Baselines for Lifetime of Organic Solar Cells

The process of accurately gauging lifetime improvements in organic photovoltaics (OPVs) or other similar emerging technologies, such as perovskites solar cells is still a major challenge. The presented work is part of a larger effort of developing a worldwide database of lifetimes that can help establishing reference baselines of stability performance for OPVs and other emerging PV technologies, which can then be utilized for pass‐fail testing standards and predicting tools. The study constitutes scanning of literature articles related to stability data of OPVs, reported until mid‐2015 and collecting the reported data into a database. A generic lifetime marker is utilized for rating the stability of various reported devices. The collected data is combined with an earlier developed and reported database, which was based on articles reported until mid‐2013. The extended database is utilized for establishing the baselines of lifetime for OPVs tested under different conditions. The work also provides the recent progress in stability of unencapsulated OPVs with different architectures, as well as presents the updated diagram of the reported record lifetimes of OPVs. The presented work is another step forward towards the development of pass‐fail testing standards and lifetime prediction tools for emerging PV technologies.     

PDZBase: a protein-protein interaction database for PDZ-domains

SUMMARY: PDZBase is a database that aims to contain all known PDZ-domain-mediated protein-protein interactions. Currently, PDZBase contains approximately 300 such interactions, which have been manually extracted from > 200 articles. The database can be queried through both sequence motif and keyword-based searches, and the sequences of interacting proteins can be visually inspected through alignments (for the comparison of several interactions), or as residue-based diagrams including schematic secondary structure information (for individual complexes).     

Neglected Tropical Diseases: A Systematic Evaluation of Research Capacity in Nigeria

Background

Nigeria carries the highest burden and diversity of neglected tropical diseases (NTDs) in sub-Saharan Africa and is preparing to scale up its efforts to control/eliminate these diseases. To achieve this it will require a range of internal technical support and expertise for mapping, monitoring and evaluating, operational research and documenting its success. In order to begin to evaluate this potential in Nigeria, this study collated and analysed information for lymphatic filariasis (LF), onchocerciasis, schistosomiasis and soil-transmitted helminths (STH), which are currently being targeted with preventive chemotherapy through mass drug administration (MDA).

Methodology/Principal Findings

Information from 299 scientific articles published on the selected NTDs in 179 journals between January 2008 and September 2013 was extracted and systematically compiled into a geo-referenced database for analysis and mapping. The highest number of articles was from the southern geo-political zones of the country. The majority of articles focused on one specific disease, and schistosomiasis and STH were found to have the highest and most wide ranging research output. The main type of study was parasitological, and the least was biotechnological. Nigerian authors were mostly affiliated with universities, and there was a wide range of international co-authors from Africa and other regions, especially the USA and UK. The majority of articles were published in journals with no known impact factor.

Conclusions/Significance

The extensive database and series of maps on the research capacity within Nigeria produced in this study highlights the current potential that exists, and needs to be fully maximized for the control/elimination of NTDs in the country. This study provides an important model approach that can be applied to other low and middle income countries where NTDs are endemic, and NTD programmes require support from the expertise within their own country, as well as internationally, to help raise their profile and importance.     

Textpresso: an ontology-based information retrieval and extraction system for biological literature

We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other organism-specific corpora of text. Textpresso can be accessed at http://www.textpresso.org or via WormBase at http://www.wormbase.org.     

口腔微生态失衡导致口腔异味的研究

目的介绍口腔微生态失调与口腔疾病的关系,口腔疾病出现口腔气味异常的机制。综合分析口腔微生态与口腔健康的研究动态及意义。展望口腔微生态调整在口腔疾病治疗中的作用研究,尤其在消除口腔异昧的积极作用。方法由第一、二作者应用计算机通过pubmed检索NCBI数据库1992年至2007年相关文献,检索词为“Micro ecology”,限定语言种类为“English”;同时检索CNKI全文数据库、维普全文数据库1995年至2007年相关文献,检索词为“微生态”,限定语言种类为中文。纳入标准：文章内容与口腔微生态相关的研究、以及在口腔疾病研究领域有关。排除标准：较陈旧的文献和重复研究。结果共收集到106篇相关文献,21篇文献纳入本文,其中,19篇为综述和述评类文献,19篇为中文杂志,2篇为外文杂志。结论致病菌大量生长繁殖,口腔微生态失调,菌斑内微生物之间以及机体与菌斑之间相互作用分解蛋白产生硫化物,这些代谢产物包括H2S、CH3SH、CH3SCH3、吲哚、甲基吲哚、挥发脂肪酸和聚胺等发出刺激性气味,产生口腔异味。治疗口腔异味应该考虑平衡口腔微生态,调整口腔菌群。口腔异味的治疗又有利于口腔菌群平衡。提示我们治疗口腔疾病应该考虑口腔微生态平衡。     

A local alignment metric for accelerating biosequence database search.

