AND/R: Advanced neutron diffractometer/reflectometer for investigation of thin films and multilayers for the life sciences

An elastic neutron scattering instrument, the advanced neutron diffractometer/reflectometer (AND/R), has recently been commissioned at the National Institute of Standards and Technology Center for Neutron Research. The AND/R is the centerpiece of the Cold Neutrons for Biology and Technology partnership, which is dedicated to the structural characterization of thin films and multilayers of biological interest. The instrument is capable of measuring both specular and nonspecular reflectivity, as well as crystalline or semicrystalline diffraction at wave-vector transfers up to approximately 2.20 Å(-1). A detailed description of this flexible instrument and its performance characteristics in various operating modes are given.D. J. M. is supported through a NSF NIRT grant Contract No. 0304062

Strengthening the community health worker programme for health improvement through enhancing training, supervision and motivation in Wakiso district, Uganda

Objective: The objective of the project was to strengthen the community health worker (CHW) programme in Ssisa sub-county, Wakiso district, Uganda by providing a coherent, structured and standardized training, supervision and motivation package so as to enhance their performance. Results: The project trained all 301 CHWs who received non-financial incentives of t-shirts, gumboots and umbrellas, and 75 of them received solar equipment to support lighting their houses and charging phones. Twenty-four of the CHWs who had coordination roles received additional training. Three motorcycles were also provided to enhance transportation of CHW coordinators during their work including supervision. By end of the project, the CHWs had conducted 40,213 household visits, carried out health education sessions with 127,011 community members, and treated 19,387 children under 5 years of age. From the project evaluation, which used both quantitative and qualitative methods, 98% of the CHWs reported having improved competence in performance of their roles. In addition, the CHWs were highly motivated to do their work. The motorcycles were instrumental in supporting the work of CHW coordinators including monthly collection of reports and distribution of medicines. The project demonstrated that by improving training, supervision and motivation, performance of CHW programmes can be enhanced

The COMBREX Project: Design, Methodology, and Initial Results

© 2013 Brian P. et al.Prior to the “genomic era,” when the acquisition of DNA sequence involved significant labor and expense, the sequencing of genes was strongly linked to the experimental characterization of their products. Sequencing at that time directly resulted from the need to understand an experimentally determined phenotype or biochemical activity. Now that DNA sequencing has become orders of magnitude faster and less expensive, focus has shifted to sequencing entire genomes. Since biochemistry and genetics have not, by and large, enjoyed the same improvement of scale, public sequence repositories now predominantly contain putative protein sequences for which there is no direct experimental evidence of function. Computational approaches attempt to leverage evidence associated with the ever-smaller fraction of experimentally analyzed proteins to predict function for these putative proteins. Maximizing our understanding of function over the universe of proteins in toto requires not only robust computational methods of inference but also a judicious allocation of experimental resources, focusing on proteins whose experimental characterization will maximize the number and accuracy of follow-on predictions.COMBREX is funded by a GO grant from the National Institute of General Medical Sciences (NIGMS) (1RC2GM092602-01).Peer Reviewe

Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

Abstract: The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group