Abstract: High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future

Abstract: Immune checkpoint blockade represents a major breakthrough in cancer therapy, however responses are not universal. Genomic and immune features in pre-treatment tumor biopsies have been reported to correlate with response in patients with melanoma and other cancers, but robust biomarkers have not been identified. We studied a cohort of metastatic melanoma patients initially treated with cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) blockade (n=53) followed by programmed death-1 (PD-1) blockade at progression (n=46), and analyzed immune signatures in longitudinal tissue samples collected at multiple time points during therapy. In these studies, we demonstrate that adaptive immune signatures in tumor biopsy samples obtained early during the course of treatment are highly predictive of response to immune checkpoint blockade, and also demonstrate differential effects on the tumor microenvironment induced by CTLA-4 and PD-1 blockade. Importantly, potential mechanisms of therapeutic resistance to immune checkpoint blockade were also identified. Significance: These studies demonstrate that adaptive immune signatures in early on-treatment tumor biopsies are predictive of response to checkpoint blockade, and yield insight into mechanisms of therapeutic resistance. These concepts have far-reaching implications in this age of precision medicine, and should be explored in immune checkpoint blockade treatment across cancer types.

Abstract: MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualization, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software.

Abstract: Objective To develop and validate an international set of classification criteria for primary Sjogren's syndrome (SS) using guidelines from the American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR). These criteria were developed for use in individuals with signs and/or symptoms suggestive of SS. Methods We assigned preliminary importance weights to a consensus list of candidate criteria items, using multi-criteria decision analysis. We tested and adapted the resulting draft criteria using existing cohort data on primary SS cases and non-SS controls, with case/non-case status derived from expert clinical judgment. We then validated the performance of the classification criteria in a separate cohort of patients. Results The final classification criteria are based on the weighted sum of 5 items: anti-SSA/Ro antibody positivity and focal lymphocytic sialadenitis with a focus score of ≥1 foci/4 mm2, each scoring 3; an abnormal ocular staining score of ≥5 (or van Bijsterveld score of ≥4), a Schirmer's test result of ≤5 mm/5 minutes, and an unstimulated salivary flow rate of ≤0.1 ml/minute, each scoring 1. Individuals with signs and/or symptoms suggestive of SS who have a total score of ≥4 for the above items meet the criteria for primary SS. Sensitivity and specificity against clinician-expert–derived case/non-case status in the final validation cohort were high, i.e., 96% (95% confidence interval [95% CI] 92–98%) and 95% (95% CI 92–97%), respectively. Conclusion Using methodology consistent with other recent ACR/EULAR-approved classification criteria, we developed a single set of data-driven consensus classification criteria for primary SS, which performed well in validation analyses and are well-suited as criteria for enrollment in clinical trials.

Abstract: Nerve injury triggers the conversion of myelin and non-myelin (Remak) Schwann cells to a cell phenotype specialized to promote repair. Distal to damage, these repair Schwann cells provide the necessary signals and spatial cues for the survival of injured neurons, axonal regeneration and target reinnervation. The conversion to repair Schwann cells involves de-differentiation together with alternative differentiation, or activation, a combination that is typical of cell type conversions often referred to as (direct or lineage) reprogramming. Thus, injury-induced Schwann cell reprogramming involves down-regulation of myelin genes combined with activation of a set of repair-supportive features, including up-regulation of trophic factors, elevation of cytokines as part of the innate immune response, myelin clearance by activation of myelin autophagy in Schwann cells and macrophage recruitment, and the formation of regeneration tracks, Bungner's bands, for directing axons to their targets. This repair programme is controlled transcriptionally by mechanisms involving the transcription factor c-Jun, which is rapidly up-regulated in Schwann cells after injury. In the absence of c-Jun, damage results in the formation of a dysfunctional repair cell, neuronal death and failure of functional recovery. c-Jun, although not required for Schwann cell development, is therefore central to the reprogramming of myelin and non-myelin (Remak) Schwann cells to repair cells after injury. In future, the signalling that specifies this cell requires further analysis so that pharmacological tools that boost and maintain the repair Schwann cell phenotype can be developed.

