Whole-genome sequencing of chronic lymphocytic leukemia identifies subgroups with distinct biological and clinical features

The value of genome-wide over targeted driver analyses for predicting clinical outcomes of cancer patients is debated. Here, we report the whole-genome sequencing of 485 chronic lymphocytic leukemia patients enrolled in clinical trials as part of the United Kingdom's 100,000 Genomes Project. We identify an extended catalog of recurrent coding and noncoding genetic mutations that represents a source for future studies and provide the most complete high-resolution map of structural variants, copy number changes and global genome features including telomere length, mutational signatures and genomic complexity. We demonstrate the relationship of these features with clinical outcome and show that integration of 186 distinct recurrent genomic alterations defines five genomic subgroups that associate with response to therapy, refining conventional outcome prediction. While requiring independent validation, our findings highlight the potential of whole-genome sequencing to inform future risk stratification in chronic lymphocytic leukemia

Quinuclidine derivatives binding to mucarinic M3 receptors

Preparation of quinuclidine salts for the treatment of diseases mediated by the muscarinic M3 receptor

Quinuclidine derivatives binding to mucarinic M3 receptors

Preparation of quinuclidine salts for the treatment of diseases mediated by the muscarinic M3 receptor

Utility, feasibility, and socio-demographic considerations in the diagnosis of bacterial respiratory tract infections by GC-IMS breath analysis

Diagnosis of respiratory tract infections, especially in primary care, is typically made on clinical features and in the absence of quick and reliable diagnostic tests. Even in secondary care, where diagnostic microbiology facilities are available, these tests take 24-48 hours to provide an indication of the aetiology. This multicentre study used a portable Gas Chromatography-Ion Mobility Spectrometer for the diagnosis of bacterial RTIs. Breath samples taken from 570 participants with 149 clinically validated bacterial and 421 non-bacterial respiratory tract infections were analysed to distinguish bacterial from non-bacterial RTIs. Through the integration of a sparse logistic regression model, we identified a moderate diagnostic accuracy of 0.73 (95% CI 0·69, 0·77) alongside a sensitivity of 0·85 (95% CI 0·79, 0·91) and a specificity of 0·55 (95% CI 0·50, 0·60). The GC-IMS diagnostic device provides a promising outlook in distinguishing bacterial from non-bacterial respiratory tract infections and was also favourably viewed by participants