Phytotoxicity test in check: Proposition of methodology for comparison of different method adaptations usually used worldwide.

Seed germination tests have been widely used in recent years to indicate the toxicity levels of samples of organic compounds, biosolids, residues and effluents. Lactuca sativa L, commonly known as lettuce, has been one of the main indicative species for these tests due to its high sensitivity to low levels of toxicity, when compared to other seeds and also because it is cultivated worldwide. Although this type of analysis or essay is being widely used, it is necessary to reflect on the various adaptations of methods used by different researchers worldwide. This work presents an innovative methodology that makes it possible to compare the different phytotoxicity methods currently used in the world, through four stages that include the coefficient of variation (CV) as the main classification criterion, also counting on an eliminatory criterion. The existence of a significant difference (P value < 0.05) between the evaluated tests was proven. The phytotoxicity test that presented the lowest CV was T8 (test with lettuce seeds at 25 °C, 60 min agitation, resting overnight, 5 mL of sample on the plate, 90 mm size plate). It has concluded that not all adaptations of this type of test are reliable. It has also concluded that there is a lack of standardization for the phytotoxicity test on a global scale, which makes the various researchers in the field end up promoting variations, adaptations for the phytotoxicity test; therefore, there is an urgent need for ways to compare these variations, as the innovation proposed by this work. With a single standard methodology, we conclude that it will make it possible to compare phytotoxicity in samples directly between countries and continents, being able to generate a worldwide panorama of phytotoxicity, publicizing and comparing the standardized phytotoxicity levels in each region.

Use of a High-Power Laser for Wound Healing: A Case Report.

Introduction: The use of low-level laser therapy to treat wounds and accelerate tissue healing has extensively been studied in recent years. The aim of this article is to describe a clinical case using an unfocused high-power laser instead of a low-power laser for therapy. Case Report: In the present article, we present the use of a high-power diode laser to treat an extensive knee injury that occurred after surgical treatment for total prosthesis due to border ischemia resulting from prolonged use of autostatic retractors. Conclusion: It is possible to use an unfocused high-power laser at a decreased intensity to accelerate healing as an adjuvant in the treatment of complicated wounds. This procedure results in reduced application time and cost and an excellent tissue response pattern similar to that reported in the literature with low-power lasers.

Semantic Predications for Complex Information Needs in Biomedical Literature.

Many complex information needs that arise in biomedical disciplines require exploring multiple documents in order to obtain information. While traditional information retrieval techniques that return a single ranked list of documents are quite common for such tasks, they may not always be adequate. The main issue is that ranked lists typically impose a significant burden on users to filter out irrelevant documents. Additionally, users must intuitively reformulate their search query when relevant documents have not been not highly ranked. Furthermore, even after interesting documents have been selected, very few mechanisms exist that enable document-to-document transitions. In this paper, we demonstrate the utility of assertions extracted from biomedical text (called semantic predications) to facilitate retrieving relevant documents for complex information needs. Our approach offers an alternative to query reformulation by establishing a framework for transitioning from one document to another. We evaluate this novel knowledge-driven approach using precision and recall metrics on the 2006 TREC Genomics Track.

ProtozoaDB: dynamic visualization and exploration of protozoan genomes.

ProtozoaDB (http://www.biowebdb.org/protozoadb) is being developed to initially host both genomics and post-genomics data from Plasmodium falciparum, Entamoeba histolytica, Trypanosoma brucei, T. cruzi and Leishmania major, but will hopefully host other protozoan species as more genomes are sequenced. It is based on the Genomics Unified Schema and offers a modern Web-based interface for user-friendly data visualization and exploration. This database is not intended to duplicate other similar efforts such as GeneDB, PlasmoDB, TcruziDB or even TDRtargets, but to be complementary by providing further analyses with emphasis on distant similarities (HMM-based) and phylogeny-based annotations including orthology analysis. ProtozoaDB will be progressively linked to the above-mentioned databases, focusing in performing a multi-source dynamic combination of information through advanced interoperable Web tools such as Web services. Also, to provide Web services will allow third-party software to retrieve and use data from ProtozoaDB in automated pipelines (workflows) or other interoperable Web technologies, promoting better information reuse and integration. We also expect ProtozoaDB to catalyze the development of local and regional bioinformatics capabilities (research and training), and therefore promote/enhance scientific advancement in developing countries.

TcruziDB: an integrated, post-genomics community resource for Trypanosoma cruzi.

TcruziDB (http://TcruziDB.org) is an integrated post-genomics database for the parasitic organism, Trypanosoma cruzi, the causative agent of Chagas' disease. TcruziDB was established in 2003 as a flat-file database with tools for mining the unannotated sequence reads and preliminary contig assemblies emerging from the Tri-Tryp genome consortium (TIGR/SBRI/Karolinska). Today, TcruziDB houses the recently published assembled genomic contigs and annotation provided by the genome consortium in a relational database supported by the Genomics Unified Schema (GUS) architecture. The combination of an annotated genome and a relational architecture has facilitated the integration of genomic data with expression data (proteomic and EST) and permitted the construction of automated analysis pipelines. TcruziDB has accepted, and will continue to accept the deposition of genomic and functional genomic datasets contributed by the research community.

GARSA: genomic analysis resources for sequence annotation.

SUMMARY: Growth of genome data and analysis possibilities have brought new levels of difficulty for scientists to understand, integrate and deal with all this ever-increasing information. In this scenario, GARSA has been conceived aiming to facilitate the tasks of integrating, analyzing and presenting genomic information from several bioinformatics tools and genomic databases, in a flexible way. GARSA is a user-friendly web-based system designed to analyze genomic data in the context of a pipeline. EST and GGS data can be analyzed using the system since it accepts (1) chromatograms, (2) download of sequences from GenBank, (3) Fasta files stored locally or (4) a combination of all three. Quality evaluation of chromatograms, vector removing and clusterization are easily performed as part of the pipeline. A number of local and customizable Blast and CDD analyses can be performed as well as Interpro, complemented with phylogeny analyses. GARSA is being used for the analyses of Trypanosoma vivax (GSS and EST), Trypanosoma rangeli (GSS, EST and ORESTES), Bothrops jararaca (EST), Piaractus mesopotamicus (EST) and Lutzomyia longipalpis (EST). AVAILABILITY: The GARSA system is freely available under GPL license (http://www.biowebdb.org/garsa/). For download requests visit http://www.biowebdb.org/garsa/ or contact Dr Alberto Dávila.

Exploring the genome of Trypanosoma vivax through GSS and in silico comparative analysis.

A survey of the Trypanosoma vivax genome was carried out by the genome sequence survey (GSS) approach resulting in 1,086 genomic sequences. A total of 455 high-quality GSS sequences were generated, consisting of 331 non-redundant sequences distributed in 264 singlets and 67 clusters in a total of 135.5 Kb of the T. vivax genome. The estimation of the overall G+C content, and the prediction of the presence of ORFs and putative genes were carried out using the Glimmer and Jemboss packages. Analysis of the obtained sequences was carried out by BLAST programs against 12 different databases and also using the Conserved Domain Database, InterProScan, and tRNAscan-SE. Along with the existing 23 T. vivax entries in the GenBank, the 32 putative genes predicted and the 331 non-redundant GSS sequences reported herein represent new potential markers for the development of PCRbased assays for specific diagnosis and typing of Trypanosoma vivax.