Abstract: The scientific study of hate speech, from a computer science point of view, is recent. This survey organizes and describes the current state of the field, providing a structured overview of previous approaches, including core algorithms, methods, and main features used. This work also discusses the complexity of the concept of hate speech, defined in many platforms and contexts, and provides a unifying definition. This area has an unquestionable potential for societal impact, particularly in online communities and digital media platforms. The development and systematization of shared resources, such as guidelines, annotated datasets in multiple languages, and algorithms, is a crucial step in advancing the automatic detection of hate speech.

Abstract: Melatonin is remarkably functionally diverse with actions as a free radical scavenger and antioxidant, circadian rhythm regulator, anti-inflammatory and immunoregulating molecule, and as an oncostatic agent. We hypothesize that the initial and primary function of melatonin in photosynthetic cyanobacteria, which appeared on Earth 3.5-3.2 billion years ago, was as an antioxidant. The evolution of melatonin as an antioxidant by this organism was necessary as photosynthesis is associated with the generation of toxic-free radicals. The other secondary functions of melatonin came about much later in evolution. We also surmise that mitochondria and chloroplasts may be primary sites of melatonin synthesis in all eukaryotic cells that possess these organelles. This prediction is made on the basis that mitochondria and chloroplasts of eukaryotes developed from purple nonsulfur bacteria (which also produce melatonin) and cyanobacteria when they were engulfed by early eukaryotes. Thus, we speculate that the melatonin-synthesizing actions of the engulfed bacteria were retained when these organelles became mitochondria and chloroplasts, respectively. That mitochondria are likely sites of melatonin formation is supported by the observation that this organelle contains high levels of melatonin that are not impacted by blood melatonin concentrations. Melatonin has a remarkable array of means by which it thwarts oxidative damage. It, as well as its metabolites, is differentially effective in scavenging a variety of reactive oxygen and reactive nitrogen species. Moreover, melatonin and its metabolites modulate a large number of antioxidative and pro-oxidative enzymes, leading to a reduction in oxidative damage. The actions of melatonin on radical metabolizing/producing enzymes may be mediated by the Keap1-Nrf2-ARE pathway. Beyond its direct free radical scavenging and indirect antioxidant effects, melatonin has a variety of physiological and metabolic advantages that may enhance its ability to limit oxidative stress.

Abstract: The key challenge for household load forecasting lies in the high volatility and uncertainty of load profiles. Traditional methods tend to avoid such uncertainty by load aggregation (to offset uncertainties), customer classification (to cluster uncertainties) and spectral analysis (to filter out uncertainties). This paper, for the first time, aims to directly learn the uncertainty by applying a new breed of machine learning algorithms—deep learning. However, simply adding layers in neural networks will cap the forecasting performance due to the occurrence of over-fitting. A novel pooling-based deep recurrent neural network is proposed in this paper which batches a group of customers’ load profiles into a pool of inputs. Essentially the model could address the over-fitting issue by increasing data diversity and volume. This paper reports the first attempts to develop a bespoke deep learning application for household load forecasting and achieved preliminary success. The developed method is implemented on Tensorflow deep learning platform and tested on 920 smart metered customers from Ireland. Compared with the state-of-the-art techniques in household load forecasting, the proposed method outperforms ARIMA by 19.5%, SVR by 13.1% and classical deep RNN by 6.5% in terms of RMSE.

