Selective nerve root block combined with posterior percutaneous cervical endoscopic discectomy for cervical spondylotic radiculopathy with double nerve root variation: A case report.

RATIONALE: The aim of this report is to present the technique of selective nerve root blockage combined with posterior percutaneous cervical endoscopic discectomy (PPECD) for cervical spondylotic radiculopathy (CSR). PATIENT CONCERNS: A 49-year-old female has pain in the skin area of the left scapular, pain in left elbow and limitation of left upper limb movement for 1.5 years. DIAGNOSIS: She was diagnosed with CSR and C6-7 double nerve root variation. INTERVENTIONS: We used selective nerve root block to determine the lesion segment and applied PPECD to relieve pressure on the patient's nerve roots. OUTCOMES: The pain symptoms disappeared after the patient was treated with C6-7 nerve root block. Endoscopic displayed C6-7 double nerve root variation on the left side of the spinal cord intraoperative. The neurological function was intact postoperatively and no recurrence of cervical disc herniation during the 5 months' follow-up period. The hospitalization time was 5 days, the operation time was 68.2 minutes and the bleeding volume was 52.6 ml. There was no change in cervical curvature and cervical disc height postoperatively. Japanese Orthopaedic Association score, SF-36 score and Visual Analogue Scale score improved significantly postoperatively. LESSONS: The application of selective nerve root blockage combined with PPECD for CSR could achieve satisfactory effect of position and decompression of the injured nerve root. Besides, we recommend that surgery be performed under general anesthesia to minimize patients' emotional stress and discomfort.

[Nitrogen uptake, distribution, and utilization in young bearing Huangguan pear trees under 15N-urea application in spring].

We investigated the characteristics of nitrogen uptake, distribution, and utilization in the three-year-old bearing Huangguan pear trees following 15N-urea application in early spring. The results showed that the growth of pear trees was mainly depended on vegetative organs such as shoots and leaves at the stage from budbreak to shoot growth arrest, but mainly on storage organs (roots) and supplemented by the formation of fruit yield and quality at the stage from shoot growth arrest stage to fruit harvest. Meanwhile, tree biomass, especially that storage organs, substantially increased. All organs, especially newly developed shoots and leaves, acquired more N in shoot growth arrest stage due to vigorous growth, with relatively higher N derived from fertilizer (Ndff). Ndff of each organ except for root was lower at fruit maturity stage than that at shoot growth stage. Most of the labeled nitrogen was distributed in the newly developed organs (shoots and leaves) from budbreak to shoot growth arrest stage, but in the storage organs during shoot growth arrest stage to fruit maturity stage. Labeled fertilizer nitrogen was mainly distributed in the storage organs, followed by the vegetative organs. Reproductive organs had the lowest allocation in the experimental stage. For the three-years-old pear trees, the ratio of absorbed N from fertilizer was responsible for 31.1% and 21.0% of total absorbed nitrogen from budbreak to shoot growth arrest stage and from shoot growth arrest stage to fruit maturity stage, respectively, with the remaining N (68.9% and 79.0% of total) being absorbed from soil N.

[Study on Extraction Methods of Characteristic Wavelength of Visible Near Infrared Spectroscopy Used for Sugar Content of Hetao Muskmelon].

Hetao muskmelon is a unique fruit in the hetao area of northwest china, which has been loved by consumers. Sugar content is the important indicator of measuring the quality and mature of muskmelons. This research uses Maya 2000 pro portable spectrometer and PR-101α portable digital refractometer to get spectrum and sugar content values of "jinhongbao" muskmelon, researches the effect of different extraction methods of characteristic wavelength (stepwise multiple linear regression (SMLR), interval partial least squares(iPLS), backward interval partial least squares (biPLS) and synergy interval partial least squares (siPLS)) on model accuracy and prediction results. The results show: using biPLS method on extraction of characteristic wavelength will the full spectrum evenly divided into 20 subintervals, the PLS factors of 14, when removing 8 subintervals, and choosing the wavelength variable numbers of 218, getting the biPLS model is best, RMSE of corresponding calibration and prediction models is 0.9961 and 1.18. So using the biPLS method of extraction on spectrum wavelength could extract effectively the characteristic wavelengths of melon sugar content, increase the ability of model prediction, and achieve rapid detecting of sugar content about muskmelons.

[Outlier sample discriminating methods for building calibration model in melons quality detecting using NIR spectra].

Outlier samples strongly influence the precision of the calibration model in soluble solids content measurement of melons using NIR Spectra. According to the possible sources of outlier samples, three methods (predicted concentration residual test; Chauvenet test; leverage and studentized residual test) were used to discriminate these outliers respectively. Nine suspicious outliers were detected from calibration set which including 85 fruit samples. Considering the 9 suspicious outlier samples maybe contain some no-outlier samples, they were reclaimed to the model one by one to see whether they influence the model and prediction precision or not. In this way, 5 samples which were helpful to the model joined in calibration set again, and a new model was developed with the correlation coefficient (r) 0. 889 and root mean square errors for calibration (RMSEC) 0.6010 Brix. For 35 unknown samples, the root mean square errors prediction (RMSEP) was 0.854 degrees Brix. The performance of this model was more better than that developed with non outlier was eliminated from calibration set (r = 0.797, RMSEC= 0.849 degrees Brix, RMSEP = 1.19 degrees Brix), and more representative and stable with all 9 samples were eliminated from calibration set (r = 0.892, RMSEC = 0.605 degrees Brix, RMSEP = 0.862 degrees).

[Study on Vis/NIR spectra detecting system for watermelons and quality predicting in motion].

To make Vis/NIR diffuse transmittance technique applied to quality prediction for watermelon in motion, the dynamic spectra detecting system was rebuilt. Spectra detecting experiments were conducted and the effects of noises caused by motion on spectra were analyzed. Then the least--square filtering method and Norris differential filtering method were adopted to eliminate the effects of noise on spectra smoothing, and statistical models between the spectra and soluble solids content were developed using partial least square method. The performance of different models was assessed in terms of correlation coefficients (r) of validation set of samples, root mean square errors of calibration (RMSEC) and root mean square errors of prediction (RMSEP). Calibration and prediction results indicated that Norris differential method was an effective method to smooth spectra and improve calibration and prediction results, especially, with r of 0.895, RMSEC of 0.549, and RMSEP of 0.760 for the calibration and prediction result of the first derivative spectra.

[Study on classification of ethylene treated and non-ethylene treated watermelons by visible/near infrared spectroscopy].

According to the fact that farmers often picked unripe watermelon and treated them with high concentration ethylene to quicken ripeness, classification experiments on the two classes of watermelon mentioned above were conducted based on the Vis/NIR spectroscopy diffuse transmittance technique. In the discriminant analysis, a method to classify them by diffuse transmittance ration at two wavelengths was adopted to discriminate them. Result of mistake ratio 32.5% for samples without ethylene treatment and 20% for ethylene treatment samples indicated that this method could discriminate the two classes of watermelons roughly. Mahalanobis distance and partial least square methods were also used here for discriminant analysis and satisfied results were obtained. The first derivative spectra with Norris derivative filtering of samples without being ethylene-treated using Mahalanobis distance discriminant analysis got the result of mistake ratio 1.67% for calibration set, no mistake for prediction set and no mistake for samples being ethylene treated. No mistake took place for the second derivative spectra using partial least square method. In discriminant analysis, spectral data pretreatment methods influence the discriminant results and it should be selected according to the analysis methods.

[Application of Vis/NIR diffuse reflectance spectroscopy to the detection and identification of transgenic tomato leaf].

The feasibility of Vis/NIR spectroscopy technique for rapid and non-invasive detection of transgenic tomato leaves from conventional ones was investigated by means of spectral diffuse reflectance mode. A total of 68 samples (38 transgenic ones and 30 non-transgenic ones) were used for classification. The calibration and validation results were analyzed via discriminant analysis (DA) and partial least squares (PLS) discriminant method using TQ 6.2. 1 quantitative software. Models based on the different spectral pre-processing methods (multiplicative signal correction (MSC), first and second derivative) were compared. It was found that the classification accuracy using DA was higher than that using PLS and the best results were gained by using spectra after MSC with InGaAs detector and the classification accuracy was 89.7% (accuracy of 86.8% for transgenic samples and 93.3% for non-transgenic ones). The results show that Vis-NIR diffuse reflectance spectroscopy technique is a feasible and fast method for non-invasive detection of transgenic and non-transgenic tomato leaves.

[Study on predicting firmness of watermelon by Vis/NIR diffuse transmittance technique].

