Mining Clinicians' Electronic Documentation to Identify Heart Failure Patients with Ineffective Self-Management: A Pilot Text-Mining Study.

Stud Health Technol Inform. 2016;225:856-857

Authors: Topaz M, Radhakrishnan K, Lei V, Zhou L

Abstract
Effective self-management can decrease up to 50% of heart failure hospitalizations. Unfortunately, self-management by patients with heart failure remains poor. This pilot study aimed to explore the use of text-mining to identify heart failure patients with ineffective self-management. We first built a comprehensive self-management vocabulary based on the literature and clinical notes review. We then randomly selected 545 heart failure patients treated within Partners Healthcare hospitals (Boston, MA, USA) and conducted a regular expression search with the compiled vocabulary within 43,107 interdisciplinary clinical notes of these patients. We found that 38.2% (n = 208) patients had documentation of ineffective heart failure self-management in the domains of poor diet adherence (28.4%), missed medical encounters (26.4%) poor medication adherence (20.2%) and non-specified self-management issues (e.g., "compliance issues", 34.6%). We showed the feasibility of using text-mining to identify patients with ineffective self-management. More natural language processing algorithms are needed to help busy clinicians identify these patients.

PMID: 27332377 [PubMed - as supplied by publisher]

Using a Text-Mining Approach to Evaluate the Quality of Nursing Records.

Stud Health Technol Inform. 2016;225:813-814

Authors: Chang HM, Chiou SF, Liu HY, Yu HC

Abstract
Nursing records in Taiwan have been computerized, but their quality has rarely been discussed. Therefore, this study employed a text-mining approach and a cross-sectional retrospective research design to evaluate the quality of electronic nursing records at a medical center in Northern Taiwan. SAS Text Miner software Version 13.2 was employed to analyze unstructured nursing event records. The results show that SAS Text Miner is suitable for developing a textmining model for validating nursing records. The sensitivity of SAS Text Miner was approximately 0.94, and the specificity and accuracy were 0.99. Thus, SAS Text Miner software is an effective tool for auditing unstructured electronic nursing records.

PMID: 27332355 [PubMed - as supplied by publisher]

A Survey of Bioinformatics Database and Software Usage through Mining the Literature.

PLoS One. 2016;11(6):e0157989

Authors: Duck G, Nenadic G, Filannino M, Brass A, Robertson DL, Stevens R

Abstract
Computer-based resources are central to much, if not most, biological and medical research. However, while there is an ever expanding choice of bioinformatics resources to use, described within the biomedical literature, little work to date has provided an evaluation of the full range of availability or levels of usage of database and software resources. Here we use text mining to process the PubMed Central full-text corpus, identifying mentions of databases or software within the scientific literature. We provide an audit of the resources contained within the biomedical literature, and a comparison of their relative usage, both over time and between the sub-disciplines of bioinformatics, biology and medicine. We find that trends in resource usage differs between these domains. The bioinformatics literature emphasises novel resource development, while database and software usage within biology and medicine is more stable and conservative. Many resources are only mentioned in the bioinformatics literature, with a relatively small number making it out into general biology, and fewer still into the medical literature. In addition, many resources are seeing a steady decline in their usage (e.g., BLAST, SWISS-PROT), though some are instead seeing rapid growth (e.g., the GO, R). We find a striking imbalance in resource usage with the top 5% of resource names (133 names) accounting for 47% of total usage, and over 70% of resources extracted being only mentioned once each. While these results highlight the dynamic and creative nature of bioinformatics research they raise questions about software reuse, choice and the sharing of bioinformatics practice. Is it acceptable that so many resources are apparently never reused? Finally, our work is a step towards automated extraction of scientific method from text. We make the dataset generated by our study available under the CC0 license here: http://dx.doi.org/10.6084/m9.figshare.1281371.

PMID: 27331905 [PubMed - as supplied by publisher]

13 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/06/22

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

13 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/06/22

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Repurposing ebselen for treatment of multidrug-resistant staphylococcal infections.

