Abstract: The mammalian nervous system executes complex behaviors controlled by specialised, precisely positioned and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse, and were grouped by developmental anatomical units, and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission and membrane conductance. We discovered several distinct, regionally restricted, astrocytes types, which obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity, followed by a secondary diversi cation. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system, and enables genetic manipulation of specific cell types.

Abstract: Dysregulation of microRNAs (miRNAs) is involved in the initiation and progression of several human cancers, including breast cancer (BC), as strong evidence has been found that miRNAs can act as oncogenes or tumor suppressor genes. This review presents the state of the art on the role of miRNAs in the diagnosis, prognosis, and therapy of BC. Based on the results obtained in the last decade, some miRNAs are emerging as biomarkers of BC for diagnosis (i.e., miR-9, miR-10b, and miR-17-5p), prognosis (i.e., miR-148a and miR-335), and prediction of therapeutic outcomes (i.e., miR-30c, miR-187, and miR-339-5p) and have important roles in the control of BC hallmark functions such as invasion, metastasis, proliferation, resting death, apoptosis, and genomic instability. Other miRNAs are of interest as new, easily accessible, affordable, non-invasive tools for the personalized management of patients with BC because they are circulating in body fluids (e.g., miR-155 and miR-210). In particular, circulating multiple miRNA profiles are showing better diagnostic and prognostic performance as well as better sensitivity than individual miRNAs in BC. New miRNA-based drugs are also promising therapy for BC (e.g., miR-9, miR-21, miR34a, miR145, and miR150), and other miRNAs are showing a fundamental role in modulation of the response to other non-miRNA treatments, being able to increase their efficacy (e.g., miR-21, miR34a, miR195, miR200c, and miR203 in combination with chemotherapy).

Abstract: Objective To compare the effects of treatments for coronavirus disease 2019 (covid-19). Design Living systematic review and network meta-analysis. Data sources WHO covid-19 database, a comprehensive multilingual source of global covid-19 literature, up to 1 March 2021 and six additional Chinese databases up to 20 February 2021. Studies identified as of 12 February 2021 were included in the analysis. Study selection Randomised clinical trials in which people with suspected, probable, or confirmed covid-19 were randomised to drug treatment or to standard care or placebo. Pairs of reviewers independently screened potentially eligible articles. Methods After duplicate data abstraction, a bayesian network meta-analysis was conducted. Risk of bias of the included studies was assessed using a modification of the Cochrane risk of bias 2.0 tool, and the certainty of the evidence using the grading of recommendations assessment, development, and evaluation (GRADE) approach. For each outcome, interventions were classified in groups from the most to the least beneficial or harmful following GRADE guidance. Results 196 trials enrolling 76 767 patients were included; 111 (56.6%) trials and 35 098 (45.72%) patients are new from the previous iteration; 113 (57.7%) trials evaluating treatments with at least 100 patients or 20 events met the threshold for inclusion in the analyses. Compared with standard care, corticosteroids probably reduce death (risk difference 20 fewer per 1000 patients, 95% credible interval 36 fewer to 3 fewer, moderate certainty), mechanical ventilation (25 fewer per 1000, 44 fewer to 1 fewer, moderate certainty), and increase the number of days free from mechanical ventilation (2.6 more, 0.3 more to 5.0 more, moderate certainty). Interleukin-6 inhibitors probably reduce mechanical ventilation (30 fewer per 1000, 46 fewer to 10 fewer, moderate certainty) and may reduce length of hospital stay (4.3 days fewer, 8.1 fewer to 0.5 fewer, low certainty), but whether or not they reduce mortality is uncertain (15 fewer per 1000, 30 fewer to 6 more, low certainty). Janus kinase inhibitors may reduce mortality (50 fewer per 1000, 84 fewer to no difference, low certainty), mechanical ventilation (46 fewer per 1000, 74 fewer to 5 fewer, low certainty), and duration of mechanical ventilation (3.8 days fewer, 7.5 fewer to 0.1 fewer, moderate certainty). The impact of remdesivir on mortality and most other outcomes is uncertain. The effects of ivermectin were rated as very low certainty for all critical outcomes, including mortality. In patients with non-severe disease, colchicine may reduce mortality (78 fewer per 1000, 110 fewer to 9 fewer, low certainty) and mechanical ventilation (57 fewer per 1000, 90 fewer to 3 more, low certainty). Azithromycin, hydroxychloroquine, lopinavir-ritonavir, and interferon-beta do not appear to reduce risk of death or have an effect on any other patient-important outcome. The certainty in effects for all other interventions was low or very low. Conclusion Corticosteroids and interleukin-6 inhibitors probably confer important benefits in patients with severe covid-19. Janus kinase inhibitors appear to have promising benefits, but certainty is low. Azithromycin, hydroxychloroquine, lopinavir-ritonavir, and interferon-beta do not appear to have any important benefits. Whether or not remdesivir, ivermectin, and other drugs confer any patient-important benefit remains uncertain. Systematic review registration This review was not registered. The protocol is publicly available in the supplementary material. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This is the fourth version of the original article published on 30 July 2020 (BMJ 2020;370:m2980), and previous versions can be found as data supplements. When citing this paper please consider adding the version number and date of access for clarity.

