125 research outputs found

    Fueling of a marine-terrestrial ecosystem by a major seabird colony

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    Seabirds redistribute nutrients between different ecosystem compartments and over vast geographical areas. This nutrient transfer may impact both local ecosystems on seabird breeding islands and regional biogeochemical cycling, but these processes are seldom considered in local conservation plans or biogeochemical models. The island of Stora Karlso in the Baltic Sea hosts the largest concentration of piscivorous seabirds in the region, and also hosts a large colony of insectivorous House martins Delichon urbicum adjacent to the breeding seabirds. We show that a previously reported unusually high insectivore abundance was explained by large amounts of chironomids-highly enriched in delta N-15-that feed on seabird residues as larvae along rocky shores to eventually emerge as flying adults. Benthic ammonium and phosphate fluxes were up to 163% and 153% higher close to the colony (1,300 m distance) than further away (2,700 m) and the estimated nutrient release from the seabirds at were in the same order of magnitude as the loads from the largest waste-water treatment plants in the region. The trophic cascade impacting insectivorous passerines and the substantial redistribution of nutrients suggest that seabird nutrient transfer should be increasingly considered in local conservation plans and regional nutrient cycling models.Peer reviewe

    Seabird surveillance: combining CCTV and artificial intelligence for monitoring and research

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    Ecological research and monitoring need to be able to rapidly convey information that can form the basis of scientifically sound management. Automated sensor systems, especially if combined with artificial intelligence, can contribute to such rapid high-resolution data retrieval. Here, we explore the prospects of automated methods to generate insights for seabirds, which are often monitored for their high conservation value and for being sentinels for marine ecosystem changes. We have developed a system of video surveillance combined with automated image processing, which we apply to common murres Uria aalge. The system uses a deep learning algorithm for object detection (YOLOv5) that has been trained on annotated images of adult birds, chicks and eggs, and outputs time, location, size and confidence level of all detections, frame-by-frame, in the supplied video material. A total of 144 million bird detections were generated from a breeding cliff over three complete breeding seasons (2019–2021). We demonstrate how object detection can be used to accurately monitor breeding phenology and chick growth. Our automated monitoring approach can also identify and quantify rare events that are easily missed in traditional monitoring, such as disturbances from predators. Further, combining automated video analysis with continuous measurements from a temperature logger allows us to study impacts of heat waves on nest attendance in high detail. Our automated system thus produces comparable, and in several cases significantly more detailed, data than those generated from observational field studies. By running in real time on the camera streams, it has the potential to supply researchers and managers with high-resolution up-to-date information on seabird population status. We describe how the system can be modified to fit various types of ecological research and monitoring goals and thereby provide up-to-date support for conservation and ecosystem management

    Bi-allelic variants in RNF170 are associated with hereditary spastic paraplegia.

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    Alterations of Ca2+ homeostasis have been implicated in a wide range of neurodegenerative diseases. Ca2+ efflux from the endoplasmic reticulum into the cytoplasm is controlled by binding of inositol 1,4,5-trisphosphate to its receptor. Activated inositol 1,4,5-trisphosphate receptors are then rapidly degraded by the endoplasmic reticulum-associated degradation pathway. Mutations in genes encoding the neuronal isoform of the inositol 1,4,5-trisphosphate receptor (ITPR1) and genes involved in inositol 1,4,5-trisphosphate receptor degradation (ERLIN1, ERLIN2) are known to cause hereditary spastic paraplegia (HSP) and cerebellar ataxia. We provide evidence that mutations in the ubiquitin E3 ligase gene RNF170, which targets inositol 1,4,5-trisphosphate receptors for degradation, are the likely cause of autosomal recessive HSP in four unrelated families and functionally evaluate the consequences of mutations in patient fibroblasts, mutant SH-SY5Y cells and by gene knockdown in zebrafish. Our findings highlight inositol 1,4,5-trisphosphate signaling as a candidate key pathway for hereditary spastic paraplegias and cerebellar ataxias and thus prioritize this pathway for therapeutic interventions

    RAB32 Ser71Arg in autosomal dominant Parkinson's disease:linkage, association, and functional analyses