Sci Rep. 2015;5:11596

Authors: Thangamani S, Younis W, Seleem MN

Abstract
Novel antimicrobials and new approaches to developing them are urgently needed. Repurposing already-approved drugs with well-characterized toxicology and pharmacology is a novel way to reduce the time, cost, and risk associated with antibiotic innovation. Ebselen, an organoselenium compound, is known to be clinically safe and has a well-known pharmacology profile. It has shown potent bactericidal activity against multidrug-resistant clinical isolates of staphylococcus aureus, including methicillin- and vancomycin-resistant S. aureus (MRSA and VRSA). We demonstrated that ebselen acts through inhibition of protein synthesis and subsequently inhibited toxin production in MRSA. Additionally, ebselen was remarkably active and significantly reduced established staphylococcal biofilms. The therapeutic efficacy of ebselen was evaluated in a mouse model of staphylococcal skin infections. Ebselen 1% and 2% significantly reduced the bacterial load and the levels of the pro-inflammatory cytokines tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β), and monocyte chemo attractant protein-1 (MCP-1) in MRSA USA300 skin lesions. Furthermore, it acts synergistically with traditional antimicrobials. This study provides evidence that ebselen has great potential for topical treatment of MRSA skin infections and lays the foundation for further analysis and development of ebselen as a potential treatment for multidrug-resistant staphylococcal infections.

PMID: 26111644 [PubMed - indexed for MEDLINE]

Alveolar rhabdomyosarcoma: morphoproteomics and personalized tumor graft testing further define the biology of PAX3-FKHR(FOXO1) subtype and provide targeted therapeutic options.

Oncotarget. 2016 Jun 15;

Authors: Brown RE, Buryanek J, Katz AM, Paz K, Wolff JE

Abstract
Alveolar rhabdomyosarcoma (ARMS) represents a block in differentiation of malignant myoblasts. Genomic events implicated in the pathogenesis of ARMS involve PAX3-FKHR (FOXO1) or PAX7-FKHR (FOXO1) translocation with corresponding fusion transcripts and fusion proteins. Commonalities in ARMS include uncontrollable proliferation and failure to differentiate. The genomic-molecular correlates contributing to the etiopathogenesis of ARMS incorporate PAX3-FKHR (FOXO1) fusion protein stimulation of the IGF-1R, c-Met and GSK3-β pathways. With sequential morphoproteomic profiling on such a case in conjunction with personalized tumor graft testing, we provide an expanded definition of the biology of PAX3-FKHR (FOXO1) ARMS that integrates genomics, proteomics and pharmacogenomics. Moreover, therapies that target the genomic and molecular biology and lead to tumoral regression and/or tumoral growth inhibition in a xenograft model of ARMS are identified.
SIGNIFICANCE: This case study could serve as a model for clinical trials using relatively low toxicity agents in both initial and maintenance therapies to induce remission and reduce the risk of recurrent disease in PAX3-FKHR (FOXO1) subtype of ARMS.

PMID: 27323832 [PubMed - as supplied by publisher]

Pharmacogenomic Genome-Wide Meta-Analysis of Blood Pressure Response to β-Blockers in Hypertensive African Americans.

Hypertension. 2016 Mar;67(3):556-63

Authors: Gong Y, Wang Z, Beitelshees AL, McDonough CW, Langaee TY, Hall K, Schmidt SO, Curry RW, Gums JG, Bailey KR, Boerwinkle E, Chapman AB, Turner ST, Cooper-DeHoff RM, Johnson JA