Abstract: Estimates of the prevalence of Parkinson’s disease in North America have varied widely and many estimates are based on small numbers of cases and from small regional subpopulations. We sought to estimate the prevalence of Parkinson’s disease in North America by combining data from a multi-study sampling strategy in diverse geographic regions and/or data sources. Five separate cohort studies in California (2), Minnesota (1), Hawaii USA (1), and Ontario, Canada (1) estimated the prevalence of PD from health-care records (3), active ascertainment through facilities, large group, and neurology practices (1), and longitudinal follow-up of a population cohort (1). US Medicare program data provided complementary estimates for the corresponding regions. Using our age- and sex-specific meta-estimates from California, Minnesota, and Ontario and the US population structure from 2010, we estimate the overall prevalence of PD among those aged ≥45 years to be 572 per 100,000 (95% confidence interval 537–614) that there were 680,000 individuals in the US aged ≥45 years with PD in 2010 and that that number will rise to approximately 930,000 in 2020 and 1,238,000 in 2030 based on the US Census Bureau population projections. Regional variations in prevalence were also observed in both the project results and the Medicare-based calculations with which they were compared. The estimates generated by the Hawaiian study were lower across age categories. These estimates can guide health-care planning but should be considered minimum estimates. Some heterogeneity exists that remains to be understood.

Abstract: Event-triggered control consists of closing the feedback loop whenever a predefined state-dependent criterion is satisfied. This paradigm is especially well suited for embedded systems and networked control systems since it is able to reduce the amount of communication and computation resources needed for control, compared to the traditional periodic implementation. In this paper, we propose a framework for the event-triggered stabilization of nonlinear systems using hybrid systems tools, that is general enough to encompass most of the existing event-triggered control techniques, which we revisit and generalize. We also derive two new event-triggering conditions which may further enlarge the inter-event times compared to the available policies in the literature as illustrated by two physical examples. These novel techniques exemplify the relevance of introducing additional variables for the design of the triggering law. The proposed approach as well as the new event-triggering strategies are flexible and we believe that they can be used to address other event-based control problems.

Abstract: Image-generating machine learning models are typically trained with loss functions based on distance in the image space. This often leads to over-smoothed results. We propose a class of loss functions, which we call deep perceptual similarity metrics (DeePSiM), that mitigate this problem. Instead of computing distances in the image space, we compute distances between image features extracted by deep neural networks. This metric better reflects perceptually similarity of images and thus leads to better results. We show three applications: autoencoder training, a modification of a variational autoencoder, and inversion of deep convolutional networks. In all cases, the generated images look sharp and resemble natural images.

