The effect of Helicobacter pylori infection and eradication in patients with gastro-oesophageal reflux disease: A parallel-group, double-blind, placebo-controlled multicentre study

Objectives: This study aimed to resolve controversy regarding the effects of Helicobacter pylori eradication therapy and H. pylori infection in gastro-oesophageal reflux disease. Design: A randomized, double-blind, multicentre trial was performed in patients presenting with reflux symptoms. H. pylori-positive patients were randomized to receive either antibiotics or placebo for 7 days. H. pylori-negative patient controls received placebo. All received esomeprazole 20 mg b.d. for 7 days, followed by 40 mg o.d. to complete an 8-week course, and were followed up for 32 weeks by telephone. Results: In this study, 198/589 (34%) patients were H. pylori-positive and 113 H. pylori-negative patients served as controls. Baseline endoscopy revealed 63% Los Angeles grade 0A and 37% Los Angeles grade BCD oesophagitis with no difference between patient groups. Symptom improvement on esomeprazole was seen in 89%. H. pylori eradication was successful in 82%. H. pylori eradication had no effect on symptomatic relapse (hazard ratio 1.15, 95% CI 0.74–1.8; p = 0.5). Overall, H. pylori-positive patients had a lower probability of relapse compared to H. pylori-negative controls (hazard ratio 0.6, 95% CI 0.43–0.85; p = 0.004). Relapse hazard was modulated also by oesophagitis grade (BCD vs. 0A, hazard ratio 2.1, 95% CI 1.5–3.0). Conclusion: Relapse of gastro-oesophageal reflux disease symptoms after a course of high dose acid suppression took longer for H. pylori-positive patients than H. pylori-negative controls; however eradication therapy had no effect on the risk of relapse; ClincialTrials.gov number, NCT00574925

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

High resolution array-CGH analysis of single cells

Heterogeneity in the genome copy number of tissues is of particular importance in solid tumor biology. Furthermore, many clinical applications such as pre-implantation and non-invasive prenatal diagnosis would benefit from the ability to characterize individual single cells. As the amount of DNA from single cells is so small, several PCR protocols have been developed in an attempt to achieve unbiased amplification. Many of these approaches are suitable for subsequent cytogenetic analyses using conventional methodologies such as comparative genomic hybridization (CGH) to metaphase spreads. However, attempts to harness array-CGH for single-cell analysis to provide improved resolution have been disappointing. Here we describe a strategy that combines single-cell amplification using GenomePlex library technology (GenomePlex(®) Single Cell Whole Genome Amplification Kit, Sigma-Aldrich, UK) and detailed analysis of genomic copy number changes by high-resolution array-CGH. We show that single copy changes as small as 8.3 Mb in single cells are detected reliably with single cells derived from various tumor cell lines as well as patients presenting with trisomy 21 and Prader–Willi syndrome. Our results demonstrate the potential of this technology for studies of tumor biology and for clinical diagnostics

Quantitative Bias in Illumina TruSeq and a Novel Post Amplification Barcoding Strategy for Multiplexed DNA and Small RNA Deep Sequencing

Here we demonstrate a method for unbiased multiplexed deep sequencing of RNA and DNA libraries using a novel, efficient and adaptable barcoding strategy called Post Amplification Ligation-Mediated (PALM). PALM barcoding is performed as the very last step of library preparation, eliminating a potential barcode-induced bias and allowing the flexibility to synthesize as many barcodes as needed. We sequenced PALM barcoded micro RNA (miRNA) and DNA reference samples and evaluated the quantitative barcode-induced bias in comparison to the same reference samples prepared using the Illumina TruSeq barcoding strategy. The Illumina TruSeq small RNA strategy introduces the barcode during the PCR step using differentially barcoded primers, while the TruSeq DNA strategy introduces the barcode before the PCR step by ligation of differentially barcoded adaptors. Results show virtually no bias between the differentially barcoded miRNA and DNA samples, both for the PALM and the TruSeq sample preparation methods. We also multiplexed miRNA reference samples using a pre-PCR barcode ligation. This barcoding strategy results in significant bias

An adolescent with both Wegener's Granulomatosis and chronic blastomycosis

We report a case of Wegener's Granulomatosis (WG) associated with blastomycosis. This appears to be the first case report of WG co-existing with a tissue proven blastomycosis infection. The temporal correlation of the two conditions suggests that blastomycosis infection (and therefore possibly other fungal infections), may trigger the systemic granulomatous vasculitis in a predisposed individual; a provocative supposition warranting further study

Laser capture microdissection in forensic research: a review

In forensic sciences, short tandem repeat (STR) analysis has become the prime tool for DNA-based identification of the donor(s) of biological stains and/or traces. Many traces, however, contain cells and, hence, DNA, from more than a single individual, giving rise to mixed genotypes and the subsequent difficulties in interpreting the results. An even more challenging situation occurs when cells of a victim are much more abundant than the cells of the perpetrator. Therefore, the forensic community seeks to improve cell-separation methods in order to generate single-donor cell populations from a mixed trace in order to facilitate DNA typing and identification. Laser capture microdissection (LCM) offers a valuable tool for precise separation of specific cells. This review summarises all possible forensic applications of LCM, gives an overview of the staining and detection options, including automated detection and retrieval of cells of interest, and reviews the DNA extraction protocols compatible with LCM of cells from forensic samples