Scavenging amphipods of the Angolan deep-sea habitat, with a focus on Abyssorchomene distinctus (Birstein and Vinogradov, 1960) (Amphipoda: Lysianassoidea)

Owing to its vast natural resources and the influence of the Congo River and associated submarine canyon, the Angolan continental margin is of both socioeconomic and ecological interest. The deep-sea ecosystems of the region are nevertheless understudied, and much of the deep-sea fauna remains undescribed. Here, we document the scavenging amphipods of the Angolan deep-sea habitat, which provides valuable new insights into the ecology of Angolan deep-sea scavengers. This can be used as an ecological baseline, against which resource-extraction impacts can be measured. A total of 7996 scavenging amphipods, representing 10 species, were identified. At least four species were new to science. The relatively low scavenger diversity of the region, combined with the large sample sizes, may be indicative of abundant food falls in the region due to the presence of the submarine canyon system. The dominant species across all samples, Abyssorchomene distinctus (Birstein and Vinogradov, 1960), was the focus of a population-level study, which was used to describe the population structure of this species and identify species traits. Of the 826 individuals of A. distinctus dissected and measured, 533 were unsexed juveniles, 149 were male, and 144 were female. Females were significantly larger than males, which is indicative of non-mate-guarding pre-copulatory behaviour, but had significantly shorter antennae, which may indicate that males use chemical cues during mate searching. Two, three, and five discrete size-based cohorts were identified for juveniles, males, and females respectively. No ovigerous females were caught but brood size of A. distinctus was estimated to be 10-38 offspring based on ovary contents

Meta-analysis of Antarctic phylogeography reveals strong sampling bias and critical knowledge gaps

DATA AVAILABILITY STATEMENT : This study used previously published genetic data from diverse studies. All metadata (GenBank accessions, paper references, geolocations etc.) for data used in this study are available from the Dryad Digital Repository: . This article contains no original data.Much of Antarctica's highly endemic terrestrial biodiversity is found in small ice-free patches. Substantial genetic differentiation has been detected among populations across spatial scales. Sampling is, however, often restricted to commonly-accessed sites and we therefore lack a comprehensive understanding of broad-scale biogeographic patterns, which could impede forecasts of the nature and impacts of future change. Here, we present a synthesis of published genetic studies across terrestrial Antarctica and the broader Antarctic region, aiming to identify current biogeographic patterns, environmental drivers of diversity and future research priorities. A database of all published genetic research from terrestrial fauna and flora (excl. microbes) across the Antarctic region was constructed. This database was then filtered to focus on the most well-represented taxa and markers (mitochondrial COI for fauna, and nuclear ITS for flora). The final dataset comprised 7222 records, spanning 153 studies of 335 different species. There was strong taxonomic bias towards flowering plants (52% of all floral data sets) and springtails (54% of all faunal data sets), and geographic bias towards the Antarctic Peninsula and Victoria Land. Recent connectivity between the Antarctic continent and neighbouring landmasses, such as South America and the Southern Ocean Islands (SOIs), was inferred for some groups, but patterns observed for most taxa were strongly influenced by sampling biases. Above-ground wind speed and habitat heterogeneity were positively correlated with genetic diversity indices overall though environment was a generally poor predictor of genetic diversity. The low resolution and variable coverage of data may also have reduced the power of our comparative inferences. In the future, higher-resolution data, such as genomic SNPs and environmental modelling, alongside targeting sampling of remote sites and under sampled taxa, will address current knowledge gaps and greatly advance our understanding of evolutionary processes across the Antarctic region.The New Zealand Antarctic Science Platform; a Royal Society of New Zealand Rutherford Discovery Fellowship via an Honours scholarship; a Royal Society of New Zealand Te Apārangi Marsden Fund grant; Biodiversa ASICS funding (EU-Biodiversa ASICS project).http://www.ecography.orghj2023Plant Production and Soil Scienc

Absence of neuronal autoantibodies in neuropsychiatric systemic lupus erythematosus

