Molecular Origins of the Mendelian Rare Diseases Reviewed by Orpha.net: A Structural Bioinformatics Investigation.

The study of rare diseases is important not only for the individuals affected but also for the advancement of medical knowledge and a deeper understanding of human biology and genetics. The wide repertoire of structural information now available from reliable and accurate prediction methods provides the opportunity to investigate the molecular origins of most of the rare diseases reviewed in the Orpha.net database. Thus, it has been possible to analyze the topology of the pathogenic missense variants found in the 2515 proteins involved in Mendelian rare diseases (MRDs), which form the database for our structural bioinformatics study. The amino acid substitutions responsible for MRDs showed different mutation site distributions at different three-dimensional protein depths. We then highlighted the depth-dependent effects of pathogenic variants for the 20,061 pathogenic variants that are present in our database. The results of this structural bioinformatics investigation are relevant, as they provide additional clues to mitigate the damage caused by MRD.

Development of an Indian Food Composition Database.

An open-access and comprehensive nutrient database is not available in India. Our objective was to develop an open-access Indian Nutrient Databank (INDB). The development of the INDB consisted of 2 stages: creating a database of the nutrient composition data of individual food items (n = 1095) and a database of commonly consumed recipes (n = 1014). The stage 1 database was primarily derived from the Indian Council of Medical Research-National Institute of Nutrition's Indian Food Composition Table (ICMR-NIN IFCT) from 2017, with gaps filled using the ICMR-NIN IFCT 2004 and nutrient databases from the United Kingdom and United States. The stage 2 database included information on the amounts of each ingredient used in each recipe, matched to a comparable item in the database from stage 1. This unique open-access resource can be used by researchers, the government, and the private and third sectors to derive nutrient intakes in India to better inform interventions and policies to address malnutrition.

Genetic network analysis indicate that individuals affected by neurodevelopmental conditions have genetic variations associated with ophthalmologic alterations: A critical review of literature.

Changes in the nervous system are related to a wide range of mental disorders, which include neurodevelopmental disorders (NDD) that are characterized by early onset mental conditions, such as schizophrenia and autism spectrum disorders and correlated conditions (ASD). Previous studies have shown distinct genetic components associated with diverse schizophrenia and ASD phenotypes, with mostly focused on rescuing neural phenotypes and brain activity, but alterations related to vision are overlooked. Thus, as the vision is composed by the eyes that itself represents a part of the brain, with the retina being formed by neurons and cells originating from the glia, genetic variations affecting the brain can also affect the vision. Here, we performed a critical systematic literature review to screen for all genetic variations in individuals presenting NDD with reported alterations in vision. Using these restricting criteria, we found 20 genes with distinct types of genetic variations, inherited or de novo, that includes SNP, SNV, deletion, insertion, duplication or indel. The variations occurring within protein coding regions have different impact on protein formation, such as missense, nonsense or frameshift. Moreover, a molecular analysis of the 20 genes found revealed that 17 shared a common protein-protein or genetic interaction network. Moreover, gene expression analysis in samples from the brain and other tissues indicates that 18 of the genes found are highly expressed in the brain and retina, indicating their potential role in adult vision phenotype. Finally, we only found 3 genes from our study described in standard public databanks of ophthalmogenetics, suggesting that the other 17 genes could be novel target for vision diseases.

Dna forensic data bank, facts and perception: The Italian experience.

In 2016 the Italian National Dna database for forensic purposes finally went live. After seven years of "operational life", numbers and results are still scarce. The aim of the study is to evaluate the actual knowledge and perceived usefulness of this investigative tool among a significant sample of Italian magistrates. The research was conducted through the administration of an anonymous structured questionnaire to magistrates belonging to the Court of Milano. The overall picture emerging from the questionnaire is a worrying lack of preparation regarding the functioning of the Dna database among judges and public prosecutors. This situation affects the performance of the instrument. The authors believe that a specific and compulsory training for magistrates should be introduced.

