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An association of European kidney specialists whose objective is advancement of medical science and of clinical work in nephrology, dialysis, renal transplantation, hypertension and related subjects. They aim at providing up-to-date knowledge, exclusively based on scientific data, independent from governments'' policies and from any influence of the industry. It is registered in England and Wales, but its area of activity mainly covers Europe and the Mediterranean area.
Proper citation: ERA-EDTA (RRID:SCR_003982) Copy
Initiative to develop a systematic, evidence-based process for evaluating genetic tests and other applications of genomic technology that are rapidly moving from research to use in clinical practice. A key objective of this process is to provide objective, timely, and credible information that is clearly linked to the scientific evidence on specific applications of genetic and genomic tests. The primary focus of EGAPP activities is an independent, nonfederal expert panel, the EGAPP Working Group. Other components of the EGAPP initiative include a federal interagency, the CDC staff and consultants, and an EGAPP initiative evaluation team.
Proper citation: EGAPP (RRID:SCR_004189) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023.Digital collection of images, with themes ranging from medical and social history to contemporary healthcare and biomedical science. The collection contains historical images from the Wellcome Library collections, Tibetan Buddhist paintings, ancient Sanskrit manuscripts written on palm leaves, beautifully illuminated Persian books and much more. The Biomedical Collection holds over 40 000 high-quality images from the clinical and biomedical sciences. Selected from the UK''s leading teaching hospitals and research institutions, it covers disease, surgery, general healthcare, sciences from genetics to neuroscience including the full range of imaging techniques. They are always looking for new high quality biomedical images from scientific researchers, clinical photographers and artists in any field of science or medicine. As a contributor you retain your original material and copyright, and receive commission and full credit each time your images are used. The annual Wellcome Images awards (previously known as Biomedical Images Awards) reward contributors for their outstanding work and winners are chosen by a panel of experts. The resulting public exhibitions are always extremely popular and receive widespread acclaim. All images on the Wellcome Images site are available free for use in: * private study and non-commercial research * examination papers * criticism and review, this applies only where there are no multiple copies made * theses submitted by a student at a higher or further education institution for the purposes of securing a degree * personal use by private individuals
Proper citation: Wellcome Images (RRID:SCR_004181) Copy
http://www.transformproject.eu/portfolio-item/d6-2-clinical-research-information-model/
A clinical research information model for the integration of clinical research covering randomized clinical trials (RCT), case-control studies and database searches into the TRANSFoRm application development. TRANSFoRm clinical research is based on primary care data, clinical data and genetic data stored in databases and electronic health records and employs the principle of reusing primary care data, adapting data collection by patient reported outcomes (PRO) and eSource based Case Report Forms. CRIM was developed using the TRANSFoRm clinical use cases of GORD and Diabetes. Their use case driven approach consisted of three levels of modelling drawing heavily on the clinical research workflow of the use cases. Different available information models were evaluated for their usefulness to represent TRANSFoRm clinical research, including for example CTOM of caBIG, Primary Care Research Object Model (PRCOM) of ePCRN and BRIDG of CDISC. The PCROM model turned out to be the most suitable and it was possible to extend and modify this model with only 12 new information objects, 3 episode of care related objects and 2 areas to satisfy all requirements of the TRANSFoRm research use cases. Now the information model covers Good Clinical Practice (GCP) compliant research, as well as case control studies and database search studies, including the interaction between patient and GP (family doctor) during patient consultation, appointment, screening, patient recruitment and adverse event reporting.
Proper citation: TRANSFoRm Clinical Research Information Model (RRID:SCR_003889) Copy
Society devoted to the advancement of the field of dialysis access through research, education and advocacy for patients with end stage kidney disease. They provide vascular access education for physicians, nurses, and other health care professionals and advocate for evidenced-based best clinical practices.
Proper citation: Vascular Access Society of the Americas (RRID:SCR_004058) Copy
A consortium that aims to transform cancer research through collaborative oncology trials that leverage the scientific and clinical expertise of the Big Ten universities. The goal is to align the conduct of cancer research through collaborative, hypothesis-driven, highly translational oncology trials that leverage the scientific and clinical expertise. The clinical trials that will be developed will be linked to molecular diagnostics, enabling researchers to understand what drives the cancers to grow and what might be done to stop them from growing. The consortium also leverages geographical locations and existing relationships among the cancer centers. One of the consortium's goals is to harmonize contracts and scientific review processes to expedite clinical trials. The consortium will only focus on phase 0 to II trials because larger trials - even a randomized phase II trial - are difficult to conduct at a single cancer center.
