Clinical feasibility tests on a novel optical on-line blood monitoring sensor for cardiopulmonary systems

An on-line determination of the oxygen saturation and hematocrit (Hct) in cardiopulmonary systems is important for control of the oxygen supply to the body and the functionality of the oxygenation systems. A novel on-line spatially resolving sensor was investigated. Diffuse reflectance of circulating blood at 700 and 810 nm wavelength was detected at different distances from the light source. The sensor was connected to the venous side of an extracorporeal circulation unit. Blood samples were taken for reference measurement after every reflectance measurement. The 72 measurements obtained for 9 patients during heart lung surgery were processed by the “partial least squares regression”. These measurements, recorded during surgery, ranged between 15% and 31% for Hct and between 69% and 95% for oxygen saturation (SatO₂). Using the “leave-one-out” validation method, values for Hct and SatO₂ were determined with a predictive root mean square error (PRMSE) of 0.8% and 2.2%, respectively. No correlations were established between differences in predicted and reference values of the determined blood parameters and the parameters Hct, SatO₂, patient, blood flow, temperature or time of measurement. A cross validation with half the measurements has shown that the Hct and SatO₂ can be predicted with a PRMSE of 2.2% in both cases. As the accuracy achieved exceeds that of existing systems, this approach could provide a promising method for on-line blood monitoring of cardiopulmonary systems.     

Iterative multi-channel coherence analysis with applications

An iterative learning algorithm for performing Multi-Channel Coherence Analysis (MCCA) is developed in this paper. MCCA is an extension of the well-known Canonical Correlation Analysis (CCA) that allows for more than two data channels to be analyzed. This paper discusses a standard method for performing MCCA and compares it to a newly developed data-driven and iterative approach. The proposed algorithm is then tested on two examples and its performance is evaluated in terms of estimation errors with respect to the values obtained using the standard MCCA algorithm. The first example uses a synthesized data set while the second example uses a real data set based on multi-spectral satellite imagery of the Earth’s surface.     

Gut microbiota dysbiosis in patients with hepatitis B virus-related cirrhosis

Introduction and aimChronic hepatitis B (CHB) is a global epidemic disease that results from hepatitis B virus (HBV) infection and may progress to liver cirrhosis. The relationship between hepatitis B virus-related cirrhosis (HBV-RC) and gut microbiota dysbiosis is still unclear. The aim of this study is to elucidate the compositional and functional characteristics of the gut microbiota in the patients with liver cirrhosis and healthy individuals.Materials and methodsWe analyzed the gut microbiome in patients with HBV-RC and healthy individuals by 16S rRNA sequencing and metagenomic sequencing of fecal samples. A total of 113 genera, 85 families, 57 orders, 44 classes and 21 phyla were performed.ResultsOur results suggests that the composition of the gut microbiota had changed in the early stages of cirrhosis. We further identified more than 17 genera with different richness in compensated and decompensated cirrhosis groups. PICRUSt analysis showed that changes in bacterial composition can lead to significant changes in gene function, which may be one of the causes of liver cirrhosis.ConclusionOur study demonstrated that the composition of gut microbiota changed at different phases of HBV-RC. Gut microbiome transformation may be a biological factor in the progression of cirrhosis.     

最小二乘曲线拟合法测量Spee氏曲线

目的 探讨在头颅侧位片上测量牙弓Spee曲度的方法并探究整平Spee氏曲线与所需间隙量的关系.方法 纳入108例错(牙合)畸形患者,收集治疗前、后头颅侧位片,使用液晶数位描图板描绘Spee氏曲线,并在MATLAB7.0中提取出,基于最小二乘法进行曲线拟合、计算.结果 Spee氏曲线拟合数学模型圆的方差最小;同一操作者的自身重复性好,不同操作者间的一致性高;与模型测量法结果未见统计学差异;预测整平本研究样本全牙列和后牙段Spee氏曲线单侧所需平均间隙量分别为:1.1±0.02mm;0.87±0.08 mm.结论 1.在头颅侧位片上可以使用圆作为数学模型,采用最小二乘法曲线拟合的方法测量Spee氏曲线.2.本研究的方法可以推算整平Spee氏曲线所需的间隙量.     

Exploiting inherent relationships in RNN architectures

We provide the relationship between the learning rate and the slope of a nonlinear activation function of a neuron within the framework of nonlinear modular cascaded systems realised through Recurrent Neural Network (RNN) architectures. This leads to reduction in the computational complexity of learning algorithms which continuously adapt the weights of such architectures, because there is a smaller number of independent parameters to optimise. Results are provided for the Gradient Descent (GD) learning algorithm and the Extended Recursive Least Squares (ERLS) algorithm, using a general nonlinear activation function of a neuron. The results obtained degenerate into the corresponding results for single RNNs, when considering only one module in such cascaded systems.     

百分位数回归及其应用

传统的直线回归中，用最小二乘法估计回归系数，要求数据的独立性，方差齐性及正态性。但医学研究中，很多资料不满足上述要求，特别是ｙ的条件分布不是正态，或方差不为常数。这类资源显然不能用传统的最小二乘法估计回归系数。     

应用近红外漫反射技术测定精氨酸阿司匹林的含量

利用近红外漫反射技术和化学计算学方法对精氨酸阿司匹林片剂中精氨酸要司匹林的含量进行了定量分析，所建预测方程对样品的预测值与真值之间的相关系数达９９．０８％。     

非线性曲线拟合确定恒温——变温动力学参数

变温动力学;;化学稳定性;;最小二乘法;;硫酸链霉素;;活化能