An econometric analysis of the desktop computer hardware market

The purpose of this study was to compare six competing econometric models which depict the relationship between hardware characteristics and machine cost for the desktop computer market. The Box-Cox methodology and multiyear data were used to facilitate this comparison. The analysis validated that the Box-Cox methodology is a viable means for evaluating competing model formulations within the field of information systems research. The results were consistent with past research that suggested a double natural log model formulation for representing the functional relationships among variables when modeling machine cost as a function of hardware attributes. Further, the more complex power transformation model formulations suggested by the Box-Cox methodology did not significantly outperform the more traditional and simpler double natural log model. More specifically, the results indicated that variables related to primary memory and microchip tedinology have the largest impact on machine cost. Additionally, variables related to madiine connectivity, machine expandability, and year of observation were also found to be significant explanatory variables for machine cost

Modeling ATP-Binding Cassette G2 (ABCG2) Substrate Specificity

How well can we predict efflux by ATP-binding cassette G2? It is estimated that there will be about 1.6 million new cases of cancer and half a million cancer deaths in the US during 2015.ATP-binding cassette (ABC) efflux transporters such as ABCG2 are overexpressed in chemotherapy-resistant cancer cells. Anticancer drugs are prone to efflux by these transporters. Being able to identify drugs that are effluxed is of great interest in drug discovery.The current arsenal of methods used to detect efflux are not easily adaptable to high throughput formats and are limited in scope, making experimental analysis an expensive prospect. Hence, computational analysis of efflux is of interest. We accumulated a dataset of ABCG2 substrates and non-substrates which contains 179 substrates and 110 non-substrates. This dataset forms the basis for all studies reported herein. We attempted to identify descriptors capable of segregating substrates and non-substrates, ending up with Log P, Polar Volume, Atom Count, Radius of Gyration, Binding Energy, Length, and Width. They had significant differential distribution that could be used to build mathematical models to fulfil our goals. A statistical learning method that creates non-linear models called Support Vector Machine generated the best predictive models. This model demonstrated between 75-80% accuracy in identifying substrates and non-substrates. Importantly our model suggests mechanistic details of the efflux process; previous reports have suggested that Arg482 in ABCG2 is critical for transport of substrates. In conclusion, we were able to address efflux of chemotherapeutic agents by the ABCG2 efflux pump using a mathematical modeling approach.https://scholarscompass.vcu.edu/uresposters/1130/thumbnail.jp

Distinguishing different stages of Parkinson's disease using composite index of speed and pen-pressure of sketching a spiral

The speed and pen-pressure while sketching a spiral are lower among Parkinson's disease (PD) patients with higher severity of the disease. However, the correlation between these features and the severity level (SL) of PD has been reported to be 0.4. There is a need for identifying parameters with a stronger correlation for considering this for accurate diagnosis of the disease. This study has proposed the use of the Composite Index of Speed and Pen-pressure (CISP) of sketching as a feature for analyzing the severity of PD. A total of 28 control group (CG) and 27 PD patients (total 55 participants) were recruited and assessed for Unified Parkinson's Disease Rating Scale (UPDRS). They drew guided Archimedean spiral on an A3 sheet. Speed, pen-pressure, and CISP were computed and analyzed to obtain their correlation with severity of the disease. The correlation of speed, pen-pressure, and CISP with the severity of PD was -0.415, -0.584, and -0.641, respectively. Mann-Whitney U test confirmed that CISP was suitable to distinguish between PD and CG, while non-parametric k-sample Kruskal-Wallis test confirmed that it was significantly different for PD SL-1 and PD SL-3. This shows that CISP during spiral sketching may be used to differentiate between CG and PD and between PD SL-1 and PD SL-3 but not SL-2

Small Quadrupole Deformation for the Dipole Bands in 112In

High spin states in $^{112}$In were investigated using $^{100}$Mo($^{16}$O, p3n) reaction at 80 MeV. The excited level have been observed up to 5.6 MeV excitation energy and spin $\sim$ 20$\hbar$ with the level scheme showing three dipole bands. The polarization and lifetime measurements were carried out for the dipole bands. Tilted axis cranking model calculations were performed for different quasi-particle configurations of this doubly odd nucleus. Comparison of the calculations of the model with the B(M1) transition strengths of the positive and negative parity bands firmly established their configurations.Comment: 10 pages, 11 figures, 2 table

Retreatment with anti-EGFR based therapies in metastatic colorectal cancer: impact of intervening time interval and prior anti-EGFR response.

