Ten principles for data sharing and commercialization.

Digital medical records have enabled us to employ clinical data in many new and innovative ways. However, these advances have brought with them a complex set of demands for healthcare institutions regarding data sharing with topics such as data ownership, the loss of privacy, and the protection of the intellectual property. The lack of clear guidance from government entities often creates conflicting messages about data policy, leaving institutions to develop guidelines themselves. Through discussions with multiple stakeholders at various institutions, we have generated a set of guidelines with 10 key principles to guide the responsible and appropriate use and sharing of clinical data for the purposes of care and discovery. Industry, universities, and healthcare institutions can build upon these guidelines toward creating a responsible, ethical, and practical response to data sharing.

Phenotype Detection Registry System (PheDRS) - Implementation of a Generalizable Single Institution Clinical Registry Architecture.

Precision medicine requires that groups of patients matching clinical or genetic characteristics be identified in a clinical care setting and treated with the appropriate intervention. In the clinical setting, this process is often facilitated by a patient registry. While the software architecture of federated patient registries for research has been well characterized, local registries focused on clinical quality and care have received less attention. Many clinical registries appear to be one-off projects that lack generalizability and the ability to scale to multiple diseases. We evaluate the applicability of existing registry guidelines for registries designed for clinical intervention, propose a software architecture more practical for single-institution clinical registries and report the implementation of a generalizable clinical patient registry architecture at the University of Alabama at Birmingham (UAB).

Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning.

OBJECTIVE: To help cancer registrars efficiently and accurately identify reportable cancer cases. MATERIAL AND METHODS: The Cancer Registry Control Panel (CRCP) was developed to detect mentions of reportable cancer cases using a pipeline built on the Unstructured Information Management Architecture - Asynchronous Scaleout (UIMA-AS) architecture containing the National Library of Medicine's UIMA MetaMap annotator as well as a variety of rule-based UIMA annotators that primarily act to filter out concepts referring to nonreportable cancers. CRCP inspects pathology reports nightly to identify pathology records containing relevant cancer concepts and combines this with diagnosis codes from the Clinical Electronic Data Warehouse to identify candidate cancer patients using supervised machine learning. Cancer mentions are highlighted in all candidate clinical notes and then sorted in CRCP's web interface for faster validation by cancer registrars. RESULTS: CRCP achieved an accuracy of 0.872 and detected reportable cancer cases with a precision of 0.843 and a recall of 0.848. CRCP increases throughput by 22.6% over a baseline (manual review) pathology report inspection system while achieving a higher precision and recall. Depending on registrar time constraints, CRCP can increase recall to 0.939 at the expense of precision by incorporating a data source information feature. CONCLUSION: CRCP demonstrates accurate results when applying natural language processing features to the problem of detecting patients with cases of reportable cancer from clinical notes. We show that implementing only a portion of cancer reporting rules in the form of regular expressions is sufficient to increase the precision, recall, and speed of the detection of reportable cancer cases when combined with off-the-shelf information extraction software and machine learning.

Development of a mother-child database for drug exposure and adverse event detection in the Military Health System.

PURPOSE: The aim of this study was to develop a mother-child linked database consisting of all eligible active duty military personnel, retirees, and their dependents in order to conduct medication-related analyses to improve the safety and quality of care in the Military Health System (MHS). METHODS: Eligible women of reproductive age with at least one pregnancy-related encounter between January 2005 and December 2013 receiving care in the MHS were included in the study population. Building on previously published algorithms, we used pregnancy-related diagnostic and procedure codes, parameterized temporal constraints, and data elements unique to the MHS to identify pregnancies ending in live births, stillbirth, spontaneous abortion, or ectopic pregnancy. Pregnancies ending in live births were matched to presumptive offspring using birth dates and family-based sponsorship identification. Antidepressant and antiepileptic use during pregnancy was evaluated using electronic pharmacy data. RESULTS: Algorithms identified 755,232 women who experienced 1,099,648 complete pregnancies with both pregnancy care encounter and pregnancy outcome. Of the 924,320 live birth pregnancies, 827,753 (90.0%) were matched to offspring. Algorithms also identified 5,663 stillbirths, 11,358 ectopic pregnancies, and 169,665 spontaneous abortions. Among the matched singleton live birth pregnancies, 7.1% of mothers were dispensed an antidepressant at any point during pregnancy, usually a selective serotonin reuptake inhibitor, (75.3%), whereas 1.3% of mothers were dispensed an antiepileptic drug.

Transforming JAK1 mutations exhibit differential signalling, FERM domain requirements and growth responses to interferon-γ.