Abstract: BACKGROUND: Pulmonary rehabilitation has become a cornerstone in the management of patients with stable Chronic Obstructive Pulmonary Disease (COPD). Systematic reviews have shown large and important clinical effects of pulmonary rehabilitation in these patients. However, in unstable COPD patients who have recently suffered an exacerbation, the effects of pulmonary rehabilitation are less established. OBJECTIVES: To assess the effects of pulmonary rehabilitation after COPD exacerbations on future hospital admissions (primary outcome) and other patient-important outcomes (mortality, health-related quality of life and exercise capacity). SEARCH STRATEGY: Trials were identified from searches of CENTRAL, MEDLINE, EMBASE, PEDRO and the Cochrane Airways Group Register of Trials. Searches were current as of March 2010. SELECTION CRITERIA: Randomized controlled trials comparing pulmonary rehabilitation of any duration after exacerbation of COPD with conventional care. Pulmonary rehabilitation programmes needed to include at least physical exercise. Control groups received conventional community care without rehabilitation. DATA COLLECTION AND ANALYSIS: We calculated pooled odds ratios and weighted mean differences (MD) using random-effects models. We requested missing data from the authors of the primary studies. MAIN RESULTS: We identified nine trials involving 432 patients. Pulmonary rehabilitation significantly reduced hospital admissions (pooled odds ratio 0.22 [95% CI 0.08 to 0.58], number needed to treat (NNT) 4 [95% CI 3 to 8], over 25 weeks) and mortality (OR 0.28; 95% CI 0.10 to 0.84), NNT 6 [95% CI 5 to 30] over 107 weeks). Effects of pulmonary rehabilitation on health-related quality of life were well above the minimal important difference when measured by the Chronic Respiratory Questionnaire (MD for dyspnea, fatigue, emotional function and mastery domains between 0.81 (fatigue; 95% CI 0.16 to 1.45) and 0.97 (dyspnea; 95% CI 0.35 to 1.58)) and the St. Georges Respiratory Questionnaire total score (MD -9.88; 95% CI -14.40 to -5.37); impacts domain (MD -13.94; 95% CI -20.37 to -7.51) and for activity limitation domain (MD -9.94; 95% CI -15.98 to -3.89)). The symptoms domain of the St. Georges Respiratory Questionnaire showed no significant improvement. Pulmonary rehabilitation significantly improved exercise capacity and the improvement was above the minimally important difference (six-minute walk test (MD 77.70 meters; 95% CI 12.21 to 143.20) and shuttle walk test (MD 64.35; 95% CI 41.28 to 87.43)). No adverse events were reported in three studies. AUTHORS' CONCLUSIONS: Evidence from nine small studies of moderate methodological quality, suggests that pulmonary rehabilitation is a highly effective and safe intervention to reduce hospital admissions and mortality and to improve health-related quality of life in COPD patients who have recently suffered an exacerbation of COPD.

Abstract: We propose a novel approach for instance-level image retrieval. It produces a global and compact fixed-length representation for each image by aggregating many region-wise descriptors. In contrast to previous works employing pre-trained deep networks as a black box to produce features, our method leverages a deep architecture trained for the specific task of image retrieval. Our contribution is twofold: (i) we leverage a ranking framework to learn convolution and projection weights that are used to build the region features; and (ii) we employ a region proposal network to learn which regions should be pooled to form the final global descriptor. We show that using clean training data is key to the success of our approach. To that aim, we use a large scale but noisy landmark dataset and develop an automatic cleaning approach. The proposed architecture produces a global image representation in a single forward pass. Our approach significantly outperforms previous approaches based on global descriptors on standard datasets. It even surpasses most prior works based on costly local descriptor indexing and spatial verification. Additional material is available at www.xrce.xerox.com/Deep-Image-Retrieval.

