Consensus Network Inference of Microarray Gene Expression Data

Genetic and protein interactions are essential to regulate cellular machinery. Their identification has become an important aim of systems biology research. In recent years, a variety of computational network inference algorithms have been employed to reconstruct gene regulatory networks from post-genomic data. However, precisely predicting these regulatory networks remains a challenge. We began our study by assessing the ability of various network inference algorithms to accurately predict gene regulatory interactions using benchmark simulated datasets. It was observed from our analysis that different algorithms have strengths and weaknesses when identifying regulatory networks, with a gene-pair interaction (edge) predicted by one algorithm not always necessarily consistent with the other. An edge not predicted by most inference algorithms may be an important one, and should not be missed. The naïve consensus (intersection) method is perhaps the most conservative approach and can be used to address this concern by extracting the edges consistently predicted across all inference algorithms; however, it lacks credibility as it does not provide a quantifiable measure for edge weights. Existing quantitative consensus approaches, such as the inverse-variance weighted method (IVWM) and the Borda count election method (BCEM), have been previously implemented to derive consensus networks from diverse datasets. However, the former method was biased towards finding local solutions in the whole network, and the latter considered species diversity to build the consensus network. In this thesis we proposed a novel consensus approach, in which we used Fishers Combined Probability Test (FCPT) to combine the statistical significance values assigned to each network edge by a number of different networking algorithms to produce a consensus network. We tested our method by applying it to a variety of in silico benchmark expression datasets of different dimensions and evaluated its performance against individual inference methods, Bayesian models and also existing qualitative and quantitative consensus techniques. We also applied our approach to real experimental data from the yeast (S. cerevisiae) network as this network has been comprehensively elucidated previously. Our results demonstrated that the FCPT-based consensus method outperforms single algorithms in terms of robustness and accuracy. In developing the consensus approach, we also proposed a scoring technique that quantifies biologically meaningful hierarchical modular networks.University of Exeter studentshi

PRESCRIPTION PATTERN OF ANTIMICROBIAL AGENTS AMONG DENTAL PRACTITIONERS IN A TERTIARY CARE CENTRE IN NORTH INDIA

Objective:The purpose of the study was to find out the pattern of antimicrobial prescription among dental practitioners in a tertiary care centre in North India. Methods:100 prescriptions of the patients attending the various dental outpatient departments of Ziauddin Ahmed Dental College, Aligarh Muslim University were collected and tabulated between January 2016 to June 2016. An observational study was done on the obtained prescriptions on various aspects like dental pathology for which antimicrobial were prescribed, antimicrobial agents used for management of acute and chronic conditions along with their dose and duration. Compliance of the patients during therapy and  adverse effects associated with the regimen was also taken into consideration and the final data was expressed as counts and percentages.Results: Out of a total of 100 patients 54 (54.0%) were males while females were numbered as 46 (42.0%) with maximum distribution of the patients between 31-40 years. On analysis the most commonly presented dental condition for which antimicrobials were prescribed were Acute/Chronic periodontitis (48%), Acute/Chronic gingivitis (32%), Caries (11%), Post RCT (4%), Pericoronitis (3%), Oral trauma (1%) and other condition (1%). For the management of above conditions  antimicrobials were the most extensively used agents which were prescribed for only 3-5 days which may not be sufficient, followed by analgesics and antimicrobial mouthwashes. Among the antimicrobials used, most frequently used agents were Amoxycillin (50%) followed by Ornidazole (21%), Ofloxacin (20%), Doxycycline (16%), Cefixime (9%) and Ciprofloxacin (3%) used either alone or in combination for the management of acute and chronic conditions. Only two patients were advised for culture & sensitivity tests prior to antimicrobial therapy because of non compliance of patients. Majority (74%) of patients completed the prescribed regimen of antimicrobials while 7 patients reported adverse drug reactions(ADRs), among which most common  were nausea and vomiting.Conclusions: In our study we found that the periodontal diseases were the most frequently reported conditions followed by acute/chronic gingivitis for which antimicrobials were prescribed while Amoxycillin and Ornidazole were the most commonly used antimicrobials for the management of various acute and chronic dental conditions, but were prescribed without culture & sensitivity in most cases. 7% patients reported ADRs. To conclude appropriate measures are to be promoted for rational prescribing and ADR reporting.Keywords: Amoxicillin, Dental, Antimicrobials, infections, Prescription pattern

