The JAK inhibitor tofacitinib suppresses synovial JAK1-STAT signalling in rheumatoid arthritis.

ObjectiveTofacitinib is an oral Janus kinase (JAK) inhibitor for the treatment of rheumatoid arthritis (RA). The pathways affected by tofacitinib and the effects on gene expression in situ are unknown. Therefore, tofacitinib effects on synovial pathobiology were investigated.MethodsA randomised, double-blind, phase II serial synovial biopsy study (A3921073; NCT00976599) in patients with RA with an inadequate methotrexate response. Patients on background methotrexate received tofacitinib 10 mg twice daily or placebo for 28 days. Synovial biopsies were performed on Days -7 and 28 and analysed by immunoassay or quantitative PCR. Clinical response was determined by disease activity score and European League Against Rheumatism (EULAR) response on Day 28 in A3921073, and at Month 3 in a long-term extension study (A3921024; NCT00413699).ResultsTofacitinib exposure led to EULAR moderate to good responses (11/14 patients), while placebo was ineffective (1/14 patients) on Day 28. Tofacitinib treatment significantly reduced synovial mRNA expression of matrix metalloproteinase (MMP)-1 and MMP-3 (p<0.05) and chemokines CCL2, CXCL10 and CXCL13 (p<0.05). No overall changes were observed in synovial inflammation score or the presence of T cells, B cells or macrophages. Changes in synovial phosphorylation of signal transducer and activator of transcription 1 (STAT1) and STAT3 strongly correlated with 4-month clinical responses (p<0.002). Tofacitinib significantly decreased plasma CXCL10 (p<0.005) at Day 28 compared with placebo.ConclusionsTofacitinib reduces metalloproteinase and interferon-regulated gene expression in rheumatoid synovium, and clinical improvement correlates with reductions in STAT1 and STAT3 phosphorylation. JAK1-mediated interferon and interleukin-6 signalling likely play a key role in the synovial response.Trial registration numberNCT00976599

Secure watermarking scheme for color DICOM images in telemedicine applications

Teleradiology plays a vital role in the medical field, which permits transmitting medical and imaging data over a communication network. It ensures data reliability and provides convenient communication for clinical interpretation and diagnostic purposes. The transmission of this medical data over a network raises the problems of legal, ethical issues, privacy, and copyright authenticity. The copyright protection of medical images is a significant issue in the medical field. Watermarking schemes are used to address these issues. A gray-level or binary image is used as a watermark frequently in color image watermarking schemes. In this paper, the authors propose a novel non-blind medical image watermarking scheme based on 2-D Lifting Wavelet Transform (LWT), Multiresolution Singular Value Decomposition (MSVD), and LU factorization to improve the robustness and authenticity of medical images. In this scheme, multiple color watermarks are embedded into the colored DICOM (Digital Imaging and Communications in Medicine) images obtained from Color Doppler images (DICOM format), and the average results achieved by our proposed scheme is 46.84 db for Peak Signal-to-Noise Ratio (PSNR), 37.46 db for Signal-to-Noise Ratio (SNR), 0.99 for Quality of Image and 0.998 for Normalized Correlation for various image processing attacks. These results make our watermarking technique an ideal candidate for medical image watermarking

Vascular function and cholecalciferol supplementation in CKD: A self-controlled case series.

Vitamin D deficiency is common and associated with mortality in chronic kidney disease (CKD) patients. Cardiovascular disease (CVD) is the commonest cause of mortality in CKD patients. In a randomized, double blind, placebo controlled trial, we have recently reported favorable effects of vitamin D supplementation on vascular & endothelial function and inflammatory biomarkers in vitamin D deficient patients with non-diabetic stage 3-4 CKD (J Am Soc Nephrol 28: 3100-3108, 2017). Subjects in the placebo group who had still not received vitamin D after completion of the trial received two oral doses 300000 IU of oral cholecalciferol at 8 weeks interval followed by flow mediated dilatation (FMD), pulse wave velocity (PWV), circulating endothelial and inflammatory markers (E-Selectin, vWF, hsCRP and IL-6), 1,25 (OH)2D, iPTH and iFGF-23 assessment at 16 weeks. 31 subjects completed this phase of the study. Last values recorded in the preceding clinical trial were taken as baseline values. Serum 25(OH)D and 1,25(OH)2D increased and FMD significantly improved after cholecalciferol supplementation [mean change in FMD%: 5.8% (95% CI: 4.0-7.5%, p<0.001]. Endothelium independent nitroglycerine mediated dilatation, PWV, iPTH, iFGF-23 and IL-6 also showed favorable changes. The data further cement the findings of beneficial effects of correction of vitamin D deficiency on vascular function

Information Discovery on Electronic Health Records Using Authority Flow Techniques

