Threat of shock promotes passive avoidance, but not active avoidance

Anxiety and stress are adaptive responses to threat that promote harm avoidance. In particular, prior work has shown that anxiety induced in humans using threat of unpredictable shock promotes behavioral inhibition in the face of harm. This is consistent with the idea that anxiety promotes passive avoidance—that is, withholding approach actions that could lead to harm. However, harm can also be avoided through active avoidance, where a (withdrawal) action is taken to avoid harm. Here, we provide the first direct within‐study comparison of the effects of threat of shock on active and passive avoidance. We operationalize passive avoidance as withholding a button press response in the face of negative outcomes, and active avoidance as lifting/releasing a button press in the face of negative outcomes. We explore the impact of threat of unpredictable shock on the learning of these behavioral responses (alongside matched responses to rewards) within a single cognitive task. We predicted that threat of shock would promote both active and passive avoidance, and that this would be driven by increased reliance on Pavlovian bias, as parameterized within reinforcement‐learning models. Consistent with our predictions, we provide evidence that threat of shock promotes passive avoidance as conceptualized by our task. However, inconsistent with predictions, we found no evidence that threat of shock promoted active avoidance, nor evidence of elevated Pavlovian bias in any condition. One hypothetical framework with which to understand these findings is that anxiety promotes passive over active harm avoidance strategies in order to conserve energy while avoiding harm

Identifying specific prefrontal neurons that contribute to autism-associated abnormalities in physiology and social behavior.

Functional imaging and gene expression studies both implicate the medial prefrontal cortex (mPFC), particularly deep-layer projection neurons, as a potential locus for autism pathology. Here, we explored how specific deep-layer prefrontal neurons contribute to abnormal physiology and behavior in mouse models of autism. First, we find that across three etiologically distinct models-in utero valproic acid (VPA) exposure, CNTNAP2 knockout and FMR1 knockout-layer 5 subcortically projecting (SC) neurons consistently exhibit reduced input resistance and action potential firing. To explore how altered SC neuron physiology might impact behavior, we took advantage of the fact that in deep layers of the mPFC, dopamine D2 receptors (D2Rs) are mainly expressed by SC neurons, and used D2-Cre mice to label D2R+ neurons for calcium imaging or optogenetics. We found that social exploration preferentially recruits mPFC D2R+ cells, but that this recruitment is attenuated in VPA-exposed mice. Stimulating mPFC D2R+ neurons disrupts normal social interaction. Conversely, inhibiting these cells enhances social behavior in VPA-exposed mice. Importantly, this effect was not reproduced by nonspecifically inhibiting mPFC neurons in VPA-exposed mice, or by inhibiting D2R+ neurons in wild-type mice. These findings suggest that multiple forms of autism may alter the physiology of specific deep-layer prefrontal neurons that project to subcortical targets. Furthermore, a highly overlapping population-prefrontal D2R+ neurons-plays an important role in both normal and abnormal social behavior, such that targeting these cells can elicit potentially therapeutic effects

Differential expression analysis for sequence count data

*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.

*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. 

*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from "http://www-huber.embl.de/users/anders/DESeq":http://www-huber.embl.de/users/anders/DESeq

The translational neural circuitry of anxiety

Anxiety is an adaptive response that promotes harm avoidance, but at the same time excessive anxiety constitutes the most common psychiatric complaint. Moreover, current treatments for anxiety—both psychological and pharmacological—hover at around 50% recovery rates. Improving treatment outcomes is nevertheless difficult, in part because contemporary interventions were developed without an understanding of the underlying neurobiological mechanisms that they modulate. Recent advances in experimental models of anxiety in humans, such as threat of unpredictable shock, have, however, enabled us to start translating the wealth of mechanistic animal work on defensive behaviour into humans. In this article, we discuss the distinction between fear and anxiety, before reviewing translational research on the neural circuitry of anxiety in animal models and how it relates to human neuroimaging studies across both healthy and clinical populations. We highlight the roles of subcortical regions (and their subunits) such as the bed nucleus of the stria terminalis, the amgydala, and the hippocampus, as well as their connectivity to cortical regions such as dorsal medial and lateral prefrontal/cingulate cortex and insula in maintaining anxiety responding. We discuss how this circuitry might be modulated by current treatments before finally highlighting areas for future research that might ultimately improve treatment outcomes for this common and debilitating transdiagnostic symptom