Abstract: Phenomenology is an approach to qualitative research that the specific focus is to identify the inherent and unchanging in the meaning of the issue under study (Langdridge, 2007). There are different approaches to phenomenology. Embree (1997) identified seven approaches namely, descriptive (transcendental constitutive) phenomenology, naturalistic constitutive phenomenology, existential phenomenology, generative historicist phenomenology, genetic phenomenology, hermeneutic (interpretive) phenomenology, and realistic phenomenology. Amongst them, descriptive and hermeneutic (interpretive) phenomenology are the two classical approaches that guide the majority of psychological research (Langdridge, 2007). Understanding the participants' lived experiences marks phenomenology as based on Husserl's philosophical work. Freeman (2011) asserted that understanding cannot be conceived as a fixing of meaning but how the meaning is generated and transformed. In order to discover meanings in the data, one needs an attitude open enough to let unexpected meanings emerge (Giorgi, 2011; Lopez & Willis, 2004). Through the fundamental methodology of "bracketing" the researcher's own experiences, the researcher does not influence the participant's understanding of the phenomenon. Although the concept of bracketing is well-suited in research that aims to explore human experience, the application and operation of bracketing remain vague and, often perplexing (Gearing, 2004). It results with disconnection of the practice of bracketing in phenomenology. Bracketing is a methodological device of phenomenological inquiry that requires deliberate putting aside one's own belief about the phenomenon under investigation or what one already knows about the subject prior to and throughout the phenomenological investigation (Carpenter, 2007). Bracketing is holding in abeyance those elements that define the limits of an experience when the nurse is uncovering a phenomenon about which s/he knows a great deal (Ray, 1985). The adoption of this attitude is unique to the phenomenological approach. Bracketing is a means of demonstrating the validity of the data collection and analysis process (Ahern, 1999). Therefore, efforts should be made by researchers to put aside their repertoires of knowledge, beliefs, values and experiences in order to accurately describe participants' life experiences. However, in the hermeneutic phenomenological approach, it is acknowledged that pre-understanding cannot be eliminated or "bracketed" (Koch, 1995); the technique of bracketing is found inconsistent and problematic within this approach (LeVasseur, 2003). There is also no single set of methods for undertaking bracketing (Gearing, 2004; Wall, Glenn, Mitchinson, & Poole, 2004). Giorgi (2011) further argued that the interpretative phenomenological analysis (IPA) provides no step in executing bracketing. The recently published phenomenological studies involving nurses as participants have mentioned the term bracketing in their methodology (Kleiman, 2004; Sale, 2007), or have explicitly acknowledged that bracketing cannot be eliminated (Humble & Cross, 2010). However, these studies offer few sources of information or strategies for actually carrying out bracketing, or for addressing the problem of demonstrating validity. This lack of discussion about strategies may leave readers wondering as to how bracketing is actually carried out or how validity can be addressed in phenomenological studies. In order to handle these challenging issues properly, there is a need for a more concrete description to elicit how bracketing can be achieved in doing phenomenology. Background This article is prompted by a concern about the issue of bracketing that we had to face while initiating a study aiming to explore the lived experiences of Psychiatric Advanced Practice Nurses (APN) in their newly adopted role perceptions and performance in Hong Kong (HK). …

Abstract: Due to the fast inference and good performance, discriminative learning methods have been widely studied in image denoising. However, these methods mostly learn a specific model for each noise level, and require multiple models for denoising images with different noise levels. They also lack flexibility to deal with spatially variant noise, limiting their applications in practical denoising. To address these issues, we present a fast and flexible denoising convolutional neural network, namely FFDNet, with a tunable noise level map as the input. The proposed FFDNet works on downsampled sub-images, achieving a good trade-off between inference speed and denoising performance. In contrast to the existing discriminative denoisers, FFDNet enjoys several desirable properties, including (i) the ability to handle a wide range of noise levels (i.e., [0, 75]) effectively with a single network, (ii) the ability to remove spatially variant noise by specifying a non-uniform noise level map, and (iii) faster speed than benchmark BM3D even on CPU without sacrificing denoising performance. Extensive experiments on synthetic and real noisy images are conducted to evaluate FFDNet in comparison with state-of-the-art denoisers. The results show that FFDNet is effective and efficient, making it highly attractive for practical denoising applications.

