Dataset for reporting of carcinoma of the urethra (in urethrectomy specimens): recommendations from the International Collaboration on Cancer Reporting (ICCR)

The International Collaboration on Cancer Reporting (ICCR) is a not‐for‐profit organisation sponsored by the Royal Colleges of Pathologists of Australasia and the United Kingdom, the College of American Pathologists, the Canadian Association of Pathologists in association with the Canadian Partnership Against Cancer, the European Society of Pathology, the American Society of Clinical Pathology and the Faculty of Pathology, Royal College of Physicians of Ireland. Its goal is to produce standardised, internationally agreed‐upon, evidence‐based datasets for cancer pathology reporting throughout the world. This paper describes the development of a cancer dataset by the multidisciplinary ICCR expert panel for the reporting of carcinoma of the urethra in urethrectomy specimens. The dataset is composed of ‘required’ (mandatory) and ‘recommended’ (non‐mandatory) elements, which are based on a review of the most recent evidence and supported by explanatory commentary. Fourteen required elements and eight recommended elements were agreed by the international dataset authoring committee to represent the essential/required (core) and recommended (non‐core) information for the reporting of carcinoma of the urethra in urethrectomy specimens. Use of an internationally agreed, structured pathology dataset for reporting carcinoma of the urethra (in urethrectomy specimens) will provide the necessary information for optimal patient management, will facilitate consistent data collection and will provide valuable data for research and international benchmarking. The dataset will be valuable for those countries and institutions that are not in a position to develop their own datasets.     

Open source platform for collaborative construction of wearable sensor datasets for human motion analysis and an application for gait analysis

Nearly every practical improvement in modeling human motion is well founded in a properly designed collection of data or datasets. These datasets must be made publicly available for the community could validate and accept them. It is reasonable to concede that a collective, guided enterprise could serve to devise solid and substantial datasets, as a result of a collaborative effort, in the same sense as the open software community does. In this way datasets could be complemented, extended and expanded in size with, for example, more individuals, samples and human actions. For this to be possible some commitments must be made by the collaborators, being one of them sharing the same data acquisition platform.In this paper, we offer an affordable open source hardware and software platform based on inertial wearable sensors in a way that several groups could cooperate in the construction of datasets through common software suitable for collaboration. Some experimental results about the throughput of the overall system are reported showing the feasibility of acquiring data from up to 6 sensors with a sampling frequency no less than 118 Hz. Also, a proof-of-concept dataset is provided comprising sampled data from 12 subjects suitable for gait analysis.     

Characterisation of data resources for in silico modelling: benchmark datasets for ADME properties

Introduction: The cost of in vivo and in vitro screening of ADME properties of compounds has motivated efforts to develop a range of in silico models. At the heart of the development of any computational model are the data; high quality data are essential for developing robust and accurate models. The characteristics of a dataset, such as its availability, size, format and type of chemical identifiers used, influence the modelability of the data.

Areas covered: This review explores the usefulness of publicly available ADME datasets for researchers to use in the development of predictive models. More than 140 ADME datasets were collated from publicly available resources and the modelability of 31 selected datasets were assessed using specific criteria derived in this study.

Expert opinion: Publicly available datasets differ significantly in information content and presentation. From a modelling perspective, datasets should be of adequate size, available in a user-friendly format with all chemical structures associated with one or more chemical identifiers suitable for automated processing (e.g. CAS number, SMILES string or InChIKey). Recommendations for assessing dataset suitability for modelling and publishing data in an appropriate format are discussed.     