Alterations in circulating lipidomic profile in patients with type 2 diabetes with or without non-alcoholic fatty liver disease

Objective: Non-alcoholic fatty liver disease (NAFLD) and Type 2 diabetes mellitus (T2DM) often coexist and drive detrimental effects in a synergistic manner. This study was designed to understand the changes in circulating lipid and lipoprotein metabolism in patients with T2DM with or without NAFLD. Methods: Four hundred thirty-four T2DM patients aged 18–60 years were included in this study. Fatty liver was assessed by FibroScan. The comprehensive metabolic lipid profiling of serum samples was assessed by using high-throughput proton NMR metabolomics. Results: Our data revealed a significant association between steatosis and serum total lipids in VLDL and LDL lipoprotein subclasses, while total lipids in HDL subclasses were negatively associated. A significant positive association was found between steatosis and concentration of lipids, phospholipids, cholesterol, and triglycerides in VLDL and LDL subclasses, while HDL subclasses were negatively associated. Furthermore, a significant, association was observed between fibrosis and concentrations of lipids, phospholipids, cholesterol, and triglycerides in very small VLDL, large, and very large HDL subclasses. Subgroup analysis revealed a decrease in the concentrations of lipids, phospholipids, cholesterol, and other lipid biomolecules in patients using antilipemic medications. Conclusion: The metabolomics results provide evidence that patients with T2DM with higher steatosis grades have altered lipid metabolomics compared to patients without steatosis. Increased lipid, phospholipids, cholesterol, and triglycerides concentration of VLDL and LDL subclasses are associated with steatosis in patients with T2DM

Enabling semantic queries across federated bioinformatics databases

MOTIVATION: Data integration promises to be one of the main catalysts in enabling new insights to be drawn from the wealth of biological data available publicly. However, the heterogeneity of the different data sources, both at the syntactic and the semantic level, still poses significant challenges for achieving interoperability among biological databases. RESULTS: We introduce an ontology-based federated approach for data integration. We applied this approach to three heterogeneous data stores that span different areas of biological knowledge: (i) Bgee, a gene expression relational database; (ii) Orthologous Matrix (OMA), a Hierarchical Data Format 5 orthology DS; and (iii) UniProtKB, a Resource Description Framework (RDF) store containing protein sequence and functional information. To enable federated queries across these sources, we first defined a new semantic model for gene expression called GenEx. We then show how the relational data in Bgee can be expressed as a virtual RDF graph, instantiating GenEx, through dedicated relational-to-RDF mappings. By applying these mappings, Bgee data are now accessible through a public SPARQL endpoint. Similarly, the materialized RDF data of OMA, expressed in terms of the Orthology ontology, is made available in a public SPARQL endpoint. We identified and formally described intersection points (i.e. virtual links) among the three data sources. These allow performing joint queries across the data stores. Finally, we lay the groundwork to enable nontechnical users to benefit from the integrated data, by providing a natural language template-based search interface

Photoreduction of CO2 with a Formate Dehydrogenase Driven by Photosystem II Using a Semi-artificial Z-Scheme Architecture.

Solar-driven coupling of water oxidation with CO2 reduction sustains life on our planet and is of high priority in contemporary energy research. Here, we report a photoelectrochemical tandem device that performs photocatalytic reduction of CO2 to formate. We employ a semi-artificial design, which wires a W-dependent formate dehydrogenase (FDH) cathode to a photoanode containing the photosynthetic water oxidation enzyme, Photosystem II, via a synthetic dye with complementary light absorption. From a biological perspective, the system achieves a metabolically inaccessible pathway of light-driven CO2 fixation to formate. From a synthetic point of view, it represents a proof-of-principle system utilizing precious-metal-free catalysts for selective CO2-to-formate conversion using water as an electron donor. This hybrid platform demonstrates the translatability and versatility of coupling abiotic and biotic components to create challenging models for solar fuel and chemical synthesis.ERC Consolidator Grant, EPSRC, Christian Doppler Research Association (Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development), the OMV group, Deutsche Forschungsgemeinschaft, European Union's Horizon 2020 MSCA, Fundação para a Ciência e Tecnologia (Portugal), COMPETE2020/POCI and European Union’s Horizon 202

p-wave triggered superconductivity in single-layer graphene on an electron-doped oxide superconductor

