Practical dynamic de Bruijn graphs.

Motivation: The de Bruijn graph is fundamental to the analysis of next generation sequencing data and so, as datasets of DNA reads grow rapidly, it becomes more important to represent de Bruijn graphs compactly while still supporting fast assembly. Previous implementations of compact de Bruijn graphs have not supported node or edge deletion, however, which is important for pruning spurious elements from the graph.

Results: Belazzougui et al.

Smoking and common mental disorders in patients with chronic conditions: An analysis of data collected via a web-based screening system.

Objective: Smoking is the largest preventable cause of death and disability in the UK and remains pervasive in people with mental disorders and in general hospital patients. We aimed to quantify the prevalence of mental disorders and smoking, examining associations between mental disorders and smoking in patients with chronic physical conditions.

Method: Data were collected via routine screening systems implemented across two London NHS Foundation Trusts.

A waste walk through clinical pharmacy: how do the 'seven wastes' of Lean techniques apply to the practice of clinical pharmacists.

Aims And Objectives: This study used a 'Lean' technique, the 'waste walk' to evaluate the activities of clinical pharmacists with reference to the seven wastes described in 'Lean' including 'defects', 'unnecessary motion', 'overproduction', 'transport of products or material', 'unnecessary waiting', 'unnecessary inventory' and 'inappropriate processing'. The objectives of the study were to categorise the activities of ward-based clinical pharmacists into waste and non-waste, provide detail around what constitutes waste activity and quantify the proportion of time attributed to each category.

Setting: This study was carried out in a district general hospital in the North West of England.