Abstract
African Americans suffer a higher prevalence of hypertension compared with other racial/ethnic groups. In this study, we performed a pharmacogenomic genome-wide association study of blood pressure (BP) response to β-blockers in African Americans with uncomplicated hypertension. Genome-wide meta-analysis was performed in 318 African American hypertensive participants in the 2 Pharmacogenomic Evaluation of Antihypertensive Responses studies: 150 treated with atenolol monotherapy and 168 treated with metoprolol monotherapy. The analysis adjusted for age, sex, baseline BP and principal components for ancestry. Genome-wide significant variants with P<5×10(-8) and suggestive variants with P<5×10(-7) were evaluated in an additional cohort of 141 African Americans treated with the addition of atenolol to hydrochlorothiazide treatment. The validated variants were then meta-analyzed in these 3 groups of African Americans. Two variants discovered in the monotherapy meta-analysis were validated in the add-on therapy. African American participants heterozygous for SLC25A31 rs201279313 deletion versus wild-type genotype had better diastolic BP response to atenolol monotherapy, metoprolol monotherapy, and atenolol add-on therapy: -9.3 versus -4.6, -9.6 versus -4.8, and -9.7 versus -6.4 mm Hg, respectively (3-group meta-analysis P=2.5×10(-8), β=-4.42 mm Hg per variant allele). Similarly, LRRC15 rs11313667 was validated for systolic BP response to β-blocker therapy with 3-group meta-analysis P=7.2×10(-8) and β=-3.65 mm Hg per variant allele. In this first pharmacogenomic genome-wide meta-analysis of BP response to β-blockers in African Americans, we identified novel variants that may provide valuable information for personalized antihypertensive treatment in this group.

PMID: 26729753 [PubMed - indexed for MEDLINE]

Point process models for localization and interdependence of punctate cellular structures.

Cytometry A. 2016 Jun 21;

Authors: Li Y, Majarian TD, Naik AW, Johnson GR, Murphy RF

Abstract
Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry.

PMID: 27327612 [PubMed - as supplied by publisher]

Analysis of in vivo single cell behavior by high throughput, human-in-the-loop segmentation of three-dimensional images.

BMC Bioinformatics. 2015;16:397

Authors: Chiang M, Hallman S, Cinquin A, de Mochel NR, Paz A, Kawauchi S, Calof AL, Cho KW, Fowlkes CC, Cinquin O

Abstract
BACKGROUND: Analysis of single cells in their native environment is a powerful method to address key questions in developmental systems biology. Confocal microscopy imaging of intact tissues, followed by automatic image segmentation, provides a means to conduct cytometric studies while at the same time preserving crucial information about the spatial organization of the tissue and morphological features of the cells. This technique is rapidly evolving but is still not in widespread use among research groups that do not specialize in technique development, perhaps in part for lack of tools that automate repetitive tasks while allowing experts to make the best use of their time in injecting their domain-specific knowledge.
RESULTS: Here we focus on a well-established stem cell model system, the C. elegans gonad, as well as on two other model systems widely used to study cell fate specification and morphogenesis: the pre-implantation mouse embryo and the developing mouse olfactory epithelium. We report a pipeline that integrates machine-learning-based cell detection, fast human-in-the-loop curation of these detections, and running of active contours seeded from detections to segment cells. The procedure can be bootstrapped by a small number of manual detections, and outperforms alternative pieces of software we benchmarked on C. elegans gonad datasets. Using cell segmentations to quantify fluorescence contents, we report previously-uncharacterized cell behaviors in the model systems we used. We further show how cell morphological features can be used to identify cell cycle phase; this provides a basis for future tools that will streamline cell cycle experiments by minimizing the need for exogenous cell cycle phase labels.
CONCLUSIONS: High-throughput 3D segmentation makes it possible to extract rich information from images that are routinely acquired by biologists, and provides insights - in particular with respect to the cell cycle - that would be difficult to derive otherwise.

PMID: 26607933 [PubMed - indexed for MEDLINE]

Applications of targeted proteomics in systems biology and translational medicine.

Proteomics. 2015 Sep;15(18):3193-208

Authors: Ebhardt HA, Root A, Sander C, Aebersold R

Abstract
Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM-MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.

PMID: 26097198 [PubMed - indexed for MEDLINE]

Molecular mechanism matters: Benefits of mechanistic computational models for drug development.

