Research on mild cognitive impairment diagnosis based on Bayesian optimized long-short-term neural network model / 生物医学工程学杂志

The recurrent neural network architecture improves the processing ability of time-series data. However, issues such as exploding gradients and poor feature extraction limit its application in the automatic diagnosis of mild cognitive impairment (MCI). This paper proposed a research approach for building an MCI diagnostic model using a Bayesian-optimized bidirectional long short-term memory network (BO-BiLSTM) to address this problem. The diagnostic model was based on a Bayesian algorithm and combined prior distribution and posterior probability results to optimize the BO-BiLSTM network hyperparameters. It also used multiple feature quantities that fully reflected the cognitive state of the MCI brain, such as power spectral density, fuzzy entropy, and multifractal spectrum, as the input of the diagnostic model to achieve automatic MCI diagnosis. The results showed that the feature-fused Bayesian-optimized BiLSTM network model achieved an MCI diagnostic accuracy of 98.64% and effectively completed the diagnostic assessment of MCI. In conclusion, based on this optimization, the long short-term neural network model has achieved automatic diagnostic assessment of MCI, providing a new diagnostic model for intelligent diagnosis of MCI.

The current applicating state of neural network-based electroencephalogram diagnosis of Alzheimer's disease / 生物医学工程学杂志

The electroencephalogram (EEG) signal is a general reflection of the neurophysiological activity of the brain, which has the advantages of being safe, efficient, real-time and dynamic. With the development and advancement of machine learning research, automatic diagnosis of Alzheimer's diseases based on deep learning is becoming a research hotspot. Started from feedforward neural networks, this paper compared and analysed the structural properties of neural network models such as recurrent neural networks, convolutional neural networks and deep belief networks and their performance in the diagnosis of Alzheimer's disease. It also discussed the possible challenges and research trends of this research in the future, expecting to provide a valuable reference for the clinical application of neural networks in the EEG diagnosis of Alzheimer's disease.

Brain tissue microstructure parameters estimation method based on proximal gradient network / 生物医学工程学杂志

Diffusion tensor imaging technology can provide information on the white matter of the brain, which can be used to explore changes in brain tissue structure, but it lacks the specific description of the microstructure information of brain tissue. The neurite orientation dispersion and density imaging make up for its shortcomings. But in order to accurately estimate the brain microstructure, a large number of diffusion gradients are needed, and the calculation is complex and time-consuming through maximum likelihood fitting. Therefore, this paper proposes a kind of microstructure parameters estimation method based on the proximal gradient network, which further avoids the classic fitting paradigm. The method can accurately estimate the parameters while reducing the number of diffusion gradients, and achieve the purpose of imaging quality better than the neurite orientation dispersion and density imaging model and accelerated microstructure imaging via convex optimization model.

Local helix parameters fitting of proteins based on dual quaternions registration method / 生物医学工程学杂志

A fitting method of calculating local helix parameters of proteins based on dual quaternions registration fitting (DQRFit) is proposed in this paper. First, the C and N atom coordinates of each residue in the protein structure data are extracted. Then the unregistered data and reference data are constructed using the sliding windows. The square sum of the distance of the data points before and after registration is regarded as an optimization goal. We calculate the optimal rotation matrix and the translation vector using the dual quaternion registration algorithm, and get the helix parameters of the secondary structure which contain the number of residues per turn( ), helix radius( )and helix pitch( ). Furthermore, we can achieve the fitting of three-helix parameters of , , simultaneously with the dual quaternion registration, and can adjust the sliding windows to adapt to different error levels. Compared with the traditional helix fitting method, DQRFit has some advantages such as low computational complexity, strong anti-interference, and high fitting accuracy. It is proven that the precision of proposed DQRFit for α helix detection is comparable to that of the dictionary of secondary structure of proteins (DSSP), and is better than that of other traditional methods. This is of great significance for the protein structure classification and functional prediction, drug design, protein structure visualization and other fields in the future.

