification is a general approach for studying the functions and mechanisms of noncoding RNAs. Here, we describe the experimental procedures for RNA antisense purification (RAP), a method for selective purification of endogenous RNA complexes from cell extracts that enables mapping of RNA interactions with chromatin. In RAP, the user cross-links cells to fix endogenous RNA complexes and purifies these complexes through hybrid capture with biotinylated antisense oligos. DNA loci that interact with the target RNA are identified using high-throughput DNA sequencing.

Main Text The physicist Richard Feynman famously wrote, “What I cannot create, I do not understand,” at the top of his final blackboard. This philosophy has inspired many in the emerging field of synthetic biology, which harnesses the power of biology to rationally engineer biomolecular systems for a variety of purposes, such as whole-cell biosensing and in vivo diagnostics (Slomovic et al., 2015). The “build-to-understand” approach (Elowitz and Lim, 2010) is complementary to top-down systems biology approaches and borrows concepts and techniques from engineering and computer science. By creating biological systems with desired architectures and functions, it aims to test design principles in relative isolation by exploring how biology’s building blocks, such as DNA-encoded genes, can be rearranged and altered to produce different phenotypes. In this issue, Cao et al. use this approach to tackle the question of how self-organizing systems maintain a constant ratio of physical pattern features with changing size, a property known as scale invariance (Cao et al., 2016).

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies., Wellcome Trust (London, England) (Core Award 090532/Z/09/Z), Wellcome Trust (London, England) (Senior Investigator Award 095552/Z/11/Z ), Wellcome Trust (London, England) (WT095908), Wellcome Trust (London, England) (WT109497), Wellcome Trust (London, England) (WT098051), Wellcome Trust (London, England) (WT086084/Z/08/Z), Wellcome Trust (London, England) (WT100956/Z/13/Z ), Wellcome Trust (London, England) (WT097307), Wellcome Trust (London, England) (WT0855322/Z/08/Z ), Wellcome Trust (London, England) (WT090770/Z/09/Z ), Wellcome Trust (London, England) (Major Overseas program in Vietnam grant 089276/Z.09/Z), Medical Research Council (Great Britain) (grant G0801823), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I02593X/1), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I021213/1), Zhongguo ke xue ji shu qing bao yan jiu suo. Office of 863 Programme of China (2012AA02A201), National Basic Research Program of China (2011CB809201), National Basic Research Program of China (2011CB809202), National Basic Research Program of China (2011CB809203), National Natural Science Foundation of China (31161130357), Shenzhen Municipal Government of China (grant ZYC201105170397A), Canadian Institutes of Health Research (grant 136855), Quebec Ministry of Economic Development, Innovation, and Exports (PSR-SIIRI-195), Germany. Bundesministerium für Bildung und Forschung (0315428A), Germany. Bundesministerium für Bildung und Forschung (01GS08201), Germany. Bundesministerium für Bildung und Forschung (BMBF-EPITREAT grant 0316190A), Deutsche Forschungsgemeinschaft (Emmy Noether Grant KO4037/1-1), Beatriu de Pinos Program (2006 BP-A 10144), Beatriu de Pinos Program (2009 BP-B 00274), Spanish National Institute for Health (grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER), Japan Society for the Promotion of Science (fellowship number PE13075), Marie Curie Actions Career Integration (grant 303772), Fonds National Suisse del la Recherche, SNSF, Scientifique (31003A_130342), National Center for Biotechnology Information (U.S.) (U54HG3067), National Center for Biotechnology Information (U.S.) (U54HG3273), National Center for Biotechnology Information (U.S.) (U01HG5211), National Center for Biotechnology Information (U.S.) (U54HG3079), National Center for Biotechnology Information (U.S.) (R01HG2898), National Center for Biotechnology Information (U.S.) (R01HG2385), National Center for Biotechnology Information (U.S.) (RC2HG5552), National Center for Biotechnology Information (U.S.) (U01HG6513), National Center for Biotechnology Information (U.S.) (U01HG5214), National Center for Biotechnology Information (U.S.) (U01HG5715), National Center for Biotechnology Information (U.S.) (U01HG5718), National Center for Biotechnology Information (U.S.) (U01HG5728), National Center for Biotechnology Information (U.S.) (U41HG7635), National Center for Biotechnology Information (U.S.) (U41HG7497), National Center for Biotechnology Information (U.S.) (R01HG4960), National Center for Biotechnology Information (U.S.) (R01HG5701), National Center for Biotechnology Information (U.S.) (R01HG5214), National Center for Biotechnology Information (U.S.) (R01HG6855), National Center for Biotechnology Information (U.S.) (R01HG7068), National Center for Biotechnology Information (U.S.) (R01HG7644), National Center for Biotechnology Information (U.S.) (DP2OD6514), National Center for Biotechnology Information (U.S.) (DP5OD9154), National Center for Biotechnology Information (U.S.) (R01CA166661), National Center for Biotechnology Information (U.S.) (R01CA172652), National Center for Biotechnology Information (U.S.) (P01GM99568), National Center for Biotechnology Information (U.S.) (R01GM59290), National Center for Biotechnology Information (U.S.) (R01GM104390), National Center for Biotechnology Information (U.S.) (T32GM7790), National Center for Biotechnology Information (U.S.) (R01HL87699), National Center for Biotechnology Information (U.S.) (R01HL104608), National Center for Biotechnology Information (U.S.) (T32HL94284), National Center for Biotechnology Information (U.S.) (HHSN268201100040C), National Center for Biotechnology Information (U.S.) (HHSN272201000025C), Lundbeck Foundation (grant R170-2014-1039, Simons Foundation (SFARI award SF51), National Science Foundation (U.S.) (Research Fellowship DGE-1147470)