Abstract: Detection of X-ray emission at a location coincident with the kilonova transient of the gravitational-wave event GW170817 provides the missing observational link between short gamma-ray bursts and gravitational waves from neutron-star mergers. Merging neutron stars are potential sources of gravitational waves and have long been predicted to produce jets of material as part of a low-luminosity transient known as a 'kilonova'. There is growing evidence that neutron-star mergers also give rise to short, hard gamma-ray bursts. A group of papers in this issue report observations of a transient associated with the gravitational-wave event GW170817—a signature of two neutron stars merging and a gamma-ray flash—that was detected in August 2017. The observed gamma-ray, X-ray, optical and infrared radiation signatures support the predictions of an outflow of matter from double neutron-star mergers and present a clear origin for gamma-ray bursts. Previous predictions differ over whether the jet material would combine to form light or heavy elements. These papers now show that the early part of the outflow was associated with lighter elements whereas the later observations can be explained by heavier elements, the origins of which have been uncertain. However, one paper (by Stephen Smartt and colleagues) argues that only light elements are needed for the entire event. Additionally, Eleonora Troja and colleagues report X-ray observations and radio emissions that suggest that the 'kilonova' jet was observed off-axis, which could explain why gamma-ray-burst detections are seen as dim. A long-standing paradigm in astrophysics is that collisions—or mergers—of two neutron stars form highly relativistic and collimated outflows (jets) that power γ-ray bursts of short (less than two seconds) duration1,2,3. The observational support for this model, however, is only indirect4,5. A hitherto outstanding prediction is that gravitational-wave events from such mergers should be associated with γ-ray bursts, and that a majority of these bursts should be seen off-axis, that is, they should point away from Earth6,7. Here we report the discovery observations of the X-ray counterpart associated with the gravitational-wave event GW170817. Although the electromagnetic counterpart at optical and infrared frequencies is dominated by the radioactive glow (known as a ‘kilonova’) from freshly synthesized rapid neutron capture (r-process) material in the merger ejecta8,9,10, observations at X-ray and, later, radio frequencies are consistent with a short γ-ray burst viewed off-axis7,11. Our detection of X-ray emission at a location coincident with the kilonova transient provides the missing observational link between short γ-ray bursts and gravitational waves from neutron-star mergers, and gives independent confirmation of the collimated nature of the γ-ray-burst emission.

Abstract: As a new classification platform, deep learning has recently received increasing attention from researchers and has been successfully applied to many domains. In some domains, like bioinformatics and robotics, it is very difficult to construct a large-scale well-annotated dataset due to the expense of data acquisition and costly annotation, which limits its development. Transfer learning relaxes the hypothesis that the training data must be independent and identically distributed (i.i.d.) with the test data, which motivates us to use transfer learning to solve the problem of insufficient training data. This survey focuses on reviewing the current researches of transfer learning by using deep neural network and its applications. We defined deep transfer learning, category and review the recent research works based on the techniques used in deep transfer learning.

Abstract: Altered olfactory function is a common symptom of COVID-19, but its etiology is unknown. A key question is whether SARS-CoV-2 (CoV-2) - the causal agent in COVID-19 - affects olfaction directly, by infecting olfactory sensory neurons or their targets in the olfactory bulb, or indirectly, through perturbation of supporting cells. Here we identify cell types in the olfactory epithelium and olfactory bulb that express SARS-CoV-2 cell entry molecules. Bulk sequencing demonstrated that mouse, non-human primate and human olfactory mucosa expresses two key genes involved in CoV-2 entry, ACE2 and TMPRSS2. However, single cell sequencing revealed that ACE2 is expressed in support cells, stem cells, and perivascular cells, rather than in neurons. Immunostaining confirmed these results and revealed pervasive expression of ACE2 protein in dorsally-located olfactory epithelial sustentacular cells and olfactory bulb pericytes in the mouse. These findings suggest that CoV-2 infection of non-neuronal cell types leads to anosmia and related disturbances in odor perception in COVID-19 patients.