Abstract: Summary Background The population infected with HIV is getting older and these people will increasingly develop age-related non-communicable diseases (NCDs). We aimed to quantify the scale of the change and the implications for HIV care in the Netherlands in the future. Methods We constructed an individual-based model of the ageing HIV-infected population, which followed patients on HIV treatment as they age, develop NCDs—including cardiovascular disease (hypertension, hypercholesterolaemia, myocardial infarctions, and strokes), diabetes, chronic kidney disease, osteoporosis, and non-AIDS malignancies—and start co-medication for these diseases. The model was parameterised by use of data for 10 278 patients from the national Dutch ATHENA cohort between 1996 and 2010. We made projections up to 2030. Findings Our model suggests that the median age of HIV-infected patients on combination antiretroviral therapy (ART) will increase from 43·9 years in 2010 to 56·6 in 2030, with the proportion of HIV-infected patients aged 50 years or older increasing from 28% in 2010 to 73% in 2030. In 2030, we predict that 84% of HIV-infected patients will have at least one NCD, up from 29% in 2010, with 28% of HIV-infected patients in 2030 having three or more NCDs. 54% of HIV-infected patients will be prescribed co-medications in 2030, compared with 13% in 2010, with 20% taking three or more co-medications. Most of this change will be driven by increasing prevalence of cardiovascular disease and associated drugs. Because of contraindications and drug–drug interactions, in 2030, 40% of patients could have complications with the currently recommended first-line HIV regimens. Interpretation The profile of patients in the Netherlands infected with HIV is changing, with increasing numbers of older patients with multiple morbidities. These changes mean that, in the near future, HIV care will increasingly need to draw on a wide range of medical disciplines, in addition to evidence-based screening and monitoring protocols to ensure continued high-quality care. These findings are based on a large dataset of HIV-infected patients in the Netherlands, but we believe that the overall patterns will be repeated elsewhere in Europe and North America. The implications of such a trend for care of HIV-infected patients in high-burden countries in Africa could present a particular challenge. Funding Medical Research Council, Bill & Melinda Gates Foundation, Rush Foundation, and Netherlands Ministry of Health, Welfare and Sport.

Abstract: The microbiota, the gut, and the brain communicate through the microbiota-gut-brain axis in a bidirectional way that involves the autonomic nervous system. The vagus nerve (VN), the principal component of the parasympathetic nervous system, is a mixed nerve composed of 80% afferent and 20% efferent fibers. The VN, because of its role in interoceptive awareness, is able to sense the microbiota metabolites through its afferents, to transfer this gut information to the central nervous system where it is integrated in the central autonomic network, and then to generate an adapted or inappropriate response. A cholinergic anti-inflammatory pathway has been described through VN's fibers, which is able to dampen peripheral inflammation and to decrease intestinal permeability, thus very probably modulating microbiota composition. Stress inhibits the VN and has deleterious effects on the gastrointestinal tract and on the microbiota, and is involved in the pathophysiology of gastrointestinal disorders such as irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD) which are both characterized by a dysbiosis. A low vagal tone has been described in IBD and IBS patients thus favoring peripheral inflammation. Targeting the VN, for example through VN stimulation which has anti-inflammatory properties, would be of interest to restore homeostasis in the microbiota-gut-brain axis.

Abstract: Sound can levitate objects of different sizes and materials through air, water and tissue. This allows us to manipulate cells, liquids, compounds or living things without touching or contaminating them. However, acoustic levitation has required the targets to be enclosed with acoustic elements or had limited manoeuvrability. Here we optimize the phases used to drive an ultrasonic phased array and show that acoustic levitation can be employed to translate, rotate and manipulate particles using even a single-sided emitter. Furthermore, we introduce the holographic acoustic elements framework that permits the rapid generation of traps and provides a bridge between optical and acoustical trapping. Acoustic structures shaped as tweezers, twisters or bottles emerge as the optimum mechanisms for tractor beams or containerless transportation. Single-beam levitation could manipulate particles inside our body for applications in targeted drug delivery or acoustically controlled micro-machines that do not interfere with magnetic resonance imaging.

Abstract: Zn-air batteries are becoming the promising power sources for portable and wearable electronic devices and hybrid/electric vehicles because of their high specific energy density and the low cost for next-generation green and sustainable energy technologies. An air electrode integrated with an oxygen electrocatalyst is the most important component and inevitably determines the performance and cost of a Zn-air battery. This article presents exciting advances and challenges related to air electrodes and their relatives. After a brief introduction of the Zn-air battery, the architectures and oxygen electrocatalysts of air electrodes and relevant electrolytes are highlighted in primary and rechargeable types with different configurations, respectively. Moreover, the individual components and major issues of flexible Zn-air batteries are also highlighted, along with the strategies to enhance the battery performance. Finally, a perspective for design, preparation, and assembly of air electrodes is proposed for the future innovations of Zn-air batteries with high performance.