Pseudolaric Acid B Inhibits Proliferation, Invasion and Epithelial-to-Mesenchymal Transition in Human Pancreatic Cancer Cell

PURPOSE: This study was aimed to investigate the effect of pseudolaric acid B (PAB) on proliferation, invasion and epithelial-to-mesenchymal transition (EMT) in pancreatic cancer cells and to explore the possible mechanism. MATERIALS AND METHODS: The pancreatic cancer cell line SW1990 was cultured and treated with PAB dose- and time-dependent manners. Cell proliferation and invasion ability were measured by MTT assay and Matrigel/Transwell test, respectively. Semi-quantitative real-time polymerase chain reaction and Western blotting were conducted to detect the expression of EMT markers and the key molecules. Finally, nude mice subcutaneous transplantation tumor model was used to confirm the therapy efficacy of PAB. RESULTS: PAB could inhibit SW1990 cell proliferation and invasion in time- and dose-dependent manners. Vimentin, fibronectin, N-cadherin, Snail, Slug, YAP, TEAD1, and Survivin were down-regulated (p < 0.01), while E-cadherin, caspase-9, MST1, and pYAP were up-regulated (p < 0.05). Combined PAB and gemcitabine treatment markedly restricted the tumor growth compared with gencitabin or PAB alone groups. CONCLUSION: PAB could inhibit the proliferation and invasion ability of pancreatic cancer cells through activating Hippo-YAP pathway and inhibiting the process of EMT.

Quaternion-based Characterization of Protein α Helix / 生物医学工程学杂志

This paper proposes a method based on quaternion for characterization a helix of proteins. The method defines the parameter called Quaternion Helix Axis Spherical Distance (QHASD) on the basis of mapping protein Cα frames' helical axis onto a unit sphere, and uses QHASD to characterize the a helix of the protein secondary structure. Application of this method has been verified based on the PDBselect database, with an a helix characterization accuracy of 91.7%. This method possesses significant advantages of high detection accuracy, low computation and clear geometric significance.

Anomaly Detection of Multivariate Time Series Based on Riemannian Manifolds / 生物医学工程学杂志

Multivariate time series problems widely exist in production and life in the society. Anomaly detection has provided people with a lot of valuable information in financial, hydrological, meteorological fields, and the research areas of earthquake, video surveillance, medicine and others. In order to quickly and efficiently find exceptions in time sequence so that it can be presented in front of people in an intuitive way, we in this study combined the Riemannian manifold with statistical process control charts, based on sliding window, with a description of the covariance matrix as the time sequence, to achieve the multivariate time series of anomaly detection and its visualization. We made MA analog data flow and abnormal electrocardiogram data from MIT-BIH as experimental objects, and verified the anomaly detection method. The results showed that the method was reasonable and effective.

Content-based language teaching and further college English reform in TCM universities / 中华医学教育探索杂志

English for Academic Purpose (EAP), putting more emphasis on cultivating students ' ability in academic study, is an integral part of College English reform, This paper aims to explore how to carry out college English reform with the focus on EAP in universities of Traditional Chinese Medicine ( TCM ) , proposing practical approaches under the guidance of Content-based Language Teaching (CBLT). The suggestions include further implementation of EAP, the coherence of the General English courses, the construction of college English course system, the establishment of multiple as-sessment system and the development of suitable teaching material. The purpose is to advance the ap-plication and specialty of teaching content and make College English teaching serve TCM students' needs of academic studies and future careers more effectively.

Automatic Classification of Epileptic Electroencephalogram Signal Based on Improved Multivariate Multiscale Entropy / 生物医学工程学杂志

Traditional sample entropy fails to quantify inherent long-range dependencies among real data. Multiscale sample entropy (MSE) can detect intrinsic correlations in data, but it is usually used in univariate data. To generalize this method for multichannel data, we introduced multivariate multiscale entropy into multiscale signals as a reflection of the nonlinear dynamic correlation. But traditional multivariate multiscale entropy has a large quantity of computation and costs a large period of time and space for more channel system, so that it can not reflect the correlation between variables timely and accurately. In this paper, therefore, an improved multivariate multiscale entropy embeds on all variables at the same time, instead of embedding on a single variable as in the traditional methods, to solve the memory overflow while the number of channels rise, and it is more suitable for the actual multivariate signal analysis. The method was tested in simulation data and Bonn epilepsy dataset. The simulation results showed that the proposed method had a good performance to distinguish correlation data. Bonn epilepsy dataset experiment also showed that the method had a better classification accuracy among the five data set, especially with an accuracy of 100% for data collection of Z and S.