Abstract: The striking and unexpected relative risk reductions in cardiovascular (CV) mortality (38%), hospitalization for heart failure (35%), and death from any cause (32%) observed in the EMPA-REG OUTCOME trial using an inhibitor of sodium-glucose cotransporter 2 (SGLT2) in patients with type 2 diabetes and high CV risk have raised the possibility that mechanisms other than those observed in the trial-modest improvement in glycemic control, small decrease in body weight, and persistent reductions in blood pressure and uric acid level-may be at play. We hypothesize that under conditions of mild, persistent hyperketonemia, such as those that prevail during treatment with SGLT2 inhibitors, β-hydroxybutyrate is freely taken up by the heart (among other organs) and oxidized in preference to fatty acids. This fuel selection improves the transduction of oxygen consumption into work efficiency at the mitochondrial level. In addition, the hemoconcentration that typically follows SGLT2 inhibition enhances oxygen release to the tissues, thereby establishing a powerful synergy with the metabolic substrate shift. These mechanisms would cooperate with other SGLT2 inhibition-induced changes (chiefly, enhanced diuresis and reduced blood pressure) to achieve the degree of cardioprotection revealed in the EMPA-REG OUTCOME trial. This hypothesis opens up new lines of investigation into the pathogenesis and treatment of diabetic and nondiabetic heart disease.

Abstract: To estimate the dynamic effects of an absorbing treatment, researchers often use two-way fixed effects regressions that include leads and lags of the treatment. We show that in settings with variation in treatment timing across units, the coefficient on a given lead or lag can be contaminated by effects from other periods, and apparent pretrends can arise solely from treatment effects heterogeneity. We propose an alternative estimator that is free of contamination, and illustrate the relative shortcomings of two-way fixed effects regressions with leads and lags through an empirical application.

Abstract: Microscopes allow us to visualize objects that are invisible to the naked eye. One type of microscope—called the electron microscope—produces images using beams of particles known as electrons, which enables them to produce more detailed images than microscopes that use light. There are several ways to prepare samples for electron microscopy. For example, in ‘electron cryo-microscopy’—or cryo-EM for short—a sample is rapidly frozen to preserve its features before it is examined under the microscope. This technique generates images that can be analyzed by computers to produce three-dimensional models of individual viruses, proteins, and other tiny objects. Unfortunately, the samples need to be exposed to high-energy beams of electrons that will damage the sample while the images are gathered, which results in sample movement and blurry images that lack the finer details. The contrast between the sample and its background is one of the factors that determine the final quality of an image. The higher the contrast, the greater the level of structural information that can be obtained, but this requires the use of longer exposures to the electron beam. To overcome this issue, researchers found that instead of recording a single image, it is possible to record movies in which the movement of the sample under the electron beam can be tracked. After the movies are gathered, the movie frames are aligned using computer software to reduce the blurring caused by the sample moving and can then be used to make three-dimensional models. Grant and Grigorieff improved this method further by studying how quickly a large virus-like particle called ‘rotavirus double-layered particle’ is damaged under the electron beam. These experiments identified an optimum range of exposure to electrons that provides the highest image contrast at any given level of detail. These findings were used to design an exposure filter that can be applied to the movie frames, allowing Grant and Grigorieff to visualize features of the virus that had not previously been observed by cryo-EM. This method was also used to study an assembly of proteins known as the proteasome, which is responsible for destroying old proteins. Grant and Grigorieff's findings should be useful for cryo-EM studies on many kinds of samples.

Abstract: Facial image manipulation has achieved great progress in recent years. However, previous methods either operate on a predefined set of face attributes or leave users little freedom to interactively manipulate images. To overcome these drawbacks, we propose a novel framework termed MaskGAN, enabling diverse and interactive face manipulation. Our key insight is that semantic masks serve as a suitable intermediate representation for flexible face manipulation with fidelity preservation. MaskGAN has two main components: 1) Dense Mapping Network (DMN) and 2) Editing Behavior Simulated Training (EBST). Specifically, DMN learns style mapping between a free-form user modified mask and a target image, enabling diverse generation results. EBST models the user editing behavior on the source mask, making the overall framework more robust to various manipulated inputs. Specifically, it introduces dual-editing consistency as the auxiliary supervision signal. To facilitate extensive studies, we construct a large-scale high-resolution face dataset with fine-grained mask annotations named CelebAMask-HQ. MaskGAN is comprehensively evaluated on two challenging tasks: attribute transfer and style copy, demonstrating superior performance over other state-of-the-art methods. The code, models, and dataset are available at https://github.com/switchablenorms/CelebAMask-HQ.

