72 research outputs found

    Scalable Sparse Cox's Regression for Large-Scale Survival Data via Broken Adaptive Ridge

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    This paper develops a new scalable sparse Cox regression tool for sparse high-dimensional massive sample size (sHDMSS) survival data. The method is a local L0L_0-penalized Cox regression via repeatedly performing reweighted L2L_2-penalized Cox regression. We show that the resulting estimator enjoys the best of L0L_0- and L2L_2-penalized Cox regressions while overcoming their limitations. Specifically, the estimator is selection consistent, oracle for parameter estimation, and possesses a grouping property for highly correlated covariates. Simulation results suggest that when the sample size is large, the proposed method with pre-specified tuning parameters has a comparable or better performance than some popular penalized regression methods. More importantly, because the method naturally enables adaptation of efficient algorithms for massive L2L_2-penalized optimization and does not require costly data driven tuning parameter selection, it has a significant computational advantage for sHDMSS data, offering an average of 5-fold speedup over its closest competitor in empirical studies

    Pore-scale Modeling of Viscous Flow and Induced Forces in Dense Sphere Packings

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    We propose a method for effectively upscaling incompressible viscous flow in large random polydispersed sphere packings: the emphasis of this method is on the determination of the forces applied on the solid particles by the fluid. Pore bodies and their connections are defined locally through a regular Delaunay triangulation of the packings. Viscous flow equations are upscaled at the pore level, and approximated with a finite volume numerical scheme. We compare numerical simulations of the proposed method to detailed finite element (FEM) simulations of the Stokes equations for assemblies of 8 to 200 spheres. A good agreement is found both in terms of forces exerted on the solid particles and effective permeability coefficients

    Novel Cell- and Tissue-Based Assays for Detecting Misfolded and Aggregated Protein Accumulation Within Aggresomes and Inclusion Bodies

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    Aggresomes and related inclusion bodies appear to serve as storage depots for misfolded and aggregated proteins within cells, which can potentially be degraded by the autophagy pathway. A homogenous fluorescence-based assay was devised to detect aggregated proteins inside aggresomes and inclusion bodies within an authentic cellular context. The assay employs a novel red fluorescent molecular rotor dye, which is essentially nonfluorescent until it binds to structural features associated with the aggregated protein cargo. Aggresomes and related structures were generated within cultured cells using various potent, cell permeable, proteasome inhibitors: MG-132, lactacystin, epoxomicin and bortezomib, and then selectively detected with the fluorescent probe. Employing the probe in combination with various fluorescein-labeled primary antibodies facilitated co-localization of key components of the autophagy system (ubiquitin, p62, and LC3) with aggregated protein cargo by fluorescence microscopy. Furthermore, cytoplasmic aggregates were highlighted in SK-N-SH human neuroblastoma cells incubated with exogenously supplied amyloid beta peptide 1–42. SMER28, a small molecule modulator of autophagy acting via an mTOR-independent mechanism, prevented the accumulation of amyloid beta peptide within these cells. The described assay allows assessment of the effects of protein aggregation directly in cells, without resorting to the use of non-physiological protein mutations or genetically engineered cell lines. With minor modification, the assay was also adapted to the analysis of frozen or formalin-fixed, paraffin-embedded tissue sections, with demonstration of co-localization of aggregated cargo with β-amyloid and tau proteins in brain tissue sections from Alzheimer’s disease patients

    Expression analysis of carbohydrate antigens in ductal carcinoma in situ of the breast by lectin histochemistry

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    <p>Abstract</p> <p>Background</p> <p>The number of breast cancer patients diagnosed with ductal carcinoma <it>in situ </it>(DCIS) continues to grow. Laboratory and clinical data indicate that DCIS can progress to invasive disease. Carbohydrate-mediated cell-cell adhesion and tumor-stroma interaction play crucial roles in tumorigenesis and tumor aggressive behavior. Breast carcinogenesis may reflect quantitative as well as qualitative changes in oligosaccharide expression, which may provide a useful tool for early detection of breast cancer. Because tumor-associated carbohydrate antigens (TACA) are implicated in tumor invasion and metastasis, the purpose of this study was to assess the expression of selected TACA by lectin histochemistry on DCIS specimens from the archival breast cancer tissue array bank of the University of Arkansas for Medical Sciences.</p> <p>Methods</p> <p>For detection of TACA expression, specimens were stained with <it>Griffonia simplicifolia </it>lectin-I (GS-I) and <it>Vicia vilosa </it>agglutinin (VVA). We studied associations of lectin reactivity with established prognostic factors, such as tumor size, tumor nuclear grade, and expression of Her-2/neu, p53 mutant and estrogen and progesterone receptors.</p> <p>Results</p> <p>We observed that both lectins showed significant associations with nuclear grade of DCIS. DCIS specimens with nuclear grades II and III showed significantly more intense reactivity than DCIS cases with nuclear grade I to GS-1 (Mean-score chi-square = 17.60, DF = 2; <it>P </it>= 0.0002) and VVA (Mean-score chi-square = 15.72, DF = 2; <it>P </it>= 0.0004).</p> <p>Conclusion</p> <p>The results suggest that the expression of VVA- and GS-I-reactive carbohydrate antigens may contribute to forming higher grade DCIS and increase the recurrence risk.</p

    Multiple Phenotypes in Adult Mice following Inactivation of the Coxsackievirus and Adenovirus Receptor (Car) Gene

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    To determine the normal function of the Coxsackievirus and Adenovirus Receptor (CAR), a protein found in tight junctions and other intercellular complexes, we constructed a mouse line in which the CAR gene could be disrupted at any chosen time point in a broad spectrum of cell types and tissues. All knockouts examined displayed a dilated intestinal tract and atrophy of the exocrine pancreas with appearance of tubular complexes characteristic of acinar-to-ductal metaplasia. The mice also exhibited a complete atrio-ventricular block and abnormal thymopoiesis. These results demonstrate that CAR exerts important functions in the physiology of several organs in vivo

    Contemporary management of cancer of the oral cavity

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    Oral cancer represents a common entity comprising a third of all head and neck malignant tumors. The options for curative treatment of oral cavity cancer have not changed significantly in the last three decades; however, the work up, the approach to surveillance, and the options for reconstruction have evolved significantly. Because of the profound functional and cosmetic importance of the oral cavity, management of oral cavity cancers requires a thorough understanding of disease progression, approaches to management and options for reconstruction. The purpose of this review is to discuss the most current management options for oral cavity cancers

    A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

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    Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Geneenvironment interactions (G x E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G x E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G x E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G x E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant GxBMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer

    The trans-ancestral genomic architecture of glycemic traits

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    Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe
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