Gold nanostars (NStars) are highly attractive for biological applications due to their surface chemistry, facile synthesis, and optical properties. Here, we synthesize NStars in HEPES buffer at different HEPES/Au ratios, producing NStars of different sizes and shapes and therefore varying optical properties. We measure the extinction coefficient of the synthesized NStars at their maximum surface plasmon resonances (SPRs), which range from 5.7 × 10⁸ to 26.8 × 10⁸ M⁻¹ cm⁻¹. Measured values correlate with those obtained from theoretical models of the NStars using the discrete dipole approximation (DDA), which we use to simulate the extinction spectra of the nanostars. Finally, because NStars are typically used in biological applications, we conjugate DNA and antibodies to the NStars and calculate the footprint of the bound biomolecules., United States. National Institutes of Health (AI100190)

Background & Aims Regeneration of the hepatic mass is crucial to liver repair. Proliferation of hepatic parenchyma is intimately dependent on angiogenesis and resident macrophage-derived cytokines. However the role of circulating monocyte interactions in vascular and hepatic regeneration is not well-defined. We investigated the role of these interactions in regeneration in the presence and absence of intact monocyte adhesion. Methods Partial hepatectomy was performed in wild-type mice and those lacking the monocyte adhesion molecule CD11b. Vascular architecture, angiogenesis and macrophage location were analyzed in the whole livers using simultaneous angiography and macrophage staining with fluorescent multiphoton microscopy. Monocyte adhesion molecule expression and sprouting-related pathways were evaluated. Results Resident macrophages (Kupffer cells) did not migrate to interact with vessels whereas infiltrating monocytes were found adjacent to sprouting points. Infiltrated monocytes colocalized with Wnt5a, angiopoietin 1 and Notch-1 in contact points and commensurate with phosphorylation and disruption of VE-cadherin. Mice deficient in CD11b showed a severe reduction in angiogenesis, liver mass regeneration and survival following partial hepatectomy, and developed unstable and leaky vessels that eventually produced an aberrant hepatic vascular network and Kupffer cell distribution. Conclusions Direct vascular interactions of infiltrating monocytes are required for an ordered vascular growth and liver regeneration. These outcomes provide insight into hepatic repair and new strategies for hepatic regeneration., National Institutes of Health (U.S.) (Grant R01 GM 49039)

A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal chemis

Xenophagy is a form of selective autophagy that involves the targeting and elimination of intracellular pathogens through several recognition, recruitment, and ubiquitination events. E3 ubiquitin ligases control substrate selectivity in the ubiquitination cascade; however, systematic approaches to map the role of E3 ligases in antibacterial autophagy have been lacking. We screened more than 600 putative human E3 ligases, identifying E3 ligases that are required for adaptor protein recruitment and LC3-bacteria colocalization, critical steps in antibacterial autophagy. An unbiased informatics approach pinpointed RNF166 as a key gene that interacts with the autophagy network and controls the recruitment of ubiquitin as well as the autophagy adaptors p62 and NDP52 to bacteria. Mechanistic studies demonstrated that RNF166 catalyzes K29- and K33-linked polyubiquitination of p62 at residues K91 and K189. Thus, our study expands the catalog of E3 ligases that mediate antibacterial autophagy and identifies a critical role for RNF166 in this process., Leona M. and Harry B. Helmsley Charitable Trust (2014PG-IBD016), National Institutes of Health (U.S.) (R01DK097485), National Institutes of Health (U.S.) (U19AI109725), National Institutes of Health (U.S.) (P30DK043351)