<p>Abstract</p> <p>Background</p> <p>As the use of electronic health records (EHRs) becomes more widespread, so does the need to search and provide effective information discovery within them. Querying by keyword has emerged as one of the most effective paradigms for searching. Most work in this area is based on traditional Information Retrieval (IR) techniques, where each document is compared individually against the query. We compare the effectiveness of two fundamentally different techniques for keyword search of EHRs.</p> <p>Methods</p> <p>We built two ranking systems. The traditional BM25 system exploits the EHRs' content without regard to association among entities within. The Clinical ObjectRank (CO) system exploits the entities' associations in EHRs using an authority-flow algorithm to discover the most relevant entities. BM25 and CO were deployed on an EHR dataset of the cardiovascular division of Miami Children's Hospital. Using sequences of keywords as queries, sensitivity and specificity were measured by two physicians for a set of 11 queries related to congenital cardiac disease.</p> <p>Results</p> <p>Our pilot evaluation showed that CO outperforms BM25 in terms of sensitivity (65% vs. 38%) by 71% on average, while maintaining the specificity (64% vs. 61%). The evaluation was done by two physicians.</p> <p>Conclusions</p> <p>Authority-flow techniques can greatly improve the detection of relevant information in EHRs and hence deserve further study.</p

Data mining to identify risk factors associated with university students dropout

. This paper presents the identification of university students dropout patterns by means of data mining techniques. The database consists of a series of questionnaires and interviews to students from several universities in Colombia. The information was processed by the Weka software following the Knowledge Extraction Process methodology with the purpose of facilitating the interpretation of results and finding useful knowledge about the students. The partial results of data mining processing on the information about the generations of students of Industrial Engineering from 2016 to 2018 are analyzed and discussed, finding relationships between family, economic, and academic issues that indicate a probable desertion risk in students with common behaviors. These relationships provide enough and appropriate information for the decision-making process in the treatment of university dropout.Universidad Peruana de Ciencias Aplicadas, Universidad de la Costa, Universidad Libre Seccional Barranquilla, Corporación Universitaria Latinoamericana

Suv4-20h Histone Methyltransferases Promote Neuroectodermal Differentiation by Silencing the Pluripotency-Associated Oct-25 Gene

Post-translational modifications (PTMs) of histones exert fundamental roles in regulating gene expression. During development, groups of PTMs are constrained by unknown mechanisms into combinatorial patterns, which facilitate transitions from uncommitted embryonic cells into differentiated somatic cell lineages. Repressive histone modifications such as H3K9me3 or H3K27me3 have been investigated in detail, but the role of H4K20me3 in development is currently unknown. Here we show that Xenopus laevis Suv4-20h1 and h2 histone methyltransferases (HMTases) are essential for induction and differentiation of the neuroectoderm. Morpholino-mediated knockdown of the two HMTases leads to a selective and specific downregulation of genes controlling neural induction, thereby effectively blocking differentiation of the neuroectoderm. Global transcriptome analysis supports the notion that these effects arise from the transcriptional deregulation of specific genes rather than widespread, pleiotropic effects. Interestingly, morphant embryos fail to repress the Oct4-related Xenopus gene Oct-25. We validate Oct-25 as a direct target of xSu4-20h enzyme mediated gene repression, showing by chromatin immunoprecipitaton that it is decorated with the H4K20me3 mark downstream of the promoter in normal, but not in double-morphant, embryos. Since knockdown of Oct-25 protein significantly rescues the neural differentiation defect in xSuv4-20h double-morphant embryos, we conclude that the epistatic relationship between Suv4-20h enzymes and Oct-25 controls the transit from pluripotent to differentiation-competent neural cells. Consistent with these results in Xenopus, murine Suv4-20h1/h2 double-knockout embryonic stem (DKO ES) cells exhibit increased Oct4 protein levels before and during EB formation, and reveal a compromised and biased capacity for in vitro differentiation, when compared to normal ES cells. Together, these results suggest a regulatory mechanism, conserved between amphibians and mammals, in which H4K20me3-dependent restriction of specific POU-V genes directs cell fate decisions, when embryonic cells exit the pluripotent state

Dropout-permanence analysis of university students using data mining

Dropout is a rejection method present in every educational system, related to the various selection processes, academic performance, and the efficiency of the system in general, that is, the result of the combination and effect of different variables. In this sense, the dropout of university students related to their academic performance is a matter of concern since several years ago. Academic information is analyzed in order to identify factors that influence students´ dropout at the University of Mumbai, India, by using a data mining technique. The data source contains information provided to the entrance (personal and educational background) and that is generated during the study period. The data selection and cleansing are made using different criteria of representation and implementation of classification algorithms such as decision trees, Bayesian networks, and rules. the following factors are identified as influential variables in the desertion: approved courses, quantity and results of attended courses, origin and age of entry of the student. Through this process, it was possible to identify the attributes that characterize the dropout cases and their relationship with the academic performance, especially in the first year of the career

Neonatal resuscitation: EN-BIRTH multi-country validation study.

BACKGROUND: Annually, 14 million newborns require stimulation to initiate breathing at birth and 6 million require bag-mask-ventilation (BMV). Many countries have invested in facility-based neonatal resuscitation equipment and training. However, there is no consistent tracking for neonatal resuscitation coverage. METHODS: The EN-BIRTH study, in five hospitals in Bangladesh, Nepal, and Tanzania (2017-2018), collected time-stamped data for care around birth, including neonatal resuscitation. Researchers surveyed women and extracted data from routine labour ward registers. To assess accuracy, we compared gold standard observed coverage to survey-reported and register-recorded coverage, using absolute difference, validity ratios, and individual-level validation metrics (sensitivity, specificity, percent agreement). We analysed two resuscitation numerators (stimulation, BMV) and three denominators (live births and fresh stillbirths, non-crying, non-breathing). We also examined timeliness of BMV. Qualitative data were collected from health workers and data collectors regarding barriers and enablers to routine recording of resuscitation. RESULTS: Among 22,752 observed births, 5330 (23.4%) babies did not cry and 3860 (17.0%) did not breathe in the first minute after birth. 16.2% (n = 3688) of babies were stimulated and 4.4% (n = 998) received BMV. Survey-report underestimated coverage of stimulation and BMV. Four of five labour ward registers captured resuscitation numerators. Stimulation had variable accuracy (sensitivity 7.5-40.8%, specificity 66.8-99.5%), BMV accuracy was higher (sensitivity 12.4-48.4%, specificity > 93%), with small absolute differences between observed and recorded BMV. Accuracy did not vary by denominator option. < 1% of BMV was initiated within 1 min of birth. Enablers to register recording included training and data use while barriers included register design, documentation burden, and time pressure. CONCLUSIONS: Population-based surveys are unlikely to be useful for measuring resuscitation coverage given low validity of exit-survey report. Routine labour ward registers have potential to accurately capture BMV as the numerator. Measuring the true denominator for clinical need is complex; newborns may require BMV if breathing ineffectively or experiencing apnoea after initial drying/stimulation or subsequently at any time. Further denominator research is required to evaluate non-crying as a potential alternative in the context of respectful care. Measuring quality gaps, notably timely provision of resuscitation, is crucial for programme improvement and impact, but unlikely to be feasible in routine systems, requiring audits and special studies

Network Inference Algorithms Elucidate Nrf2 Regulation of Mouse Lung Oxidative Stress

A variety of cardiovascular, neurological, and neoplastic conditions have been associated with oxidative stress, i.e., conditions under which levels of reactive oxygen species (ROS) are elevated over significant periods. Nuclear factor erythroid 2-related factor (Nrf2) regulates the transcription of several gene products involved in the protective response to oxidative stress. The transcriptional regulatory and signaling relationships linking gene products involved in the response to oxidative stress are, currently, only partially resolved. Microarray data constitute RNA abundance measures representing gene expression patterns. In some cases, these patterns can identify the molecular interactions of gene products. They can be, in effect, proxies for protein–protein and protein–DNA interactions. Traditional techniques used for clustering coregulated genes on high-throughput gene arrays are rarely capable of distinguishing between direct transcriptional regulatory interactions and indirect ones. In this study, newly developed information-theoretic algorithms that employ the concept of mutual information were used: the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE), and Context Likelihood of Relatedness (CLR). These algorithms captured dependencies in the gene expression profiles of the mouse lung, allowing the regulatory effect of Nrf2 in response to oxidative stress to be determined more precisely. In addition, a characterization of promoter sequences of Nrf2 regulatory targets was conducted using a Support Vector Machine classification algorithm to corroborate ARACNE and CLR predictions. Inferred networks were analyzed, compared, and integrated using the Collective Analysis of Biological Interaction Networks (CABIN) plug-in of Cytoscape. Using the two network inference algorithms and one machine learning algorithm, a number of both previously known and novel targets of Nrf2 transcriptional activation were identified. Genes predicted as novel Nrf2 targets include Atf1, Srxn1, Prnp, Sod2, Als2, Nfkbib, and Ppp1r15b. Furthermore, microarray and quantitative RT-PCR experiments following cigarette-smoke-induced oxidative stress in Nrf2+/+ and Nrf2−/− mouse lung affirmed many of the predictions made. Several new potential feed-forward regulatory loops involving Nrf2, Nqo1, Srxn1, Prdx1, Als2, Atf1, Sod1, and Park7 were predicted. This work shows the promise of network inference algorithms operating on high-throughput gene expression data in identifying transcriptional regulatory and other signaling relationships implicated in mammalian disease

Intelligent and Distributed Data Warehouse for Student’s Academic Performance Analysis

In the academic world, a large amount of data is handled each day, ranging from student’s assessments to their socio-economic data. In order to analyze this historical information, an interesting alternative is to implement a Data Warehouse. However, Data Warehouses are not able to perform predictive analysis by themselves, so machine intelligence techniques can be used for sorting, grouping, and predicting based on historical information to improve the analysis quality. This work describes a Data Warehouse architecture to carry out an academic performance analysis of students