How my clinical placement in Australia helped me to become the clinician I am today

In the global society in which we live the graduate speech-language pathologist needs to be prepared for working with a culturally diverse client group and for the possibility that they may work in a country other than the one in which they trained. International clinical placement opportunities are a common method for many Australian speech language pathology programs to prepare students for an international career and for working with a culturally diverse client group. There have been many reported benefits for students taking part in these placements. But what are the benefits for overseas students who participate in a placement in Australia? This clinical insights article asked five clinicians who had trained in the UK and who had completed a placement in Australia during their training to reflect on this experience. They reported many benefits both personally and professionally. They felt that their Australian placement experience prepared them to work with a culturally diverse client group and shaped who they areas clinicians. There were also additional benefits for the service in which they now worked

Proteome-based plasma biomarkers for Alzheimer's disease

Alzheimer's disease is a common and devastating disease for which there is no readily available biomarker to aid diagnosis or to monitor disease progression. Biomarkers have been sought in CSF but no previous study has used two-dimensional gel electrophoresis coupled with mass spectrometry to seek biomarkers in peripheral tissue. We performed a case-control study of plasma using this proteomics approach to identify proteins that differ in the disease state relative to aged controls. For discovery-phase proteomics analysis, 50 people with Alzheimer's dementia were recruited through secondary services and 50 normal elderly controls through primary care. For validation purposes a total of 511 subjects with Alzheimer's disease and other neurodegenerative diseases and normal elderly controls were examined. Image analysis of the protein distribution of the gels alone identifies disease cases with 56% sensitivity and 80% specificity. Mass spectrometric analysis of the changes observed in two-dimensional electrophoresis identified a number of proteins previously implicated in the disease pathology, including complement factor H (CFH) precursor and α-2-macroglobulin (α- 2M). Using semi-quantitative immunoblotting, the elevation of CFH and α- 2M was shown to be specific for Alzheimer's disease and to correlate with disease severity although alternative assays would be necessary to improve sensitivity and specificity. These findings suggest that blood may be a rich source for biomarkers of Alzheimer's disease and that CFH, together with other proteins such as α- 2M may be a specific markers of this illness. © 2006 The Author(s).link_to_subscribed_fulltex

Interaction testing and polygenic risk scoring to estimate the association of common genetic variants with treatment resistance in schizophrenia

Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n=10 501) and individuals with non-TRS (n=20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r² = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r² = 1.09%; P = .04). Conclusions and Relevance In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.Funding/Support: This work was supported by Medical Research Council Centre grant MR/ L010305/1, Medical Research Council Program grant MR/P005748/1, and Medical Research Council Project grants MR/L011794/1 and MC_PC_17212 to Cardiff University and by the National Centre for Mental Health, funded by the Welsh Government through Health and Care Research Wales. This work acknowledges the support of the Supercomputing Wales project, which is partially funded by the European Regional Development Fund via the Welsh Government. Dr Pardiñas was supported by an Academy of Medical Sciences Springboard Award (SBF005\1083). Dr Andreassen was supported by the Research Council of Norway (grants 283798, 262656, 248980, 273291, 248828, 248778, and 223273); KG Jebsen Stiftelsen, South-East Norway Health Authority, and the European Union’s Horizon 2020 Research and Innovation Programme (grant 847776). Dr Ajnakina was supported by an National Institute for Health Research postdoctoral fellowship (PDF-2018-11-ST2-020). Dr Joyce was supported by the University College London Hospitals/UCL University College London Biomedical Research Centre. Dr Kowalec received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement (793530) from the government of Canada Banting postdoctoral fellowship programme and the University of Manitoba. Dr Sullivan was supported by the Swedish Research Council (Vetenskapsrådet, D0886501), the European Union’s Horizon 2020 programme (COSYN, 610307) and the US National Institute of Mental Health (U01 MH109528 and R01 MH077139). The Psychiatric Genomics Consortium was partly supported by the National Institute Of Mental Health (grants R01MH124873). The Sweden Schizophrenia Study was supported by the National Institute Of Mental Health (grant R01MH077139). The STRATA consortium was supported by a Stratified Medicine Programme grant to Dr MacCabe from the Medical Research Council (grant MR/L011794/1), which funded the research and supported Drs Pardiñas, Smart, Kassoumeri, Murray, Walters, and MacCabe. Dr Smart was supported by a Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital National Health Service Foundation Trust. The AESOP (US) cohort was funded by the UK Medical Research Council (grant G0500817). The Belfast (UK) cohort was funded by the Research and Development Office of Northern Ireland. The Bologna (Italy) cohort was funded by the European Community’s Seventh Framework program (HEALTH-F2-2010–241909, project EU-GEI). The Genetics and Psychosis project (London, UK) cohort was funded by the UK National Institute of Health Research Specialist Biomedical Research Centre for Mental Health, South London and the Maudsley National Health Service Mental Health Foundation Trust (SLAM) and the Institute of Psychiatry, Psychology, and Neuroscience at King’s College London; Psychiatry Research Trust; Maudsley Charity Research Fund; and the European Community’s Seventh Framework program (HEALTH-F2-2009-241909, project EU-GEI). The Lausanne (Switzerland) cohort was funded by the Swiss National Science Foundation (grants 320030_135736/1, 320030-120686, 324730-144064, 320030-173211, and 171804); the National Center of Competence in Research Synaptic Bases of Mental Diseases from the Swiss National Science Foundation (grant 51AU40_125759); and Fondation Alamaya. The Oslo (Norway) cohort was funded by the Research Council of Norway (grant 223273/F50, under the Centers of Excellence funding scheme, 300309, 283798) and the South-Eastern Norway Regional Health Authority (grants 2006233, 2006258, 2011085, 2014102, 2015088, and 2017-112). The Paris (France) cohort was funded by European Community’s Seventh Framework program (HEALTH-F2-2010–241909, project EU-GEI). The Prague (Czech Republic) cohort was funded by the Ministry of Health of the Czech Republic (grant NU20-04-00393). The Santander (Spain) cohort was funded by the following grants to Dr Crespo-Facorro: Instituto de Salud Carlos III (grants FIS00/3095, PI020499, PI050427, and PI060507), Plan Nacional de Drogas Research (grant 2005-Orden sco/3246/2004), SENY Fundatio Research (grant 2005-0308007), Fundacion Marques de Valdecilla (grant A/02/07, API07/011) and Ministry of Economy and Competitiveness and the European Fund for Regional Development (grants SAF2016-76046-R and SAF2013-46292-R). The West London (UK) cohort was funded by The Wellcome Trust (grants 042025, 052247, and 064607)

MdaB and NfrA, Two novel reductases important in the survival and persistence of the major enteropathogen Campylobacter jejuni

The paralogues RrpA and RrpB, which are members of the MarR family of DNA binding proteins, are important for the survival of the global bacterial foodborne pathogen Campylobacter jejuni under redox stress. We report that RrpA is a positive regulator of mdaB, encoding a flavin-dependent quinone reductase that contributes to the protection from redox stress mediated by structurally diverse quinones, while RrpB negatively regulates the expression of cj1555c (renamed nfrA for NADPH-flavin reductase A), encoding a flavin reductase. NfrA reduces riboflavin at a greater rate than its derivatives, suggesting that exogenous free flavins are the natural substrate. MdaB and NfrA both prefer NADPH as an electron donor. Cysteine substitution and posttranslational modification analyses indicated that RrpA and RrpB employ a cysteine-based redox switch. Complete genome sequence analyses revealed that mdaB is frequently found in Campylobacter and related Helicobacter spp., while nfrA is predominant in C. jejuni strains. Quinones and flavins are redox cycling agents secreted by a wide range of cell types that can form damaging superoxide by one-electron reactions. We propose a model for stress adaptation where MdaB and NfrA facilitate a two-electron reduction mechanism to the less toxic hydroquinones, thus aiding survival and persistence of this major pathogen. IMPORTANCE Changes in cellular redox potential result in alteration in the oxidation state of intracellular metabolites and enzymes; consequently, cells make adjustments that favor growth and survival. The work we present here answers some of the many questions that have remained elusive over the years of investigation into the enigmatic microaerophile bacterium Campylobacter jejuni. We employed molecular approaches to understand the regulation mechanisms and functional analyses to reveal the roles of two novel quinone and flavin reductases; both serve as major pools of cellular redox-active molecules. This work extends our knowledge on bacterial redox sensing mechanisms and the significance of hemostasis

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results: The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04). Conclusions and Relevance: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance

CATALISE: A multinational and multidisciplinary Delphi consensus study. Identifying language impairments in children

Delayed or impaired language development is a common developmental concern, yet thereis little agreement about the criteria used to identify and classify language impairments inchildren. Children's language difficulties are at the interface between education, medicineand the allied professions, who may all adopt different approaches to conceptualising them.Our goal in this study was to use an online Delphi technique to see whether it was possibleto achieve consensus among professionals on appropriate criteria for identifying childrenwho might benefit from specialist services. We recruited a panel of 59 experts representingten disciplines (including education, psychology, speech-language therapy/pathology, paediatricsand child psychiatry) from English-speaking countries (Australia, Canada, Ireland,New Zealand, United Kingdom and USA). The starting point for round 1 was a set of 46statements based on articles and commentaries in a special issue of a journal focusing onthis topic. Panel members rated each statement for both relevance and validity on a sevenpointscale, and added free text comments. These responses were synthesised by the firsttwo authors, who then removed, combined or modified items with a view to improving consensus.The resulting set of statements was returned to the panel for a second evaluation(round 2). Consensus (percentage reporting 'agree' or 'strongly agree') was at least 80 percentfor 24 of 27 round 2 statements, though many respondents qualified their responsewith written comments. These were again synthesised by the first two authors. The resultingconsensus statement is reported here, with additional summary of relevant evidence, and aconcluding commentary on residual disagreements and gaps in the evidence base.</p

Assessing the Effects of Responsible Leadership and Ethical Conflict on Behavioral Intention

[[abstract]]This study develops a research model that elaborates how responsible leadership and ethical conflict influence employees from the perspectives of role theory and attachment theory. Its empirical results reveal that turnover intention indirectly relates to ethical conflict and responsible leadership via the mediating mechanisms of organizational identification and organizational uncertainty. At the same time, helping intention indirectly relates to ethical conflict and responsible leadership only through organizational identification. Finally, the managerial implications for international business and research limitations based on the empirical results are discussed.[[notice]]補正完