28 research outputs found

    Comparison of the physical properties and sealing ability of MTA and Portland cement

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    Master'sMASTER OF SCIENC

    Efficient derivation of dopaminergic neurons from SOX1(-) floor plate cells under defined culture conditions.

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    BACKGROUND: Parkinson's disease (PD) is a severe neurodegenerative disease associated with loss of dopaminergic neurons. Derivation of dopaminergic neurons from human embryonic stem cells (hESCs) could provide new therapeutic options for PD therapy. Dopaminergic neurons are derived from SOX(-) floor plate (FP) cells during embryonic development in many species and in human cell culture in vitro. Early treatment with sonic hedgehog (Shh) has been reported to efficiently convert hESCs into FP lineages. METHODS: In this study, we attempted to utilize a Shh-free approach in deriving SOX1(-) FP cells from hESCs in vitro. Neuroectoderm conversion from hESCs was achieved with dual inhibition of the BMP4 (LDN193189) and TGF-β signaling pathways (SB431542) for 24 h under defined culture conditions. RESULTS: Following a further 5 days of treatment with LDN193189 or LDN193189 + SB431542, SOX1(-) FP cells constituted 70-80 % of the entire cell population. Upon treatment with Shh and FGF8, the SOX1(-) FP cells were efficiently converted to functional Nurr1(+) and TH(+) dopaminergic cells (patterning), which constituted more than 98 % of the entire cell population. However, when the same growth factors were applied to SOX1(+) cells, only less than 4 % of the cells became Nurr1(+), indicating that patterning was effective only if SOX1 expression was down-regulated. After transplanting the Nurr1(+) and TH(+) cells into a hemiparkinsonian rat model, significant improvements were observed in amphetamine induced ipslateral rotations, apomorphine induced contra-lateral rotations and Rota rod motor tests over a duration of 8 weeks. CONCLUSIONS: Our findings thus provide a convenient approach to FP development and functional dopaminergic neuron derivation.published_or_final_versio

    A clinical study of arrhythmias associated with acute coronary syndrome: a hospital based study of a high risk and previously undocumented population

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    Background: ACS represents a global epidemic. Arrhythmia in ACS is common. Careful investigation may lead to further improvement of prognosis. Retrospectively analyzed the year- round data of our center. Study was undertaken to analyze the incidence, frequency and type of arrhythmias in ACS. This is to aid timely intervention and to modify the outcome. Identification of the type of arrhythmia is of therapeutic and prognostic importance.Methods: This cross sectional analytical study was conducted in the Department of Cardiology, Apollo Hospitals Dhaka, from January 2019 to January 2020 with ACS patients. Enrolled consecutively and data analyzed.Results: There were 500 patients enrolled considering inclusion and exclusion criteria. Sample was subdivided into 3 groups on the type of ACS. Group-I with UA, Group-II with NSTE - ACS and Group-III with STE - ACS. Different types of arrhythmia noted. Types of arrhythmia were correlated with type of ACS. 500 patients included. Mean age 55.53±12.70, 71.6% male and 28.4% female. 60.4% hypertensive, 46.2% diabetic, 20.2% positive family history of CAD, 32.2% current smoker, 56.4% dyslipidaemic and 9.6% asthmatic. 31.2% UA, 39.2% NSTE-ACS and 29.6% STE-ACS. Type of arrhythmias noted. 22% sinus tachycardia, 20.2% sinus bradycardia, 9% atrial fibrillation, 5.2% ventricular ectopic, 4.8% supra ventricular ectopic, 2.8% bundle branch block, 2.2% atrio-ventricular block, 1% broad complex tachycardia, 0.4% narrow complex tachycardia, 0.2% sinus node dysfunction and 32.2% without any arrhythmia. Significant incidences of arrhythmia detected - respectively 29.8%, 39.2% and 31%, p<0.001.Conclusions: In conclusion, arrhythmias in ACS are common. More attention should be paid to improve their treatment and prognosis

    Step Stress Partially Accelerated Life Tests and Estimating Costs of Maintenance Service Policy for the Power Function Distribution under Progressive Type-II Censoring

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    The present paper illustrates how to analyze and design the accelerated life testing (ALTg) plans for the improvement of the quality and reliability of the product. We focus on estimating the costs of maintenance service policy because it plays a very important role in manufacturing organization and providing cost-effective equipment and maintenance.. When the lifetime of units follows power function distribution, the partially step-stress accelerated life test is assumed. The maximum likelihood estimates (MLEs) are obtained under the progressive Type-II censoring. Using the Fisher Information matrix, the asymptotic variance and covariance matrix are obtained. The confidence intervals (CIs) of the estimators are also constructed. Furthermor, a simulation study is conducted to check the results accuracy

    Accelerated Life Test Plans and Age-Replacement Policy under Warranty on Burr Type-X distribution with Type-II Censoring

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    In this paper, we describe how to design and analyze the accelerated life testing (ALTg) plans for the improvement of the quality and the reliability of the product. We also focus on finding the expected cost rate and the expected total cost for age-replacement under warranty policy. The problem is studied using constant stress, under the assumption that the lifetimes of the units follow Burr Type-X distribution for predicting the cost of age replacement under warranty policy. Asymptotic variance and covariance matrix of the estimators are obtained by using the Fisher Information Matrix. Confidence intervals for parameters and respective errors are also obtained. A simulation study is performed to illustrate the statistical properties of the parameters and confidence bound. In the last, numerical examples are also carried out to illustrate the theoretical results

    Comparison of dexmedetomidine and midazolam for conscious sedation in dental surgery monitored by bispectral index

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    10.1016/j.bjoms.2012.08.013British Journal of Oral and Maxillofacial Surgery515428-433BJOS

    Deep Convolutional Clustering-Based Time Series Anomaly Detection

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    This paper presents a novel approach for anomaly detection in industrial processes. The system solely relies on unlabeled data and employs a 1D-convolutional neural network-based deep autoencoder architecture. As a core novelty, we split the autoencoder latent space in discriminative and reconstructive latent features and introduce an auxiliary loss based on k-means clustering for the discriminatory latent variables. We employ a Top-K clustering objective for separating the latent space, selecting the most discriminative features from the latent space. We use the approach to the benchmark Tennessee Eastman data set to prove its applicability. We provide different ablation studies and analyze the method concerning various downstream tasks, including anomaly detection, binary and multi-class classification. The obtained results show the potential of the approach to improve downstream tasks compared to standard autoencoder architectures
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