A national repository of complete radiotherapy plans: design, Results, and experiences.

BACKGROUND: Previously, many radiotherapy (RT) trials were based on a few selected dose measures. Many research questions, however, rely on access to the complete dose information. To support such access, a national RT plan database was created. The system focuses on data security, ease of use, and re-use of data. This article reports on the development and structure, and the functionality and experience of this national database. METHODS AND MATERIALS: A system based on the DICOM-RT standard, DcmCollab, was implemented with direct connections to all Danish RT centres. Data is segregated into any number of collaboration projects. User access to the system is provided through a web interface. The database has a finely defined access permission model to support legal requirements. RESULTS: Currently, data for more than 14,000 patients have been submitted to the system, and more than 50 research projects are registered. The system is used for data collection, trial quality assurance, and audit data set generation.Users reported that the process of submitting data, waiting for it to be processed, and then manually attaching it to a project was resource intensive. This was accommodated with the introduction of triggering features, eliminating much of the need for users to manage data manually. Many other features, including structure name mapping, RT plan viewer, and the Audit Tool were developed based on user input. CONCLUSION: The DcmCollab system has provided an efficient means to collect and access complete datasets for multi-centre RT research. This stands in contrast with previous methods of collecting RT data in multi-centre settings, where only singular data points were manually reported. To accommodate the evolving legal environment, DcmCollab has been defined as a 'data processor', meaning that it is a tool for other research projects to use rather than a research project in and of itself.

COVID-19 vaccination in pregnancy: the impact of multimorbidity and smoking status on vaccine hesitancy, a cohort study of 25,111 women in Wales, UK.

BACKGROUND: Multimorbidity, smoking status, and pregnancy are identified as three risk factors associated with more severe outcomes following a SARS-CoV-2 infection, thus vaccination uptake is crucial for pregnant women living with multimorbidity and a history of smoking. This study aimed to examine the impact of multimorbidity, smoking status, and demographics (age, ethnic group, area of deprivation) on vaccine hesitancy among pregnant women in Wales using electronic health records (EHR) linkage. METHODS: This cohort study utilised routinely collected, individual-level, anonymised population-scale linked data within the Secure Anonymised Information Linkage (SAIL) Databank. Pregnant women were identified from 13th April 2021 to 31st December 2021. Survival analysis was employed to examine and compare the length of time to vaccination uptake in pregnancy by considering multimorbidity, smoking status, as well as depression, diabetes, asthma, and cardiovascular conditions independently. The study also assessed the variation in uptake by multimorbidity, smoking status, and demographics, both jointly and separately for the independent conditions, using hazard ratios (HR) derived from the Cox regression model. RESULTS: Within the population cohort, 8,203 (32.7%) received at least one dose of the COVID-19 vaccine during pregnancy, with 8,572 (34.1%) remaining unvaccinated throughout the follow-up period, and 8,336 (33.2%) receiving the vaccine postpartum. Women aged 30 years or older were more likely to have the vaccine in pregnancy. Those who had depression were slightly but significantly more likely to have the vaccine compared to those without depression (HR = 1.08, 95% CI 1.03 to 1.14, p = 0.002). Women living with multimorbidity were 1.12 times more likely to have the vaccine compared to those living without multimorbidity (HR = 1.12, 95% CI 1.04 to 1.19, p = 0.001). Vaccine uptakes were significantly lower among both current smokers and former smokers compared to never smokers (HR = 0.87, 95% CI 0.81 to 0.94, p < 0.001 and HR = 0.92, 95% CI 0.85 to 0.98, p = 0.015 respectively). Uptake was also lower among those living in the most deprived areas compared to those living in the most affluent areas (HR = 0.89, 95% CI 0.83 to 0.96, p = 0.002). CONCLUSION: Younger women, living without multimorbidity, current and former smokers, and those living in the more deprived areas are less likely to have the vaccine, thus, a targeted approach to vaccinations may be required for these groups. Pregnant individuals living with multimorbidity exhibit a slight but statistically significant reduction in vaccine hesitancy towards COVID-19 during pregnancy.