Abstract: The past decade has seen a reawakening of solid-state approaches to chemical synthesis, driven by the search for new, cleaner synthetic methodologies. Mechanochemistry, i.e., chemical transformations initiated or sustained by mechanical force, has been advancing particularly rapidly, from a laboratory curiosity to a widely applicable technique that not only enables a cleaner route to chemical transformations but offers completely new opportunities in making and screening for molecules and materials. This Outlook provides a brief overview of the recent achievements and opportunities created by mechanochemistry, including access to materials, molecular targets, and synthetic strategies that are hard or even impossible to access by conventional means.

Abstract: Autophagy is a cytoplasmic degradation system, which is important for starvation adaptation and cellular quality control. Recent advances in understanding autophagy highlight its importance under physiological and pathological conditions. However, methods for monitoring autophagic activity are complicated and the results are sometimes misinterpreted. Here, we review the methods used to identify autophagic structures, and to measure autophagic flux in cultured cells and animals. We will also describe the existing autophagy reporter mice that are useful for autophagy studies and drug testing. Lastly, we will consider the attempts to monitor autophagy in samples derived from humans.

Abstract: The CHiME challenge series aims to advance far field speech recognition technology by promoting research at the interface of signal processing and automatic speech recognition. This paper presents the design and outcomes of the 3rd CHiME Challenge, which targets the performance of automatic speech recognition in a real-world, commercially-motivated scenario: a person talking to a tablet device that has been fitted with a six-channel microphone array. The paper describes the data collection, the task definition and the baseline systems for data simulation, enhancement and recognition. The paper then presents an overview of the 26 systems that were submitted to the challenge focusing on the strategies that proved to be most successful relative to the MVDR array processing and DNN acoustic modeling reference system. Challenge findings related to the role of simulated data in system training and evaluation are discussed.

Abstract: Since decades it has been known that non-protein-coding RNAs have important cellular functions. Deep sequencing recently facilitated the discovery of thousands of novel transcripts, now classified as long noncoding RNAs (lncRNAs), in many vertebrate and invertebrate species. LncRNAs are involved in a wide range of cellular mechanisms, from almost all aspects of gene expression to protein translation and stability. Recent findings implicate lncRNAs as key players of cellular differentiation, cell lineage choice, organogenesis and tissue homeostasis. Moreover, lncRNAs are involved in pathological conditions such as cancer and cardiovascular disease, and therefore provide novel biomarkers and pharmaceutical targets. Here we discuss examples illustrating the versatility of lncRNAs in gene control, development and differentiation, as well as in human disease.

Abstract: N6-methyladenosine (m6A) is the most abundant internal modification of eukaryotic messenger RNA (mRNA) and plays critical roles in RNA biology. The function of this modification is mediated by m6A-selective 'reader' proteins of the YTH family, which incorporate m6A-modified mRNAs into pathways of RNA metabolism. Here, we show that the m6A-binding protein YTHDC1 mediates export of methylated mRNA from the nucleus to the cytoplasm in HeLa cells. Knockdown of YTHDC1 results in an extended residence time for nuclear m6A-containing mRNA, with an accumulation of transcripts in the nucleus and accompanying depletion within the cytoplasm. YTHDC1 interacts with the splicing factor and nuclear export adaptor protein SRSF3, and facilitates RNA binding to both SRSF3 and NXF1. This role for YTHDC1 expands the potential utility of chemical modification of mRNA, and supports an emerging paradigm of m6A as a distinct biochemical entity for selective processing and metabolism of mammalian mRNAs.

