Long-Term Cognitive Decline After Newly Diagnosed Heart Failure: Longitudinal Analysis in the CHS (Cardiovascular Health Study).

Background: Heart failure (HF) is associated with cognitive impairment. However, we know little about the time course of cognitive change after HF diagnosis, the importance of comorbid atrial fibrillation, or the role of ejection fraction. We sought to determine the associations of incident HF with rates of cognitive decline and whether these differed by atrial fibrillation status or reduced versus preserved ejection fraction.

Estimation of sequencing error rates in short reads.

Background: Short-read data from next-generation sequencing technologies are now being generated across a range of research projects. The fidelity of this data can be affected by several factors and it is important to have simple and reliable approaches for monitoring it at the level of individual experiments.

Results: We developed a fast, scalable and accurate approach to estimating error rates in short reads, which has the added advantage of not requiring a reference genome.

A review of orbital and intracranial magnetic resonance imaging in 79 canine and 13 feline patients (2004-2010).

Objective: To review the distribution of orbital and intracranial disease in canine and feline patients undergoing magnetic resonance imaging (MRI) following referral to a veterinary ophthalmologist and to correlate results of MRI with pathologic conditions including neoplasia, suspected optic neuritis (ON) and orbital cellulitis. Recognized and emerging imaging techniques are reviewed.

Procedure: Medical records of 79 canine and 13 feline patients were reviewed.

A simulation-based approach for evaluating microarray analyses.

The biological complexity of gene expression makes simulation of gene expression data difficult. We propose a spike-in simulation that adds a single simulated gene to the data set of interest. Features of this spike-in gene may be manipulated to observe how often the spiked-in gene appears in the list of differentially expressed genes.

Improved statistical tests for differential gene expression by shrinking variance components estimates.

Combining information across genes in the statistical analysis of microarray data is desirable because of the relatively small number of data points obtained for each individual gene. Here we develop an estimator of the error variance that can borrow information across genes using the James-Stein shrinkage concept. A new test statistic (FS) is constructed using this estimator.

Proteotypic classification of spontaneous and transgenic mammary neoplasms.

Introduction: Mammary tumors in mice are categorized by using morphologic and architectural criteria. Immunolabeling for terminal differentiation markers was compared among a variety of mouse mammary neoplasms because expression of terminal differentiation markers, and especially of keratins, provides important information on the origin of neoplastic cells and their degree of differentiation.

Methods: Expression patterns for terminal differentiation markers were used to characterize tumor types and to study tumor progression in transgenic mouse models of mammary neoplasia (mice overexpressing Neu (Erbb2), Hras, Myc, Notch4, SV40-TAg, Tgfa, and Wnt1), in spontaneous mammary carcinomas, and in mammary neoplasms associated with infection by the mouse mammary tumor virus (MMTV).

A postgenomic method for predicting essential genes at subsaturation levels of mutagenesis: application to Mycobacterium tuberculosis.

We describe a postgenomic in silico approach for identifying genes that are likely to be essential and estimate their proportion in haploid genomes. With the knowledge of all sites eligible for mutagenesis and an experimentally determined partial list of nonessential genes from genome mutagenesis, a Bayesian statistical method provides reasonable predictions of essential genes with a subsaturation level of random mutagenesis. For mutagenesis, a transposon such as Himar1 is suitable as it inserts randomly into TA sites.

Relationships and differentially expressed genes among pancreatic cancers examined by large-scale serial analysis of gene expression.

Pancreatic adenocarcinoma is among the most fatal of cancers, in part because of late diagnosis and a lack of effective therapies. Comprehensive studies are needed to better understand and address the cellular mechanisms and pathways of tumorigenesis. Serial analysis of gene expression was used to analyze gene expression profiles of pancreatic cancer cell lines, short-term cultures of normal pancreatic ductal epithelium, and primary pancreatic cancer tissue.