HostSeq: a Canadian whole genome sequencing and clinical data resource.

HostSeq was launched in April 2020 as a national initiative to integrate whole genome sequencing data from 10,000 Canadians infected with SARS-CoV-2 with clinical information related to their disease experience. The mandate of HostSeq is to support the Canadian and international research communities in their efforts to understand the risk factors for disease and associated health outcomes and support the development of interventions such as vaccines and therapeutics. HostSeq is a collaboration among 13 independent epidemiological studies of SARS-CoV-2 across five provinces in Canada. Aggregated data collected by HostSeq are made available to the public through two data portals: a phenotype portal showing summaries of major variables and their distributions, and a variant search portal enabling queries in a genomic region. Individual-level data is available to the global research community for health research through a Data Access Agreement and Data Access Compliance Office approval. Here we provide an overview of the collective project design along with summary level information for HostSeq. We highlight several statistical considerations for researchers using the HostSeq platform regarding data aggregation, sampling mechanism, covariate adjustment, and X chromosome analysis. In addition to serving as a rich data source, the diversity of study designs, sample sizes, and research objectives among the participating studies provides unique opportunities for the research community.

Understanding Views Around the Creation of a Consented, Donated Databank of Clinical Free Text to Develop and Train Natural Language Processing Models for Research: Focus Group Interviews With Stakeholders.

BACKGROUND: Information stored within electronic health records is often recorded as unstructured text. Special computerized natural language processing (NLP) tools are needed to process this text; however, complex governance arrangements make such data in the National Health Service hard to access, and therefore, it is difficult to use for research in improving NLP methods. The creation of a donated databank of clinical free text could provide an important opportunity for researchers to develop NLP methods and tools and may circumvent delays in accessing the data needed to train the models. However, to date, there has been little or no engagement with stakeholders on the acceptability and design considerations of establishing a free-text databank for this purpose. OBJECTIVE: This study aimed to ascertain stakeholder views around the creation of a consented, donated databank of clinical free text to help create, train, and evaluate NLP for clinical research and to inform the potential next steps for adopting a partner-led approach to establish a national, funded databank of free text for use by the research community. METHODS: Web-based in-depth focus group interviews were conducted with 4 stakeholder groups (patients and members of the public, clinicians, information governance leads and research ethics members, and NLP researchers). RESULTS: All stakeholder groups were strongly in favor of the databank and saw great value in creating an environment where NLP tools can be tested and trained to improve their accuracy. Participants highlighted a range of complex issues for consideration as the databank is developed, including communicating the intended purpose, the approach to access and safeguarding the data, who should have access, and how to fund the databank. Participants recommended that a small-scale, gradual approach be adopted to start to gather donations and encouraged further engagement with stakeholders to develop a road map and set of standards for the databank. CONCLUSIONS: These findings provide a clear mandate to begin developing the databank and a framework for stakeholder expectations, which we would aim to meet with the databank delivery.

Development and first results of a national databank on care and treatment outcome after traumatic brain injury.