Abstract: Biofilm is a complex structure of microbiome having different bacterial colonies or single type of cells in a group; adhere to the surface. These cells are embedded in extracellular polymeric substances, a matrix which is generally composed of eDNA, proteins and polysaccharides, showed high resistance to antibiotics. It is one of the major causes of infection persistence especially in nosocomial settings through indwelling devices. Quorum sensing plays an important role in regulating the biofilm formation. There are many approaches being used to control infections by suppressing its formation but CRISPR-CAS (gene editing technique) and photo dynamic therapy (PDT) are proposed to be used as therapeutic approaches to subside bacterial biofim infections, especially caused by deadly drug resistant bad bugs.

Abstract: Meat and meat products are a fundamental part of the human diet. The protein and vitamin content, as well as essential fatty acids, gives them an appropriate composition to complete the nutritional requirements. However, meat constituents are susceptible to degradation processes. Among them, the most important, after microbial deterioration, are oxidative processes, which affect lipids, pigments, proteins and vitamins. During these reactions a sensory degradation of the product occurs, causing consumer rejection. In addition, there is a nutritional loss that leads to the formation of toxic substances, so the control of oxidative processes is of vital importance for the meat industry. Nonetheless, despite lipid oxidation being widely investigated for decades, the complex reactions involved in the process, as well as the different pathways and factors that influenced them, make that lipid oxidation mechanisms have not yet been completely understood. Thus, this article reviews the fundamental mechanisms of lipid oxidation, the most important oxidative reactions, the main factors that influence lipid oxidation, and the routine methods to measure compounds derived from lipid oxidation in meat.

Abstract: Global biodiversity in freshwater and the oceans is declining at high rates. Reliable tools for assessing and monitoring aquatic biodiversity, especially for rare and secretive species, are important for efficient and timely management. Recent advances in DNA sequencing have provided a new tool for species detection from DNA present in the environment. In this study, we tested whether an environmental DNA (eDNA) metabarcoding approach, using water samples, can be used for addressing significant questions in ecology and conservation. Two key aquatic vertebrate groups were targeted: amphibians and bony fish. The reliability of this method was cautiously validated in silico, invitro and insitu. When compared with traditional surveys or historical data, eDNA metabarcoding showed a much better detection probability overall. For amphibians, the detection probability with eDNA metabarcoding was 0.97 (CI=0.90-0.99) vs. 0.58 (CI=0.50-0.63) for traditional surveys. For fish, in 89% of the studied sites, the number of taxa detected using the eDNA metabarcoding approach was higher or identical to the number detected using traditional methods. We argue that the proposed DNA-based approach has the potential to become the next-generation tool for ecological studies and standardized biodiversity monitoring in a wide range of aquatic ecosystems. see also the Perspective by Hoffmann, Schubert and Calvignac-Spencer.

Abstract: Developing highly conductive, stable, and active nonprecious hydrogen evolution reaction (HER) catalysts is a key step for the proposed hydrogen economy. However, few catalysts, except for noble metals, meet all the requirements. By using state-of-the-art density functional calculations, herein we demonstrate that 2D MXenes, like Ti2C, V2C, and Ti3C2, are terminated by a mixture of oxygen atoms and hydroxyl, while Nb2C and Nb4C3O2 are fully terminated by oxygen atoms under standard conditions [pH 0, p(H2) = 1 bar, U = 0 V vs standard hydrogen electrode], findings in good agreement with experimental observation. Furthermore, all these MXenes are conductive under standard conditions, thus allowing high charge transfer kinetics during the HER. Remarkably, the Gibbs free energy for the adsorption of atomic hydrogen (ΔGH*0) on the terminated O atoms (e.g., Ti2CO2) is close to the ideal value (0 eV). Our results demonstrate terminated oxygens as catalytic active sites for the HER at these materials and highligh...