Pharmacogenomics and Implications for Nursing Practice.

J Nurs Scholarsh. 2015 Nov;47(6):496-504

Authors: Cheek DJ, Bashore L, Brazeau DA

Abstract
PURPOSE: This article aims to introduce the nurse to pharmacogenomics and its implications for clinical practice with regard to drug therapy.
ORGANIZING CONSTRUCTS: Pharmacogenomics is discussed with regard to the basic tenets, relationships to common health conditions, education and practice resources, and implications for nursing practice.
METHODS: Peer-reviewed literature, websites, and expert professional guidelines were reviewed with relation to pharmacogenomics and nursing practice.
FINDINGS: The genetic-genomic literature has grown significantly since the completion of the Human Genome Project in 2003. This information is now being translated into practice with regard to the patient's genetic profile and the impact on drug therapy, which is pharmacogenomics.
CONCLUSIONS: The utilization of the patient genetic-genomic profile is beginning to have an impact on patient drug therapy in clinical practice.
CLINICAL RELEVANCE: Nurses are in the position to make sure, with the increased translation of pharmacogenomics into clinical practice, that adverse drug reactions are avoided and doses are optimized.

PMID: 26470020 [PubMed - indexed for MEDLINE]

An unusual case of disseminated adenovirus infection in a cystic fibrosis, liver transplant patient.

J Clin Virol. 2016 Jun 13;81:64-67

Authors: Mitchell SL, Kajon AE, Kaplan SL, Kim J, Cárdenas AM

PMID: 27331823 [PubMed - as supplied by publisher]

Inflammation induced by inhaled lipopolysaccharide depends on particle size in healthy volunteers.

Br J Clin Pharmacol. 2016 Jun 22;

Authors: Doyen VA, Pilcer G, Huy Duc Dinh P, Corazza F, Bernard A, Bergmann P, Lefevre N, Amighi K, Michel O

Abstract
AIM: In drug development, lung anti-inflammatory properties of new molecules are currently tested on the inhaled LPS model. The total and regional lung bioavailability of inhaled particles depends significantly on their size. The objective was to compare inflammatory responses in healthy volunteers after the inhalation of lipopolysaccharide (LPS) of varying droplet size.
METHODS: Three nebulizers were characterized by different droplet size distributions [mean mass median aerodynamic diameters: Microcirrus (2.0 µm), MB2 (3.2 µm), and Pari (7.9 µm)]. Participants inhaled three boluses of 20 µg (technetium 99 m-labeled) solution of LPS, randomly delivered by each nebulizer. We measured the lung deposition of the nebulized LPS by gamma-scintigraphy, while blood and sputum biomarkers were evaluated before and after challenges.
RESULTS: MB2 and Pari achieved greater lung deposition than Microcirrus [171.5 (±72.9) and 217.6 (±97.8) counts/pixel, respectively, versus 67.9 (±20.6) counts/pixel; p < 0.01]. MB2 and Pari caused greater blood C-reactive protein and more total cells and neutrophils in sputum compared to Microcirrus (p < 0.05). C-reactive protein level correlated positively with lung deposition (p < 0.01).
CONCLUSIONS: Inhalation of large droplets of LPS featured greater lung deposition and induced a more pronounced systemic and bronchial inflammatory response than small droplets. The systemic inflammatory response correlated with lung deposition. NCT01081392.

PMID: 27331367 [PubMed - as supplied by publisher]

Gastrointestinal Manifestations of Cystic Fibrosis.

Gastroenterol Hepatol (N Y). 2016 Jan;12(1):43-7

Authors: Sabharwal S

Abstract
Cystic fibrosis has historically been considered a pulmonary disease, but with the increasing life expectancy of these patients, gastrointestinal manifestations are becoming more important. Furthermore, nutritional status is closely linked to pulmonary function and, thus, overall mortality. This article discusses gastrointestinal manifestations (which involve nutritional, pancreatic, hepatobiliary, and, in particular, gastrointestinal tract issues) of cystic fibrosis as well as management of the disease. In addition, the article discusses studies that have been critical to our understanding of gastrointestinal manifestations of cystic fibrosis.

PMID: 27330503 [PubMed]

Diagnosis and Early Life Risk Factors for Bronchiectasis in Cystic Fibrosis: a Review.

Expert Rev Respir Med. 2016 Jun 22;

Authors: Sly PD, Wainwright CE

Abstract
INTRODUCTION: Lung disease in cystic fibrosis begins in early life with neutrophil-dominated inflammation and infection, is progressive and results in structural lung damage characterised by bronchial dilation and bronchiectasis. Preventative strategies must be employed in early life but require a better understanding of how bronchiectasis develops.
AREAS COVERED: In this review we have addressed the diagnosis and early life risk factors for bronchiectasis in young children with cystic fibrosis. A systematic review was not performed and the literature reviewed was known to the authors. Expert commentary: Bronchiectasis represents a process of progressive dilatation and damage of airway walls and is traditionally considered to be irreversible. Diagnosis is primarily by detecting a bronchial:arterial ratio of >1 on chest CT scan. Lung volume has a greater influence on airway diameter than on arterial making control of lung volume during scanning critical. Early life risk factors for the onset and progression bronchiectasis include: severe cystic fibrosis genotype; neutrophilic inflammation with free neutrophil elastase activity in the lung; and pulmonary infection. Bronchiectasis develops in the majority of children before they reach school age despite the best current therapy. To prevent bronchiectasis novel therapies are going to have to be given to infants.

PMID: 27329819 [PubMed - as supplied by publisher]

Paediatric nasal polyps in cystic fibrosis.

BMJ Case Rep. 2016;2016

Authors: Mohd Slim MA, Dick D, Trimble K, McKee G

Abstract
Patients with cystic fibrosis (CF) are at increased risk of nasal polyps. We present the case of a 17-month-old Caucasian patient with CF who presented with hypertelorism causing cycloplegic astigmatism, right-sided mucoid discharge, snoring and noisy breathing. Imaging suggested bilateral mucoceles in the ethmoid sinuses. Intraoperatively, bilateral soft tissue masses were noted, and both posterior choanae were patent. Polypectomy and bilateral mega-antrostomies were performed. Histological examination revealed inflammatory nasal polyposis typical of CF. The role of early functional endoscopic sinus surgery (FESS) in children with CF nasal polyposis remains questionable as the recurrence rate is higher, and no improvement in pulmonary function has been shown. Our case, however, clearly demonstrates the beneficial upper airway symptom relief and normalisation of facial appearance following FESS in a child with this condition.

PMID: 27329094 [PubMed - in process]

Comprehensive analysis of high-throughput screens with HiTSeekR.

Nucleic Acids Res. 2016 Jun 21;

Authors: List M, Schmidt S, Christiansen H, Rehmsmeier M, Tan Q, Mollenhauer J, Baumbach J

Abstract
High-throughput screening (HTS) is an indispensable tool for drug (target) discovery that currently lacks user-friendly software tools for the robust identification of putative hits from HTS experiments and for the interpretation of these findings in the context of systems biology. We developed HiTSeekR as a one-stop solution for chemical compound screens, siRNA knock-down and CRISPR/Cas9 knock-out screens, as well as microRNA inhibitor and -mimics screens. We chose three use cases that demonstrate the potential of HiTSeekR to fully exploit HTS screening data in quite heterogeneous contexts to generate novel hypotheses for follow-up experiments: (i) a genome-wide RNAi screen to uncover modulators of TNFα, (ii) a combined siRNA and miRNA mimics screen on vorinostat resistance and (iii) a small compound screen on KRAS synthetic lethality. HiTSeekR is publicly available at http://hitseekr.compbio.sdu.dk It is the first approach to close the gap between raw data processing, network enrichment and wet lab target generation for various HTS screen types.

PMID: 27330136 [PubMed - as supplied by publisher]

Network pharmacology of cancer: From understanding of complex interactomes to the design of multi-target specific therapeutics from nature.