PURPOSE: In absence of comprehensive data collection on traumatic brain injury (TBI), the German Society for Neurosurgery (DGNC) and the German Society for Trauma Surgery (DGU) developed a TBI databank for German-speaking countries. METHODS: From 2016 to 2020, the TBI databank DGNC/DGU was implemented as a module of the TraumaRegister (TR) DGU and tested in a 15-month pilot phase. Since its official launch in 2021, patients from the TR-DGU (intermediate or intensive care unit admission via shock room) with TBI (AIS head ≥ 1) can be enrolled. A data set of > 300 clinical, imaging, and laboratory variables, harmonized with other international TBI data collection structures is documented, and the treatment outcome is evaluated after 6- and 12 months. RESULTS: For this analysis, 318 patients in the TBI databank could be included (median age 58 years; 71% men). Falls were the most common cause of injury (55%), and antithrombotic medication was frequent (28%). Severe or moderate TBI were only present in 55% of patients, while 45% suffered a mild injury. Nevertheless, intracranial pathologies were present in 95% of brain imaging with traumatic subarachnoid hemorrhages (76%) being the most common. Intracranial surgeries were performed in 42% of cases. In-hospital mortality after TBI was 21% and surviving patients could be discharged after a median hospital stay of 11 days. At the 6-and 12 months follow-up, a favorable outcome was achieved by 70% and 90% of the participating TBI patients, respectively. Compared to a European cohort of 2138 TBI patients treated in the ICU between 2014 and 2017, patients in the TBI databank were already older, frailer, fell more commonly at home. CONCLUSION: Within five years, the TBI databank DGNC/DGU of the TR-DGU could be established and is since then prospectively enrolling TBI patients in German-speaking countries. With its large and harmonized data set and a 12-month follow-up, the TBI databank is a unique project in Europe, already allowing comparisons to other data collection structures and indicating a demographic change towards older and frailer TBI patients in Germany.

The effect of extended participation windows on attendance at cervical cancer screening.

Research has long since confirmed the benefits of regular cervical cancer screening (CCS) worldwide. However, some developed countries have low participation rates despite well-organized screening programs. Given that studies in Europe typically define participation in 12-month windows from an invitation, we evaluated both whether extending this defined time window could reveal the true participation rate and how sociodemographic determinants affect participation delays. This involved linking data from the Lifelines population-based cohort with CCS-related data from the Dutch Nationwide Pathology Databank and including data for 69 185 women eligible for screening in the Dutch CCS program between 2014 and 2018. We then estimated and compared the participation rates for 15- and 36-month time windows and categorized women by the primary screening window into timely participation (within 15 months) and delayed participation (within 15-36 months) groups, before performing multivariable logistic regression to evaluate the association between delayed participation and the sociodemographic determinants. Participation rates for the 15- and 36-month windows were 71.1% and 77.0%, respectively, with participation considered timely in 49 224 cases and delayed in 4047 cases. Delayed participation was associated with age 30-35 years (odds ratio [OR]: 2.88, 95 %CI: 2.67-3.11), higher education (OR: 1.50, 95 %CI: 1.35-1.67), the high-risk human papillomavirus test-based program (OR: 1.67, 95 %CI: 1.56-1.79), and pregnancy (OR: 4.61, 95 %CI: 3.88-5.48). These findings show that a 36-month window for monitoring attendance at CCS better reflects the actual participation rate by accommodating possible delayed uptake among younger, pregnant, and highly educated women.

Evaluating the cost of managing patients with cellulitis in Wales, UK: A 20-year population-scale study.

This study aimed to estimate costs associated with managing patients with cellulitis from the UK National Health Service (NHS) perspective. The analysis was undertaken through the Secure Anonymised Information Linkage Databank, which brings together population-scale, individual-level anonymised linked data from a wide range of sources, including 80% of primary care general practices within Wales (population coverage ~3.2 million). The data covered a 20-year period from 1999 to 2019. All patients linked to the relevant codes were tracked through primary care settings, recording the number of general practice visits (number of days with an event recorded) and number of in-patient stays. Resources were valued in monetary terms (£ sterling), with costs determined from national published sources of unit costs. These resources were then extrapolated out to reflect UK NHS costs. This is the first attempt to estimate the financial burden of cellulitis using routine data sources on a national scale. The estimated direct annual costs to the Welsh NHS (£28 554 338) are considerable. In-Patient events and length of stay costs are the main cost drivers, with annual Welsh NHS estimates of £19 664 126 with primary care events costing £8 890 212. Initiatives to support patients and healthcare professionals in identifying early signs/risks of cellulitis, improve the accuracy of initial diagnosis, prevent cellulitis recurrence, and improve evidence-based treatment pathways would result in major financial savings, to both the Welsh and UK NHS. In light of these findings, Wales has developed the innovative National Lymphoedema cellulitis Improvement Programme to address these burdens; providing a proactive model of cellulitis care.

Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration.

BACKGROUND: The CVD-COVID-UK consortium was formed to understand the relationship between COVID-19 and cardiovascular diseases through analyses of harmonised electronic health records (EHRs) across the four UK nations. Beyond COVID-19, data harmonisation and common approaches enable analysis within and across independent Trusted Research Environments. Here we describe the reproducible harmonisation method developed using large-scale EHRs in Wales to accommodate the fast and efficient implementation of cross-nation analysis in England and Wales as part of the CVD-COVID-UK programme. We characterise current challenges and share lessons learnt. METHODS: Serving the scope and scalability of multiple study protocols, we used linked, anonymised individual-level EHR, demographic and administrative data held within the SAIL Databank for the population of Wales. The harmonisation method was implemented as a four-layer reproducible process, starting from raw data in the first layer. Then each of the layers two to four is framed by, but not limited to, the characterised challenges and lessons learnt. We achieved curated data as part of our second layer, followed by extracting phenotyped data in the third layer. We captured any project-specific requirements in the fourth layer. RESULTS: Using the implemented four-layer harmonisation method, we retrieved approximately 100 health-related variables for the 3.2 million individuals in Wales, which are harmonised with corresponding variables for > 56 million individuals in England. We processed 13 data sources into the first layer of our harmonisation method: five of these are updated daily or weekly, and the rest at various frequencies providing sufficient data flow updates for frequent capturing of up-to-date demographic, administrative and clinical information. CONCLUSIONS: We implemented an efficient, transparent, scalable, and reproducible harmonisation method that enables multi-nation collaborative research. With a current focus on COVID-19 and its relationship with cardiovascular outcomes, the harmonised data has supported a wide range of research activities across the UK.

Determining Current Medications Usage within a Cohort of Patients in the UK-A Descriptive Retrospective Study.

Swansea University's United Kingdom (UK) Multiple Sclerosis (MS) Register is a platform that contains information on more than 17,600 people with MS living in the UK. The register has been in operation since 2011 and represents comprehensive information about people living with MS in the UK. It is considered the first register of its kind that can link information from patients to clinical data and has been established to answer different information needs about MS. Aim: To elucidate the trends in patterns of medicines currently used by people with MS in the UK MS register. Methods: This study follows an exploratory descriptive design using the UK MS register as data resource. A number of 4516 people completed the EQ-5D survey out of 8736 people who have given their consent to answer online questionnaires which represents around 52% of the register total population. Descriptive analysis and tests were performed with SPSS to address the research objectives. Results: There are several medicine names entered by people with MS in their profiles. These medicines are used either to manage MS symptoms or to treat its associated complications. Among the medicine types revealed in this study, disease modifying drugs (DMDs), muscle relaxants, and anticonvulsants are the medicine types mainly used by people with MS followed by antidepressant and antianxiety medicines. Conclusions: From the antidepressants used most widely, amitriptyline was chosen as a subject medicine for further investigation in the remaining studies of this research due to its high frequency use, the elevated depression rates discovered among people with MS who seek information on it online, and the high online content noted on websites about this medicine.

Rationalisation of the UK Nutrient Databank for Incorporation in a Web-Based Dietary Recall for Implementation in the UK National Diet and Nutrition Survey Rolling Programme.