We introduce a metric for local sequence alignments that has utility for accelerating optimal alignment searches without loss of sensitivity. The metric's triangle inequality property permits identification of redundant database entries guaranteed to have optimal alignments to the query sequence that fall below a specified score threshold, thereby permitting comparisons to these entries to be skipped. We prove the existence of the metric for a variety of scoring systems, including the most commonly used ones, and show that a triangle inequality can be established as well for nucleotide-to-protein sequence comparisons. We discuss a database clustering and search strategy that takes advantage of the triangle inequality. The strategy permits moderate but significant acceleration of searches against the widely used "nr" protein database. It also provides a theoretically based method for database clustering in general and provides a standard against which to compare heuristic clustering strategies.     

The RNA WikiProject: community annotation of RNA families

The online encyclopedia Wikipedia has become one of the most important online references in the world and has a substantial and growing scientific content. A search of Google with many RNA-related keywords identifies a Wikipedia article as the top hit. We believe that the RNA community has an important and timely opportunity to maximize the content and quality of RNA information in Wikipedia. To this end, we have formed the RNA WikiProject (http://en.wikipedia.org/wiki/Wikipedia:WikiProject_RNA) as part of the larger Molecular and Cellular Biology WikiProject. We have created over 600 new Wikipedia articles describing families of noncoding RNAs based on the Rfam database, and invite the community to update, edit, and correct these articles. The Rfam database now redistributes this Wikipedia content as the primary textual annotation of its RNA families. Users can, therefore, for the first time, directly edit the content of one of the major RNA databases. We believe that this Wikipedia/Rfam link acts as a functioning model for incorporating community annotation into molecular biology databases.     

BBID: the biological biochemical image database

The Biological Biochemical Image Database is a WWW accessible relational database of archived images from research articles that describe regulatory pathways of higher eukaryotes. Pathway information is annotated and can be queried in the study of complex gene expression. In this way, complex regulatory pathways can be tested empirically in an efficient manner in the context of large-scale gene-expression systems.     

LitDB - Keeping Track of Research Papers From Your Institute Made Simple

Background

In science peer-reviewed publications serve as an important indicator of scientific excellence and productivity. Therefore, every scientist and institution must carefully maintain and update records of their scientific publications. However, in most institutions and universities articles are often managed in a redundant file-based and non-central way. Whereas excellent reference management software packages such as Zotero, Endnote or Mendeley exist to manage bibliographies and references when writing scientific articles, we are not aware of any open source database solution keeping track of publication records from large scientific groups, entire institutions and/or universities.

Results

We here describe LitDB, a novel open source literature database solution for easy maintenance of publication lists assigned to various topics. In the last 2 years more than 50 users have been using LitDB at our research institute. The LitDB system is accessed via a web browser. Publications can be uploaded through direct exports from reference manager libraries or by entering PubMed IDs. Single users or user groups can track their citation counts, h-index and impact factor statistics and gain insights into the publication records of other users. It offers various visualization functions like coauthor networks and provides ways to organize publications from dedicated projects and user groups. The latter is in particular beneficial to manage publication lists of large research groups and research initiatives through a “crowd-sourcing” effort.

Conclusions

Keeping track of papers authored and published by a research group, institute or university is an important and non-trivial task. By using a centralized web-based platform for publication management such as LitDB the compilation of project- and group-related publication lists becomes easily manageable and it is less likely that papers are forgotten along the way.

     

An Atlas on genes and chromosomes in oncology and haematology.

The "Atlas of Genetics and Cytogenetics in Oncology and Haematology" http://www.infobiogen.fr/services/chromcancer is a peer-reviewed and free internet database aimed at genes involved in cancer, cytogenetics and clinical entities in cancer, and cancer-prone diseases. It contains concise and updated review articles, a huge portal towards genetics and/or cancer databases, and teaching materials in genetics for the students. This database is made for and by clinicians and researchers, who are encouraged to contribute. The Atlas is part of the genome project. It provides information in cancer epidemiology. It contributes to research, university and post-university teaching, and telemedicine. It contributes to 'meta-medicine', a mediation using new information technology, between the overflowing information provided by the scientific community and the individual practitioner.     