Pharmacol Res. 2016 Jun 18;

Authors: Poornima P, Kumar JD, Zhao Q, Blunder M, Efferth T

Abstract
Despite massive investments in drug research and development, the significant decline in the number of new drugs approved or translated to clinical use raises the question, whether single targeted drug discovery is the right approach. To combat complex systemic diseases that harbour robust biological networks such as cancer, single target intervention is proved to be ineffective. In such cases, network pharmacology approaches are highly useful, because they differ from conventional drug discovery by addressing the ability of drugs to target numerous proteins or networks involved in a disease. Pleiotropic natural products are one of the promising strategies due to their multi-targeting and due to lower side effects. In this review, we discuss the application of network pharmacology for cancer drug discovery. We provide an overview of the current state of knowledge on network pharmacology, focus on different technical approaches and implications for cancer therapy (e.g. polypharmacology and synthetic lethality), and illustrate the therapeutic potential with selected examples (Green tea polyphenolics, Eleutherococcus senticosus, Rhodiola rosea, and Schisandra chinensis). Finally, we present future perspectives on their plausible applications for diagnosis and therapy of cancer.

PMID: 27329331 [PubMed - as supplied by publisher]

Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli.

Microb Cell Fact. 2016;15(1):112

Authors: Jahan N, Maeda K, Matsuoka Y, Sugimoto Y, Kurata H

Abstract
BACKGROUND: A kinetic model provides insights into the dynamic response of biological systems and predicts how their complex metabolic and gene regulatory networks generate particular functions. Of many biological systems, Escherichia coli metabolic pathways have been modeled extensively at the enzymatic and genetic levels, but existing models cannot accurately reproduce experimental behaviors in a batch culture, due to the inadequate estimation of a specific cell growth rate and a large number of unmeasured parameters.
RESULTS: In this study, we developed a detailed kinetic model for the central carbon metabolism of E. coli in a batch culture, which includes the glycolytic pathway, tricarboxylic acid cycle, pentose phosphate pathway, Entner-Doudoroff pathway, anaplerotic pathway, glyoxylate shunt, oxidative phosphorylation, phosphotransferase system (Pts), non-Pts and metabolic gene regulations by four protein transcription factors: cAMP receptor, catabolite repressor/activator, pyruvate dehydrogenase complex repressor and isocitrate lyase regulator. The kinetic parameters were estimated by a constrained optimization method on a supercomputer. The model estimated a specific growth rate based on reaction kinetics and accurately reproduced the dynamics of wild-type E. coli and multiple genetic mutants in a batch culture.
CONCLUSIONS: This model overcame the intrinsic limitations of existing kinetic models in a batch culture, predicted the effects of multilayer regulations (allosteric effectors and gene expression) on central carbon metabolism and proposed rationally designed fast-growing cells based on understandings of molecular processes.

PMID: 27329289 [PubMed - in process]

Lipid metabolism in mycobacteria--Insights using mass spectrometry-based lipidomics.

Biochim Biophys Acta. 2016 Jan;1861(1):60-7

Authors: Crick PJ, Guan XL

Abstract
Diseases including tuberculosis and leprosy are caused by species of the Mycobacterium genus and are a huge burden on global health, aggravated by the emergence of drug resistant strains. Mycobacteria have a high lipid content and complex lipid profile including several unique classes of lipid. Recent years have seen a growth in research focused on lipid structures, metabolism and biological functions driven by advances in mass spectrometry techniques and instrumentation, particularly the use of electrospray ionization. Here we review the contributions of lipidomics towards the advancement of our knowledge of lipid metabolism in mycobacterial species.

PMID: 26515252 [PubMed - indexed for MEDLINE]

Inflammatory gene networks in term human decidual cells define a potential signature for cytokine-mediated parturition.