The UK National Diet and Nutrition Survey rolling programme (NDNS RP) commenced in 2008 and moved in 2019 from a traditional paper food diary to a web-based 24 h recall, Intake24. This paper describes the approach to update and downsize the underlying UK Nutrient Databank (NDB) for efficient data management and integration into Intake24. Consumption data from the first 10 years (2008/2009 to 2017/2018) of NDNS RP informed decisions on whether foods from the extensive UK NDB were to be retained, excluded, revised or added to for creation of a rationalised NDB. Overall, 5933 food codes in the extensive NDB were reduced to 2481 food codes in the rationalised NDB. Impact on assessment of nutrient intakes was evaluated by re-coding NDNS 2017 data using the rationalised NDB. Small differences were observed between estimated intakes (Cohen's d ≤ 0.1) for all nutrients and there was a good level of agreement (Cohen's κ ≥ 0.6) between the extensive and rationalised NDBs. The evaluation provides confidence in dietary intake estimates for ongoing nutritional surveillance in the UK and strengthens the evidence of a good agreement between concise food databases and large food databases incorporated into web-based 24 h recalls for estimating nutrient intakes at the population level.

Educational achievements of children aged 10-11 years with cystic fibrosis. A data linkage study in Wales.

Introduction: As people with cystic fibrosis (CF) lead longer, healthier lives, educational qualifications and employment prospects are increasingly important. However, little is known about the social consequences of CF, in particular, any impact on educational achievements and the support children with CF receive in schools. Objectives: To assess the educational achievements of children with CF in Wales compared to the general Welsh population, and the additional learning support children with CF receive in schools. Methods: We conducted a population-scale data linkage study of all children born in Wales using the Secure Anonymised Information Linkage (SAIL) Databank. We used anonymised individual-level population-scale health and administrative data sources to identify children with CF born between 2000 - 2015, linked to educational attainment records. We calculated the percentage of children that reached expected levels in statutory assessment at age 10-11, Key Stage 2 (KS2), and compared this to educational outcomes in the general population. We also assessed the percentage of children with CF that received extra learning support. Results: Out of 150 eligible children, 119 had KS2 results. 77% (95% CI: 69%-84%) of children achieved expected levels in English, 81% (95% CI: 73% -87%) in Mathematics and 82% (95% CI: 75% - 88%) in Science. In the comparable general Welsh population, 83.4% to 91.1% achieved the expected level in English, 84.9% to 91.6% in Maths, and 87.1% to 92.2% in Science across the years of the study. 70% of children with CF received extra learning support. Conclusions: Children with CF in Wales may have worse educational achievements than the general population. More research is needed to inform policies and interventions to better support children with CF to reach their full educational potential and employment opportunities.

A web-based interactive physiologically based pharmacokinetic (iPBPK) model for meloxicam in broiler chickens and laying hens.

Meloxicam is a non-steroidal anti-inflammatory drug (NSAID) commonly used in food-producing animals, including chickens in an extralabel manner. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model for meloxicam in broiler chickens and laying hens to facilitate withdrawal interval (WDI) estimations. The model structure for broiler chickens contained six compartments including plasma, muscle, liver, kidney, fat and rest of body, while an additional compartment of ovary was included for laying hens. The model adequately simulated available pharmacokinetic data of meloxicam in plasma of broiler chickens as well as tissue and egg data of laying hens. The model was converted to a web-based interface and used to predict WDIs following extralabel administrations. The results showed that the estimated WDIs were 50, 44, 11, 3, 3, 22 and 4 days for liver, kidney, muscle, fat, ovary, yolk and white, respectively in laying hens after 14 repeated oral administrations of meloxicam (1 mg/kg) at 24-h intervals. This model provides a useful and flexible tool for risk assessment and management of residues for meat and eggs from chickens treated with meloxicam and will serve as a basis for extrapolation to other NSAID drugs and other poultry species to aid animal-derived food safety assessment.

An Interactive Generic Physiologically Based Pharmacokinetic (igPBPK) Modeling Platform to Predict Drug Withdrawal Intervals in Cattle and Swine: A Case Study on Flunixin, Florfenicol, and Penicillin G.