Pharmacol Res. 2015 Sep;99:149-54

Authors: Clegg LE, Mac Gabhann F

Abstract
Making drug development a more efficient and cost-effective process will have a transformative effect on human health. A key, yet underutilized, tool to aid in this transformation is mechanistic computational modeling. By incorporating decades of hard-won prior knowledge of molecular interactions, cellular signaling, and cellular behavior, mechanistic models can achieve a level of predictiveness that is not feasible using solely empirical characterization of drug pharmacodynamics. These models can integrate diverse types of data from cell culture and animal experiments, including high-throughput systems biology experiments, and translate the results into the context of human disease. This provides a framework for identification of new drug targets, measurable biomarkers for drug action in target tissues, and patient populations for which a drug is likely to be effective or ineffective. Additionally, mechanistic models are valuable in virtual screening of new therapeutic strategies, such as gene or cell therapy and tissue regeneration, identifying the key requirements for these approaches to succeed in a heterogeneous patient population. These capabilities, which are distinct from and complementary to those of existing drug development strategies, demonstrate the opportunity to improve success rates in the drug development pipeline through the use of mechanistic computational models.

PMID: 26093283 [PubMed - indexed for MEDLINE]

Expanding the yeast protein arginine methylome.

Proteomics. 2015 Sep;15(18):3232-43

Authors: Plank M, Fischer R, Geoghegan V, Charles PD, Konietzny R, Acuto O, Pears C, Schofield CJ, Kessler BM

Abstract
Protein arginine methylation is a PTM involved in various cellular processes in eukaryotes. Recent discoveries led to a vast expansion of known sites in higher organisms, indicating that this modification is more widely spread across the proteome than previously assumed. An increased knowledge of sites in lower eukaryotes may facilitate the elucidation of its functions. In this study, we present the discovery of arginine mono-methylation sites in Saccharomyces cerevisiae by a combination of immunoaffinity enrichment and MS/MS. As detection of methylation is prone to yield false positives, we demonstrate the need for stringent measures to avoid elevated false discovery rates. To this end, we employed MethylSILAC in combination with a multistep data analysis strategy. We report 41 unambiguous methylation sites on 13 proteins. Our results indicate that, while substantially less abundant, arginine methylation follows similar patterns as in higher eukaryotes in terms of sequence context and functions of methylated proteins. The majority of sites occur on RNA-binding proteins participating in processes from transcription and splicing to translation and RNA degradation. Additionally, our data suggest a bias for localization of arginine methylation in unstructured regions of proteins, which frequently involves Arg-Gly-Gly motifs or Asn-rich contexts.

PMID: 26046779 [PubMed - indexed for MEDLINE]

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae.

Proteomics. 2015 Sep;15(18):3126-39

Authors: Jarnuczak AF, Eyers CE, Schwartz JM, Grant CM, Hubbard SJ

Abstract
Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs.

PMID: 25689132 [PubMed - indexed for MEDLINE]

12 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/06/21

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

8 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/06/21

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Macrophages Contribute to the Spermatogonial Niche in the Adult Testis.

Cell Rep. 2015 Aug 18;12(7):1107-19

Authors: DeFalco T, Potter SJ, Williams AV, Waller B, Kan MJ, Capel B

Abstract
The testis produces sperm throughout the male reproductive lifespan by balancing self-renewal and differentiation of spermatogonial stem cells (SSCs). Part of the SSC niche is thought to lie outside the seminiferous tubules of the testis; however, specific interstitial components of the niche that regulate spermatogonial divisions and differentiation remain undefined. We identified distinct populations of testicular macrophages, one of which lies on the surface of seminiferous tubules, in close apposition to areas of tubules enriched for undifferentiated spermatogonia. These macrophages express spermatogonial proliferation- and differentiation-inducing factors, such as colony-stimulating factor 1 (CSF1) and enzymes involved in retinoic acid (RA) biosynthesis. We show that transient depletion of macrophages leads to a disruption in spermatogonial differentiation. These findings reveal an unexpected role for macrophages in the spermatogonial niche in the testis and raise the possibility that macrophages play previously unappreciated roles in stem/progenitor cell regulation in other tissues.

PMID: 26257171 [PubMed - indexed for MEDLINE]

EMR Documentation of Physician-Patient Communication Following Genomic Counseling for Actionable Complex Disease and Pharmacogenomic Results.

