Electrophoretically Co-Deposited Collagen-Lactoferrin Membranes with Enhanced Pro-Regenerative Properties for Oral Soft Tissue Regeneration.

The quality of soft tissue defect regeneration after dental surgeries largely determines their final success. Collagen membranes have been proposed for the healing of such defects, but in some cases, they do not guarantee a sufficient volume of the regenerated tissue and vascularization. For this purpose, lactoferrin, a protein with natural pro-regenerative, anti-inflammatory, and pro-angiogenic activity, can be added to collagen. In this article, we used a semipermeable barrier-assisted electrophoretic deposition (SBA-EPD) method for the production of collagen-lactoferrin membranes. The membrane structure was studied by SEM, and its mechanical properties were shown. The lactoferrin release kinetics were shown by ELISA within 75 h. When tested in vitro, we demonstrated that the collagen-lactoferrin membranes significantly increased the proliferation of keratinocytes (HaCaT) and fibroblasts (977hTERT) compared to blank collagen membranes. In vivo, on the vestibuloplasty and free gingival graft harvesting models, we showed that collagen-lactoferrin membranes decreased the wound inflammation and increased the healing rates and regeneration quality. In some parameters, collagen-lactoferrin membranes outperformed not only blank collagen membranes, but also the commercial membrane Mucograft®. Thus, we proved that collagen-lactoferrin membranes produced by the SBA-EPD method may be a valuable alternative to commercially used membranes for soft tissue regeneration in the oral cavity.

The BioStudies database-one stop shop for all data supporting a life sciences study.

BioStudies (www.ebi.ac.uk/biostudies) is a new public database that organizes data from biological studies. Typically, but not exclusively, a study is associated with a publication. BioStudies offers a simple way to describe the study structure, and provides flexible data deposition tools and data access interfaces. The actual data can be stored either in BioStudies or remotely, or both. BioStudies imports supplementary data from Europe PMC, and is a resource for authors and publishers for packaging data during the manuscript preparation process. It also can support data management needs of collaborative projects. The growth in multiomics experiments and other multi-faceted approaches to life sciences research mean that studies result in a diversity of data outputs in multiple locations. BioStudies presents a solution to ensuring that all these data and the associated publication(s) can be found coherently in the longer term.

Updates to BioSamples database at European Bioinformatics Institute.

The BioSamples database at the EBI (http://www.ebi.ac.uk/biosamples) provides an integration point for BioSamples information between technology specific databases at the EBI, projects such as ENCODE and reference collections such as cell lines. The database delivers a unified query interface and API to query sample information across EBI's databases and provides links back to assay databases. Sample groups are used to manage related samples, e.g. those from an experimental submission, or a single reference collection. Infrastructural improvements include a new user interface with ontological and key word queries, a new query API, a new data submission API, complete RDF data download and a supporting SPARQL endpoint, accessioning at the point of submission to the European Nucleotide Archive and European Genotype Phenotype Archives and improved query response times.

The BioSample Database (BioSD) at the European Bioinformatics Institute.

The BioSample Database (http://www.ebi.ac.uk/biosamples) is a new database at EBI that stores information about biological samples used in molecular experiments, such as sequencing, gene expression or proteomics. The goals of the BioSample Database include: (i) recording and linking of sample information consistently within EBI databases such as ENA, ArrayExpress and PRIDE; (ii) minimizing data entry efforts for EBI database submitters by enabling submitting sample descriptions once and referencing them later in data submissions to assay databases and (iii) supporting cross database queries by sample characteristics. Each sample in the database is assigned an accession number. The database includes a growing set of reference samples, such as cell lines, which are repeatedly used in experiments and can be easily referenced from any database by their accession numbers. Accession numbers for the reference samples will be exchanged with a similar database at NCBI. The samples in the database can be queried by their attributes, such as sample types, disease names or sample providers. A simple tab-delimited format facilitates submissions of sample information to the database, initially via email to biosamples@ebi.ac.uk.

SAIL--a software system for sample and phenotype availability across biobanks and cohorts.

SUMMARY: The Sample avAILability system-SAIL-is a web based application for searching, browsing and annotating biological sample collections or biobank entries. By providing individual-level information on the availability of specific data types (phenotypes, genetic or genomic data) and samples within a collection, rather than the actual measurement data, resource integration can be facilitated. A flexible data structure enables the collection owners to provide descriptive information on their samples using existing or custom vocabularies. Users can query for the available samples by various parameters combining them via logical expressions. The system can be scaled to hold data from millions of samples with thousands of variables. AVAILABILITY: SAIL is available under Aferro-GPL open source license: https://github.com/sail.

Large scale integration of drug-target information reveals poly-pharmacological drug action mechanisms in tumor cell line growth inhibition assays.

Understanding therapeutic mechanisms of drug anticancer cytotoxicity represents a key challenge in preclinical testing. Here we have performed a meta-analysis of publicly available tumor cell line growth inhibition assays (~ 70 assays from 6 independent experimental groups covering ~ 500 000 molecules) with the primary goal of understanding molecular therapeutic mechanisms of cancer cytotoxicity. To implement this we have collected currently available information on protein targets for molecules that were tested in the assays. We used a statistical methodology to identify protein targets overrepresented among molecules exhibiting cancer cytotoxicity with the particular focus of identifying overrepresented patterns consisting of several proteins (i.e. proteins "A" and "B" and "C"). Our analysis demonstrates that targeting individual proteins can result in a significant increase (up to 50-fold) of the observed odds for a molecule to be an efficient inhibitor of tumour cell line growth. However, further insight into potential molecular mechanisms reveals a multi-target mode of action: targeting a pattern of several proteins drastically increases the observed odds (up to 500-fold) for a molecule to be tumour cytotoxic. In contrast, molecules targeting only one protein but not targeting an additional set of proteins tend to be nontoxic. Our findings support a poly-pharmacology drug discovery paradigm, demonstrating that anticancer cytotoxicity is a product, in most cases, of multi-target mode of drug action.