Violative chemical residues in edible tissues from food-producing animals are of global public health concern. Great efforts have been made to develop physiologically based pharmacokinetic (PBPK) models for estimating withdrawal intervals (WDIs) for extralabel prescribed drugs in food animals. Existing models are insufficient to address the food safety concern as these models are either limited to 1 specific drug or difficult to be used by non-modelers. This study aimed to develop a user-friendly generic PBPK platform that can predict tissue residues and estimate WDIs for multiple drugs including flunixin, florfenicol, and penicillin G in cattle and swine. Mechanism-based in silico methods were used to predict tissue/plasma partition coefficients and the models were calibrated and evaluated with pharmacokinetic data from Food Animal Residue Avoidance Databank (FARAD). Results showed that model predictions were, in general, within a 2-fold factor of experimental data for all 3 drugs in both species. Following extralabel administration and respective U.S. FDA-approved tolerances, predicted WDIs for both cattle and swine were close to or slightly longer than FDA-approved label withdrawal times (eg, predicted 8, 28, and 7 days vs labeled 4, 28, and 4 days for flunixin, florfenicol, and penicillin G in cattle, respectively). The final model was converted to a web-based interactive generic PBPK platform. This PBPK platform serves as a user-friendly quantitative tool for real-time predictions of WDIs for flunixin, florfenicol, and penicillin G following FDA-approved label or extralabel use in both cattle and swine, and provides a basis for extrapolating to other drugs and species.

The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis.

Publishing studies using standardized, machine-readable formats will enable machines to perform meta-analyses on demand. To build a semantically enhanced technology that embodies these functions, we developed the Cooperation Databank (CoDa)-a databank that contains 2,636 studies on human cooperation (1958-2017) conducted in 78 societies involving 356,283 participants. Experts annotated these studies along 312 variables, including the quantitative results (13,959 effects). We designed an ontology that defines and relates concepts in cooperation research and that can represent the relationships between results of correlational and experimental studies. We have created a research platform that, given the data set, enables users to retrieve studies that test the relation of variables with cooperation, visualize these study results, and perform (a) meta-analyses, (b) metaregressions, (c) estimates of publication bias, and (d) statistical power analyses for future studies. We leveraged the data set with visualization tools that allow users to explore the ontology of concepts in cooperation research and to plot a citation network of the history of studies. CoDa offers a vision of how publishing studies in a machine-readable format can establish institutions and tools that improve scientific practices and knowledge.

Design and Development of a Medical Image Databank for Assisting Studies in Radiomics.

CompreHensive Digital ArchiVe of Cancer Imaging - Radiation Oncology (CHAVI-RO) is a multi-tier WEB-based medical image databank. It supports archiving de-identified radiological and clinical datasets in a relational database. A semantic relational database model is designed to accommodate imaging and treatment data of cancer patients. It aims to provide key datasets to investigate and model the use of radiological imaging data in response to radiation. This domain of research area addresses the modeling and analysis of complete treatment data of oncology patient. A DICOM viewer is integrated for reviewing the uploaded de-identified DICOM dataset. In a prototype system we carried out a pilot study with cancer data of four diseased sites, namely breast, head and neck, brain, and lung cancers. The representative dataset is used to estimate the data size of the patient. A role-based access control module is integrated with the image databank to restrict the user access limit. We also perform different types of load tests to analyze and quantify the performance of the CHAVI databank.

Determining the impact of unknown individuals in criminality using network analysis of DNA matches.

Criminal offenders missing from police files limit the capacity to reconstruct criminal networks for criminological research and operational purposes. Recent studies show that forensic DNA databanks offer potential to address this problem, through large-scale analysis of DNA matches, many of which involve unidentified offenders. Applying social network analysis (SNA) to 18 years of DNA match data from Québec, Canada, we found that 1400 unknowns do not occupy more marginal positions in the network than 13,000 known offenders, and explain up to 18% of SNA values (e.g., betweenness centrality) for the latter while supporting 46% of their clustering values. Our results contrast with previous studies, showing moreover that unknown individuals who are positioned centrally in a network may have a larger impact than previously expected on investigation policing with implications for forensic intelligence.