PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data.

Although the majority of bacteria are harmless or even beneficial to their host, others are highly virulent and can cause serious diseases, and even death. Due to the constantly decreasing cost of high-throughput sequencing there are now many completely sequenced genomes available from both human pathogenic and innocuous strains. The data can be used to identify gene families that correlate with pathogenicity and to develop tools to predict the pathogenicity of newly sequenced strains, investigations that previously were mainly done by means of more expensive and time consuming experimental approaches. We describe PathogenFinde

Early influences on cardiovascular and renal development

The hypothesis that a developmental component plays a role in subsequent disease initially arose from epidemiological studies relating birth size to both risk factors for cardiovascular disease and actual cardiovascular disease prevalence in later life. The findings that small size at birth is associated with an increased risk of cardiovascular disease have led to concerns about the effect size and the causality of the associations. However, recent studies have overcome most methodological flaws and suggested small effect sizes for these associations for the individual, but an potential important effect size on a population level. Various mechanisms underlying these associations have been hypothesized, including fetal undernutrition, genetic susceptibility and postnatal accelerated growth. The specific adverse exposures in fetal and early postnatal life leading to cardiovascular disease in adult life are not yet fully understood. Current studies suggest that both environmental and genetic factors in various periods of life may underlie the complex associations of fetal growth retardation and low birth weight with cardiovascular disease in later life. To estimate the population effect size and to identify the underlying mechanisms, well-designed epidemiological studies are needed. This review is focused on specific adverse fetal exposures, cardiovascular adaptations and perspectives for new studies. Copyrigh

PREDICT Plus: development and validation of a prognostic model for early breast cancer that includes HER2.

Background: Predict (www.predict.nhs.uk) is an online, breast cancer prognostication and treatment benefit tool. The aim of this study was to incorporate the prognostic effect of HER2 status in a new version (Predict þ ), and to compare its performance with the original Predict and Adjuvant!. Methods: The prognostic effect of HER2 status was based on an analysis of data from 10 179 breast cancer patients from 14 studies in the Breast Cancer Association Consortium. The hazard ratio estimates were incorporated into Predict. The validation study was based on 1653 patients with early-stage invasive breast cancer identified from the British Columbia Breast Cancer Outcomes Unit. Predicted overall survival (OS) and breast cancer-specific survival (BCSS) for Predict þ , Predict and Adjuvant! were compared with observed outcomes. Results: All three models performed well for both OS and BCSS. Both Predict models provided better BCSS estimates than Adjuvant!. In the subset of patients with HER2-positive tumours, Predict þ performed substantially better than the other two models for both OS and BCSS. Conclusion: Predict þ is the first clinical breast cancer prognostication tool that includes tumour HER2 status. Use of the model might lead to more accurate absolute treatment benefit predictions for individual patients

Method and system for fetal weight estimation

A method for fetal weight estimation wherein fetal biometric parameters are ultrasonically measured and further physiological and phenomenological pregnancy parameters are determined for a plurality of sample cases. The fetal weight for each of the sample cases is then determined by precision weighing at birth. A database is then created based on the known sample cases and mathematical prediction models are generated from the database. For the case under examination for which fetal weight is to be predicted, the fetal biometric parameters are ultrasonically measured and further physiological and phenomenological pregnancy parameters are determined. The fetal weight of the case under examination is predicted by using a mathematical prediction model and a multinormal probabilistic model is used as a mathematical model