Recent work has highlighted roles for JAK (Janus kinase) family members in haemopoietic diseases. Although sequencing efforts have uncovered transforming JAK1 mutations in acute leukaemia, they have also identified non-transforming JAK1 mutations. Thus with limited knowledge of the mechanisms of JAK1 activation by mutation, sequencing may not readily identify transforming mutations. Therefore we sought to further understand the repertoire of transforming mutations of JAK1. We identified seven randomly generated transforming JAK1 mutations, including V658L and a deletion of amino acids 629-630 in the pseudokinase domain, as well as L910P, F938S, P960S, K1026E and Y1035C within the kinase domain. These mutations led to differential signalling activation, but exhibited similar transforming abilities, in BaF3 cells. Interestingly, these properties did not always correlate with JAK1 activation-loop phosphorylation. We also identified a JAK1 mutant that did not require a functional FERM (4.1/ezrin/radixin/moesin) domain for transformation. Although we isolated a mutation of JAK1 at residue Val658, which is found mutated in acute leukaemia patients, most of the mutations we identified are within the kinase domain and have yet to be identified in patients. Interestingly, compared with cells expressing JAK1-V658F, cells expressing these mutants had higher STAT1 (signal transducer and activator of transcription 1) phosphorylation and were more sensitive to interferon-γ-mediated growth inhibition. The differential STAT1 activation and interferon-sensitivity of JAK1 mutants may contribute to the determination of which specific JAK1 mutations ultimately contribute to disease and thus are identified in patients. Our characterization of these novel mutations contributes to a better understanding of mutational activation of JAK1.

Distribution of frogs in rice bays within an irrigated agricultural area: links to pesticide usage and farm practices.

In the Coleambally irrigation area (NSW, Australia), the occurrence of four tadpole and frog species in rice bays on farms growing either rice only or both rice and corn was studied over two seasons. In addition to analysis of species occurrence, both gonadal histology and assessment of Batrachochytrium dendrobatidis infection rates were performed. The rice acreage available as potential tadpole habitat was extensively distributed throughout the irrigation area, but more corn was grown in the northern region compared with the southern region. The mean abundance of Litoria raniformis tadpoles was significantly lower in the northern sites compared with the southern sites. In contrast, tadpoles of Limnodynastes fletcheri, Limnodynastes tasmaniensis, and Crinia parinsignifera had a uniform distribution across all study sites. A principal components analysis showed a relationship between farm type and the rice herbicide applied when the crops were initially sown, with sites occupied by Litoria raniformis in the beginning being predominantly rice-only farms. A discriminant analysis showed that low concentrations of the corn herbicide metolachlor and increased pH were the main variables studied that determined site occupation by L. raniformis. This suggested that farms growing only rice (and not corn) with high algal production were the preferred sites. The rates of chytrid infection and gonadal malformations were low across both regions. Histology of the gonads of metamorphs showed that L. raniformis gonadal differentiation is slow compared to that of the two Limnodynastes species. We concluded that farm practices associated with increased corn cropping in the northern region, rather than any direct effect of corn herbicides, determine the reduced presence of Litoria raniformis in the northern region.

Use of natural language programming to extract medication from unstructured electronic medical records.

The purpose of this study is to evaluate the feasibility of applying natural language processing in the automated extraction of medications information from unstructured electronic records. Sixty-two documents containing medications were subjected to both manual and automated extraction. Both were able to identify over 90% medications. The automated method identified more medications than manual review, 97% vs 92%. However, the automated extraction included a substantial percentage (17%) of non-medication items but none with manual review.

Dynamics and anchoring of heterochromatic loci during development.

Positioning a euchromatic gene near heterochromatin can influence its expression. To better understand expression-relevant changes in locus positioning, we monitored in vivo movement of centromeres and a euchromatic locus (with and without a nearby insertion of heterochromatin) in developing Drosophila tissue. In most undifferentiated nuclei, the rate of diffusion and step size of the locus is unaffected by the heterochromatic insertion. Interestingly, although the movement observed here is non directional, the heterochromatic insertion allows the flanking euchromatic region to enter and move within the heterochromatic compartment. This study also finds that a constraint on chromatin movement is imposed which is a factor of distance from the centric heterochromatic compartment. This restraint prevents the heterochromatic locus from moving away from the centric heterochromatin compartment. Therefore, because of the constraint, even distinct and non-random nuclear organizations can be attained from random chromatin movements. We also find a general constraint on chromatin movement is imposed during differentiation, which stabilizes changes in nuclear organization in differentiated nuclei.

Spatial and rainfall related patterns of bacterial contamination in Sydney Harbour estuary.

Water quality in recreational areas in Sydney Harbour, Australia, was analysed first to identify spatial patterns in faecal coliform and enterococci densities, and then to determine the relationship between bacterial densities and catchment rainfall. Non-metric multidimensional scaling separated sites closest to the mouth of the harbour from those further up the harbour's west and north-west arms. Sites closest to the harbour mouth generally had lower frequencies of high bacterial densities that exceeded median water quality guideline values. We attribute this to greater tidal flushing at sites closer to the harbour mouth. Eight site groups were identified within the harbour. Within each group, multiple regression analyses indicated rainfall accounted for between 15 and 66% of the variability in the bacterial densities. Variation in bacterial densities explained by rainfall was lower for sites closer to the harbour mouth where tidal flushing is greatest. Thus, our findings indicate that simple rainfall-based regression models are appropriate for predicting bacterial concentrations when flushing at a site is limited. More complex models incorporating a suite of environmental variables may improve the ability to predict bacterial concentrations at well-flushed sites, but even then, their predictive ability may be low.