Aggregated Modelling Analysis Of Power Flow From Wind Power Plant Into Grid System Using MATLAB/ SIMULINK Software

In consistent with the growth in demand, complexity of electric power systems has evolved to meet the requirements of supply. Power is generated from non-renewable, fossil fuels and nuclear fuel while renewable energy resources mainly include solar and wind. Power from Wind plants WP has shown a fast growth in the last decades due to their economic benefits especially at areas with the proper wind speed and the possibility to connect wind generators in distribution or transmission power networks. Conventional power unit generators are of high generation capacities, therefore smaller numbers are required in power plant, in other hand wind turbines WP are of smaller capacities therefore, Wind Power Plants (WPPs) consist of dozens or hundreds of low-power units. Time domain simulations of WPPs may take too much time if detailed models are considered in such studies while reduced order models used in interconnection studies of synchronous machines with full converter technology significantly reduce computational time (1, 2). The performance of all models is evaluated based on time domain simulations in the Simulink/MATLAB environment. The work includes the simulation of 50 MW WPP constructed from 18 MW doubly fed induction generators (DFIGs) aggregated (reduced) to one system of Nx2.78 MW generation capacity interconnected to existing conventional system network through 132 kV grid. The analysis includes active and power flow at the farm and the PCC terminals also power flow at PCC has been assessed for different level of WP penetration. Outputs from the MATLAB/SIMULINK modeling and simulation introduces the level of the grid voltage, current active and reactive power in the PCC and the wind farm terminal

Impacts Power Flow And Quality Of Penetrating 50MW Wind Plant Into Stand Alone Grid

The demand for electricity is continuously growing due to the development in community's macro-economic parameters; Population and the Gross Domestic Product (GDP). Currently, electricity is mainly generated from conventional sources including fossil fuels (oil, coal, gas, etc.) and nuclear fuel. The increase in demand increases the concerns about depletion of fossil fuels, increasing of carbon dioxide (C02) and other emissions, environmental pollution, and climate changes. Global energy agencies have been urged to look for sustainable and environment friend resources. Renewable energy resources especially wind and solar resources are found ambitious sources that can be developed to share other resources in supplying sustainable environmental friend power due to their economic benefits as compared with other resources and technologies. Energy generated from wind is growing faster than other renewable resources especially at areas with proper wind speed and characteristics capable to generate high power at small land and the possibility to interconnect wind networks with distribution or transmission power networks. Predictability of wind availability and characteristics is limited; therefore, the output of wind turbines cannot be controlled to the same extent as conventional generation technologies. This study involves assessing the impact of interconnecting a 50 MW wind plant at different penetration levels into a 132-kV grid powering a region in the sultanate of Oman isolated (islanded) from the main national grid. The assessment includes mutual impacts on power quality and flow, grid voltage flickering and performance of the network and the farm under steady state and disturbance conditions. The wind plant is constructed from an 18-equal capacity DFIG wind turbines modelled using the simulation from MA TLAB/Simulink available in the college. Parameters of control and operation parameters were developed to fit the wind plant operating conditions. The penetration levels considered in the research include I, 9 & 18 wind turbines in operation respectively which represent 5.5 %, 50 % and 100 % of the maximum farm generation capacity. The research outcomes revealed that penetrating the wind plant at the levels mentioned above provide high accuracy of compliance with the national and international standards and codes and that it shall not conflict the requirements of power quality and security of supply restricted in grid code and regulations. The outcomes obtained also provide high degree of confidence for integrating the wind plant with the existing grid network at the proposed point of common connection (PCC) without any additional extra works required on the existing network rather than those required for adaptation requirements

Accelerated ageing and renal dysfunction links lower socioeconomic status and dietary phosphate intake

Background: We have sought to explore the impact of dietary Pi intake on human age related health in the pSoBid cohort (n=666) to explain the disparity between health and deprivation status in this cohort. As hyperphosphataemia is a driver of accelerated ageing in rodent models of progeria we tested whether variation in Pi levels in man associate with measures of biological ageing and health. Results: We observed significant relationships between serum Pi levels and markers of biological age (telomere length (p=0.040) and DNA methylation content (p=0.028), gender and chronological age (p=0.032). When analyses were adjusted for socio-economic status and nutritional factors, associations were observed between accelerated biological ageing (telomere length, genomic methylation content) and dietary derived Pi levels among the most deprived males, directly related to the frequency of red meat consumption. Conclusions: Accelerated ageing is associated with high serum Pi levels and frequency of red meat consumption. Our data provide evidence for a mechanistic link between high intake of Pi and age-related morbidities tied to socio-economic status