Nonparametric method of estimating survival functions containing right-censored and interval-censored data / 生物医学工程学杂志

Missing data represent a general problem in many scientific fields, especially in medical survival analysis. Dealing with censored data, interpolation method is one of important methods. However, most of the interpolation methods replace the censored data with the exact data, which will distort the real distribution of the censored data and reduce the probability of the real data falling into the interpolation data. In order to solve this problem, we in this paper propose a nonparametric method of estimating the survival function of right-censored and interval-censored data and compare its performance to SC (self-consistent) algorithm. Comparing to the average interpolation and the nearest neighbor interpolation method, the proposed method in this paper replaces the right-censored data with the interval-censored data, and greatly improves the probability of the real data falling into imputation interval. Then it bases on the empirical distribution theory to estimate the survival function of right-censored and interval-censored data. The results of numerical examples and a real breast cancer data set demonstrated that the proposed method had higher accuracy and better robustness for the different proportion of the censored data. This paper provides a good method to compare the clinical treatments performance with estimation of the survival data of the patients. This pro vides some help to the medical survival data analysis.

Epileptic EEG signal classification based on wavelet packet transform and multivariate multiscale entropy / 生物医学工程学杂志

In this paper, a new method combining wavelet packet transform and multivariate multiscale entropy for the classification of epilepsy EEG signals is introduced. Firstly, the original EEG signals are decomposed at multi-scales with the wavelet packet transform, and the wavelet packet coefficients of the required frequency bands are extracted. Secondly, the wavelet packet coefficients are processed with multivariate multiscale entropy algorithm. Finally, the EEG data are classified by support vector machines (SVM). The experimental results on the international public Bonn epilepsy EEG dataset show that the proposed method can efficiently extract epileptic features and the accuracy of classification result is satisfactory.

Study on the steropsis in children after unilateral cataract extraction / 中国医师杂志

Objective To asses stereoacuity and the factors that influence stereopsis in children after unilateral cataract extraction.Methods Sixty-two children who were diagnosed as unilateral cataract and underwent cataract extraction with intraocular lens implantation were included in this study.Data are recorded on age at presentation and the surgery,the presence of strabismus,the refractive error,and the best corrected distant visual acuity (BCDVA) of both eyes and stereoacuity.Sixty-two patients were followed up for 14 ～ 60 months.Results Sixty-two patients were divided into two groups according to stereoacuity.Thirty-one patients in group A achieved stereopsis better than 400 s of arc.Group B had 31 patients whose stereoacuity was poorer than 400 s of arc.The mean age at presentation and surgery were 4.6 ± 3.4 and 6.3 ±4.5 years in group A and 2.1 ±2.1 and 2.4 ±2.2 years in group B.51.6％ of patients in group A achieved a BCDVA of 20/40 or better,but in group B,only 6.5％ of patients achieved a BCDVA of 20/40.Those who had strabismus after cataract surgery were 6.5％ in group A and 35.5％ in group B.There was statistically significant difference in age at presentation and the surgery (t =4.03,4.53,P ＜0.01),good BCDVA(x2 =15.34,P ＜ 0.01) and absence of strabismus (x2 =7.88,P ＜ 0.01) between two groups.Conclusions Stereopsis can develop in children after pediatric unilateral cataract extraction and intraocular lens implantation.Good stereoacuity is correlated with later manifesting cataracts,absence of strabismus and good BCDVA.

Characteristics of cytochrome P450 and its application / 国际肿瘤学杂志

Cytochrome P450(CYP450)is the most important family of enzymes in microsomal mixedfunction oxidase,widely distributed in vivo.CYP450 is involved in the metabolism of many exogenous compounds,the generation of endogenous substances,in particularly,affecting the occurrence and development of the tumors and their drug treatment,in the fields of medical and pharmaceutical research,cytochrome P450 has been very noticeable.

Magnetic resonance cholangiopancreatography to analyze the risk factor before laparoscopic cholecystectomy / 中华消化内镜杂志

Objective To assess the diagnostic value of MRCP before LC.Methods 944 cases with chronic calculous cholecystitis underwent MRCP before LC from June 2004 to June 2007 in our department.incidence rate of cholecvstolithiasis together with common bile duct stones and incidence rate of anatomic abnormity of bile duct were collected.Results The incidence rate of cholecvstolithiasis together with common bile duct stones were 8.1%(77/944),and the oecurence ofACBDS were 1.2%(11/944).The incidence rate of anatomic abnormity of bile duct were 3.7%(35/944).ConclusionMRCP can not only offer a excellent diagnostic value of ACBDS and anatomic abnormity of bile duct,but also reduce the occurrence of CBDS remainder and iatrogenic bile duct iniuries.