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An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient’s phenotype. The development of two new ontologies — the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation — will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO—a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations—evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)—mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas.

In microbending experiments of metal foils an increase of non-dimensional bending moment with decreasing foil thickness has been observed, which indicates the obvious presence of size effects. It is attributed to plastic strain gradient. So a constitutive model taking into account plastic strain gradient together with conventional plastic strain hardening is proposed to analyze the non-dimensional bending moment in microbending process. It is confirmed that the predictions by using the proposed hardening model agree well with the experimental data, while those determined by using conventional elastoplastic model cannot capture such size effects. A semi-empirical expression is reasonable to determine the material intrinsic length as a function of shear modulus, initial yield strength, length of Burger’s vector, grain size, and macro geometrical characteristic scale of the specimen.

In the general hospital setting, alcohol-use disorders very commonly remain undetected.

This pilot study has been designed to collect preliminary data on the use of a new antiepileptic drug in the management of alcoholic patients. Oxcarbazepine (OXC) blocks voltage-sensitive sodium channels. Its metabolite reduces high-voltage–activated calcium currents in striatal and cortical neurons, thus reducing glutamatergic transmission at corticostriatal synapses. This reduction is of interest in the treatment of alcohol dependence, as acamprosate (ACP) modulates NMDA receptors, resulting in an inhibition of glutamatergic transmission. Furthermore, OXC has revealed a mood-stabilizing effect in bipolar affective disorders. We have compared OXC with ACP in relapse prevention in recently withdrawn alcohol-dependent patients.

Objectives: This pilot study has been designed to collect preliminary data on the use of a new antiepileptic drug in the management of alcoholic patients. Oxcarbazepine (OXC) blocks voltage‐sensitive sodium channels. Its metabolite reduces high‐voltage–activated calcium currents in striatal and cortical neurons, thus reducing glutamatergic transmission at corticostriatal synapses. This reduction is of interest in the treatment of alcohol dependence, as acamprosate (ACP) modulates NMDA receptors, resulting in an inhibition of glutamatergic transmission. Furthermore, OXC has revealed a mood‐stabilizing effect in bipolar affective disorders. We have compared OXC with ACP in relapse prevention in recently withdrawn alcohol‐dependent patients.

Bacterial antigens recognized by CD8⁺ T cells in the context of MHC class I are thought to play a crucial role in protection against pathogenic intracellular bacteria. Here, we demonstrate the induction of HLA-A*0201-restricted CD8⁺ T cell responses against six new high-affinity HLA-A*0201-binding CTL epitopes, encoded within an immunodominant and highly conserved antigen of Mycobacteria, the heat shock protein 65 (hsp65). One of these epitopes, Mhsp65(9369), is identical in a large number of pathogenic bacteria, and is recognized in a CD8-independent fashion. Mhsp65(9369) could be presented by either mycobacterial hsp65-pulsed target cells or BCG-infected macrophages. Interestingly, T cells specific for this epitope did not recognize the corresponding human hsp65 homologue, probably due to structural differences as revealed by modeling studies. Furthermore, in vitro proteasome digestion analyses show that, whereas the mycobacterial hsp65 epitope is efficiently generated, the human hsp65 homologue is not, thus avoiding the induction of autoreactivity. Collectively, these findings describe high-affinity HLA class I-binding epitopes that are naturally processed and are recognized efficiently by MHC class I-restricted CD8⁺ T cells, providing a rational basis for the development of subunit vaccine strategies against tuberculosis and other intracellular infectious diseases.