Abstract: It is unknown whether the human immune system frequently mounts a T cell response against mutations expressed by common epithelial cancers. Using a next-generation sequencing approach combined with high-throughput immunologic screening, we demonstrated that tumor-infiltrating lymphocytes (TILs) from 9 out of 10 patients with metastatic gastrointestinal cancers contained CD4(+) and/or CD8(+) T cells that recognized one to three neo-epitopes derived from somatic mutations expressed by the patient's own tumor. There were no immunogenic epitopes shared between these patients. However, we identified in one patient a human leukocyte antigen-C*08:02-restricted T cell receptor from CD8(+) TILs that targeted the KRAS(G12D) hotspot driver mutation found in many human cancers. Thus, a high frequency of patients with common gastrointestinal cancers harbor immunogenic mutations that can potentially be exploited for the development of highly personalized immunotherapies.

Abstract: The fall armyworm, Spodoptera frugiperda (J.E. Smith, 1797) (Lepidoptera: Noctuidae), is the most important noctuid pest in the Americas and has recently become an invasive pest in Africa. A detailed record of S. frugiperda's host plants is essential to better understand the biology and ecology of this pest, conduct future studies, and develop Integrated Pest Management programmes. In this study, we collected and systematically arranged the fragmented bibliographic information on S. frugiperda feeding records. Furthermore, we registered new records of host plants for S. frugiperda based on eight years of surveys in Brazil. The literature review and surveys resulted in a total of 353 S. frugiperda larval host plant records belonging to 76 plant families, principally Poaceae (106), Asteraceae (31) and Fabaceae (31). The literature search revealed 274 (77 % of total) bibliographic records, while 82 (23 %) are new records from surveys in Brazil. The new comprehensive and updated host plant list will improve our understanding of pest biology and management, as well as facilitate future studies on this pest.

Abstract: Importance Amid the current opioid epidemic in the United States, the enhanced recovery after surgery pathway (ERAS) has emerged as one of the best strategies to improve the value and quality of surgical care and has been increasingly adopted for a broad range of complex surgical procedures. The goal of this article was to outline important components of opioid-sparing analgesic regimens. Observations Regional analgesia, acetaminophen, nonsteroidal anti-inflammatory agents, gabapentinoids, tramadol, lidocaine, and/or theN-methyl-d-aspartate class of glutamate receptor antagonists have been shown to be effective adjuncts to narcotic analgesia. Nonsteroidal anti-inflammatory agents are not associated with an increase in postoperative bleeding. A meta-analysis of 27 randomized clinical trials found no difference in postoperative bleeding between the groups taking ketorolac tromethamine (33 of 1304 patients [2.5%]) and the control groups (21 of 1010 [2.1%]) (odds ratio [OR], 1.1; 95% CI, 0.61-2.06;P = .72). After adoption of the multimodal analgesia approach for a colorectal ERAS pathway, most patients used less opioids while in the hospital and many did not need opioids after hospital discharge, although approximately 50% of patients received some opioid during their stay. Conclusions and Relevance Multimodal analgesia is readily available and the evidence is strong to support its efficacy. Surgeons should use this effective approach for patients both using and not using the ERAS pathway to reduce opioid consumption.

Abstract: Quantum Monte Carlo techniques aim at providing a description of complex quantum systems such as nuclei and nucleonic matter from first principles, i.e., realistic nuclear interactions and currents. The methods are similar to those used for many-electron systems in quantum chemistry and condensed matter physics, but are extended to include spin-isospin, tensor, spin-orbit, and three-body interactions. This review shows how to build the atomic nucleus from the ground up. Examples include the structure of light nuclei, electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter.

Abstract: In this chapter we provide an overview of the concept of blockchain technology and its potential to disrupt the world of banking through facilitating global money remittance, smart contracts, automated banking ledgers and digital assets. In this regard, we first provide a brief overview of the core aspects of this technology, as well as the second-generation contract-based developments. From there we discuss key issues that must be considered in developing such ledger based technologies in a banking context.

