B-nodes: a new scalable high level abstraction model

This paper proposes a new modeling technique called B-Nodes. B-Nodes represent a new, high-level abstraction that allows technical detail to be controlled using top-down recursive decomposition. This abstraction. is independent of architectural detail and can therefore accommodate rapid changes in technology. The use of recursive decomposition allows B-Nodes to be used not only for entire e-commerce system but also sub-modules within this system. The use of fundamental units allows the performance of heterogeneous technologies to be compared and other units to be derived. Results to date indicate no comparable model exists. Should further work validate this technique the authors recommend its use as a standard technique in information systems analysis and desig

A case for systems thinking and system dynamics

Systems thinking is a way of thinking that focuses on the relationships between the parts forming a purposeful whole. System dynamics is concerned with building computer models of complex problem situations and then experimenting with and studying the behaviour of these models over time. This paper is a review of systems thinking that considers its unique history and influences, paradigms and methodologies, and presents a case for the system dynamics methodology as the best tool for the most diverse range of problem situation

Perturbed myoepithelial cell differentiation in BRCA mutation carriers and in ductal carcinoma in situ.

Myoepithelial cells play key roles in normal mammary gland development and in limiting pre-invasive to invasive breast tumor progression, yet their differentiation and perturbation in ductal carcinoma in situ (DCIS) are poorly understood. Here, we investigated myoepithelial cells in normal breast tissues of BRCA1 and BRCA2 germline mutation carriers and in non-carrier controls, and in sporadic DCIS. We found that in the normal breast of non-carriers, myoepithelial cells frequently co-express the p63 and TCF7 transcription factors and that p63 and TCF7 show overlapping chromatin peaks associated with differentiated myoepithelium-specific genes. In contrast, in normal breast tissues of BRCA1 mutation carriers the frequency of p63+TCF7+ myoepithelial cells is significantly decreased and p63 and TCF7 chromatin peaks do not overlap. These myoepithelial perturbations in normal breast tissues of BRCA1 germline mutation carriers may play a role in their higher risk of breast cancer. The fraction of p63+TCF7+ myoepithelial cells is also significantly decreased in DCIS, which may be associated with invasive progression

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Spectrum of mutational signatures in T-cell lymphoma reveals a key role for UV radiation in cutaneous T-cell lymphoma

Funder: Galderma; doi: http://dx.doi.org/10.13039/501100009754Funder: NIHR-BRC Cambridge core grantFunder: National Institute for Health Research; doi: http://dx.doi.org/10.13039/501100000272Funder: NHS EnglandAbstract: T-cell non-Hodgkin’s lymphomas develop following transformation of tissue resident T-cells. We performed a meta-analysis of whole exome sequencing data from 403 patients with eight subtypes of T-cell non-Hodgkin’s lymphoma to identify mutational signatures and associated recurrent gene mutations. Signature 1, indicative of age-related deamination, was prevalent across all T-cell lymphomas, reflecting the derivation of these malignancies from memory T-cells. Adult T-cell leukemia-lymphoma was specifically associated with signature 17, which was found to correlate with the IRF4 K59R mutation that is exclusive to Adult T-cell leukemia-lymphoma. Signature 7, implicating UV exposure was uniquely identified in cutaneous T-cell lymphoma (CTCL), contributing 52% of the mutational burden in mycosis fungoides and 23% in Sezary syndrome. Importantly this UV signature was observed in CD4 + T-cells isolated from the blood of Sezary syndrome patients suggesting extensive re-circulation of these T-cells through skin and blood. Analysis of non-Hodgkin’s T-cell lymphoma cases submitted to the national 100,000 WGS project confirmed that signature 7 was only identified in CTCL strongly implicating UV radiation in the pathogenesis of cutaneous T-cell lymphoma

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

Associations of autozygosity with a broad range of human phenotypes

Abstract: In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding