Carcinogenesis in Prostate Cancer: The role of Long Non-Coding RNAs

LncRNAs appear to play a considerable role in tumourigenesis through regulating key processes in cancer cells such as proliferative signalling, replicative immortality, invasion and metastasis, evasion of growth suppressors, induction of angiogenesis and resistance to apoptosis. LncRNAs have been reported to play a role in prostate cancer, particularly in regulating the androgen receptor signalling pathway. In this review article, we summarise the role of 34 lncRNAs in prostate cancer with a particular focus on their role in the androgen receptor signalling pathway and the epithelial to mesenchymal transition pathway

A brief review: Multimedia authoring modeling

Multimedia Authoring is a way to develop a multimedia presentation. Multimedia content includes images, sounds, videos, texts, and animations. The Kernel Mechanism of Multimedia Authoring consists of the Multimedia Authoring Programming Language and the Multimedia Authoring Model. Multimedia Authoring modeling is designed to enable the Multimedia Authoring function appropriately. Since the beginning of designing multimedia authoring tools, various studies were conducted to create a multimedia authoring model. Multimedia Authoring models that have been studied in existing research are Petri Nets, Hoare Logic, and LOTOS. The three models use different approaches. Petri Net uses a model based on graph calculations, Hoare logic uses mathematical logic, and LOTOS uses a formal specification language. Each of these models has been developed and modified to have higher capabilities. This model modification has advantages over the original model. This review article discusses the development and modifications of these models

α-Syntrophin Modulates Myogenin Expression in Differentiating Myoblasts

α-Syntrophin is a scaffolding protein linking signaling proteins to the sarcolemmal dystrophin complex in mature muscle. However, α-syntrophin is also expressed in differentiating myoblasts during the early stages of muscle differentiation. In this study, we examined the relationship between the expression of α-syntrophin and myogenin, a key muscle regulatory factor.The absence of α-syntrophin leads to reduced and delayed myogenin expression. This conclusion is based on experiments using muscle cells isolated from α-syntrophin null mice, muscle regeneration studies in α-syntrophin null mice, experiments in Sol8 cells (a cell line that expresses only low levels of α-syntrophin) and siRNA studies in differentiating C2 cells. In primary cultured myocytes isolated from α-syntrophin null mice, the level of myogenin was less than 50% that from wild type myocytes (p<0.005) 40 h after differentiation induction. In regenerating muscle, the expression of myogenin in the α-syntrophin null muscle was reduced to approximately 25% that of wild type muscle (p<0.005). Conversely, myogenin expression is enhanced in primary cultures of myoblasts isolated from a transgenic mouse over-expressing α-syntrophin and in Sol8 cells transfected with a vector to over-express α-syntrophin. Moreover, we find that myogenin mRNA is reduced in the absence of α-syntrophin and increased by α-syntrophin over-expression. Immunofluorescence microscopy shows that α-syntrophin is localized to the nuclei of differentiating myoblasts. Finally, immunoprecipitation experiments demonstrate that α-syntrophin associates with Mixed-Lineage Leukemia 5, a regulator of myogenin expression.We conclude that α-syntrophin plays an important role in regulating myogenesis by modulating myogenin expression

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Anti-KIF20B autoantibodies are associated with cranial neuropathy in systemic lupus erythematosus

Background: Cranial neuropathies (CN) are a rare neuropsychiatric SLE (NPSLE) manifestation. Previous studies reported that antibodies to the kinesin family member 20B (KIF20B) (anti-KIF20B) protein were associated with idiopathic ataxia and CN. We assessed anti-KIF20B as a potential biomarker for NPSLE in an international SLE inception cohort. Methods: Individuals fulfilling the revised 1997 American College of Rheumatology (ACR) SLE classification criteria were enrolled from 31 centres from 1999 to 2011 and followed annually in the Systemic Lupus Erythematosus International Collaborating Clinics inception cohort. Anti-KIF20B testing was performed on baseline (within 15 months of diagnosis or first annual visit) samples using an addressable laser bead immunoassay. Logistic regression (penalised maximum likelihood and adjusting for confounding variables) examined the association between anti-KIF20B and NPSLE manifestations (1999 ACR case definitions), including CN, occurring over the first 5 years of follow-up. Results: Of the 1827 enrolled cohort members, baseline serum and 5 years of follow-up data were available on 795 patients who were included in this study: 29.8% were anti-KIF20B-positive, 88.7% female, and 52.1% White. The frequency of anti-KIF20B positivity differed only for those with CN (n=10) versus without CN (n=785) (70.0% vs 29.3%; OR 5.2, 95% CI 1.4, 18.5). Compared with patients without CN, patients with CN were more likely to fulfil the ACR haematological (90.0% vs 66.1%; difference 23.9%, 95% CI 5.0%, 42.8%) and ANA (100% vs 95.7%; difference 4.3%, 95% CI 2.9%, 5.8%) criteria. In the multivariate analysis adjusting for age at baseline, female, White race and ethnicity, and ACR haematological and ANA criteria, anti-KIF20B positivity remained associated with CN (OR 5.2, 95% CI 1.4, 19.1). Conclusion: Anti-KIF20B is a potential biomarker for SLE-related CN. Further studies are needed to examine how autoantibodies against KIF20B, which is variably expressed in a variety of neurological cells, contribute to disease pathogenesis

Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes

OBJECTIVES: A novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes. METHODS: Demographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset. RESULTS: Cluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2. CONCLUSION: Four discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk

α-Syntrophin Modulates Myogenin Expression in Differentiating Myoblasts

α-Syntrophin is a scaffolding protein linking signaling proteins to the sarcolemmal dystrophin complex in mature muscle. However, α-syntrophin is also expressed in differentiating myoblasts during the early stages of muscle differentiation. In this study, we examined the relationship between the expression of α-syntrophin and myogenin, a key muscle regulatory factor.The absence of α-syntrophin leads to reduced and delayed myogenin expression. This conclusion is based on experiments using muscle cells isolated from α-syntrophin null mice, muscle regeneration studies in α-syntrophin null mice, experiments in Sol8 cells (a cell line that expresses only low levels of α-syntrophin) and siRNA studies in differentiating C2 cells. In primary cultured myocytes isolated from α-syntrophin null mice, the level of myogenin was less than 50% that from wild type myocytes (p<0.005) 40 h after differentiation induction. In regenerating muscle, the expression of myogenin in the α-syntrophin null muscle was reduced to approximately 25% that of wild type muscle (p<0.005). Conversely, myogenin expression is enhanced in primary cultures of myoblasts isolated from a transgenic mouse over-expressing α-syntrophin and in Sol8 cells transfected with a vector to over-express α-syntrophin. Moreover, we find that myogenin mRNA is reduced in the absence of α-syntrophin and increased by α-syntrophin over-expression. Immunofluorescence microscopy shows that α-syntrophin is localized to the nuclei of differentiating myoblasts. Finally, immunoprecipitation experiments demonstrate that α-syntrophin associates with Mixed-Lineage Leukemia 5, a regulator of myogenin expression.We conclude that α-syntrophin plays an important role in regulating myogenesis by modulating myogenin expression