International audienceThis study aimed to characterise both neuronal autoantibodies and levels of interferon α, two proposed causative agents in neuropsychiatric systemic lupus erythematosus (NPSLE). Cerebrospinal fluid (CSF) and plasma from 35 patients with systemic lupus erythematosus (SLE; 15 with NPSLE) showed no antibodies against natively expressed N-methyl-D-aspartate receptors (NMDARs), or the surface of live hippocampal neurons. By comparison to controls (n = 104), patients with SLE had antibodies that bound to a peptide representing the extracellular domain of NMDARs (p < 0.0001), however, binding was retained against both rearranged peptides and no peptide (r = 0.85 and r = 0.79, respectively, p < 0.0001). In summary, neuronal-surface reactive antibodies were not detected in NPSLE. Further, while interferon α levels were higher in SLE (p < 0.0001), they lacked specificity for NPSLE. Our findings mandate a search for novel biomarkers in this condition. ANN NEUROL 2020

Using Policy Labs as a process to bring evidence closer to public policymaking: a guide to one approach

While robust evidence is one ingredient in the policymaking process, it is by no means the only one. Engaging with policymakers and the policymaking process requires collaborative working models, navigating through the experiences, values and perspectives of policymakers and other stakeholders, as well as communicating evidence in an accessible manner. As a response to these requirements, over recent years there has been proliferation of activities that engage producers of evidence (specifically, academics), policymakers, practitioners, and the public in policy formulation, implementation and evaluation. In this article, we describe one engagement approach for facilitating research evidence uptake into policy and practice—an activity called a ‘Policy Lab’—as conducted by the team at The Policy Institute at King’s College London on numerous policy challenges over the past four years. Drawing on our experience in running 15 Policy Labs between January 2015 and September 2019, we (a) provide a guide to how we have run Policy Labs, while sharing our learning on what has worked best in conducting them and (b) demonstrate how these labs can contribute to bringing evidence closer to policymaking, by comparing their characteristics to enablers for doing so identified in the literature. While this approach to Policy Labs is not the only one of its kind, we suggest that these types of Labs manifest characteristics identified in previous studies for influencing the policymaking process; namely: providing a forum for open, honest conversations around a policy topic; creating new networks, collaborations and partnerships between academics and policymakers; synthesising available evidence on a policy topic in a robust and accessible format; and providing timely access to evidence relevant to a policy issue. We recognise the limitations of measuring and evaluating how these Labs change policy in the long-term and recommend viewing the Policy Lab as part of a process for engaging evidence and policymaking and not an isolated activity. This process serves to build a coalition through participation of diverse communities (thereby establishing ‘trust’), work on the language and presentation of evidence (thereby enabling effective ‘translation’ of evidence) and engage policymakers early to respond when policy windows emerge (thereby taking into account ‘timing’ for creating policy action)

A Science-Based Policy for Managing Free-Roaming Cats

Free-roaming domestic cats (i.e., cats that are owned or unowned and are considered ‘at large’) are globally distributed non-native species that have marked impacts on biodiversity and human health. Despite clear scientific evidence of these impacts, free-roaming cats are either unmanaged or managed using scientifically unsupported and ineffective approaches (e.g., trap-neuter-release [TNR]) in many jurisdictions around the world. A critical first initiative for effective, science-driven management of cats must be broader political and legislative recognition of free-roaming cats as a non-native, invasive species. Designating cats as invasive is important for developing and implementing science-based management plans, which should include efforts to prevent cats from becoming free-roaming, policies focused on responsible pet ownership and banning outdoor cat feeding, and better enforcement of existing laws. Using a science-based approach is necessary for responding effectively to the politically charged and increasingly urgent issue of managing free-roaming cat populations

High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning

Left ventricular hypertrophy (LVH) results from chronic remodeling caused by a broad range of systemic and cardiovascular disease including hypertension, aortic stenosis, hypertrophic cardiomyopathy, and cardiac amyloidosis. Early detection and characterization of LVH can significantly impact patient care but is limited by under-recognition of hypertrophy, measurement error and variability, and difficulty differentiating etiologies of LVH. To overcome this challenge, we present EchoNet-LVH - a deep learning workflow that automatically quantifies ventricular hypertrophy with precision equal to human experts and predicts etiology of LVH. Trained on 28,201 echocardiogram videos, our model accurately measures intraventricular wall thickness (mean absolute error [MAE] 1.4mm, 95% CI 1.2-1.5mm), left ventricular diameter (MAE 2.4mm, 95% CI 2.2-2.6mm), and posterior wall thickness (MAE 1.2mm, 95% CI 1.1-1.3mm) and classifies cardiac amyloidosis (area under the curve of 0.83) and hypertrophic cardiomyopathy (AUC 0.98) from other etiologies of LVH. In external datasets from independent domestic and international healthcare systems, EchoNet-LVH accurately quantified ventricular parameters (R2 of 0.96 and 0.90 respectively) and detected cardiac amyloidosis (AUC 0.79) and hypertrophic cardiomyopathy (AUC 0.89) on the domestic external validation site. Leveraging measurements across multiple heart beats, our model can more accurately identify subtle changes in LV geometry and its causal etiologies. Compared to human experts, EchoNet-LVH is fully automated, allowing for reproducible, precise measurements, and lays the foundation for precision diagnosis of cardiac hypertrophy. As a resource to promote further innovation, we also make publicly available a large dataset of 23,212 annotated echocardiogram videos