Electron pairing in the vast majority of superconductors follows the Bardeen-Cooper-Schrieffer theory of superconductivity, which describes the condensation of electrons into pairs with antiparallel spins in a singlet state with an s-wave symmetry. Unconventional superconductivity was predicted in single-layer graphene (SLG), with the electrons pairing with a $\textit{p}$-wave or chiral d-wave symmetry, depending on the position of the Fermi energy with respect to the Dirac point. By placing SLG on an electron-doped (non-chiral) d-wave superconductor and performing local scanning tunnelling microscopy and spectroscopy, here we show evidence for a $\textit{p}$-wave triggered superconducting density of states in SLG. The realization of unconventional superconductivity in SLG offers an exciting new route for the development of p-wave superconductivity using two-dimensional materials with transition temperatures above 4.2 K.The work was funded by the following agencies: Royal Society (‘Superconducting Spintronics’), Leverhulme Trust (IN-2013-033), Schiff Foundation, the EPSRC (EP/N017242/1, EP/G037221/1, EP/K01711X/1, EP/K017144/1, EP/N010345/1, EP/M507799/1, EP/L016087/1), ERC Grant Hetero2D, EU Graphene Flagship, COST Action MP-1201, MSCA-IFEF-ST No. 656485-Spin3, Outstanding Academic Fellows programme at NTNU, Research Council of Norway (205591, 216700 and 24080)

Neurite outgrowth inhibitory levels of organophosphates induce tissue transglutaminase activity in differentiating N2a cells: evidence for covalent adduct formation

Organophosphate compounds (OPs) induce both acute and delayed neurotoxic effects, the latter of which is believed to involve their interaction with proteins other than acetylcholinesterase. However, few OP-binding proteins have been identified that may have a direct role in OP-induced delayed neurotoxicity. Given their ability to disrupt Ca2+ homeostasis, a key aim of the current work was to investigate the effects of sub-lethal neurite outgrowth inhibitory levels of OPs on the Ca2+-dependent enzyme tissue transglutaminase (TG2). At 1–10 µM, the OPs phenyl saligenin phosphate (PSP) and chlorpyrifos oxon (CPO) had no effect cell viability but induced concentration-dependent decreases in neurite outgrowth in differentiating N2a neuroblastoma cells. The activity of TG2 increased in cell lysates of differentiating cells exposed for 24 h to PSP and chlorpyrifos oxon CPO (10 µM), as determined by biotin-cadaverine incorporation assays. Exposure to both OPs (3 and/or 10 µM) also enhanced in situ incorporation of the membrane permeable substrate biotin-X-cadaverine, as indicated by Western blot analysis of treated cell lysates probed with ExtrAvidin peroxidase and fluorescence microscopy of cell monolayers incubated with FITC-streptavidin. Both OPs (10 µM) stimulated the activity of human and mouse recombinant TG2 and covalent labelling of TG2 with dansylamine-labelled PSP was demonstrated by fluorescence imaging following SDS-PAGE. A number of TG2 substrates were tentatively identified by mass spectrometry, including cytoskeletal proteins, chaperones and proteins involved protein synthesis and gene regulation. We propose that the elevated TG2 activity observed is due to the formation of a novel covalent adduct between TG2 and OPs

Captive reptile mortality rates in the home and implications for the wildlife trade

The trade in wildlife and keeping of exotic pets is subject to varying levels of national and international regulation and is a topic often attracting controversy. Reptiles are popular exotic pets and comprise a substantial component of the live animal trade. High mortality of traded animals raises welfare concerns, and also has implications for conservation if collection from the wild is required to meet demand. Mortality of reptiles can occur at any stage of the trade chain from collector to consumer. However, there is limited information on mortality rates of reptiles across trade chains, particularly amongst final consumers in the home. We investigated mortality rates of reptiles amongst consumers using a specialised technique for asking sensitive questions, additive Randomised Response Technique (aRRT), as well as direct questioning (DQ). Overall, 3.6% of snakes, chelonians and lizards died within one year of acquisition. Boas and pythons had the lowest reported mortality rates of 1.9% and chameleons had the highest at 28.2%. More than 97% of snakes, 87% of lizards and 69% of chelonians acquired by respondents over five years were reported to be captive bred and results suggest that mortality rates may be lowest for captive bred individuals. Estimates of mortality from aRRT and DQ did not differ significantly which is in line with our findings that respondents did not find questions about reptile mortality to be sensitive. This research suggests that captive reptile mortality in the home is rather low, and identifies those taxa where further effort could be made to reduce mortality rate