169 research outputs found

    Determination of the star valency of a graph

    Get PDF
    AbstractThe star valency of a graph G is the minimum, over all star decompositions π, of the maximum number of elements in π incident with a vertex. The maximum average degree of G, denoted by dmax-ave(G), is the maximum average degree of all subgraphs of G. In this paper, we prove that the star valency of G is either ⌈dmax-ave(G)/2⌉ or ⌈dmax-ave(G)/2⌉+1, and provide a polynomial time algorithm for determining the star valency of a graph

    The Litsea genome and the evolution of the laurel family

    Get PDF
    The laurel family within the Magnoliids has attracted attentions owing to its scents, variable inflorescences, and controversial phylogenetic position. Here, we present a chromosome-level assembly of the Litsea cubeba genome, together with low-coverage genomic and transcriptomic data for many other Lauraceae. Phylogenomic analyses show phylogenetic discordance at the position of Magnoliids, suggesting incomplete lineage sorting during the divergence of monocots, eudicots, and Magnoliids. An ancient whole-genome duplication (WGD) event occurred just before the divergence of Laurales and Magnoliales; subsequently, independent WGDs occurred almost simultaneously in the three Lauralean lineages. The phylogenetic relationships within Lauraceae correspond to the divergence of inflorescences, as evidenced by the phylogeny of FUWA, a conserved gene involved in determining panicle architecture in Lauraceae. Monoterpene synthases responsible for production of specific volatile compounds in Lauraceae are functionally verified. Our work sheds light on the evolution of the Lauraceae, the genetic basis for floral evolution and specific scents

    Plasma cell subtypes analyzed using artificial intelligence algorithm for predicting biochemical recurrence, immune escape potential, and immunotherapy response of prostate cancer

    Get PDF
    BackgroundPlasma cells as an important component of immune microenvironment plays a crucial role in immune escape and are closely related to immune therapy response. However, its role for prostate cancer is rarely understood. In this study, we intend to investigate the value of a new plasma cell molecular subtype for predicting the biochemical recurrence, immune escape and immunotherapy response in prostate cancer.MethodsGene expression and clinicopathological data were collected from 481 prostate cancer patients in the Cancer Genome Atlas. Then, the immune characteristics of the patients were analyzed based on plasma cell infiltration fractions. The unsupervised clustering based machine learning algorithm was used to identify the molecular subtypes of the plasma cell. And the characteristic genes of plasma cell subtypes were screened out by three types of machine learning models to establish an artificial neural network for predicting plasma cell subtypes. Finally, the prediction artificial neural network of plasma cell infiltration subtypes was validated in an independent cohort of 449 prostate cancer patients from the Gene Expression Omnibus.ResultsThe plasma cell fraction in prostate cancer was significantly decreased in tumors with high T stage, high Gleason score and lymph node metastasis. In addition, low plasma cell fraction patients had a higher risk of biochemical recurrence. Based on the differential genes of plasma cells, plasma cell infiltration status of PCa patients were divided into two independent molecular subtypes(subtype 1 and subtype 2). Subtype 1 tends to be immunosuppressive plasma cells infiltrating to the PCa region, with a higher likelihood of biochemical recurrence, more active immune microenvironment, and stronger immune escape potential, leading to a poor response to immunotherapy. Subsequently, 10 characteristic genes of plasma cell subtype were screened out by three machine learning algorithms. Finally, an artificial neural network was constructed by those 10 genes to predict the plasma cell subtype of new patients. This artificial neural network was validated in an independent validation set, and the similar results were gained.ConclusionsPlasma cell infiltration subtypes could provide a potent prognostic predictor for prostate cancer and be an option for potential responders to prostate cancer immunotherapy

    Вихретоковый анизотропный термоэлектрический первичный преобразователь лучистого потока

    Get PDF
    Представлена оригинальная конструкция первичного преобразователя лучистого потока, который может служить основой для создания приемника неселективного излучения с повышенной чувствительностью

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

    No full text
    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    CALCULATION METHOD IMPROVEMENT FOR CONTACT FATIGUE RELIABILITY OF CYLINDRICAL HELICAL GEAR

    No full text
    Reliability and fuzzy theory was applied to analyze the contact fatigue reliability of cylindrical helical gear. Furthermore, the calculation method has been improved. The reliability for contact fatigue of cylindrical helical gear after working a period of time was obtained used Matlab as a tool for numerical simulation and it has been compared with the results based on general approaches. The result shows that the improved method is more comprehensive consideration than general methods. Moreover, it provides a reference for reliability calculation of the gear
    corecore