The DataHarmonizer: a tool for faster data harmonization, validation, aggregation and analysis of pathogen genomics contextual information.

Pathogen genomics is a critical tool for public health surveillance, infection control, outbreak investigations as well as research. In order to make use of pathogen genomics data, they must be interpreted using contextual data (metadata). Contextual data include sample metadata, laboratory methods, patient demographics, clinical outcomes and epidemiological information. However, the variability in how contextual information is captured by different authorities and how it is encoded in different databases poses challenges for data interpretation, integration and their use/re-use. The DataHarmonizer is a template-driven spreadsheet application for harmonizing, validating and transforming genomics contextual data into submission-ready formats for public or private repositories. The tool's web browser-based JavaScript environment enables validation and its offline functionality and local installation increases data security. The DataHarmonizer was developed to address the data sharing needs that arose during the COVID-19 pandemic, and was used by members of the Canadian COVID Genomics Network (CanCOGeN) to harmonize SARS-CoV-2 contextual data for national surveillance and for public repository submission. In order to support coordination of international surveillance efforts, we have partnered with the Public Health Alliance for Genomic Epidemiology to also provide a template conforming to its SARS-CoV-2 contextual data specification for use worldwide. Templates are also being developed for One Health and foodborne pathogens. Overall, the DataHarmonizer tool improves the effectiveness and fidelity of contextual data capture as well as its subsequent usability. Harmonization of contextual information across authorities, platforms and systems globally improves interoperability and reusability of data for concerted public health and research initiatives to fight the current pandemic and future public health emergencies. While initially developed for the COVID-19 pandemic, its expansion to other data management applications and pathogens is already underway.

FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration.

The construction of high capacity data sharing networks to support increasing government and commercial data exchange has highlighted a key roadblock: the content of existing Internet-connected information remains siloed due to a multiplicity of local languages and data dictionaries. This lack of a digital lingua franca is obvious in the domain of human food as materials travel from their wild or farm origin, through processing and distribution chains, to consumers. Well defined, hierarchical vocabulary, connected with logical relationships-in other words, an ontology-is urgently needed to help tackle data harmonization problems that span the domains of food security, safety, quality, production, distribution, and consumer health and convenience. FoodOn (http://foodon.org) is a consortium-driven project to build a comprehensive and easily accessible global farm-to-fork ontology about food, that accurately and consistently describes foods commonly known in cultures from around the world. FoodOn addresses food product terminology gaps and supports food traceability. Focusing on human and domesticated animal food description, FoodOn contains animal and plant food sources, food categories and products, and other facets like preservation processes, contact surfaces, and packaging. Much of FoodOn's vocabulary comes from transforming LanguaL, a mature and popular food indexing thesaurus, into a World Wide Web Consortium (W3C) OWL Web Ontology Language-formatted vocabulary that provides system interoperability, quality control, and software-driven intelligence. FoodOn compliments other technologies facilitating food traceability, which is becoming critical in this age of increasing globalization of food networks.

Long-Term Outcome of Endoprosthetic Replacement for Proximal Femur Giant Cell Tumor.

INTRODUCTION: Giant cell tumor (GCT) of bone is locally aggressive benign tumor involving the epiphysis of long bones in young adults. Various treatment options include intralesional curettage, extended curettage, wide resection, resection and reconstruction and amputation. The main variables to be considered for planning treatment include the site of involvement and Campanacci stage of the tumor. Functional and oncological outcomes of these treatment options vary widely, the predominant detrimental factor being tumor recurrence rate. AIM: A study was conducted to evaluate the long-term oncological and functional outcome of patients with GCT of the proximal femur that underwent tumor resection and endoprosthetic replacement. MATERIALS AND METHODS: Eleven patients with Campanacci stage-III GCT of proximal femur who underwent wide excision of tumor and endoprosthesis replacement with a mean follow-up the duration of 10.6 years were assessed using standard proforma. The treatment outcome was evaluated using the Revised Musculoskeletal Tumor Society Rating Scale for the lower extremity. RESULTS: At mean follow-up the duration of 10.6 years, none of the cases had tumor recurrence, infection, prosthesis loosening or dislocation. All the patients were community ambulators among whom eight patients were walking without support while three patients were using a cane for support. The mean total Musculoskeletal Tumor Society Score was 26.8 out of 30 indicating the good outcome. CONCLUSIONS: The authors recommend that wide resection and endoprosthetic replacement should be considered as a preferred treatment option for proximal femur GCT as the functional, and oncological outcome is satisfactory with this modality of treatment.

ProKinO: an ontology for integrative analysis of protein kinases in cancer.

BACKGROUND: Protein kinases are a large and diverse family of enzymes that are genomically altered in many human cancers. Targeted cancer genome sequencing efforts have unveiled the mutational profiles of protein kinase genes from many different cancer types. While mutational data on protein kinases is currently catalogued in various databases, integration of mutation data with other forms of data on protein kinases such as sequence, structure, function and pathway is necessary to identify and characterize key cancer causing mutations. Integrative analysis of protein kinase data, however, is a challenge because of the disparate nature of protein kinase data sources and data formats. RESULTS: Here, we describe ProKinO, a protein kinase-specific ontology, which provides a controlled vocabulary of terms, their hierarchy, and relationships unifying sequence, structure, function, mutation and pathway information on protein kinases. The conceptual representation of such diverse forms of information in one place not only allows rapid discovery of significant information related to a specific protein kinase, but also enables large-scale integrative analysis of protein kinase data in ways not possible through other kinase-specific resources. We have performed several integrative analyses of ProKinO data and, as an example, found that a large number of somatic mutations (∼288 distinct mutations) associated with the haematopoietic neoplasm cancer type map to only 8 kinases in the human kinome. This is in contrast to glioma, where the mutations are spread over 82 distinct kinases. We also provide examples of how ontology-based data analysis can be used to generate testable hypotheses regarding cancer mutations. CONCLUSION: We present an integrated framework for large-scale integrative analysis of protein kinase data. Navigation and analysis of ontology data can be performed using the ontology browser available at: http://vulcan.cs.uga.edu/prokino.

Muscle Eye Brain Disease; a Rare Form of Syndromic Congenital Muscular Dystrophy

Congenital muscular dystrophy (CMD) is a heterogeneous group of disorders characterized by muscular hypotonia since birth and the histologic features of muscular dystrophy. Syndromic congenital muscular dystrophies are clinically similar autosomal recessive disorders characterized by congenital muscular dystrophy, lissencephaly, and eye anomalies. We present a case of a rare form of syndromic congenital muscular dystrophy in an eight year old girl, born of firstdegree consanguinity. She had: global develop