Am J Obstet Gynecol. 2016 Feb;214(2):284.e1-284.e47

Authors: Ibrahim SA, Ackerman WE, Summerfield TL, Lockwood CJ, Schatz F, Kniss DA

Abstract
BACKGROUND: Inflammation is a proximate mediator of preterm birth and fetal injury. During inflammation several microRNAs (22 nucleotide noncoding ribonucleic acid (RNA) molecules) are up-regulated in response to cytokines such as interleukin-1β. MicroRNAs, in most cases, fine-tune gene expression, including both up-regulation and down-regulation of their target genes. However, the role of pro- and antiinflammatory microRNAs in this process is poorly understood.
OBJECTIVE: The principal goal of the work was to examine the inflammatory genomic profile of human decidual cells challenged with a proinflammatory cytokine known to be present in the setting of preterm parturition. We determined the coding (messenger RNA) and noncoding (microRNA) sequences to construct a network of interacting genes during inflammation using an in vitro model of decidual stromal cells.
STUDY DESIGN: The effects of interleukin-1β exposure on mature microRNA expression were tested in human decidual cell cultures using the multiplexed NanoString platform, whereas the global inflammatory transcriptional response was measured using oligonucleotide microarrays. Differential expression of select transcripts was confirmed by quantitative real time-polymerase chain reaction. Bioinformatics tools were used to infer transcription factor activation and regulatory interactions.
RESULTS: Interleukin-1β elicited up- and down-regulation of 350 and 78 nonredundant transcripts (false discovery rate < 0.1), respectively, including induction of numerous cytokines, chemokines, and other inflammatory mediators. Whereas this transcriptional response included marked changes in several microRNA gene loci, the pool of fully processed, mature microRNA was comparatively stable following a cytokine challenge. Of a total of 6 mature microRNAs identified as being differentially expressed by NanoString profiling, 2 (miR-146a and miR-155) were validated by quantitative real time-polymerase chain reaction. Using complementary bioinformatics approaches, activation of several inflammatory transcription factors could be inferred downstream of interleukin-1β based on the overall transcriptional response. Further analysis revealed that miR-146a and miR-155 both target genes involved in inflammatory signaling, including Toll-like receptor and mitogen-activated protein kinase pathways.
CONCLUSION: Stimulation of decidual cells with interleukin-1β alters the expression of microRNAs that function to temper proinflammatory signaling. In this setting, some microRNAs may be involved in tissue-level inflammation during the bulk of gestation and assist in pregnancy maintenance.

PMID: 26348374 [PubMed - indexed for MEDLINE]

Using quantitative systems pharmacology for novel drug discovery.

Expert Opin Drug Discov. 2015 Dec;10(12):1315-31

Authors: Pérez-Nueno VI

Abstract
INTRODUCTION: Over the past three decades, the predominant paradigm in drug discovery was designing selective ligands for a specific target to avoid unwanted side effects. However, in the last 5 years, the aim has shifted to take into account the biological network in which they interact. Quantitative and Systems Pharmacology (QSP) is a new paradigm that aims to understand how drugs modulate cellular networks in space and time, in order to predict drug targets and their role in human pathophysiology.
AREAS COVERED: This review discusses existing computational and experimental QSP approaches such as polypharmacology techniques combined with systems biology information and considers the use of new tools and ideas in a wider 'systems-level' context in order to design new drugs with improved efficacy and fewer unwanted off-target effects.
EXPERT OPINION: The use of network biology produces valuable information such as new indications for approved drugs, drug-drug interactions, proteins-drug side effects and pathways-gene associations. However, we are still far from the aim of QSP, both because of the huge effort needed to model precisely biological network models and the limited accuracy that we are able to reach with those. Hence, moving from 'one molecule for one target to give one therapeutic effect' to the 'big systems-based picture' seems obvious moving forward although whether our current tools are sufficient for such a step is still under debate.

PMID: 26328768 [PubMed - indexed for MEDLINE]

Defining bacterial regulons using ChIP-seq.

