1,046 research outputs found

    Fast, scalable, Bayesian spike identification for multi-electrode arrays

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    We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes overlap, and accounts for intrinsic variability of spikes from each unit. As MEAs grow larger, it is important to find spike-identification methods that are scalable, that is, the computational cost of spike fitting should scale well with the number of units observed. Our algorithm accomplishes this goal, and is fast, because it exploits the spatial locality of each unit and the basic biophysics of extracellular signal propagation. Human intervention is minimized and streamlined via a graphical interface. We illustrate our method on data from a mammalian retina preparation and document its performance on simulated data consisting of spikes added to experimentally measured background noise. The algorithm is highly accurate

    A high-quality bonobo genome refines the analysis of hominid evolution

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    The divergence of chimpanzee and bonobo provides one of the few examples of recent hominid speciation1,2. Here we describe a fully annotated, high-quality bonobo genome assembly, which was constructed without guidance from reference genomes by applying a multiplatform genomics approach. We generate a bonobo genome assembly in which more than 98% of genes are completely annotated and 99% of the gaps are closed, including the resolution of about half of the segmental duplications and almost all of the full-length mobile elements. We compare the bonobo genome to those of other great apes1,3,4,5 and identify more than 5,569 fixed structural variants that specifically distinguish the bonobo and chimpanzee lineages. We focus on genes that have been lost, changed in structure or expanded in the last few million years of bonobo evolution. We produce a high-resolution map of incomplete lineage sorting and estimate that around 5.1% of the human genome is genetically closer to chimpanzee or bonobo and that more than 36.5% of the genome shows incomplete lineage sorting if we consider a deeper phylogeny including gorilla and orangutan. We also show that 26% of the segments of incomplete lineage sorting between human and chimpanzee or human and bonobo are non-randomly distributed and that genes within these clustered segments show significant excess of amino acid replacement compared to the rest of the genome

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Evolution of Thermally Pulsing Asymptotic Giant Branch Stars V: Constraining the Mass Loss and Lifetimes of Intermediate Mass, Low Metallicity AGB Stars

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    Thermally pulsing asymptotic giant branch (TP-AGB) stars are relatively short lived (less than a few Myr), yet their cool effective temperatures, high luminosities, efficient mass loss, and dust production can dramatically affect the chemical enrichment histories and the spectral energy distributions of their host galaxies. The ability to accurately model TP-AGB stars is critical to the interpretation of the integrated light of distant galaxies, especially in redder wavelengths. We continue previous efforts to constrain the evolution and lifetimes of TP-AGB stars by modeling their underlying stellar populations. Using Hubble Space Telescope (HST) optical and near-infrared photometry taken of 12 fields of 10 nearby galaxies imaged via the Advanced Camera for Surveys Nearby Galaxy Survey Treasury and the near-infrared HST/SNAP follow-up campaign, we compare the model and observed TP-AGB luminosity functions as well as the ratio of TP-AGB to red giant branch stars. We confirm the best-fitting mass-loss prescription, introduced by Rosenfield et al., in which two different wind regimes are active during the TP-AGB, significantly improves models of many galaxies that show evidence of recent star formation. This study extends previous efforts to constrain TP-AGB lifetimes to metallicities ranging -1.59 less than or similar to [Fe/H] <= -0.56 and initial TP-AGB masses up to similar to 4 M-circle dot, which include TP-AGB stars that undergo hot-bottom burning. \ua9 2016. The American Astronomical Society. All rights reserved

    Identification of a sex-linked SNP marker in the salmon louse (Lepeophtheirus salmonis) using RAD sequencing