Clin Genet. 2016 Jun 20;

Authors: Sweet K, Sturm AC, Schmidlen T, Hovick S, Peng J, Manickam K, Salikhova A, McElroy J, Scheinfeldt L, Toland AE, Scott Roberts J, Christman M

Abstract
Genomic risk information for potentially actionable complex diseases and pharmacogenomics communicated through genomic counseling may motivate physicians and patients to take preventive actions. The Ohio State University-Coriell Personalized Medicine Collaborative is a randomized trial to measure the effects of in-person genomic counseling on chronic disease patients provided with multiplex results. Nine personalized genomic risk reports were provided to patients through a web portal, and to physicians via electronic medical record (EMR). Active arm participants (98, 39% female) received genomic counseling within one month of report viewing; control arm subjects (101, 54% female) could access counseling 3-months post-report viewing. We examined whether genomic counseling affected documentation of physician-patient communication by reviewing the first clinical note following the patient's genomic counseling visit or report upload to the EMR. Multivariable logistic regression modeling estimated the independent effect of genomic counseling on physician-patient communication, as Intention to Treat (ITT) and Per Protocol (PP), adjusted for physician educational intervention. Counselees in the active arm had more physician-patient communications than control subjects (ITT, OR: 3.76 (95% CI: 1.38 - 10.22, P < 0.0094); PP, OR: 5.53 (95% CI: 2.20 - 13.90, P = 0.0017). In conclusion, genomic counseling appreciably affected physician-patient communication following receipt of potentially actionable genomic risk information.

PMID: 27322592 [PubMed - as supplied by publisher]

Integrating heterogeneous drug sensitivity data from cancer pharmacogenomic studies.

Oncotarget. 2016 Jun 14;

Authors: Pozdeyev N, Yoo M, Mackie R, Schweppe RE, Tan AC, Haugen BR

Abstract
The consistency of in vitro drug sensitivity data is of key importance for cancer pharmacogenomics. Previous attempts to correlate drug sensitivities from the large pharmacogenomics databases, such as the Cancer Cell Line Encyclopedia (CCLE) and the Genomics of Drug Sensitivity in Cancer (GDSC), have produced discordant results. We developed a new drug sensitivity metric, the area under the dose response curve adjusted for the range of tested drug concentrations, which allows integration of heterogeneous drug sensitivity data from the CCLE, the GDSC, and the Cancer Therapeutics Response Portal (CTRP). We show that there is moderate to good agreement of drug sensitivity data for many targeted therapies, particularly kinase inhibitors. The results of this largest cancer cell line drug sensitivity data analysis to date are accessible through the online portal, which serves as a platform for high power pharmacogenomics analysis.

PMID: 27322211 [PubMed - as supplied by publisher]

Pre-Examination Factors Affecting Molecular Diagnostic Test Results and Interpretation: a Case-Based Approach.

Clin Chim Acta. 2016 Jun 16;

Authors: Payne DA, Baluchova K, Peoc'h KH, van Schaik RH, Chan KC, Maekawa M, Mamotte C, Russomando G, Rousseau F, Ahmad-Nejad P, IFCC Committee for Molecular Diagnostics (C-MD)

Abstract
BACKGROUND: Multiple organizations produce guidance documents that provide opportunities to harmonize quality practices for diagnostic testing. The International Organization for Standardization ISO 15189 standard addresses requirements for quality in management and technical aspects of the clinical laboratory. One technical aspect addresses the complexities of the pre-examination phase prior to diagnostic testing.
METHODS: The Committee for Molecular Diagnostics of the International Federation for Clinical Chemistry and Laboratory Medicine (also known as, IFCC C-MD) conducted a survey of international molecular laboratories and determined ISO 15189 to be the most referenced guidance document. In this review, the IFCC C-MD provides case-based examples illustrating the value of select pre-examination processes as these processes relate to molecular diagnostic testing. Case-based examples in infectious disease, oncology, inherited disease and pharmacogenomics address the utility of: 1) providing information to patients and users, 2) designing requisition forms, 3) obtaining informed consent and 4) maintaining sample integrity prior to testing.
CONCLUSIONS: The pre-examination phase requires extensive and consistent communication between the laboratory, the healthcare provider and the end user. The clinical vignettes presented in this paper illustrate the value of applying select ISO 15189 recommendations for general laboratory to the more specialized area of Molecular Diagnostics.

PMID: 27321365 [PubMed - as supplied by publisher]