60 research outputs found

    Unique DNA Repair Gene Variations and Potential Associations with the Primary Antibody Deficiency Syndromes IgAD and CVID

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    BACKGROUND: Despite considerable effort, the genetic factors responsible for >90% of the antibody deficiency syndromes IgAD and CVID remain elusive. To produce a functionally diverse antibody repertoire B lymphocytes undergo class switch recombination. This process is initiated by AID-catalyzed deamination of cytidine to uridine in switch region DNA. Subsequently, these residues are recognized by the uracil excision enzyme UNG2 or the mismatch repair proteins MutSalpha (MSH2/MSH6) and MutLalpha (PMS2/MLH1). Further processing by ubiquitous DNA repair factors is thought to introduce DNA breaks, ultimately leading to class switch recombination and expression of a different antibody isotype. METHODOLOGY/PRINCIPAL FINDINGS: Defects in AID and UNG2 have been shown to result in the primary immunodeficiency hyper-IgM syndrome, leading us to hypothesize that additional, potentially more subtle, DNA repair gene variations may underlie the clinically related antibody deficiencies syndromes IgAD and CVID. In a survey of twenty-seven candidate DNA metabolism genes, markers in MSH2, RAD50, and RAD52 were associated with IgAD/CVID, prompting further investigation into these pathways. Resequencing identified four rare, non-synonymous alleles associated with IgAD/CVID, two in MLH1, one in RAD50, and one in NBS1. One IgAD patient carried heterozygous non-synonymous mutations in MLH1, MSH2, and NBS1. Functional studies revealed that one of the identified mutations, a premature RAD50 stop codon (Q372X), confers increased sensitivity to ionizing radiation. CONCLUSIONS: Our results are consistent with a class switch recombination model in which AID-catalyzed uridines are processed by multiple DNA repair pathways. Genetic defects in these DNA repair pathways may contribute to IgAD and CVID

    Data-analysis strategies for image-based cell profiling

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    Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.Peer reviewe

    Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

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    Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability
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