BackgroundThis retrospective study aims to investigate the activity of retreatment with anti-EGFR-based therapies in order to explore the concept of clonal evolution by evaluating the impact of prior activity and intervening time interval.MethodsEighty-nine KRAS exon 2-wild-type metastatic colorectal patients were retreated on phase I/II clinical trials containing anti-EGFR therapies after progressing on prior cetuximab or panitumumab. Response on prior anti-EGFR therapy was defined retrospectively per physician-records as response or stable disease ≥6 months. Multivariable statistical methods included a multiple logistic regression model for response, and Cox proportional hazards model for progression-free survival.ResultsRetreatment anti-EGFR agents were cetuximab (n = 76) or cetuximab plus erlotinib (n = 13). The median interval time between prior and retreatment regimens was 4.57 months (range: 0.46-58.7). Patients who responded to the prior cetuximab or panitumumab were more likely to obtain clinical benefit to the retreatment compared to the non-responders in both univariate (p = 0.007) and multivariate analyses (OR: 3.38, 95 % CI: 1.27, 9.31, p = 0.019). The clinical benefit rate on retreatment also showed a marginally significant association with interval time between the two anti-EGFR based therapies (p = 0.053). Median progression-free survival on retreatment was increased in prior responders (4.9 months, 95 % CI: 3.6, 6.2) compared to prior non-responders (2.5 months, 95 % CI, 1.58, 3.42) in univariate (p = 0.064) and multivariate analysis (HR: 0.70, 95 % CI: 0.43-1.15, p = 0.156).ConclusionOur data lends support to the concept of clonal evolution, though the clinical impact appears less robust than previously reported. Further work to determine which patients benefit from retreatment post progression is needed

Chromosome-wide mapping of DNA methylation patterns in normal and malignant prostate cells reveals pervasive methylation of gene-associated and conserved intergenic sequences

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background DNA methylation has been linked to genome regulation and dysregulation in health and disease respectively, and methods for characterizing genomic DNA methylation patterns are rapidly emerging. We have developed/refined methods for enrichment of methylated genomic fragments using the methyl-binding domain of the human MBD2 protein (MBD2-MBD) followed by analysis with high-density tiling microarrays. This MBD-chip approach was used to characterize DNA methylation patterns across all non-repetitive sequences of human chromosomes 21 and 22 at high-resolution in normal and malignant prostate cells. Results Examining this data using computational methods that were designed specifically for DNA methylation tiling array data revealed widespread methylation of both gene promoter and non-promoter regions in cancer and normal cells. In addition to identifying several novel cancer hypermethylated 5' gene upstream regions that mediated epigenetic gene silencing, we also found several hypermethylated 3' gene downstream, intragenic and intergenic regions. The hypermethylated intragenic regions were highly enriched for overlap with intron-exon boundaries, suggesting a possible role in regulation of alternative transcriptional start sites, exon usage and/or splicing. The hypermethylated intergenic regions showed significant enrichment for conservation across vertebrate species. A sampling of these newly identified promoter (ADAMTS1 and SCARF2 genes) and non-promoter (downstream or within DSCR9, C21orf57 and HLCS genes) hypermethylated regions were effective in distinguishing malignant from normal prostate tissues and/or cell lines. Conclusions Comparison of chromosome-wide DNA methylation patterns in normal and malignant prostate cells revealed significant methylation of gene-proximal and conserved intergenic sequences. Such analyses can be easily extended for genome-wide methylation analysis in health and disease.Published versio

Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription.

DNA sequence variation has been associated with quantitative changes in molecular phenotypes such as gene expression, but its impact on chromatin states is poorly characterized. To understand the interplay between chromatin and genetic control of gene regulation, we quantified allelic variability in transcription factor binding, histone modifications, and gene expression within humans. We found abundant allelic specificity in chromatin and extensive local, short-range, and long-range allelic coordination among the studied molecular phenotypes. We observed genetic influence on most of these phenotypes, with histone modifications exhibiting strong context-dependent behavior. Our results implicate transcription factors as primary mediators of sequence-specific regulation of gene expression programs, with histone modifications frequently reflecting the primary regulatory event

An Active Learning Approach for Rapid Characterization of Endothelial Cells in Human Tumors

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers