Efficacy and Safety of Opioids for the Prevention of Etomidate-Induced Myoclonus: A Meta-Analysis.

Etomidate is a widely used hypnotic drug for induction of general anesthesia and sedation, especially in elderly patients and hemodynamically unstable patients. Myoclonus, however, is the most prominent problem during induction of anesthesia with etomidate. Many agents have been used to prevent it and opioid is one of them. This meta-analysis was to evaluate effects of opioids pretreatment for preventing etomidate-induced myoclonus. We searched the PubMed, EMBASE, and the Cochrane Library databases and published studies in English updated to September 2015. Randomized controlled trials of opioids versus placebo/control in patients were included. We evaluated the prophylactic effect of opioids on etomidate-induced myoclonus. All statistical analysis was performed using RevMan 5.2 software. Nine randomized controlled trials involving 604 participants were included. The results indicated that compared with placebo/control, opioids allow more patients to experience no myoclonic movements after etomidate injection [risk ratio (RR) 2.76, 95% confidence interval (CI) 1.75-4.37, P < 0.0001]. The numbers of patients with mild myoclonus [(RR) 0.53, 95% (CI) 0.36-0.78, P = 0.001], moderate myoclonus [(RR) 0.36, 95% (CI) 0.23-0.55, P < 0.00001], and severe myoclonus [(RR) 0.20, 95% (CI) 0.08-0.52, P = 0.0009] after etomidate injection were significantly decreased with the pretreatment of opioids. This meta-analysis suggests that pretreatment with opioids before injecting etomidate was effective for preventing etomidate-induced myoclonus and can reduce the intensity of myoclonus without any adverse effects.

[Research on Space Target Recognition Algorithm Based on Spectral Information].

Because of ground observation instruments and other factors, we can not recognize the space target only from the external shape in the image. Since the reflection spectrum of the space target is determined by the surface material of space object, spectral analysis technique can be used for classifying the space objects. Based on the K-nearest neighbor algorithm (KNN), a method called adaptive weight k-local hyperplane (AWKH) is proposed in this paper. The main improvement of the algorithm is that weight discrimination is added in the processes of calculating the hyperplane distance between predicted samples. The algorithm constructs a hyperplane model by using the difference between the groups and within group ratio for the weights of features. In order to verify the classification effectiveness and efficiency of the algorithm, this paper carried out four sets of verification experiments. In the first set of experiments, 9 kinds of common materials were extracted from the database of United State Geological Survey. Then 3 kinds of these materials were mixed into multi-class objections. In the second and third sets of experiments, the spectra of four normal space target materials were mixed in different classes. Then these classes were identified from the visible and near-infrared wave bands. In the fourth set of experiments, four square models of hexahedron were classified by the spectra of their surface material. The experimental results indicate that the AWKH algorithm has more advantages in identification accuracy and effectiveness of the complex samples by comparing with the support vector machine (SVM) method.

Observation of broadband unidirectional transmission by fusing the one-way edge states of gyromagnetic photonic crystals.

We experimentally demonstrate a broadband one-way transmission by merging the operating bands of two types of one-way edge modes that are associated with Bragg scattering and magnetic surface plasmon (MSP) resonance, respectively. By tuning the configuration of gyromagnetic photonic crystals and applied bias magnetic field, the fused bandwidth of unidirectional propagation is up to 2 GHz in microwave frequency range, much larger than either of the individual one-way bandwidth associated with Bragg scattering or MSP resonance. Our scheme for broadband one-way transmission paves the way for the practical applications of one-way transmission.

Realization of self-guided unidirectional waveguides by a chain of gyromagnetic rods.

To achieve a unidirectional transmission waveguide with miniature dimensions and flexible geometry, we propose a self-guided unidirectional waveguide composed of a chain of gyromagnetic rods. Two configurations of the waveguides were demonstrated. One is of a zigzag chain form, the other is a straight-line chain. These two types of waveguides have very wide one-way edge mode bandwidths. The simulated and experimental results illustrate their extraordinary wideband one-way transmission characteristics. They can also be expected to function as flexible platforms for practical applications because of their thin transverse dimensions and robustness to bending.

[The net analyte preprocessing combined with radial basis partial least squares regression applied in noninvasive measurement of blood glucose].

In order to improve the prediction accuracy of quantitative analysis model in the near-infrared spectroscopy of blood glucose, this paper, by combining net analyte preprocessing (NAP) algorithm and radial basis functions partial least squares (RBFPLS) regression, builds a nonlinear model building method which is suitable for glucose measurement of human, named as NAP-RBFPLS. First, NAP is used to pre-process the near-infrared spectroscopy of blood glucose, in order to effectively extract the information which only relates to glucose signal from the original near-infrared spectra, so that it could effectively weaken the occasional correlation problems of the glucose changes and the interference factors which are caused by the absorption of water, albumin, hemoglobin, fat and other components of the blood in human body, the change of temperature of human body, the drift of measuring instruments, the changes of measuring environment, and the changes of measuring conditions; and then a nonlinear quantitative analysis model is built with the near-infrared spectroscopy data after NAP, in order to solve the nonlinear relationship between glucose concentrations and near-infrared spectroscopy which is caused by body strong scattering. In this paper, the new method is compared with other three quantitative analysis models building on partial least squares (PLS), net analyte preprocessing partial least squares (NAP-PLS) and RBFPLS respectively. At last, the experimental results show that the nonlinear calibration model, developed by combining NAP algorithm and RBFPLS regression, which was put forward in this paper, greatly improves the prediction accuracy of prediction sets, and what has been proved in this paper is that the nonlinear model building method will produce practical applications for the research of non-invasive detection techniques on human glucose concentrations.

[Calibration transfer without standards for spectral analysis based on stability competitive adaptive reweighted sampling].

A novel calibration transfer method based on stability competitive adaptive reweighted sampling (SCARS) was proposed in the present paper. An informative criterion, i. e. the stability index, defined as the absolute value of regression coefficient divided by its standard deviation was used. And the root mean squared error of prediction (RMSEP) after transfer was also used. The wavelength variables which were important and insensitive to influence of measurement parameters were selected. And then the differences in responses of different instruments or measurement conditions for a specific sample were eliminated or reduced to improve the calibration transfer results. Moreover, in the proposed method, the spectral variables were compressed, making calibration transfer more stable. The application of the proposed method to calibration transfer of NIR analysis was evaluated by analyzing the corn with different NIR spectrometers. The results showed that this method can well correct the difference between instruments and improve the analytical accuracy. The transfer results obtained by the proposed method, orthogonal signal correction (OSC), Monte Carlo uninformative variable elimination (MCUVE) and competitive adaptive reweighted sampling (CARS), respectively, for corn with different NIR spectrometers indicated that the former gave the best analytical accuracy, and was effective for the spectroscopic data compression which can simplify and optimize the transfer process.

Effect and Safety of Herbal Medicine Foot Baths in Patients with Diabetic Peripheral Neuropathy: A Multicenter Double-Blind Randomized Controlled Trial.

OBJECTIVE: To evaluate the effect and safety of foot baths with Tangbi Waixi Decoction (TW) in treating patients with diabetic peripheral neuropathy (DPN). METHODS: It is a multicenter double-blinded randomized controlled trial. Participants with DPN were recruited between November 18, 2016 and May 30, 2018 from 8 hospitals in China. All patients received basic treatments for glycemic management. Patients received foot baths with TW herbal granules either 66.9 g (intervention group) or 6.69 g (control group) for 30 min once a day for 2 weeks and followed by a 2-week rest, as a therapeutic course. If the Toronto Clinical Scoring System total score (TCSS-TS) ⩾6 points, the patients received a total of 3 therapeutic courses (for 12 weeks) and were followed up for 12 weeks. The primary outcome was change in TCSS-TS score at 12 and 24 weeks. Secondary outcomes included changes in bilateral motor nerve conduction velocity (MNCV) and sensory nerve conduction velocity (SNCV) of the median and common peroneal nerve. Safety was also assessed. RESULTS: Totally 632 patients were enrolled, and 317 and 315 were randomized to the intervention and control groups, respectively. After the 12-week intervention, patients in both groups showed significant declines in TCSSTS scores, and significant increases in MNCV and SNCV of the median and common peroneal nerves compared with pre-treatment (P<0.05). The reduction of TCSS-TS score at 12 weeks and the increase of SNCV of median nerve at 24 weeks in the control group were greater than those in the intervention group (P<0.05). The number of adverse events did not differ significantly between groups (P>0.05), and no serious adverse event was related with treatment. CONCLUSION: Treatment of TW foot baths was safe and significantly benefitted patients with DPN. A low dose of TW appeared to be more effective than a high dose. (Registry No. ChiCTR-IOR-16009331).

Cutting edge: Nicastrin and related components of γ-secretase generate a peptide epitope facilitating immune recognition of intracellular mycobacteria, through MHC class II-dependent priming of T cells.

Bacillus Calmette-Guérin (BCG), the antituberculosis vaccine, localizes within immature phagosomes of macrophages and dendritic cells (APCs), and avoids lysosomal degradation. BCG-derived antigenic peptides are thus inefficiently processed by APCs, and we investigated alternate mechanisms of Ag processing. Proteomics identified that BCG phagosomes are enriched for nicastrin, APH, and presenilin components of γ-secretase, a multimeric protease. Using an in vitro Ag presentation assay and BCG-infected APCs, we found γ-secretase components to cleave BCG-derived Ag85B to produce a peptide epitope, which, in turn, primed IL-2 release from Ag85B-specific T cell hybridoma. siRNA knockdown or chemical inhibition of γ-secretase components using L685458 decreased the ability of BCG or Mycobacterium tuberculosis-infected APCs to present Ag85B. In addition, L685485 inhibition of γ-secretase led to a decreased ability of BCG-dendritic cells to immunize mice and induce Ag85B-specific CD4 T cells in vivo. Because BCG and M. tuberculosis sequester within APCs preventing immune recognition, γ-secretase components appear to fortuitously process the immunodominant Ag85B, facilitating immune recognition.

[A dimension reduction method applied in spectrum analysis].

It is the premise of establishing stable and accurate model to extract useful information from spectrum data in Vis/NIR spectrum analysis technology. ISOMAP is a dimension reduction method, and can effectively extract the intrinsic low dimension from high dimensional data, but is sensitive to noise and neighborhood parameter. In this paper, an improved ISOMAP algorithm, called supervised dimension reduction, is proposed. It guides the construction of the neighborhood graph using correlation owned by spectrum data, and reduces sensitivity to noise and neighborhood parameter. The algorithm was applied to two datasets, and then PLS models were established. The experiment results indicated that the improved algorithm was less sensitive to the neighborhood size and more robust and more topologically stable. In addition, smaller dimension was extracted, and the model precision was improved at the same time.

[Research on Raman spectra quantitative analysis model of ethanol aqueous solution based on net analyte signal].

Raman spectroscopy technique could satisfy industrial field measurement requirements because of the advantages of rapidity and nondestructiveness. Thus, It has been widely used in a variety of quantitative and qualitative analysis fields. The volume ration of alcohol and water in alcoholic beverages, i. e. the ethanol content, is a key factor in the detection of the quality of wine products. The development of the detection system for quick, easy and real-time ethanol content measurement is of great significance for national production. In the present paper, net signal analysis method (NAS) was used in the ethanol content quantitative analysis of Raman spectra from the ethanol aqueous solution. The linear regression model was developed between the net signal of ethanol and its concentration. The results showed that the qualitative analysis method based on net signal analysis was superior to the traditional linear regression method such as the MLR method based on the feature peak intensity and the PLS model. It not only improved the prediction accuracy of the model but also enhanced the robustness of the model. Because the model established by the NAS-MLR method is simple and stable, it is possible to develop the portable measurement instruments in future.

Identification of colitis and cancer in colon biopsies by Fourier Transform Infrared spectroscopy and chemometrics.