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    The salmon louse (Lepeophtheirus salmonis (Krøyer, 1837)) is a parasitic copepod that can, if untreated, cause considerable damage to Atlantic salmon (Salmo salar Linnaeus, 1758) and incurs significant costs to the Atlantic salmon mariculture industry. Salmon lice are gonochoristic and normally show sex ratios close to 1:1. While this observation suggests that sex determination in salmon lice is genetic, with only minor environmental influences, the mechanism of sex determination in the salmon louse is unknown. This paper describes the identification of a sex-linked Single Nucleotide Polymorphism (SNP) marker, providing the first evidence for a genetic mechanism of sex determination in the salmon louse. Restriction site-associated DNA sequencing (RAD-seq) was used to isolate SNP markers in a laboratory-maintained salmon louse strain. A total of 85 million raw Illumina 100 base paired-end reads produced 281,838 unique RAD-tags across 24 unrelated individuals. RAD marker Lsa101901 showed complete association with phenotypic sex for all individuals analysed, being heterozygous in females and homozygous in males. Using an allele-specific PCR assay for genotyping, this SNP association pattern was further confirmed for three unrelated salmon louse strains, displaying complete association with phenotypic sex in a total of 96 genotyped individuals. The marker Lsa101901 was located in the coding region of the prohibitin-2 gene, which showed a sex-dependent differential expression, with mRNA levels determined by RT-qPCR about 1.8-fold higher in adult female than adult male salmon lice. This study's observations of a novel sex-linked SNP marker are consistent with sex determination in the salmon louse being genetic and following a female heterozygous system. Marker Lsa101901 provides a tool to determine the genetic sex of salmon lice, and could be useful in the development of control strategies

    Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

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    The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales

    Real-world data using mHealth apps in rhinitis, rhinosinusitis and their multimorbidities

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    Digital health is an umbrella term which encompasses eHealth and benefits from areas such as advanced computer sciences. eHealth includes mHealth apps, which offer the potential to redesign aspects of healthcare delivery. The capacity of apps to collect large amounts of longitudinal, real-time, real-world data enables the progression of biomedical knowledge. Apps for rhinitis and rhinosinusitis were searched for in the Google Play and Apple App stores, via an automatic market research tool recently developed using JavaScript. Over 1500 apps for allergic rhinitis and rhinosinusitis were identified, some dealing with multimorbidity. However, only six apps for rhinitis (AirRater, AllergyMonitor, AllerSearch, Husteblume, MASK-air and Pollen App) and one for rhinosinusitis (Galenus Health) have so far published results in the scientific literature. These apps were reviewed for their validation, discovery of novel allergy phenotypes, optimisation of identifying the pollen season, novel approaches in diagnosis and management (pharmacotherapy and allergen immunotherapy) as well as adherence to treatment. Published evidence demonstrates the potential of mobile health apps to advance in the characterisation, diagnosis and management of rhinitis and rhinosinusitis patients.Peer reviewe

    The ARIA-MASK-air® approach

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    Funding Information: The authors thank Ms Véronique Pretschner for submitting the paper. MASK‐air has been supported by Charité Universitätsmedizin Berlin, EU grants (EU Structural and Development Funds Languedoc Roussillon and Region PACA; POLLAR: EIT Health; Twinning: EIP on AHA; Twinning DHE: H2020; Catalyse: Horizon Europe) and educational grants from Mylan‐Viatris, ALK, GSK, Novartis, Stallergènes‐Greer and Uriach. None for the study. ® Publisher Copyright: © 2023 The Authors. Clinical and Translational Allergy published by John Wiley & Sons Ltd on behalf of European Academy of Allergy and Clinical Immunology.MASK-air®, a validated mHealth app (Medical Device regulation Class IIa) has enabled large observational implementation studies in over 58,000 people with allergic rhinitis and/or asthma. It can help to address unmet patient needs in rhinitis and asthma care. MASK-air® is a Good Practice of DG Santé on digitally-enabled, patient-centred care. It is also a candidate Good Practice of OECD (Organisation for Economic Co-operation and Development). MASK-air® data has enabled novel phenotype discovery and characterisation, as well as novel insights into the management of allergic rhinitis. MASK-air® data show that most rhinitis patients (i) are not adherent and do not follow guidelines, (ii) use as-needed treatment, (iii) do not take medication when they are well, (iv) increase their treatment based on symptoms and (v) do not use the recommended treatment. The data also show that control (symptoms, work productivity, educational performance) is not always improved by medications. A combined symptom-medication score (ARIA-EAACI-CSMS) has been validated for clinical practice and trials. The implications of the novel MASK-air® results should lead to change management in rhinitis and asthma.publishersversionpublishe
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