Hirsutism: Diagnosis and management

Background:Hirsutism is defined as excess hair growth in androgen-dependent areas of the body in women.Objective: This article provides an updated review of hirsutism, focusing on the etiologies, clinical features, approach to diagnostic evaluation, and treatment options.Methods: The PubMed database was searched for English-language articles published from 1981 to the present, using the terms hirsutism, polycystic ovarian syndrome, congenital adrenal hyperplasia, hirsutism diagnosis, and hirsutism treatment. Reference lists from review articles on hirsutism during this time period were also examined.Results: While there are many causes of hirsutism, the majority of patients have a benign process that may be idiopathic. In some circumstances, hirsutism is a sign of functional ovarian hyperandrogenism or congenital adrenal hyperplasia. Even more rarely, it is the presenting sign of an internal malignancy.Conclusions: Hirsutism clinically presents in women as excessive hair growth in androgen-dependent areas. It is a particularly important diagnosis to make, because it often significantly affects a woman's perception of her femininity and less commonly can be a sign of an underlying malignancy or a cutaneous manifestation of a condition with significant cardiovascular or other morbidity. A variety of treatments exist to help minimize the appearance of unwanted hair.     

hmChIP: a database and web server for exploring publicly available human and mouse ChIP-seq and ChIP-chip data

hmChIP is a database of genome-wide chromatin immunoprecipitation (ChIP) data in human and mouse. Currently, the database contains 2016 samples from 492 ChIP-seq and ChIP-chip experiments, representing a total of 170 proteins and 11 069 914 protein-DNA interactions. A web server provides interface for database query. Protein-DNA binding intensities can be retrieved from individual samples for user-provided genomic regions. The retrieved intensities can be used to cluster samples and genomic regions to facilitate exploration of combinatorial patterns, cell-type dependencies, and cross-sample variability of protein-DNA interactions. AVAILABILITY: http://jilab.biostat.jhsph.edu/database/cgi-bin/hmChIP.pl.     

Applying for grant funds: there's help around the corner

Scientists should know where to get help when they write grant proposals. Books, videos, consultants and colleagues can all be useful. The World Wide Web is an excellent resource for finding competitors, collaborators and a wealth of other useful information such as funding agencies, available grant money, pertinent articles and form pages for grant applications. Software is available to help you make an outline of your proposal, prepare the required figures and tables and build a database of references from which to create a bibliography. This article will point you in the right direction for a plethora of information and resources.     

Saccharomyces genome database: underlying principles and organisation

A scientific database can be a powerful tool for biologists in an era where large-scale genomic analysis, combined with smaller-scale scientific results, provides new insights into the roles of genes and their products in the cell. However, the collection and assimilation of data is, in itself, not enough to make a database useful. The data must be incorporated into the database and presented to the user in an intuitive and biologically significant manner. Most importantly, this presentation must be driven by the user's point of view; that is, from a biological perspective. The success of a scientific database can therefore be measured by the response of its users - statistically, by usage numbers and, in a less quantifiable way, by its relationship with the community it serves and its ability to serve as a model for similar projects. Since its inception ten years ago, the Saccharomyces Genome Database (SGD) has seen a dramatic increase in its usage, has developed and maintained a positive working relationship with the yeast research community, and has served as a template for at least one other database. The success of SGD, as measured by these criteria, is due in large part to philosophies that have guided its mission and organisation since it was established in 1993. This paper aims to detail these philosophies and how they shape the organisation and presentation of the database.     

A database and tools for 3-D protein structure comparison and alignment using the Combinatorial Extension (CE) algorithm

The database reported here is derived using the Combinatorial Extension (CE) algorithm which compares pairs of protein polypeptide chains and provides a list of structurally similar proteins along with their structure alignments. Using CE, structure-structure alignments can provide insights into biological function. When a protein of known function is shown to be structurally similar to a protein of unknown function, a relationship might be inferred; a relationship not necessarily detectable from sequence comparison alone. Establishing structure-structure relationships in this way is of great importance as we enter an era of structural genomics where there is a likelihood of an increasing number of structures with unknown functions being determined. Thus the CE database is an example of a useful tool in the annotation of protein structures of unknown function. Comparisons can be performed on the complete PDB or on a structurally representative subset of proteins. The source protein(s) can be from the PDB (updated monthly) or uploaded by the user. CE provides sequence alignments resulting from structural alignments and Cartesian coordinates for the aligned structures, which may be analyzed using the supplied Compare3D Java applet, or downloaded for further local analysis. Searches can be run from the CE web site, http://cl.sdsc.edu/ce.html, or the database and software downloaded from the site for local use.     

Entomopathogen ID: a curated sequence resource for entomopathogenic fungi

We report the development of a publicly accessible, curated nucleotide sequence database of hypocrealean entomopathogenic fungi. The goal is to provide a platform for users to easily access sequence data from taxonomic reference strains. The database can be used to accurately identify unknown entomopathogenic fungi based on sequence data for a variety of phylogenetically informative loci. The database provides full multi-locus sequence alignment capabilities. The initial release contains data compiled for 525 strains covering the phylogenetic diversity of three important entomopathogenic families: Clavicipitaceae, Cordycipitaceae, and Ophiocordycipitaceae. Furthermore, Entomopathogen ID can be expanded to other fungal clades of insect pathogens, as sequence data becomes available. The database will allow isolate characterisation and evolutionary analyses. We contend that this freely available, web-accessible database will facilitate the broader community to accurately identify fungal entomopathogens, which will allow users to communicate research results more effectively.