Cultivating employees' communal relationship and organizational citizenship behavior through authentic leadership: studying the influence of procedural justice.

BACKGROUND: Leaders play vital role in organization to accomplish organizational goals and establish healthy working environment. This study addresses the effect of authentic leadership on employees' communal relationship and organizational citizenship behavior (OCB). In addition, this research also examines how procedural justice augments the effect of authentic leadership on both aforementioned employees' behavioral outcomes. MATERIALS AND METHODS: Using a cross-sectional design, data were collected from 425 employees working in banking sector of Pakistan. It was hypothesized that authentic leadership would positively predict employees' communal relationship and OCB. Furthermore, we also assumed that procedural justice will strengthen the relationship between authentic leadership, both behavioral outcomes, that is, employees' communal relationship and OCB. RESULTS: Analyses reveal that authentic leadership positively predicts employees' communal relationship and OCB. In addition, procedural justice was found to positively moderate the effect of authentic leadership on employees' communal relationship and OCB. CONCLUSION: To our knowledge, this is the first study to investigate the relationships among authentic leadership, procedural justice, communal relationship, and OCBs in the South Asian context. This is the first study to report the moderating role of procedural justice in the relationship between authentic leadership and communal relationship and OCB. The practical implications of study findings and direction for future research are discussed.

Towards precision medicine: discovering novel gynecological cancer biomarkers and pathways using linked data.

BACKGROUND: Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing a massive amount of sequencing datasets. Often, these datasets are published from the isolated and different sequencing facilities. Consequently, the process of sharing and aggregating multisite sequencing datasets are thwarted by issues such as the need to discover relevant data from different sources, built scalable repositories, the automation of data linkage, the volume of the data, efficient querying mechanism, and information rich intuitive visualisation. RESULTS: We present an approach to link and query different sequencing datasets (TCGA, COSMIC, REACTOME, KEGG and GO) to indicate risks for four cancer types - Ovarian Serous Cystadenocarcinoma (OV), Uterine Corpus Endometrial Carcinoma (UCEC), Uterine Carcinosarcoma (UCS), Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) - covering the 16 healthy tissue-specific genes from Illumina Human Body Map 2.0. The differentially expressed genes from Illumina Human Body Map 2.0 are analysed together with the gene expressions reported in COSMIC and TCGA repositories leading to the discover of potential biomarkers for a tissue-specific cancer. CONCLUSION: We analyse the tissue expression of genes, copy number variation (CNV), somatic mutation, and promoter methylation to identify associated pathways and find novel biomarkers. We discovered twenty (20) mutated genes and three (3) potential pathways causing promoter changes in different gynaecological cancer types. We propose a data-interlinked platform called BIOOPENER that glues together heterogeneous cancer and biomedical repositories. The key approach is to find correspondences (or data links) among genetic, cellular and molecular features across isolated cancer datasets giving insight into cancer progression from normal to diseased tissues. The proposed BIOOPENER platform enriches mutations by filling in missing links from TCGA, COSMIC, REACTOME, KEGG and GO datasets and provides an interlinking mechanism to understand cancer progression from normal to diseased tissues with pathway components, which in turn helped to map mutations, associated phenotypes, pathways, and mechanism.

Paraneoplastic Cushing Syndrome Due To Wilm's Tumor.

Paraneoplastic syndromes are rare disorders that are triggered by an altered immune system response to neoplasm. Paraneoplastic syndromes may be the first or the most prominent manifestations of cancer. Wilm's tumor is the most frequent pediatric renal malignancy and usually presents with abdominal mass. Unusual presentations like acquired von Willebrand disease, sudden death due to pulmonary embolism and Cushing syndrome have been described in the literature. Cushing syndrome, as the presenting symptom of a malignant renal tumor in children, is a very rare entity. Few case reports are available in the literature exploring the option of preoperative chemotherapy as well as upfront nephrectomy. We report a rare case of paraneoplastic Cushing syndrome due to a Wilm's tumor. Based on gradual decrease of postoperative weight, blood pressure, serum adrenocorticotropic hormone, and plasma cortisol levels, along with histological confirmation of Wilm's tumor, paraneoplastic Cushing syndrome due to Wilm's tumor was confirmed.

BioFed: federated query processing over life sciences linked open data.