Identification of molecular markers of delayed graft function based on the regulation of biological ageing

Introduction: Delayed graft function is a prevalent clinical problem in renal transplantation for which there is no objective system to predict occurrence in advance. It can result in a significant increase in the necessity for hospitalisation post-transplant and is a significant risk factor for other post-transplant complications. Methodology: The importance of microRNAs (miRNAs), a specific subclass of small RNA, have been clearly demonstrated to influence many pathways in health and disease. To investigate the influence of miRNAs on renal allograft performance post-transplant, the expression of a panel of miRNAs in pre-transplant renal biopsies was measured using qPCR. Expression was then related to clinical parameters and outcomes in two independent renal transplant cohorts. Results: Here we demonstrate, in two independent cohorts of pre-implantation human renal allograft biopsies, that a novel pre-transplant renal performance scoring system (GRPSS), can determine the occurrence of DGF with a high sensitivity (>90%) and specificity (>60%) for donor allografts pre-transplant, using just three senescence associated microRNAs combined with donor age and type of organ donation. Conclusion: These results demonstrate a relationship between pre-transplant microRNA expression levels, cellular biological ageing pathways and clinical outcomes for renal transplantation. They provide for a simple, rapid quantitative molecular pre-transplant assay to determine post-transplant allograft function and scope for future intervention. Furthermore, these results demonstrate the involvement of senescence pathways in ischaemic injury during the organ transplantation process and an indication of accelerated bio-ageing as a consequence of both warm and cold ischaemia

Operative management and outcomes in patients with myxomas: A single-center experience

BackgroundCardiac myxoma is a rare cardiac tumor that may be asymptomatic or can cause embolization or intracardiac obstruction, leading to heart failure, sudden cardiac death, and arrhythmia. This study aims to report an 11-year experience of a single center in the management of cardiac myxoma.MethodThis study is a single-center retrospective case series. Eighty cases of cardiac myxoma were collected in Ibn Albitar's specialized center for cardiac surgery. Transthoracic echocardiography was used to make the preoperative diagnosis in all patients. The surgeries were undertaken through the standard approach of a median sternotomy. All four cardiac chambers were thoroughly explored for additional myxomas. The major objective of the operations was complete tumor resection.ResultThe mean age of the patients was 46.3 years. Females (67.5%) were predominant over males (32.5%). Shortness of breath was the most common symptom (86.25%). The left atrium was the most affected site (83.75%), followed by the right atrium (13.75%). Coronary artery bypass grafting was required as the secondary or associated intervention in 19 (23.75%) cases. The recurrence rate was 11.25%, with a mortality rate of 3.75%.ConclusionRecurrence and tumor embolism are risks of surgical intervention for myxoma. Good preparation using transthoracic echocardiography as a diagnostic tool and standard median sternotomy to complete resection of the tumors can decrease the rate of recurrence, embolism, and even mortality

Expression Atlas update: gene and protein expression in multiple species.

The EMBL-EBI Expression Atlas is an added value knowledge base that enables researchers to answer the question of where (tissue, organism part, developmental stage, cell type) and under which conditions (disease, treatment, gender, etc) a gene or protein of interest is expressed. Expression Atlas brings together data from >4500 expression studies from >65 different species, across different conditions and tissues. It makes these data freely available in an easy to visualise form, after expert curation to accurately represent the intended experimental design, re-analysed via standardised pipelines that rely on open-source community developed tools. Each study's metadata are annotated using ontologies. The data are re-analyzed with the aim of reproducing the original conclusions of the underlying experiments. Expression Atlas is currently divided into Bulk Expression Atlas and Single Cell Expression Atlas. Expression Atlas contains data from differential studies (microarray and bulk RNA-Seq) and baseline studies (bulk RNA-Seq and proteomics), whereas Single Cell Expression Atlas is currently dedicated to Single Cell RNA-Sequencing (scRNA-Seq) studies. The resource has been in continuous development since 2009 and it is available at https://www.ebi.ac.uk/gxa