Methods. 2015 Sep 15;86:80-8

Authors: Myers KS, Park DM, Beauchene NA, Kiley PJ

Abstract
Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is a powerful method that identifies protein-DNA binding sites in vivo. Recent studies have illustrated the value of ChIP-seq in studying transcription factor binding in various bacterial species under a variety of growth conditions. These results show that in addition to identifying binding sites, correlation of ChIP-seq data with expression data can reveal important information about bacterial regulons and regulatory networks. In this chapter, we provide an overview of the current state of knowledge about ChIP-seq methodology in bacteria, from sample preparation to raw data analysis. We also describe visualization and various bioinformatic analyses of processed ChIP-seq data.

PMID: 26032817 [PubMed - indexed for MEDLINE]

Systems biology approaches to defining transcription regulatory networks in halophilic archaea.

Methods. 2015 Sep 15;86:102-14

Authors: Darnell CL, Schmid AK

Abstract
To survive complex and changing environmental conditions, microorganisms use gene regulatory networks (GRNs) composed of interacting regulatory transcription factors (TFs) to control the timing and magnitude of gene expression. Genome-wide datasets; such as transcriptomics and protein-DNA interactions; and experiments such as high throughput growth curves; facilitate the construction of GRNs and provide insight into TF interactions occurring under stress. Systems biology approaches integrate these datasets into models of GRN architecture as well as statistical and/or dynamical models to understand the function of networks occurring in cells. Previously, these types of studies have focused on traditional model organisms (e.g. Escherichia coli, yeast). However, recent advances in archaeal genetics and other tools have enabled a systems approach to understanding GRNs in these relatively less studied archaeal model organisms. In this report, we outline a systems biology workflow for generating and integrating data focusing on the TF regulator. We discuss experimental design, outline the process of data collection, and provide the tools required to produce high confidence regulons for the TFs of interest. We provide a case study as an example of this workflow, describing the construction of a GRN centered on multi-TF coordinate control of gene expression governing the oxidative stress response in the hypersaline-adapted archaeon Halobacterium salinarum.

PMID: 25976837 [PubMed - indexed for MEDLINE]

Textual Analysis and Data Mining: An Interpreting Research on Nursing.

Stud Health Technol Inform. 2016;225:948

Authors: De Caro W, Mitello L, Marucci AR, Lancia L, Sansoni J

Abstract
Every day there is a data explosion on the web. In 2013, 5 exabytes of content were created each day. Every hour internet networks carries a quantity of texts equivalent to twenty billion books. For idea Iit is a huge mass of information on the linguistic behavior of people and society that was unthinkable until a few years ago. It is an opportunity for valuable analysis for understanding social phenomena, also in nursing and health care sector.This poster shows the the steps of an idealy strategy for textual statistical analysis and the process of extracting useful information about health care, referring expecially nursing care from journal and web information. We show the potential of web tools of Text Mining applications (DTM, Wordle, Voyant Tools, Taltac 2.10, Treecloud and other web 2.0 app) analyzing text data and information extraction about sentiment, perception, scientific activites and visibility of nursing. This specific analysis is conduct analyzing "Repubblica", first newspaper in Italy (years of analisys: 2012-14) and one italian scientific nursing journal (years: 2012-14).

PMID: 27332424 [PubMed - as supplied by publisher]

Application of Text Mining in Cancer Symptom Management.

Stud Health Technol Inform. 2016;225:930-931

Authors: Lee YJ, Donovan H

Abstract
Fatigue continues to be one of the main symptoms that afflict ovarian cancer patients and negatively affects their functional status and quality of life. To manage fatigue effectively, the symptom must be understood from the perspective of patients. We utilized text mining to understand the symptom experiences and strategies that were associated with fatigue among ovarian cancer patients. Through text analysis, we determined that descriptors such as energetic, challenging, frustrating, struggling, unmanageable, and agony were associated with fatigue. Descriptors such as decadron, encourager, grocery, massage, relaxing, shower, sleep, zoloft, and church were associated with strategies to ameliorate fatigue. This study demonstrates the potential of applying text mining in cancer research to understand patients' perspective on symptom management. Future study will consider various factors to refine the results.

PMID: 27332415 [PubMed - as supplied by publisher]

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]

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