Achilles tendon resting angle is able to detect deficits after an Achilles tendon rupture, but it is not a surrogate for direct measurements of tendon elongation, function or symptoms.

PURPOSE: The aim of this study was to investigate how the Achilles tendon resting angle (ATRA), an indirect measurement of tendon elongation, correlates with ultrasonography (US) measurements of the Achilles tendon length 6 and 12 months after an acute ATR and relates to other clinical outcome measurements such as heel-rise height, jumping ability and patient-reported outcome measurements (PROMs). METHODS: Patients were included following acute Achilles tendon rupture (ATR). Achilles tendon length, ATRA, heel-rise height (HRH), drop countermovement jump (Drop CMJ) and PROMs (Achilles tendon total rupture score (ATRS) and physical activity scale (PAS)) were evaluated 6 and 12 months after injury. Achilles tendon length was evaluated using US, while the ATRA was measured with a goniometer. RESULTS: Sixty patients (13 women, 47 men), mean (SD) age 43 (9) years, with an acute ATR undergoing either surgical (35%) or non-surgical (65%) treatment were evaluated. A negative correlation (r = - 0.356, p = 0.010) between relative ATRA and tendon elongation was seen at 12 months after ATR. There were also significant positive correlations at 6 and 12 months between relative ATRA and HRH (r = 0.330, p = 0.011 and r = 0.379, p = 0.004). There were no correlations between ATRA and ATRS or ATRA and Drop CMJ, at either 6 or 12 months after the injury. CONCLUSION: In combination with other clinical evaluations such as HRH and US, ATRA could be a clinical tool for indirect measurements of tendon elongation. However, ATRA cannot be recommended as a direct surrogate for US for determining Achilles tendon length. LEVEL OF EVIDENCE: III.

The Ontology for Biomedical Investigations.

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

Experiences in supporting the structured collection of cancer nanotechnology data using caNanoLab.

The cancer Nanotechnology Laboratory (caNanoLab) data portal is an online nanomaterial database that allows users to submit and retrieve information on well-characterized nanomaterials, including composition, in vitro and in vivo experimental characterizations, experimental protocols, and related publications. Initiated in 2006, caNanoLab serves as an established resource with an infrastructure supporting the structured collection of nanotechnology data to address the needs of the cancer biomedical and nanotechnology communities. The portal contains over 1,000 curated nanomaterial data records that are publicly accessible for review, comparison, and re-use, with the ultimate goal of accelerating the translation of nanotechnology-based cancer therapeutics, diagnostics, and imaging agents to the clinic. In this paper, we will discuss challenges associated with developing a nanomaterial database and recognized needs for nanotechnology data curation and sharing in the biomedical research community. We will also describe the latest version of caNanoLab, caNanoLab 2.0, which includes enhancements and new features to improve usability such as personalized views of data and enhanced search and navigation.

caNanoLab: data sharing to expedite the use of nanotechnology in biomedicine.

The use of nanotechnology in biomedicine involves the engineering of nanomaterials to act as therapeutic carriers, targeting agents and diagnostic imaging devices. The application of nanotechnology in cancer aims to transform early detection, targeted therapeutics and cancer prevention and control. To assist in expediting and validating the use of nanomaterials in biomedicine, the National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology, in collaboration with the NCI Alliance for Nanotechnology in Cancer (Alliance), has developed a data sharing portal called caNanoLab. caNanoLab provides access to experimental and literature curated data from the NCI Nanotechnology Characterization Laboratory, the Alliance and the greater cancer nanotechnology community.

Development of FuGO: an ontology for functional genomics investigations.

The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the "semantic glue" to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans.

The MGED Ontology: a resource for semantics-based description of microarray experiments.

MOTIVATION: The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. RESULTS: Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. AVAILABILITY: The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). CONTACT: Stoeckrt@pcbi.upenn.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Interlaboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays.

A key step in bringing gene expression data into clinical practice is the conduct of large studies to confirm preliminary models. The performance of such confirmatory studies and the transition to clinical practice requires that microarray data from different laboratories are comparable and reproducible. We designed a study to assess the comparability of data from four laboratories that will conduct a larger microarray profiling confirmation project in lung adenocarcinomas. To test the feasibility of combining data across laboratories, frozen tumor tissues, cell line pellets, and purified RNA samples were analyzed at each of the four laboratories. Samples of each type and several subsamples from each tumor and each cell line were blinded before being distributed. The laboratories followed a common protocol for all steps of tissue processing, RNA extraction, and microarray analysis using Affymetrix Human Genome U133A arrays. High within-laboratory and between-laboratory correlations were observed on the purified RNA samples, the cell lines, and the frozen tumor tissues. Intraclass correlation within laboratories was only slightly stronger than between laboratories, and the intraclass correlation tended to be weakest for genes expressed at low levels and showing small variation. Finally, hierarchical cluster analysis revealed that the repeated samples clustered together regardless of the laboratory in which the experiments were done. The findings indicate that under properly controlled conditions it is feasible to perform complete tumor microarray analysis, from tissue processing to hybridization and scanning, at multiple independent laboratories for a single study.

Cloning of BCAS3 (17q23) and BCAS4 (20q13) genes that undergo amplification, overexpression, and fusion in breast cancer.

In breast cancer, several chromosomal sites frequently undergo amplification, implicating the location of genes important for tumor development and progression. Here we cloned two novel genes, breast carcinoma amplified sequence 3 (BCAS3) and 4 (BCAS4), from the two most common amplification sites in breast cancer, 17q23 and 20q13. The BCAS3 gene at 17q23 spans more than 600 kb at the genomic level and was predicted to encode a 913 amino acid nuclear protein. The BCAS4 gene at 20q13.2 encodes a 211 amino acid cytoplasmic protein. Both BCAS3 and BCAS4 represent novel genes with no homologies to any other known gene or protein. In the MCF7 breast cancer cell line, the BCAS3 and BCAS4 genes were co-amplified, and cloning of a highly overexpressed 1.3-kb transcript revealed a rearrangement fusing the last two exons of BCAS3 with BCAS4. The fusion led to a novel message in which only the first exon of BCAS4 and part of exon 23 of BCAS3 were transcribed. The BCAS4-BCAS3 fusion transcript was detected only in MCF7 cells, but the BCAS4 gene was also overexpressed in nine of 13 breast cancer cell lines. In conclusion, our results indicate that these novel genes, BCAS3 at 17q23 and BCAS4 at 20q13.2, undergo amplification, overexpression, and fusion in breast cancer and therefore may have a role in the frequent chromosomal alterations affecting these two loci.

Physical and transcript map of the hereditary prostate cancer region at xq27.

We have recently mapped a locus for hereditary prostate cancer (termed HPCX) to the long arm of the X chromosome (Xq25-q27) through a genome-wide linkage study. Here we report the construction of an approximately 9-Mb sequence-ready bacterial clone contig map of Xq26.3-q27.3. The contig was constructed by screening BAC/PAC libraries with markers spaced at approximately 85-kb intervals. We identified overlapping clones by end-sequencing framework clones to generate 407 new sequence-tagged sites, followed by PCR verification of overlaps. Contig assembly was based on clone restriction fingerprinting and the landmark information. We identified a minimal overlap contig for genomic sequencing, which has yielded 7.7 Mb of finished sequence and 1.5 Mb of draft sequence. The transcriptional mapping effort localized 57 known and predicted genes by database searching, STS content mapping, and sequencing, followed by sequence annotation. These transcriptional units represent candidate genes for HPCX and multiple other hereditary diseases at Xq26.3-q27.3.