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  1. Article: The Attitudes of Healthcare Students to Mindfulness-Based Interventions.

    Dunlea, S / Doherty, A M

    Irish medical journal

    2023  Volume 116, Issue 7, Page(s) 815

    MeSH term(s) Humans ; Mindfulness ; Attitude
    Language English
    Publishing date 2023-08-17
    Publishing country Ireland
    Document type Journal Article
    ZDB-ID 193134-9
    ISSN 0332-3102 ; 0021-129X
    ISSN 0332-3102 ; 0021-129X
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.B 148: Show issues Location:
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  2. Article ; Online: Teamwork and its impact on chronic disease clinical outcomes in primary care: a systematic review and meta-analysis.

    Tandan, Meera / Dunlea, Shane / Cullen, Walter / Bury, Gerard

    Public health

    2024  Volume 229, Page(s) 88–115

    Abstract: Objective: Teamwork positively affects staff performance and patient outcomes in chronic disease management. However, there is limited research on the impact of specific team components on clinical outcomes. This review aims to explore the impact of ... ...

    Abstract Objective: Teamwork positively affects staff performance and patient outcomes in chronic disease management. However, there is limited research on the impact of specific team components on clinical outcomes. This review aims to explore the impact of teamwork components on key clinical outcomes of chronic diseases in primary care.
    Study design: Systematic review and meta-analysis.
    Methods: This systematic review and meta-analysis conducted searching EMBASE, PubMed, Cochrane Central Register of Controlled Trials. Studies included must have at least one teamwork component, conducted in primary care for selected chronic diseases, and report an impact of teamwork on clinical outcomes. Mean differences and 95% confidence intervals were used to determine pooled effects of intervention.
    Results: A total of 54 studies from 1988 to 2021 were reviewed. Shared decision-making, roles sharing, and leadership were missing in most studies. Team-based intervention showed a reduction in mean systolic blood pressure (MD = 5.88, 95% CI 3.29-8.46, P= <0.001, I
    Conclusion: Team-based interventions improve outcomes for chronic diseases, but more research is needed on managing cholesterol, hospitalizations, and chronic obstructive pulmonary disease. Studies with 4-5 team components were more effective in reducing systolic blood pressure and diastolic blood pressure. Heterogeneity should be considered, and additional research is needed to optimize interventions for specific patient populations.
    MeSH term(s) Humans ; Cholesterol ; Chronic Disease ; Glycated Hemoglobin ; Primary Health Care ; Pulmonary Disease, Chronic Obstructive/therapy ; Patient Care Team/organization & administration
    Chemical Substances Cholesterol (97C5T2UQ7J) ; Glycated Hemoglobin
    Language English
    Publishing date 2024-02-26
    Publishing country Netherlands
    Document type Journal Article ; Meta-Analysis ; Systematic Review
    ZDB-ID 427333-3
    ISSN 1476-5616 ; 0033-3506
    ISSN (online) 1476-5616
    ISSN 0033-3506
    DOI 10.1016/j.puhe.2024.01.019
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Hepatitis C Infection and Treatment among Injecting Drug Users Attending General Practice: A Systematic Review and Meta-Analysis.

    Tandan, Meera / Dunlea, Shane / Bury, Gerard

    International journal of environmental research and public health

    2023  Volume 20, Issue 8

    Abstract: Background: The care provided in general practice to intravenous drug users (IDUs) with hepatitis C (HCV) extends beyond opioid substitution therapy. An aggregated analysis of HCV service utilization within general practice specifically related to ... ...

    Abstract Background: The care provided in general practice to intravenous drug users (IDUs) with hepatitis C (HCV) extends beyond opioid substitution therapy. An aggregated analysis of HCV service utilization within general practice specifically related to diagnosis and treatment outcomes remains unknown from previous literature.
    Aims: This study aims to estimate the prevalence of HCV and analyze data related to the diagnosis and treatment-related outcomes of HCV patients with a history of intravenous drug use in the general practice setting.
    Design and setting: A systematic review and meta-analysis in general practice.
    Methods: This review included studies published in the following databases: EMBASE, PubMed, and Cochrane Central Register of Controlled Trials. Two reviewers independently extracted data in standard forms in Covidence. A meta-analysis was done using a DerSimonian and Laird random-effects model with inverse variance weighting.
    Results: A total of 20,956 patients from 440 general practices participated in the 18 selected studies. A meta-analysis of 15 studies showed a 46% (95% confidence interval (CI), 26-67%) prevalence rate of hepatitis C amongst IDUs. Genotype information was available in four studies and treatment-related outcomes in 11 studies. Overall, treatment uptake was 9%, with a cure rate of 64% (95% CI, 43-83%). However, relevant information, such as specific treatment regimens, treatment duration and doses, and patient comorbidities, was poorly documented in these studies.
    Conclusion: The prevalence of HCV in IDUs is 46% in general practice. Only ten studies reported HCV-related treatment outcomes; however, the overall uptake rate was below 10%, with a cure rate of 64%. Likewise, the genotypic variants of HCV diagnoses, medication types, and doses were poorly reported, suggesting a need for further research into this aspect of care within this patient group to ensure optimal treatment outcomes.
    MeSH term(s) Humans ; Drug Users ; Hepatitis C/drug therapy ; Hepatitis C/epidemiology ; Hepatitis C/diagnosis ; Substance Abuse, Intravenous/epidemiology ; Hepacivirus ; Family Practice ; Prevalence
    Language English
    Publishing date 2023-04-18
    Publishing country Switzerland
    Document type Meta-Analysis ; Systematic Review ; Journal Article ; Review
    ZDB-ID 2175195-X
    ISSN 1660-4601 ; 1661-7827
    ISSN (online) 1660-4601
    ISSN 1661-7827
    DOI 10.3390/ijerph20085569
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Classification of a large microarray data set: algorithm comparison and analysis of drug signatures.

    Natsoulis, Georges / El Ghaoui, Laurent / Lanckriet, Gert R G / Tolley, Alexander M / Leroy, Fabrice / Dunlea, Shane / Eynon, Barrett P / Pearson, Cecelia I / Tugendreich, Stuart / Jarnagin, Kurt

    Genome research

    2005  Volume 15, Issue 5, Page(s) 724–736

    Abstract: A large gene expression database has been produced that characterizes the gene expression and physiological effects of hundreds of approved and withdrawn drugs, toxicants, and biochemical standards in various organs of live rats. In order to derive ... ...

    Abstract A large gene expression database has been produced that characterizes the gene expression and physiological effects of hundreds of approved and withdrawn drugs, toxicants, and biochemical standards in various organs of live rats. In order to derive useful biological knowledge from this large database, a variety of supervised classification algorithms were compared using a 597-microarray subset of the data. Our studies show that several types of linear classifiers based on Support Vector Machines (SVMs) and Logistic Regression can be used to derive readily interpretable drug signatures with high classification performance. Both methods can be tuned to produce classifiers of drug treatments in the form of short, weighted gene lists which upon analysis reveal that some of the signature genes have a positive contribution (act as "rewards" for the class-of-interest) while others have a negative contribution (act as "penalties") to the classification decision. The combination of reward and penalty genes enhances performance by keeping the number of false positive treatments low. The results of these algorithms are combined with feature selection techniques that further reduce the length of the drug signatures, an important step towards the development of useful diagnostic biomarkers and low-cost assays. Multiple signatures with no genes in common can be generated for the same classification end-point. Comparison of these gene lists identifies biological processes characteristic of a given class.
    MeSH term(s) Algorithms ; Animals ; Bone Marrow/metabolism ; Classification/methods ; Dose-Response Relationship, Drug ; Gene Expression Regulation ; Kidney/metabolism ; Liver/metabolism ; Logistic Models ; Male ; Myocardium/metabolism ; Oligonucleotide Array Sequence Analysis/methods ; Oligonucleotide Array Sequence Analysis/standards ; Pharmaceutical Preparations/metabolism ; Principal Component Analysis ; RNA, Messenger/isolation & purification ; Rats ; Rats, Sprague-Dawley ; Reproducibility of Results
    Chemical Substances Pharmaceutical Preparations ; RNA, Messenger
    Language English
    Publishing date 2005-05
    Publishing country United States
    Document type Comparative Study ; Journal Article
    ZDB-ID 1284872-4
    ISSN 1549-5469 ; 1088-9051 ; 1054-9803
    ISSN (online) 1549-5469
    ISSN 1088-9051 ; 1054-9803
    DOI 10.1101/gr.2807605
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  5. Article: Development of a large-scale chemogenomics database to improve drug candidate selection and to understand mechanisms of chemical toxicity and action.

    Ganter, Brigitte / Tugendreich, Stuart / Pearson, Cecelia I / Ayanoglu, Eser / Baumhueter, Susanne / Bostian, Keith A / Brady, Lindsay / Browne, Leslie J / Calvin, John T / Day, Gwo-Jen / Breckenridge, Naiomi / Dunlea, Shane / Eynon, Barrett P / Furness, L Mike / Ferng, Joe / Fielden, Mark R / Fujimoto, Susan Y / Gong, Li / Hu, Christopher /
    Idury, Radha / Judo, Michael S B / Kolaja, Kyle L / Lee, May D / McSorley, Christopher / Minor, James M / Nair, Ramesh V / Natsoulis, Georges / Nguyen, Peter / Nicholson, Simone M / Pham, Hang / Roter, Alan H / Sun, Dongxu / Tan, Siqi / Thode, Silke / Tolley, Alexander M / Vladimirova, Antoaneta / Yang, Jian / Zhou, Zhiming / Jarnagin, Kurt

    Journal of biotechnology

    2005  Volume 119, Issue 3, Page(s) 219–244

    Abstract: Successful drug discovery requires accurate decision making in order to advance the best candidates from initial lead identification to final approval. Chemogenomics, the use of genomic tools in pharmacology and toxicology, offers a promising enhancement ...

    Abstract Successful drug discovery requires accurate decision making in order to advance the best candidates from initial lead identification to final approval. Chemogenomics, the use of genomic tools in pharmacology and toxicology, offers a promising enhancement to traditional methods of target identification/validation, lead identification, efficacy evaluation, and toxicity assessment. To realize the value of chemogenomics information, a contextual database is needed to relate the physiological outcomes induced by diverse compounds to the gene expression patterns measured in the same animals. Massively parallel gene expression characterization coupled with traditional assessments of drug candidates provides additional, important mechanistic information, and therefore a means to increase the accuracy of critical decisions. A large-scale chemogenomics database developed from in vivo treated rats provides the context and supporting data to enhance and accelerate accurate interpretation of mechanisms of toxicity and pharmacology of chemicals and drugs. To date, approximately 600 different compounds, including more than 400 FDA approved drugs, 60 drugs approved in Europe and Japan, 25 withdrawn drugs, and 100 toxicants, have been profiled in up to 7 different tissues of rats (representing over 3200 different drug-dose-time-tissue combinations). Accomplishing this task required evaluating and improving a number of in vivo and microarray protocols, including over 80 rigorous quality control steps. The utility of pairing clinical pathology assessments with gene expression data is illustrated using three anti-neoplastic drugs: carmustine, methotrexate, and thioguanine, which had similar effects on the blood compartment, but diverse effects on hepatotoxicity. We will demonstrate that gene expression events monitored in the liver can be used to predict pathological events occurring in that tissue as well as in hematopoietic tissues.
    MeSH term(s) 5-Aminolevulinate Synthetase/biosynthesis ; Animals ; Antineoplastic Agents/pharmacology ; Antineoplastic Agents/toxicity ; Automation ; Bile Ducts/pathology ; Biotechnology/methods ; Carmustine/toxicity ; Computational Biology ; Databases as Topic ; Dose-Response Relationship, Drug ; Down-Regulation ; Drug Design ; Drug Industry/methods ; Gene Expression ; Humans ; Hyperplasia/etiology ; Liver/drug effects ; Male ; Methotrexate/toxicity ; Nucleic Acid Hybridization ; Oligonucleotide Array Sequence Analysis ; Organ Size ; Pharmacology/methods ; RNA/chemistry ; RNA, Complementary/metabolism ; Rats ; Rats, Sprague-Dawley ; Reticulocytes/cytology ; Reticulocytes/metabolism ; Thioguanine/toxicity ; Time Factors ; Tissue Distribution ; Toxicology/methods
    Chemical Substances Antineoplastic Agents ; RNA, Complementary ; RNA (63231-63-0) ; 5-Aminolevulinate Synthetase (EC 2.3.1.37) ; ALAS2 protein, human (EC 2.3.1.37) ; Thioguanine (FTK8U1GZNX) ; Carmustine (U68WG3173Y) ; Methotrexate (YL5FZ2Y5U1)
    Language English
    Publishing date 2005-09-29
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 843647-2
    ISSN 1873-4863 ; 0168-1656 ; 1389-0352
    ISSN (online) 1873-4863
    ISSN 0168-1656 ; 1389-0352
    DOI 10.1016/j.jbiotec.2005.03.022
    Database MEDical Literature Analysis and Retrieval System OnLINE

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