Abstract: Health care-associated infections (HCAIs) are infections that occur while receiving health care, developed in a hospital or other health care facility that first appear 48 hours or more after hospital admission, or within 30 days after having received health care. Multiple studies indicate that the common types of adverse events affecting hospitalized patients are adverse drug events, HCAIs, and surgical complications. The US Center for Disease Control and Prevention identifies that nearly 1.7 million hospitalized patients annually acquire HCAIs while being treated for other health issues and that more than 98,000 patients (one in 17) die due to these. Several studies suggest that simple infection-control procedures such as cleaning hands with an alcohol-based hand rub can help prevent HCAIs and save lives, reduce morbidity, and minimize health care costs. Routine educational interventions for health care professionals can help change their hand-washing practices to prevent the spread of infection. In support of this, the WHO has produced guidelines to promote hand-washing practices among member countries.

Abstract: The composite-factor estimation dichotomy has been the epicenter of a long and ongoing debate among proponents and detractors of the use of the partial least squares PLS approach for structural equation modeling SEM. In this brief research note the author discusses the implementation of a new method to conduct factor-based PLS-SEM analyses, which could be a solid step in the resolution of this debate. This method generates estimates of both true composites and factors, in two stages, fully accounting for measurement error. The author's discussion is based on an illustrative model in the field of e-collaboration. A Monte Carlo experiment suggests that model parameters generated by the method are asymptotically unbiased. The method is implemented as part of the software WarpPLS, starting in version 5.0. This note provides enough details for the method's implementation in other venues such as R and GNU Octave.

Abstract: PurposePatients with cancer are more likely to file for bankruptcy than the general population, but the impact of severe financial distress on health outcomes among patients with cancer is not known.MethodsWe linked Western Washington SEER Cancer Registry records with federal bankruptcy records for the region. By using propensity score matching to account for differences in several demographic and clinical factors between patients who did and did not file for bankruptcy, we then fit Cox proportional hazards models to examine the relationship between bankruptcy filing and survival.ResultsBetween 1995 and 2009, 231,596 persons were diagnosed with cancer. Patients who filed for bankruptcy (n = 4,728) were more likely to be younger, female, and nonwhite, to have local- or regional- (v distant-) stage disease at diagnosis, and have received treatment. After propensity score matching, 3,841 patients remained in each group (bankruptcy v no bankruptcy). In the matched sample, mean age was 53.0 years, 54% were men...

Abstract: There is a tremendous desire to attribute causes to weather and climate events that is often challenging from a physical standpoint. Headlines attributing an event solely to either human-induced climate change or natural variability can be misleading when both are invariably in play. The conventional attribution framework struggles with dynamically driven extremes because of the small signal-to-noise ratios and often uncertain nature of the forced changes. Here, we suggest that a different framing is desirable, which asks why such extremes unfold the way they do. Specifically, we suggest that it is more useful to regard the extreme circulation regime or weather event as being largely unaffected by climate change, and question whether known changes in the climate system's thermodynamic state affected the impact of the particular event. Some examples briefly illustrated include 'snowmaggedon' in February 2010, superstorm Sandy in October 2012 and supertyphoon Haiyan in November 2013, and, in more detail, the Boulder floods of September 2013, all of which were influenced by high sea surface temperatures that had a discernible human component.

Abstract: To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects) We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology

Abstract: We consider the problem of depth estimation from a single monocular image in this work. It is a challenging task as no reliable depth cues are available, e.g., stereo correspondences, motions etc. Previous efforts have been focusing on exploiting geometric priors or additional sources of information, with all using hand-crafted features. Recently, there is mounting evidence that features from deep convolutional neural networks (CNN) are setting new records for various vision applications. On the other hand, considering the continuous characteristic of the depth values, depth estimations can be naturally formulated into a continuous conditional random field (CRF) learning problem. Therefore, we in this paper present a deep convolutional neural field model for estimating depths from a single image, aiming to jointly explore the capacity of deep CNN and continuous CRF. Specifically, we propose a deep structured learning scheme which learns the unary and pairwise potentials of continuous CRF in a unified deep CNN framework. The proposed method can be used for depth estimations of general scenes with no geometric priors nor any extra information injected. In our case, the integral of the partition function can be analytically calculated, thus we can exactly solve the log-likelihood optimization. Moreover, solving the MAP problem for predicting depths of a new image is highly efficient as closed-form solutions exist. We experimentally demonstrate that the proposed method outperforms state-of-the-art depth estimation methods on both indoor and outdoor scene datasets.