BACKGROUND: Biomedical data, e.g. from knowledge bases and ontologies, is increasingly made available following open linked data principles, at best as RDF triple data. This is a necessary step towards unified access to biological data sets, but this still requires solutions to query multiple endpoints for their heterogeneous data to eventually retrieve all the meaningful information. Suggested solutions are based on query federation approaches, which require the submission of SPARQL queries to endpoints. Due to the size and complexity of available data, these solutions have to be optimised for efficient retrieval times and for users in life sciences research. Last but not least, over time, the reliability of data resources in terms of access and quality have to be monitored. Our solution (BioFed) federates data over 130 SPARQL endpoints in life sciences and tailors query submission according to the provenance information. BioFed has been evaluated against the state of the art solution FedX and forms an important benchmark for the life science domain. METHODS: The efficient cataloguing approach of the federated query processing system 'BioFed', the triple pattern wise source selection and the semantic source normalisation forms the core to our solution. It gathers and integrates data from newly identified public endpoints for federated access. Basic provenance information is linked to the retrieved data. Last but not least, BioFed makes use of the latest SPARQL standard (i.e., 1.1) to leverage the full benefits for query federation. The evaluation is based on 10 simple and 10 complex queries, which address data in 10 major and very popular data sources (e.g., Dugbank, Sider). RESULTS: BioFed is a solution for a single-point-of-access for a large number of SPARQL endpoints providing life science data. It facilitates efficient query generation for data access and provides basic provenance information in combination with the retrieved data. BioFed fully supports SPARQL 1.1 and gives access to the endpoint's availability based on the EndpointData graph. Our evaluation of BioFed against FedX is based on 20 heterogeneous federated SPARQL queries and shows competitive execution performance in comparison to FedX, which can be attributed to the provision of provenance information for the source selection. CONCLUSION: Developing and testing federated query engines for life sciences data is still a challenging task. According to our findings, it is advantageous to optimise the source selection. The cataloguing of SPARQL endpoints, including type and property indexing, leads to efficient querying of data resources over the Web of Data. This could even be further improved through the use of ontologies, e.g., for abstract normalisation of query terms.

SAFE: SPARQL Federation over RDF Data Cubes with Access Control.

BACKGROUND: Several query federation engines have been proposed for accessing public Linked Open Data sources. However, in many domains, resources are sensitive and access to these resources is tightly controlled by stakeholders; consequently, privacy is a major concern when federating queries over such datasets. In the Healthcare and Life Sciences (HCLS) domain real-world datasets contain sensitive statistical information: strict ownership is granted to individuals working in hospitals, research labs, clinical trial organisers, etc. Therefore, the legal and ethical concerns on (i) preserving the anonymity of patients (or clinical subjects); and (ii) respecting data ownership through access control; are key challenges faced by the data analytics community working within the HCLS domain. Likewise statistical data play a key role in the domain, where the RDF Data Cube Vocabulary has been proposed as a standard format to enable the exchange of such data. However, to the best of our knowledge, no existing approach has looked to optimise federated queries over such statistical data. RESULTS: We present SAFE: a query federation engine that enables policy-aware access to sensitive statistical datasets represented as RDF data cubes. SAFE is designed specifically to query statistical RDF data cubes in a distributed setting, where access control is coupled with source selection, user profiles and their access rights. SAFE proposes a join-aware source selection method that avoids wasteful requests to irrelevant and unauthorised data sources. In order to preserve anonymity and enforce stricter access control, SAFE's indexing system does not hold any data instances-it stores only predicates and endpoints. The resulting data summary has a significantly lower index generation time and size compared to existing engines, which allows for faster updates when sources change. CONCLUSIONS: We validate the performance of the system with experiments over real-world datasets provided by three clinical organisations as well as legacy linked datasets. We show that SAFE enables granular graph-level access control over distributed clinical RDF data cubes and efficiently reduces the source selection and overall query execution time when compared with general-purpose SPARQL query federation engines in the targeted setting.

Intrarenal neuroblastoma: a diagnostic challenge.

Abdominal masses in children are usually retroperitoneal in location and 50% are renal in origin. In infants less than 2 months, majority of renal masses are benign; frequency of malignancy increases with age. Wilms'tumor is the commonest solid intrarenal tumors. However, occasionally neuroblastoma occurs in the kidney. Neuroblastoma in 50% of cases presents before 2 years of age, and 75% before 4 years. Neuroblastomas can occur anywhere along the neuroectodermal sympathetic chain, although adrenal medulla is the commonest site (50 - 70%). Intrarenal neuroblastoma is a rare clinical diagnosis. It clinically and radiologically mimics Wilms'tumor and it is difficult to differentiate between the two preoperatively. Lung metastasis and vascular invasion are also rare in neuroblastoma but rather common in Wilms'tumor. We present case of a patient who had extensive renal involvement with neuroblastoma and pulmonary metastasis, clinically and radiologically it was difficult to differentiate between the Wilms'tumor and neuroblastoma.

Primary renal Ewing's sarcoma: a rare entity.

Ewing's sarcoma, a primitive neuroectodermal tumour is a rare entity belonging to a family of neoplasms of neuroectodermal origin. These highly aggressive neoplasms primarily affect older children and young adults. They primarily involve the bones or soft tissues. A quarter of Ewing's sarcomas occur principally in the soft tissues with primary involvement of the kidney being exceptionally rare. We hereby, present a case of 6 years old girl child with primary Ewing's sarcoma of the kidney who presented with abdominal mass and posed much diagnostic challenge. The patient underwent complete surgical excision of tumour, and is being treated with aggressive adjuvant chemotherapy.