Cancer is a disease that does great harms to the health of human beings. FT-IR spectroscopy could identify variability at the molecular level in biological specimens. It is a rapid and noninvasive method, which could be used intraoperatively to modify surgical procedures. The aim of this paper is to identify and separate cancer from colitis in endoscopic colon biopsies through the use of FT-IR spectroscopy. A total of 88 endoscopic colon samples, including 41 cases of colitis and 47 cases of colon cancer, were obtained. Specimens were placed on an ATR accessory linked to FT-IR spectrometer with a MCT detector for greater stability and sensitivity. Later, specimens were sent for the histological examination as the reference in the spectral analysis. 41 colitis and 47 cancer specimens were compared. Spectra preprocessed with smoothing and normalization were used for discrimination analysis. PCA was processed to simplify the spectrum data set. Naive Bayes classifier model was constructed for diagnostic classification. Leave-one-out cross-validation method was utilized to assess the discrimination results. The sensitivity of FT-IR detection for cancer achieves 97.6%. The results showed that colon cancer could be distinguished from colitis with high accuracy using FT-IR spectroscopy and chemometrics.

[The method of removing high-frequency noise in pulse wave signal in detecting oxygen saturation of human].

Photoplethysmography can be used to noninvasively detect oxygen saturation of human. When detecting by photoplethysmography, because of the disturbance of random noise in the process of signal acquisition, there is high-frequency noise, which affects the final prediction accuracy of oxygen saturation. Therefore empirical mode decomposition(EMD) method based on consecutive mean square error(CMSE) criterion is employed, which can remove high-frequency noise from pulse wave signal. The present paper used a self-developed photoplethysmography acquiring device to obtain the pulse wave signal, employed the above mentioned method to remove high-frequency noise, and adopted frequency spectrum of the signal to evaluate the effect. The results showed that: this method could effectively remove high-frequency noise from pulse wave signal. This would be beneficial for improving the prediction accuracy of oxygen saturation of human.

[Development of human blood glucose noninvasive measurement system based on near infrared spectral technology].

A small non-invasive measurement system for human blood glucose has been developed, which can achieve fast, real-time and non invasive measurement of human blood glucose. The device is mainly composed of four parts, i. e. fixture, light system, data acquisition and processing systems, and spectrometer. A new scheme of light source driving was proposed, which can meet the requirements of light source under a variety of conditions of spectral acquisition. An integrated fixture design was proposed, which not only simplifies the optical structure of the system, but also improves the reproducibility of measurement conditions. The micro control system mainly achieves control function, dealing with data, data storage and so on. As the most important component, microprocessor DSP TMS320F2812 has many advantages, such as low power, high processing speed, high computing ability and so on. Wavelet denoising is used to pretreat the spectral data, which can decrease the loss of incident light and improve the signal-to-noise ratio. Kernel partial least squares method was adopted to build the mathematical model, which can improve the precision of the system. In the calibration experiment of the system, the standard values were measured by One-Touch. The correlation coefficient between standard blood glucose values and truth values is 0.95. The root mean square error of measurement is 0.6 mmol x L(-1). The system has good reproducibility.

[Research on continuum power regression in noninvasive measurement of human blood glucose].

Accurate measurement of human blood glucose concentration is very significant for the treatment of diabetes. In the present paper, the method of continuum power regression can improve the predictive accuracy of noninvasive measurement of human blood glucose concentration with near infrared spectroscopy. This method is the expansion of the traditional method of partial least squares (PLS). It can achieve simpleness, and can significantly improve predictive accuracy when the power coefficient is fit. Using the method, quantitative analysis models of four ingredient experiment and noninvasive experiment of body were established, and these models can be used to predict the predictive samples. Experimental results show that compared with the PLS, the quantitative analysis models of this method not only can improve predictive accuracy, but also can set different power coefficient for different individuals to achieve the best results of models. According to different individuals, the power coefficient can be selected flexibly, which is of great value to the research on noninvasive measurement of human blood glucose concentration with near infrared spectroscopy.

Characteristics and sources of atmospheric polycyclic aromatic hydrocarbons (PAHs) in Shanghai, China.