Watermelon is a popular fruit in the world and firmness (FM) is one of the major characteristics used for assessing watermelon quality. The objective of the present research was to study the potential of visible/near Infrared (Vis/NIR) diffuse transmittance spectroscopy as a way for the nondestructive measurement of FM of watermelon. Statistical models between the spectra and FM were developed using partial least square (PLS) and principle component regression (PCR) methods. Performance of different models was assessed in terms of correlation coefficients (r) of validation set of samples and root mean square errors of prediction (RMSEP). Models for three kinds of mathematical treatments of spectra (original, first derivative and second derivative) were established. Savitsky-Goaly filter smoothing method was used for spectra data smoothing. The PLS model of the second derivative spectra gave the best prediction of FM, with a correlation coefficient (r) of 0. 974 and root mean square errors of prediction (RMSEP) of 0. 589 N using Savitsky-Goaly filter smoothing method. The results of this study indicate that NIR diffuse transmittance spectroscopy can be used to predict the FM of watermelon. The Vis/NIR diffuse transmittance technique will be valuable for the nandestructive detection large shape and thick peel fruits'.

[Estimation of soluble solids content of apple fresh juice by FTNIR spectroscopy].

The feasibility of Fourier transform near infrared (FTNIR) spectroscopic technology for rapid quantifying the soluble solids content (SSC) of apple fresh juice was investigated by means of spectral transmittance technique. A total of 60 juice samples were used to develop the calibration models. The relationship between laboratory SSC and FTNIR spectra of apple fresh juices was analyzed via principal component regression (PCR) and partial least squares (PLS) regression method using TQ 6.2.1 quantitative software. Models based on different spectral ranges were compared. Performance of different models was assessed in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r2) of validation set of samples. The best prediction models had a RMSEP of 0.603 degree Brix and correlation coefficient (r2) of 0.997 for SSC. The results show that FTNIR transmittance technique is a feasible, accurate and fast method for non-invasive estimation of fruit fresh juice soluble solids content.

Measurement of soluble solids content in watermelon by Vis/NIR diffuse transmittance technique.

Watermelon is a popular fruit in the world with soluble solids content (SSC) being one of the major characteristics used for assessing its quality. This study was aimed at obtaining a method for nondestructive SSC detection of watermelons by means of visible/near infrared (Vis/NIR) diffuse transmittance technique. Vis/NIR transmittance spectra of intact watermelons were acquired using a low-cost commercially available spectrometer operating over the range 350~1000 nm. Spectra data were analyzed by two multivariate calibration techniques: partial least squares (PLS) and principal component regression (PCR) methods. Two experiments were designed for two varieties of watermelons [Qilin (QL), Zaochunhongyu (ZC)], which have different skin thickness range and shape dimensions. The influences of different data preprocessing and spectra treatments were also investigated. Performance of different models was assessed in terms of root mean square errors of calibration (RMSEC), root mean square errors of prediction (RMSEP) and correlation coefficient (r) between the predicted and measured parameter values. Results showed that spectra data preprocessing influenced the performance of the calibration models. The first derivative spectra showed the best results with high correlation coefficient of determination [r=0.918 (QL); r=0.954 (ZC)], low RMSEP [0.65 degrees Brix (QL); 0.58 degrees Brix (ZC)], low RMSEC [0.48 degrees Brix (QL); 0.34 degrees Brix (ZC)] and small difference between the RMSEP and the RMSEC by PLS method. The nondestructive Vis/NIR measurements provided good estimates of SSC index of watermelon, and the predicted values were highly correlated with destructively measured values for SSC. The models based on smoothing spectra (Savitzky-Golay filter smoothing method) did not enhance the performance of calibration models obviously. The results indicated the feasibility of Vis/NIR diffuse transmittance spectral analysis for predicting watermelon SSC in a nondestructive way.

Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits.

Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describing the relationship between SSC and the NIR spectra of citrus fruits were developed and evaluated. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this study. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits was analyzed via principle component regression (PCR) and partial least squares (PLS) regression method. Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all spectra to reduce the effects of sample size, light scattering, instrument noise, etc. Different baseline correction methods were applied to improve the spectral data quality. Among them the second derivative method after baseline correction produced best noise removing capability and yielded optimal calibration models. A total of 170 NIR spectra were acquired; 135 NIR spectra were used to develop the calibration model; the remaining spectra were used to validate the model. The developed PLS model describing the relationship between SSC and NIR reflectance spectra could predict SSC of 35 samples with correlation coefficient of 0.995 and RMSEP of 0.79 degrees Brix.