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    BACKGROUND: Parkinson's disease is a progressive neurodegenerative disorder with multifactorial causes, among which genetic risk factors play a part. The RAB GTPases are regulators and substrates of LRRK2, and variants in the LRRK2 gene are important risk factors for Parkinson's disease. We aimed to explore genetic variability in RAB GTPases within cases of familial Parkinson's disease.METHODS: We did whole-exome sequencing in probands from families in Canada and Tunisia with Parkinson's disease without a genetic cause, who were recruited from the Centre for Applied Neurogenetics (Vancouver, BC, Canada), an international consortium that includes people with Parkinson's disease from 36 sites in 24 countries. 61 RAB GTPases were genetically screened, and candidate variants were genotyped in relatives of the probands to assess disease segregation by linkage analysis. Genotyping was also done to assess variant frequencies in individuals with idiopathic Parkinson's disease and controls, matched for age and sex, who were also from the Centre for Applied Neurogenetics but unrelated to the probands or each other. All participants were aged 18 years or older. The sequencing and genotyping findings were validated by case-control association analyses using bioinformatic data obtained from publicly available clinicogenomic databases (AMP-PD, GP2, and 100 000 Genomes Project) and a private German clinical diagnostic database (University of TĂŒbingen). Clinical and pathological findings were summarised and haplotypes were determined. In-vitro studies were done to investigate protein interactions and enzyme activities.FINDINGS: Between June 1, 2010, and May 31, 2017, 130 probands from Canada and Tunisia (47 [36%] female and 83 [64%] male; mean age 72·7 years [SD 11·7; range 38-96]; 109 White European ancestry, 18 north African, two east Asian, and one Hispanic] underwent whole-exome sequencing. 15 variants in RAB GTPase genes were identified, of which the RAB32 variant c.213C&gt;G (Ser71Arg) cosegregated with autosomal dominant Parkinson's disease in three families (nine affected individuals; non-parametric linkage Z score=1·95; p=0·03). 2604 unrelated individuals with Parkinson's disease and 344 matched controls were additionally genotyped, and five more people originating from five countries (Canada, Italy, Poland, Turkey, and Tunisia) were identified with the RAB32 variant. From the database searches, in which 6043 individuals with Parkinson's disease and 62 549 controls were included, another eight individuals were identified with the RAB32 variant from four countries (Canada, Germany, UK, and USA). Overall, the association of RAB32 c.213C&gt;G (Ser71Arg) with Parkinson's disease was significant (odds ratio [OR] 13·17, 95% CI 2·15-87·23; p=0·0055; I2=99·96%). In the people who had the variant, Parkinson's disease presented at age 54·6 years (SD 12·75, range 31-81, n=16), and two-thirds had a family history of parkinsonism. RAB32 Ser71Arg heterozygotes shared a common haplotype, although penetrance was incomplete. Findings in one individual at autopsy showed sparse neurofibrillary tangle pathology in the midbrain and thalamus, without Lewy body pathology. In functional studies, RAB32 Arg71 activated LRRK2 kinase to a level greater than RAB32 Ser71.INTERPRETATION: RAB32 Ser71Arg is a novel genetic risk factor for Parkinson's disease, with reduced penetrance. The variant was found in individuals with Parkinson's disease from multiple ethnic groups, with the same haplotype. In-vitro assays show that RAB32 Arg71 activates LRRK2 kinase, which indicates that genetically distinct causes of familial parkinsonism share the same mechanism. The discovery of RAB32 Ser71Arg also suggests several genetically inherited causes of Parkinson's disease originated to control intracellular immunity. This shared aetiology should be considered in future translational research, while the global epidemiology of RAB32 Ser71Arg needs to be assessed to inform genetic counselling.FUNDING: National Institutes of Health, the Canada Excellence Research Chairs program, Aligning Science Across Parkinson's, the Michael J Fox Foundation for Parkinson's Research, and the UK Medical Research Council.</p

    A multi-biometric iris recognition system based on a deep learning approach

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    YesMultimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, intra-class variability, non-universality, and vulnerability to spoofing. In this paper, an efficient and real-time multimodal biometric system is proposed based on building deep learning representations for images of both the right and left irises of a person, and fusing the results obtained using a ranking-level fusion method. The trained deep learning system proposed is called IrisConvNet whose architecture is based on a combination of Convolutional Neural Network (CNN) and Softmax classifier to extract discriminative features from the input image without any domain knowledge where the input image represents the localized iris region and then classify it into one of N classes. In this work, a discriminative CNN training scheme based on a combination of back-propagation algorithm and mini-batch AdaGrad optimization method is proposed for weights updating and learning rate adaptation, respectively. In addition, other training strategies (e.g., dropout method, data augmentation) are also proposed in order to evaluate different CNN architectures. The performance of the proposed system is tested on three public datasets collected under different conditions: SDUMLA-HMT, CASIA-Iris- V3 Interval and IITD iris databases. The results obtained from the proposed system outperform other state-of-the-art of approaches (e.g., Wavelet transform, Scattering transform, Local Binary Pattern and PCA) by achieving a Rank-1 identification rate of 100% on all the employed databases and a recognition time less than one second per person