A field campaign was conducted to measure and analyze 13 polycyclic aromatic hydrocarbons (PAHs) in six major zones in the city of Shanghai, P.R. China from August 2006 to April 2007. Ambient air samples were collected seasonally using passive air samplers, and gas chromatography-mass spectroscopy was used in this field campaign. The results showed that there was a sequence of 13 PAHs at Phen > FA > Pyr > Chr > Fl > An > BaA > BbFA > BghiP > IcdP > BkFA > BaP > DahA and the sum of these PAHs is 36.01 +/- 10.85 ng/m(3) in gas phase. FL, Phen, FA, Pyr, and Chr were the dominant PAHs in gas phase in the city. They contributed 90% of total PAHs in the gas phase. Proportion of measured PAHs with three, four, five, and six rings to total PAHs was 53%, 42%, 3%, and 2%, respectively. The highest concentration of SigmaPAHs (the sum of 13 PAHs) occurred in the wintertime and the lowest was in the summer. This investigation suggested that traffic, wood combustion, and metal scrap burn emissions were dominant sources of the concentrations of PAHs in six city zones compared with coal burning and industry emissions. Further, the traffic emission sources of PAHs in the city were attributed mostly to gasoline-powered vehicles compared with diesel-powered vehicles. It was revealed that the seasonal changes in PAHs in the city depended on different source types. Metal scrap burn was found to be the major source of PAHs during the autumn, while the PAH levels in the atmosphere for winter and spring seasons were mainly influenced by wood and biomass combustion. Comparisons of PAHs among different city zones and with several other cities worldwide were also made and discussed.

[A path-length correction method on biochemical parameter nondestructive measuring of folium].

Vis/NIR spectroscopy technology is capable of analyzing the content of biochemical parameter in folium rapidly and nondestructively. In the process of spectrum analysis, the variations in path-length between different samples exist, with the random light scattering and leaf thickness perturbations, which influence the precision of quantitative analysis model. In order to resolve this problem, an improved path-length correction method based on Extended Multiplicative Scattering Correction is presented. In this paper, firstly the theory of EMSC algorithm is deduced. EMSC method incorporates both chemical terms and wavelength functions to help realize the efficient separation of path-length and interest concentration. Secondly two experiments were implemented to demonstrate the validity of the method. In Experiment 1, sixteen samples of different thickness but almost the same chlorophyll content were selected, and how the path-length affects the spectrum was compared, after EMSC preprocessing, the variable coefficient of spectrum could approach the repeatability error of spectrometer. In Experiment 2, thirty-two samples of different thickness and chlorophyll content were selected. PLS model established using cross validation was employed to evaluate the efficiency of the presented algorithm. Before the preprocessing, the root mean squared error of prediction is 3.9 SPAD with 5 principal components. After preprocessing, the predicted root mean squared error is 2.2 SPAD with 12 principal components. The results indicate that the improved EMSC preprocessing method could exactly eliminate the spectrum difference caused by the path-length variations between different foliums, enhance the sensitivity of concentration and spectral data, and increase the precision of calibrated model.

[A principal components selection method based on the modified randomization test for avoiding over-fit and under-fit in spectra calibration].

More or less principal components often give an over-fit or under-fit quantitative calibration model. In order to avoid over-fit or under-fit in spectra calibration, a principal components selection method based on a modified randomization test is proposed. Three near infrared spectra experiments (the complexity of the sample components in each experiment is increasing by degrees) are introduced in this paper for evaluating the proposed method. The method is compared with the cross-validation method. And the spectra model complexity of how to affect the prediction performance of calibration is discussed. Then the adaptability of this modified randomization test to the uncertainty complex spectra model is also discussed. The results indicate that the proposed method has no process of leaving some samples out like cross-validation does, and all the training samples are considered when selecting principal components, so the problem of over-fit or under-fit can be avoided, which is benefit to improve prediction performance of calibration in spectral analysis. And the modified randomization test method is different with the commonly used randomization test that a simplified criterion is introduced here and it is easy to implement. With the proposed method, the authors can have a visualized and interactive process when selecting principal components. For these three experiments, 4, 5 and 8 selected principal components are employed in calibration respectively and the prediction result is the best for the independent external prediction sets. It is also implied that the proposed method is adaptable to the complex samples with more variables and little samples.

[Application of partial robust M-regression in noninvasive measurement of human blood glucose concentration with near-infrared spectroscopy].