Abstract: We update the capabilities of the open-knowledge software instrument Modules for Experiments in Stellar Astrophysics (MESA). RSP is a new functionality in MESAstar that models the nonlinear radial stellar pulsations that characterize RR Lyrae, Cepheids, and other classes of variable stars. We significantly enhance numerical energy conservation capabilities, including during mass changes. For example, this enables calculations through the He flash that conserve energy to better than 0.001%. To improve the modeling of rotating stars in MESA, we introduce a new approach to modifying the pressure and temperature equations of stellar structure, as well as a formulation of the projection effects of gravity darkening. A new scheme for tracking convective boundaries yields reliable values of the convective core mass and allows the natural emergence of adiabatic semiconvection regions during both core hydrogen- and helium-burning phases. We quantify the parallel performance of MESA on current-generation multicore architectures and demonstrate improvements in the computational efficiency of radiative levitation. We report updates to the equation of state and nuclear reaction physics modules. We briefly discuss the current treatment of fallback in core-collapse supernova models and the thermodynamic evolution of supernova explosions. We close by discussing the new MESA Testhub software infrastructure to enhance source code development.

Abstract: Accurate and rapid typing of pathogens is essential for effective surveillance and outbreak detection. Conventional serotyping of Escherichia coli is a delicate, laborious, time-consuming, and expensive procedure. With whole-genome sequencing (WGS) becoming cheaper, it has vast potential in routine typing and surveillance. The aim of this study was to establish a valid and publicly available tool for WGS-based in silico serotyping of E. coli applicable for routine typing and surveillance. A FASTA database of specific O-antigen processing system genes for O typing and flagellin genes for H typing was created as a component of the publicly available Web tools hosted by the Center for Genomic Epidemiology (CGE) (www.genomicepidemiology.org). All E. coli isolates available with WGS data and conventional serotype information were subjected to WGS-based serotyping employing this specific SerotypeFinder CGE tool. SerotypeFinder was evaluated on 682 E. coli genomes, 108 of which were sequenced for this study, where both the whole genome and the serotype were available. In total, 601 and 509 isolates were included for O and H typing, respectively. The O-antigen genes wzx , wzy , wzm , and wzt and the flagellin genes fliC , flkA , fllA , flmA , and flnA were detected in 569 and 508 genome sequences, respectively. SerotypeFinder for WGS-based O and H typing predicted 560 of 569 O types and 504 of 508 H types, consistent with conventional serotyping. In combination with other available WGS typing tools, E. coli serotyping can be performed solely from WGS data, providing faster and cheaper typing than current routine procedures and making WGS typing a superior alternative to conventional typing strategies.

Abstract: EMT and MET comprise the processes by which cells transit between epithelial and mesenchymal states, and they play integral roles in both normal development and cancer metastasis. This article reviews these processes and the molecular pathways that contribute to them. First, we compare embryogenesis and development with cancer metastasis. We then discuss the signaling pathways and the differential expression and down-regulation of receptors in both tumor cells and stromal cells, which play a role in EMT and metastasis. We further delve into the clinical implications of EMT and MET in several types of tumors, and lastly, we discuss the role of epigenetic events that regulate EMT/MET processes. We hypothesize that reversible epigenetic events regulate both EMT and MET, and thus, also regulate the development of different types of metastatic cancers.

Abstract: Here, we present a general framework for combining visual odometry and lidar odometry in a fundamental and first principle method The method shows improvements in performance over the state of the art, particularly in robustness to aggressive motion and temporary lack of visual features The proposed on-line method starts with visual odometry to estimate the ego-motion and to register point clouds from a scanning lidar at a high frequency but low fidelity Then, scan matching based lidar odometry refines the motion estimation and point cloud registration simultaneouslyWe show results with datasets collected in our own experiments as well as using the KITTI odometry benchmark Our proposed method is ranked #1 on the benchmark in terms of average translation and rotation errors, with a 075% of relative position drift In addition to comparison of the motion estimation accuracy, we evaluate robustness of the method when the sensor suite moves at a high speed and is subject to significant ambient lighting changes

Abstract: We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (GeneVec) for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups). Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB) with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be considered as pre-training for various applications of deep learning in bioinformatics. The related data is available at Life Language Processing Website: http://llp.berkeley.edu and Harvard Dataverse: http://dx.doi.org/10.7910/DVN/JMFHTN.