Proper citation: Big Ten Cancer Research Consortium (RRID:SCR_004025) Copy
Consortium that created the capability to detect Adverse Drug Response (ADR) signals by creating the infrastructure for large-scale monitoring of drug safety using electronic health records (EHR). The platform leverages EHR''''s comprising demographics, drug use and clinical data of over 30 million patients from several European countries. Special attention was given to patient groups that are not routinely involved in clinical trials, for ethical or practical reasons (e.g. pregnant women, elderly people, people using many drugs simultaneously, and children). This project also studies and compares a number of different techniques that all aim to detect unexpected or disproportional rates of events. The algorithms that they studied originate not only from the field of (pharmaco)epidemiology, but also from fields such as bio-terrorism, machine learning, and classical signal detection. EU-ADR specific objectives are: To detect events, To relate these events to drugs, To develop hypothesis that explain adverse events, To detect adverse events earlier, and To avoid false positives. The web-based platform is available at https://bioinformatics.ua.pt/euadr/ EU-ADR has contributed to the ability to conduct better drug safety studies based on the re-use of healthcare data. By facilitating the early detection of adverse drug reactions, but also providing key information on populations at risk, potential drug interactions, potential underlying mechanisms and intervening pathways in adverse events, etc., the project will allow for improved and more complete information to be available for drug and healthcare delivery, leading to increased patient safety and its associated cost savings. The EU-ADR system can be considered as a complementary tool to already existing pharamcovigilance systems. Should the system be widespread in the long term, it has the potential to contribute to the development of future electronic health record systems, insofar as the expected benefits of these IT tools are only fully attainable when EHRs develop themselves in consistency, richness and formats that allow them to be subject of such tools. In anticipation, EU-ADR has been designed to be modular and scalable, so that different EHR databases (other than those participating in the Consortium) can be progressively enlisted in the future, adopt the software for data extraction and therefore become susceptible of exploitation by the system, for maximum global effect.
Proper citation: EU-ADR (RRID:SCR_004028) Copy
http://clinicaltrials.gov/show/NCT01211678
A consortium evaluating a new biomarker screening test that might help identify patients with rheumatoid arthritis (RA) who are unlikely to benefit from anti-tumor necrosis factor-alpha (TNFalpha) medications. BATTER-UP will enroll around 1,000 patients being treated by one of several marketed anti-TNF RA drugs: Enbrel, Remicade, Humira, Simponi, or Cimzia. Through data analyses and predictive response modeling, the consortium aims to better understand which patients with RA will derive the greatest benefit from TNF inhibitors. The investigators in this observational study will attempt to validate an 8-gene biomarker set based on work by Biogen Idec researchers as likely to predict anti-TNF responsiveness in patients with RA. In preliminary results, the 8-gene biomarker set predicted with 89% accuracy individuals who did not reach European League Against Rheumatism (EULAR) Disease Activity Score (DAS)-28 good response after 14 weeks of treatment. The 8 genes included in the screen are CLTB, MXRA7, CXorf52, COL4A3BP, YIPF6, FAM44A, SFRS2, and PGK1. Biological samples and clinical outcome information will be used to confirm and extend the utility of previously published biomarkers that can predict response to anti-TNF agents. These data may also generate new hypotheses for further testing. The BATTER-UP samples and data will be established as a reference set for investigation of personalized medicine in RA. The study will be a resource of DNA and other biological materials that can be investigated for biomarkers in the future as new technologies arise.
Proper citation: Biomarkers of Anti-TNF Treatment Efficacy in Rheumatoid Arthritis - Unresponsive Populations (RRID:SCR_004019) Copy
http://mips.gsf.de/services/genomes/uwe25/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. This is the official database of the environmental chlamydia genome project. This resource provides access to finished sequence for Parachlamydia-related symbiont UWE25 and to a wide range of manual annotations, automatical analyses and derived datasets. Functional classification and description has been manually annotated according to the Annotation guidelines. Chlamydiae are the major cause of preventable blindness and sexually transmitted disease. Genome analysis of a chlamydia-related symbiont of free-living amoebae revealed that it is twice as large as any of the pathogenic chlamydiae and had few signs of recent lateral gene acquisition. We showed that about 700 million years ago the last common ancestor of pathogenic and symbiotic chlamydiae was already adapted to intracellular survival in early eukaryotes and contained many virulence factors found in modern pathogenic chlamydiae, including a type III secretion system. Ancient chlamydiae appear to be the originators of mechanisms for the exploitation of eukaryotic cells. Environmental chlamydiae have recently been recognized as obligate endosymbionts of free-living amoebae and have been implicated as potential human pathogens. Environmental chlamydiae form a deep branching evolutionary lineage within the medically important order Chlamydiales. Despite their high diversity and ubiquitous distribution in clinical and environmental samples only limited information about genetics and ecology of these microorganisms is available. The Parachlamydia-related Acanthamoeba symbiont UWE25 was therefore selected as representative environmental chlamydia strain for whole genome sequencing. Comparative genome analysis was performed using PEDANT and simap. Sponsors: The environmental chlamydia genome project was funded by the bmb+f (German Federal Ministry of Education and Research) and is part of the Competence Network PathoGenoMiK.