In the study of non-invasive measurement of human blood glucose concentration with near-infrared spectroscopy, the partial robust M-regression (PRM) is proposed in the present paper to solve the robustness of calibration model affected by outliers existing in the spectra data set. While keeping the good properties of M-estimators if an appropriate weighting scheme is chosen, PRM inherits the speed of computation and easy realization of the iterative reweighted partial least squares (IRPLS) algorithm, but is robust to all types of outliers. With the pretreatment of spectra based on PRM, the root mean square error of prediction (RMSEP) of calibration model was presented and compared with partial least squares (PLS). Experimental results show that the robust calibration model PRM produces better prediction of glucose than the model of PLS when the components of the samples increase which is significant for non-invasive prediction of blood glucose levels.

Different Performance of Intravertebral Vacuum Clefts in Kümmell's Disease and Relevant Treatment Strategies.

OBJECTIVES: This study aimed to present the different pattern of intravertebral vacuum cleft (IVC) related to high risk of cement complications in minimally invasive treatments for Kümmell's disease (KD) and relevant treatment strategies. METHODS: A retrospective study from January 2016 to January 2018 was conducted at Wuhan Fourth Hospital and comprised 35 patients with Kümmell's disease. There were seven males and 28 females, and the mean age of the patients was 70.4 years. The patterns of IVC in KD were analyzed. These patients were divided into three groups based on the treatment method used. The treatment methods included long-segment fixation (LSF), posterior short-segment fixation (SSF), and percutaneous kyphoplasty (PKP). We retrospectively reviewed outcomes, including the Oswestry Disability Index (ODI), visual analog scale (VAS) score, anterior height of affected vertebrae, kyphotic Cobb angle, and complications. RESULTS: All patients were followed up for 12-38 months. According to their radiographic appearance we could observe two main patterns of clefts. Pattern I, clefts that were found to be near to the endplate and connected with intervertebral space, the endplate was incomplete. Pattern II, IVC traversed to anterior edge of the vertebral body affected. Both were related to high risk of cement complications in minimal invasive treatments for KD. Good results have been achieved in LSF and SSF groups, the VAS, ODI, anterior height of affected vertebrae and kyphotic Cobb angle showed statistically significant differences between pre- and post-operation and between pre- and final follow-up (P < 0.05). In PKP group, although the VSA and ODI showed statistically significant differences between pre- and post-operation and between pre- and final follow-up (P < 0.05), we could observe that the VSA and ODI rebounded a little at the final follow-up. Cement leakage into intervertebral space occurred in four (44.45%) patients of PKP group. CONCLUSIONS: PKP should be chosen carefully if the IVC of the patient presents to be pattern I or II. LSF and SSF are safe and effective, and can achieve satisfactory correction of kyphosis and vertebral height, with pain relief and improvement in patient's daily life, with few complications.

[A hyperspectral subpixel target detection method based on inverse least squares method].

In the present paper, an inverse least square (ILS) method combined with the Mahalanobis distance outlier detection method is discussed to detect the subpixel target from the hyperspectral image. Firstly, the inverse model for the target spectrum and all the pixel spectra was established, in which the accurate target spectrum was obtained previously, and then the SNV algorithm was employed to preprocess each original pixel spectra separately. After the pretreatment, the regressive coefficient of ILS was calculated with partial least square (PLS) algorithm. Each point in the vector of regressive coefficient corresponds to a pixel in the image. The Mahalanobis distance was calculated with each point in the regressive coefficient vector. Because Mahalanobis distance stands for the extent to which samples deviate from the total population, the point with Mahalanobis distance larger than the 3sigma was regarded as the subpixel target. In this algorithm, no other prior information such as representative background spectrum or modeling of background is required, and only the target spectrum is needed. In addition, the result of the detection is insensitive to the complexity of background. This method was applied to AVIRIS remote sensing data. For this simulation experiment, AVIRIS remote sensing data was free downloaded from the NASA official websit, the spectrum of a ground object in the AVIRIS hyperspectral image was picked up as the target spectrum, and the subpixel target was simulated though a linear mixed method. The comparison of the subpixel detection result of the method mentioned above with that of orthogonal subspace projection method (OSP) was performed. The result shows that the performance of the ILS method is better than the traditional OSP method. The ROC (receive operating characteristic curve) and SNR were calculated, which indicates that the ILS method possesses higher detection accuracy and less computing time than the OSP algorithm.