Drug-eluting stents are accepted as mainstream endovascular therapy, yet concerns for their safety may be under-appreciated. While failure from restenosis has dropped to below 5%, the risk of stent thrombosis and associated mortality remain relatively high. Further optimization of drug release is required to minimize thrombosis risk while maintaining therapeutic dose. The complex three-dimensional geometry of deployed stents together with the combination of diffusive and advective drug transport render an intuitive understanding of the situation exceedingly difficult. In situations such as this, computational modeling has proven essential, helping define the limits of efficacy, determine the mode and mechanism of drug release, and identify alternatives to avoid toxicity. A particularly challenging conformation is encountered in coronary arteries with overlapping stents. To study hemodynamics and drug deposition in such vessels we combined high-resolution, multi-scale ex vivo computed tomography with a flow and mass transfer computational model. This approach ensures high geometric fidelity and precise, simultaneous calculation of blood flow velocity, shear stress and drug distribution. Our calculations show that drug uptake by the arterial tissue is dependent both on the patterns of flow disruption near the wall, as well as on the relative positioning of drug-eluting struts. Overlapping stent struts lead to localized peaks of drug concentration that may increase the risk of thrombosis. Such peaks could be avoided by anisotropic stent structure or asymmetric drug release designed to yield homogeneous drug distribution along the coronary artery and, at the least, suggest that these issues need to remain in the forefront of consideration in clinical practice., National Institutes of Health (U.S.) (Grant R01 GM 49039)

The orchestrated action of genes controls complex biological phenotypes, yet the systematic discovery of gene and drug combinations that modulate these phenotypes in human cells is labor intensive and challenging to scale. Here, we created a platform for the massively parallel screening of barcoded combinatorial gene perturbations in human cells and translated these hits into effective drug combinations. This technology leverages the simplicity of the CRISPR-Cas9 system for multiplexed targeting of specific genomic loci and the versatility of combinatorial genetics en masse (CombiGEM) to rapidly assemble barcoded combinatorial genetic libraries that can be tracked with high-throughput sequencing. We applied CombiGEM-CRISPR to create a library of 23,409 barcoded dual guide-RNA (gRNA) combinations and then perform a high-throughput pooled screen to identify gene pairs that inhibited ovarian cancer cell growth when they were targeted. We validated the growth-inhibiting effects of specific gene sets, including epigenetic regulators KDM4C/BRD4 and KDM6B/BRD4, via individual assays with CRISPR-Cas–based knockouts and RNA-interference–based knockdowns. We also tested small-molecule drug pairs directed against our pairwise hits and showed that they exerted synergistic antiproliferative effects against ovarian cancer cells. We envision that the CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes., National Institutes of Health (U.S.) (Grants DP2OD008435, P50GM098792, and R01 NS089076), United States. Office of Naval Research (Grant N00014-13-1-0424), United States. Defense Threat Reduction Agency, Lawrence Ellison Foundation (New Scholar in Aging Award), Croucher Foundation, Natural Sciences and Engineering Research Council of Canada (Postdoctoral Fellowship)

The accurate assessment of a patient's risk of adverse events remains a mainstay of clinical care. Commonly used risk metrics have been based on logistic regression models that incorporate aspects of the medical history, presenting signs and symptoms, and lab values. More sophisticated methods, such as Artificial Neural Networks (ANN), form an attractive platform to build risk metrics because they can easily incorporate disparate pieces of data, yielding classifiers with improved performance. Using two cohorts consisting of patients admitted with a non-ST-segment elevation acute coronary syndrome, we constructed an ANN that identifies patients at high risk of cardiovascular death (CVD). The ANN was trained and tested using patient subsets derived from a cohort containing 4395 patients (Area Under the Curve (AUC) 0.743) and validated on an independent holdout set containing 861 patients (AUC 0.767). The ANN 1-year Hazard Ratio for CVD was 3.72 (95% confidence interval 1.04-14.3) after adjusting for the TIMI Risk Score, left ventricular ejection fraction, and B-type natriuretic peptide. A unique feature of our approach is that it captures small changes in the ST segment over time that cannot be detected by visual inspection. These findings highlight the important role that ANNs can play in risk stratification.

Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell’s RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts’ cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution., National Human Genome Research Institute (U.S.) (P50 HG006193)

Purpose Specific absorption rate (SAR) amplification around active implantable medical devices during diagnostic MRI procedures poses a potential risk for patient safety. In this study, we present a parallel transmit (pTx) strategy that can be used to safely scan patients with deep brain stimulation (DBS) implants. Methods We performed electromagnetic simulations at 3T using a uniform phantom and a multitissue realistic head model with a generic DBS implant. Our strategy is based on using implant-friendly modes, which are defined as the modes of an array that reduce the local SAR around the DBS lead tip. These modes are used in a spokes pulse design algorithm in order to produce highly uniform magnitude least-squares flip angle excitations. Results Local SAR (1 g) at the lead tip is reduced below 0.1 W/kg compared with 31.2 W/kg, which is obtained by a simple quadrature birdcage excitation without any sort of SAR mitigation. For the multitissue realistic head model, peak 10 g local SAR and global SAR are obtained as 4.52 W/kg and 0.48 W/kg, respectively. A uniform axial flip angle is also obtained (NRMSE <3%). Conclusion Parallel transmit arrays can be used to generate implant-friendly modes and to reduce SAR around DBS implants while constraining peak local SAR and global SAR and maximizing flip angle homogeneity. Magn Reson Med 73:1896–1903, 2015., National Institute of Biomedical Imaging and Bioengineering (U.S.) (R01EB006847), National Institute of Biomedical Imaging and Bioengineering (U.S.) (R01EB007942)