Proper citation: Protochlamydia amoebophila UWE25 (RRID:SCR_008222) Copy
http://dtp.nci.nih.gov/docs/3d_database/dis3d.html
The NCI DIS 3D database is a collection of 3D structures for over 400,000 drugs. The database is an extension of the NCI Drug Information System. The structural information stored in the DIS is only the connection table for each drug. The connection table is just a list of which atoms are connected and how they are connected. It is essentially a searcheable database of three-dimensional structures has been developed from the chemistry database of the NCI Drug Information System (DIS), a file of about 450,000 primarily organic compounds which have been tested by NCI for anticancer activity. The DIS database is very similar in size and content to the proprietary databases used in the pharmaceutical industry; its development began in the 1950s; and this history led to a number of problems in the generation of 3D structures. This information can be searched to find drugs that share similar patterns of connections, which can correlate with similar biological activity. But the cellular targets for drug action, as well as the drugs themselves, are 3 dimensional objects and advances in computer hardware and software have reached the point where they can be represented as such. In many cases the important points of interaction between a drug and its target can be represented by a 3D arrangement of a small number of atoms. Such a group of atoms is called a pharmacophore. The pharmacophore can be used to search 3D databases and drugs that match the pharmacophore could have similar biological activity, but have very different patterns of atomic connections. Having a diverse set of lead compounds increases the chances of finding an active compound with acceptable properties for clinical development. Sponsor: The ICBG are supported by the Cooperative Agreement mechanism, with funds from nine components of the NIH, the National Science Foundation, and the Foreign Agricultural Service of the USDA.
Proper citation: National Cancer Institute 3D Structure Database (RRID:SCR_008211) Copy
A database housing longitudinal relational research data from over 4,000 research subjects. The database includes the following types of data: physical and neurological exam findings, neurocognitive test scores, personal and family history of dementia, personal demographic genotypes (APOE, HLA), age at service evaluations, age at onset, age at death, clinical diagnosis, neuropathology diagnosis, tissue inventory information (when available), health status, medications, laboratory tests, and MRI data.
Proper citation: Layton Center Clinical Data Resources (RRID:SCR_008822) Copy
http://www.cnio.es/ES/grupos/plantillas/presentacion.asp?grupo=50004308
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The need to use human neoplastic tissue under ideal conditions is currently of particular importance due to the development molecular pathology techniques that allow large-scale studies of genetic expression that are also of clinical significance. The Tumour Bank Network (TBN), instigated and coordinated by the Molecular Pathology Programme (MMP) aims to respond to this need by the promoting of Tumour Banks in Spanish hospitals. This will be achieved through the application of homogeneous procedures for the collection, processing and storage of neoplastic and normal tissue samples in such a way as to make molecular studies possible, avoiding that avoid the intrinsic bias of multi-centre studies possible. These Hospital Tumour Banks are based within the Pathology Departments of the collaborating Hospitals, that are interconnected through a computer-based network. In this way, each Centre''s tissue remains in the Hospital itself, thereby playing a key role in the development of the welfare, teaching and research activities within the Hospital. At the same time, it represents a tool to encourage of multi-hospital cancer research and of cooperation between basic and clinical researchers, constituting important collaboration between biomedical disciplines. The design does not correspond to a Central Tumour Bank, but that of a cooperative and coordinated Network of Hospital Banks, based on simple, homogeneous and optimal tissue treatment protocols. This Network is promoted by the Centro Nacional de Investigaciones Oncologicas (CNIO), which thereby undertakes the work of coordinating the network, using and maintaining the database, adhering to quality control. The aim of the CNIO's TBN is to acquire neoplastic and control non-neoplastic material of all types of malignant neoplasias, in the form of tissue fixed in formalin and paraffin embedded, of samples that are unfixed or frozen according to conventional methods as set out in Annexe 1 and even, exceptionally as fresh tissue. When other types of samples are required to carry out a specific project, the central office of the TBN will draw up a protocol with the group leading the project for the collection and maintenance of the tissue and clinicopathological data required for the proposed research. These protocols will be disseminated among the Associated Hospitals in order to gather the previously agreed number cases. Basic data surrounding the processing and preservation conditions for each case will be sent to the central office of the Bank, which under no circumstances will reveal the identity of the patient. Any Spanish cancer research team will be able to request tissue from the Tissue Bank Network. Absolute priority will be afforded to projects whose principal researcher belongs to one of the Associated Centres of the TNB, to other institutions with special agreements concerning the exchange of samples, and to the CNIO's researchers.