    Embracing Monogenic Parkinson's Disease: The MJFF Global Genetic PD Cohort

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    Background: As gene-targeted therapies are increasingly being developed for Parkinson's disease (PD), identifying and characterizing carriers of specific genetic pathogenic variants is imperative. Only a small fraction of the estimated number of subjects with monogenic PD worldwide are currently represented in the literature and availability of clinical data and clinical trial-ready cohorts is limited. Objective: The objectives are to (1) establish an international cohort of affected and unaffected individuals with PD-linked variants; (2) provide harmonized and quality-controlled clinical characterization data for each included individual; and (3) further promote collaboration of researchers in the field of monogenic PD. Methods: We conducted a worldwide, systematic online survey to collect individual-level data on individuals with PD-linked variants in SNCA, LRRK2, VPS35, PRKN, PINK1, DJ-1, as well as selected pathogenic and risk variants in GBA and corresponding demographic, clinical, and genetic data. All registered cases underwent thorough quality checks, and pathogenicity scoring of the variants and genotype–phenotype relationships were analyzed. Results: We collected 3888 variant carriers for our analyses, reported by 92 centers (42 countries) worldwide. Of the included individuals, 3185 had a diagnosis of PD (ie, 1306 LRRK2, 115 SNCA, 23 VPS35, 429 PRKN, 75 PINK1, 13 DJ-1, and 1224 GBA) and 703 were unaffected (ie, 328 LRRK2, 32 SNCA, 3 VPS35, 1 PRKN, 1 PINK1, and 338 GBA). In total, we identified 269 different pathogenic variants; 1322 individuals in our cohort (34%) were indicated as not previously published. Conclusions: Within the MJFF Global Genetic PD Study Group, we (1) established the largest international cohort of affected and unaffected individuals carrying PD-linked variants; (2) provide harmonized and quality-controlled clinical and genetic data for each included individual; (3) promote collaboration in the field of genetic PD with a view toward clinical and genetic stratification of patients for gene-targeted clinical trials. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

    Using global team science to identify genetic parkinson's disease worldwide.

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    No abstract available

    Hydrogeochemical evolution of groundwater in a Quaternary sediment and Cretaceous sandstone unconfined aquifer in Northwestern China

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    A better understanding of the hydrogeochemical evolution of groundwater in vulnerable aquifers is important for the protection of water resources. To assess groundwater chemistry, groundwater sampling was performed from different representative aquifers in 2012–2013. A Piper trilinear diagram showed that the groundwater types can be classified into Na–SO4 and Na–Cl types. Only one groundwater sample was Na–HCO3 type. The dominant cations for all samples were Na+. However, the dominant anions varied from HCO3− to SO42−, and as well Cl−. The mean total dissolved solid (TDS) content of groundwater in the region was 1889 mg/L. Thus, only 20% of groundwater samples meet Chinese drinking water standards (< 1000 mg/L). Principal component analysis (PCA) combined with hierarchical cluster analysis (HCA) and self-organizing maps (SOM) were applied for the classification of the groundwater geochemistry. The three first principal components explained 58, 20, and 16% of the variance, respectively. The first component reflects sulfate minerals (gypsum, anhydrite) and halite dissolution, and/or evaporation in the shallow aquifer. The second and third components are interpreted as carbonate rock dissolution. The reason for two factors is that the different aquifers give rise to different degree of hydrogeochemical evolution (different travel distances and travel times). Identified clusters for evolution characteristic and influencing factors were confirmed by the PCA–HCA methods. Using information from eight ion components and SOM, formation mechanisms and influencing factors for the present groundwater quality were determined

    Analysis of DNM3 and VAMP4 as genetic modifiers of LRRK2 Parkinson's disease.

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    The LRRK2 gene has rare (p.G2019S) and common risk variants for Parkinson's disease (PD). DNM3 has previously been reported as a genetic modifier of the age at onset in PD patients carrying the LRRK2 p.G2019S mutation. We analyzed this effect in a new cohort of LRRK2 p.G2019S heterozygotes (n = 724) and meta-analyzed our data with previously published data (n = 754). VAMP4 is in close proximity to DNM3, and was associated with PD in a recent study, so it is possible that variants in this gene may be important. We also analyzed the effect of VAMP4 rs11578699 on LRRK2 penetrance. Our analysis of DNM3 in previously unpublished data does not show an effect on age at onset in LRRK2 p.G2019S carriers; however, the inter-study heterogeneity may indicate ethnic or population-specific effects of DNM3. There was no evidence for linkage disequilibrium between DNM3 and VAMP4. Analysis of sporadic patients stratified by the risk variant LRRK2 rs10878226 indicates a possible interaction between common variation in LRRK2 and VAMP4 in disease risk
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