乳腺癌中KIF4A基因表达的临床意义及基因富集分析

目的 探讨驱动蛋白超家族4A （kinesin family member 4A,KIF4A）在乳腺癌中的表达及与临床病理特征、预后的关系。方法 利用GEO数据库的GSE3494公共数据集和TCGA数据库的乳腺癌样本及其临床资料,采用χ²检验进行KIF4A与临床病理特征的相关性分析,Kaplan-Meier法进行生存分析。通过基因富集分析预测乳腺癌中高表达KIF4A所富集的基因集。结果 KIF4A在不同Elston组织学分级和TNM分期的乳腺癌肿瘤样本中表达差异有统计学意义（P=0.000）。GSE3494和TCGA数据库中KIF4A与ER水平、PR水平均显著相关（P=0.000）;与年龄仅TCGA数据库分析结果差异有统计学意义（P=0.000）。此外,GSE3494数据集中,KIF4A与肿瘤大小、淋巴结浸润均显著相关（P=0.000）;TCGA数据库中,KIF4A仅与T分期显著相关（P=0.000）,与N分期（P=0.081）、M分期（P=0.372）均不相关。KIF4A高表达的乳腺癌患者预后较差,其疾病特异生存期（P=0.001）和总体生存率（P=0.005）均远低于KIF4A低表达患者,且富集了与细胞分裂、细胞周期调控、DNA复制及DNA损伤修复有关的基因集。结论 KIF4A与乳腺癌多个临床病理指标相关,可作为潜在的乳腺癌预后标志物和治疗靶标进一步研究。     

National Emergency Medical Services Information System (NEMSIS)

The absence of emergency medical services (EMS) patient care data has hindered development andevaluation of EMS systems. The National Highway Traffic Safety Administration (NHTSA), in cooperation with the Health Resources andServices Administration (HRSA), has provided funding to the National Association of State EMS Directors to develop a National EMS Information System (NEMSIS). NEMSIS is being designed to provide a uniform national EMS dataset, with standard terms, definitions, andvalues, as well as a national EMS database, with aggregated data from all states on a limited number of data elements. Forty-eight of the states, the District of Columbia, andthree territories signed a memorandum of agreement documenting support for the NEMSIS project andexpressing a desire for full implementation of the NEMSIS dataset. NHTSA has agreed to house the National EMS Database at its National Center for Statistics andAnalysis. NHTSA, in cooperation with HRSA andthe Centers for Disease Control andPrevention, recently entered into a cooperative agreement with the University of Utah School of Medicine to operate a NEMSIS Technical Assistance Center that will provide related assistance to official EMS agencies andto commercial software vendors. The Technical Assistance Center will also biannually assess state andterritorial capabilities to provide data to the national EMS database. NEMSIS will provide a uniform national EMS dataset, with standard terms, definitions, andvalues, as well as a national EMS database, with aggregated data from all states on a limited number of data elements. Many of the potential benefits of implementation of NEMSIS are enumerated in this report.     

Enrichment map profiling of the cancer invasion front suggests regulation of colorectal cancer progression by the bone morphogenetic protein antagonist,gremlin-1

The cancer invasion front (CIF), a spatially-recognized area due to the frequent presence of peritumoral desmoplastic reaction, represents a cancer site where many hallmarks of cancer metastasis occur. It is now strongly suggested that the desmoplastic microenvironment holds crucial information for determining tumor development and progression. Despite extensive research on tumor-host cell interactions at CIFs, the exact paracrine molecular network that is hardwired into the proteome of the stromal and cancer subpopulations remains partially understood. Here, we interrogated the signaling pathways and the molecular functional signatures across the proteome of a desmoplastic coculture model system of colorectal cancer progression. We discovered a group of bone morphogenetic protein (BMP) antagonists that coordinates major biological programs in CIFs, including cell proliferation, invasion, migration and differentiation processes. Using a mathematical model of cancer cell progression, coupled to in vitro cell migration assays, we demonstrated that the prominent BMP antagonist gremlin-1 (GREM1) may trigger motility of cancer cell cohorts. Our data collectively demonstrate that the desmoplastic CIFs deploy a microenvironmental signature, based on BMP antagonism, in order to regulate the motogenic fates of cancer cell cohorts invading the adjacent stroma.