Proper citation: Spanish National Tumour Bank Network (RRID:SCR_008707) Copy
http://www.vaccineinjury.info/vaccine-damage-reports-2010.html
Database of case reports of adverse reactions to vaccinations. There are 806 reports (May 2013). If you would like to report a case, please go to report your own vaccine reaction. The user may search by keywords or sort by vaccine, country, age, outcome, gender and hospital admission.
Proper citation: Vaccine damage reports database (RRID:SCR_010740) Copy
https://genome-cancer.ucsc.edu/
A suite of web-based tools to visualize, integrate and analyze cancer genomics and its associated clinical data. It is possible to display your own clinical data within one of their datasets.
Proper citation: UCSC Cancer Genomics Browser (RRID:SCR_011796) Copy
http://www.scienceexchange.com/facilities/specimen-bank-bwh-harvard
Core facility that provides the following services: Open repositories service, Sample processing service, Medical/pathology informatics support service, BWH tissue repository service.
The Specimen Bank provides materials to investigators with IRB-approved protocols. Staff are available to assist with selection of samples appropriate for downstream applications, development of processing protocols or preparation of derivatives from clinical materials. IT Staff are also available to assist researchers with creation of queries for prospective sample collection or queries to select samples from specific cohorts. Their goal is to drive quality research in an efficient and cost-effective manner. Each year they provide tens of thousands of samples to area researchers. Getting started: Partners investigators and study staff may request a Crimson user account to help manage studies and collected materials.
Proper citation: BWH Specimen Bank (RRID:SCR_012316) Copy
http://tcm.lifescience.ntu.edu.tw/index.html
TCMGeneDIT is a database system providing association information about traditional Chinese medicines (TCMs), genes, diseases, TCM effects and TCM ingredients automatically mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information collected from public databases are also available. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in deducing possible synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. TCMGeneDIT is a unique database of various association information about TCMs. The database integrating TCMs with life sciences and biomedical studies would facilitate the modern clinical research and the understanding of therapeutic mechanisms of TCMs and gene regulations.
Proper citation: TCMGeneDIT (RRID:SCR_013396) Copy
Core whose aim is to translate basic science research into effective diagnostic and therapeutic strategies that will improve the lives of patients by interrupting the pathogenesis of chronic kidney disease and its attendant high risk of cardiovascular disability and death. It combines comprehensive human genetics with phenotyping of subjects.
Proper citation: George M. O'Brien Kidney Research Core Center - UT Southwestern Medical Center Clinical and Translational Core (RRID:SCR_015295) Copy
http://cunorc.org/cores/clinical-core/
Core facility for the University of Colorado Anschutz Medical Campus Nutrition and Obesity Research Center. Core provides NORC members assistance with clinical research studies involving modification of body weight.
Proper citation: University of Colorado Anschutz Medical Campus Nutrition and Obesity Research Center Clinical Intervention and Translation Core Facility (RRID:SCR_015912) Copy
https://sdrc.stanford.edu/sdrc-research-cores/dctc/home/
With the following services from the Diabetes Clinical and Translational Core (DCTC), members will receive training in biospecimen preservation, study design, data analysis, data management, use of statistical software and clinical trial conduct.
Proper citation: Stanford Diabetes Research Center Diabetes Clinical and Translational Core (RRID:SCR_016212) Copy
https://sdrc.stanford.edu/sdrc-research-cores/dimc/home/
Core facility that provides immune monitoring assays at the RNA, protein, and cellular level, as well as archiving, reporting, and data mining support for clinical and translational studies related to Diabetes. The DIMC is a specialized subcore of the Human Immune Monitoring Center (HIMC) at Stanford.
Proper citation: Stanford Diabetes Research Center Diabetes Immune Monitoring Core (RRID:SCR_016210) Copy
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