Search for heavy neutrinos mixing with tau neutrinos

We report on a search for heavy neutrinos (\nus) produced in the decay D_s\to \tau \nus at the SPS proton target followed by the decay \nudecay in the NOMAD detector. Both decays are expected to occur if \nus is a component of $\nu_{\tau}$.\ From the analysis of the data collected during the 1996-1998 runs with $4.1\times10^{19}$ protons on target, a single candidate event consistent with background expectations was found. This allows to derive an upper limit on the mixing strength between the heavy neutrino and the tau neutrino in the \nus mass range from 10 to 190 $\rm MeV$. Windows between the SN1987a and Big Bang Nucleosynthesis lower limits and our result are still open for future experimental searches. The results obtained are used to constrain an interpretation of the time anomaly observed in the KARMEN1 detector.\Comment: 20 pages, 7 figures, a few comments adde

Genome-Wide Association Reveals Pigmentation Genes Play a Role in Skin Aging

Loss of fine skin patterning is a sign of both aging and photoaging. Studies investigating the genetic contribution to skin patterning offer an opportunity to better understand a trait that influences both physical appearance and risk of keratinocyte skin cancer. We undertook a meta-analysis of genome-wide association studies (GWAS) of a measure of skin pattern (microtopography score) damage in 1,671 twin pairs and 1,745 singletons (N = 5,087) drawn from three independent cohorts. We identified that rs185146 near SLC45A2 is associated with a skin aging trait (p = 4.1 × 10-9); to our knowledge this is previously unreported. We also confirm previously identified loci, rs12203592 near IRF4 (p = 8.8 × 10-13), and rs4268748 near MC1R (p = 1.2 × 10-15). At all three loci we highlight putative functionally relevant SNPs. There are a number of red hair/low pigmentation alleles of MC1R; we found that together these MC1R alleles explained 4.1% of variance in skin pattern damage. We also show that skin aging and reported experience of sunburns was proportional to the degree of penetrance for red hair of alleles of MC1R. Our work has uncovered genetic contributions to skin aging and confirmed previous findings, showing that pigmentation is a critical determinate of skin aging

A Genome-Wide Association Study Identifies Novel Alleles Associated with Hair Color and Skin Pigmentation

We conducted a multi-stage genome-wide association study of natural hair color in more than 10,000 men and women of European ancestry from the United States and Australia. An initial analysis of 528,173 single nucleotide polymorphisms (SNPs) genotyped on 2,287 women identified IRF4 and SLC24A4 as loci highly associated with hair color, along with three other regions encompassing known pigmentation genes. We confirmed these associations in 7,028 individuals from three additional studies. Across these four studies, SLC24A4 rs12896399 and IRF4 rs12203592 showed strong associations with hair color, with p = 6.0×10−62 and p = 7.46×10−127, respectively. The IRF4 SNP was also associated with skin color (p = 6.2×10−14), eye color (p = 6.1×10−13), and skin tanning response to sunlight (p = 3.9×10−89). A multivariable analysis pooling data from the initial GWAS and an additional 1,440 individuals suggested that the association between rs12203592 and hair color was independent of rs1540771, a SNP between the IRF4 and EXOC2 genes previously found to be associated with hair color. After adjustment for rs12203592, the association between rs1540771 and hair color was not significant (p = 0.52). One variant in the MATP gene was associated with hair color. A variant in the HERC2 gene upstream of the OCA2 gene showed the strongest and independent association with hair color compared with other SNPs in this region, including three previously reported SNPs. The signals detected in a region around the MC1R gene were explained by MC1R red hair color alleles. Our results suggest that the IRF4 and SLC24A4 loci are associated with human hair color and skin pigmentation