Low versus high radioiodine activity for ablation of the thyroid remnant after thyroidectomy in Han Chinese with low-risk differentiated thyroid cancer.

AIM: The aim of this study was to compare the efficacy and adverse effects of radioiodine (131I) therapy between two groups of patients with low-risk differentiated thyroid cancer (DTC) who received 30 mCi or 100 mCi radioiodine for ablation of the thyroid remnant after total thyroidectomy. METHODS: The study cohort was 173 patients, 85 of whom were given 30 mCi of radioiodine and the others were given 100 mCi of radioiodine. Follow-up involved neck ultrasonography, measurement of serum levels of thyroglobulin and whole-body scans to evaluate the response of radioiodine treatment. All patients were assessed for adverse effects. RESULTS: Of the 173 patients, 170 (98.3%) patients finally achieved successful ablation. The prevalence of successful ablation was 77.6% in the low-dose group versus 71.5% in the high-dose group after the first dose administration (P=0.36), 79% in the low-dose group versus 88% in the high-dose group after the second dose administration (P=0.416), and 97.6% in the low-dose group versus 98.9% in the high-dose group after the final ablation (P=0.54). We found no significant differences between the two groups. No patient had an adverse effect with a severity grade ⩾2 and the prevalence of adverse effects in the high-dose group was higher than that in the low-dose group, especially for nausea, neck pain, and sore throat. CONCLUSION: These data suggest that a low dose of radioiodine is as effective as a high dose of radioiodine for ablation of the thyroid remnant after total thyroidectomy for low-risk DTC. Moreover, low-dose radioiodine therapy is associated with a lower prevalence of adverse events.

Genetic screening for mutations in the chip gene in intracranial aneurysm patients of Chinese Han nationality.

We performed a case-control study to investigate whether SNPs of CHIP might affect the development of IA in Chinese Han nationality. We believe we are the first to have screened IA patients for mutations in the CHIP gene to determine the association with these variants. The study group comprised 224 Chinese Han nationality patients with at least one intracranial aneurysm and 238 unrelated healthy Han nationality controls. Genomic DNA was isolated from blood leukocytes. The entire coding regions of CHIP were genotyped by PCR amplification and DNA sequencing. Differences in genotype and allele frequencies between patients and controls were tested by the chi-square method. Genotype and allele frequencies of the SNP rs116166850 was demonstrated to be in Hardy-Weinberg equilibrium. No significant difference in genotype or allele frequencies between case and control groups was detected at the SNP. Our data do not support the hypothesis of a major role for the CHIP gene in IA development in the Chinese Han population.

[Applications of near infrared reflectance spectroscopy technique to determination of forage mycotoxins].

The near infrared reflectance spectroscopy technique (NIRS) has been explored at many fields such as agriculture, food, chemical, medicine, and so on, due to its rapid, effective, non-destructive, and on-line characteristics. Fungi invasion in forage materials during processing and storage would generate mycotoxins, which were harmful for people and animal through food chains. The determination of mycotoxins included the overelaborated pretreatments such as milling, extracting, chromatography and subsequent process such as enzyme linked immunosorbent assay, high performance liquid chromatography, and thin layer chromatography. The authors hope that high precision and low detection limit spectrum instrument, and software technology and calibration model of mycotoxins determination, will fast measure accurately the quality and quantity of mycotoxins, which will provide basis for reasonable process and utilization of forage and promote the application of NIRS in the safety livestock product.

Role of large-conductance calcium-activated potassium channels of coronary arteries in heart preservation.

BACKGROUND: Large-conductance calcium-activated potassium channels (BK(Ca)) of vascular smooth muscle cells (VSMCs) play an important role in the regulation of vascular tone. We tested the hypotheses that the alteration of arterial relaxation after exposure to ischemia or hyperkalemia is attributable to the alteration in the activities of BK(Ca) by using the patch-clamp technique and force measurement. METHODS: VSMCs were enzymatically isolated from porcine coronary arteries, with the primary cultures used for patch-clamp study. BK(Ca) currents were recorded in a whole-cell configuration (n = 5 in each group). The BK(Ca) activator NS1619 (-7 to -4.5 logM)-induced relaxation was studied myographically in small porcine coronary arteries (n = 6 per group). The effects of global ischemia for 1 hour and hyperkalemia (20 to 120 mmol/liter) were tested. RESULTS: Ischemia for 1 hour markedly reduced the BK(Ca) current from 119.8 +/- 11.4 pA/pF to 86.0 +/- 3.7 pA/pF (p < 0.05). The rise of extracellular K(+) resulted in increased BK(Ca) currents in a concentration-dependent manner (5.4 mmol/liter: 31.6 +/- 3.4 pA/pF; 20 mmol/liter: 73.6 +/- 11.4 pA/pF; 60 mmol/liter: 108.6 +/- 20.6 pA/pF; 120 mmol/liter: 135.2 +/- 20.5 pA/pF; p < 0.05). NS1619-induced relaxation was suppressed by ischemia (71.4 +/- 2.2% vs 95.3 +/- 1.6%; p < 0.01) and was inferior in K(+) pre-contraction, as compared with U(46619) (a thromboxane A(2) mimetic) pre-contraction (p < 0.05). CONCLUSIONS: In coronary circulation: (1) the BK(Ca) current density and related vasorelaxation are reduced after ischemia; and (2) hyperkalemia induces dual effects; the depolarization obscures the compensatory increase of the BK(Ca) activity. These findings imply that BK(Ca) activators may be used in cardioplegia or heart preservation solutions to protect the function of this ion channel.

[Study on hyper-spectral remote sensing models for monitoring damage of Oedaleus asiaticus (Orthoptera : Acrididae)].

In the present paper, the ASD Field Spec Pro FRTM spectroradiometer was used for measuring damages of O. asiaticus in Xilin GolLeague, Inner Mongolia. First, the hyper-spectral data were analyzed and the canopy reflectance spectral data were compared between the healthy leaves and the infected leaves of Leymus chinensis. Second, the regression models between the leaf area index (LAI) and the hyper-spectral parameters were built, and different varieties of the O. asiaticus damage were used to test its precision. The results showed that there was a high correlation of three hyper-spectral data between the LAI and the first derivative data. Moreover the disease index (DI) model, which is mostly suitable for use in indicating the intensity of grasshoppers damage in the study area, containing the ratio of the sum of first derivative within red peak regions (620-760 nm, SDr) to the sum of first derivative within blue peak regions (430-470 nm, SDb) was the best one. From the model, there were no damage if DI was over 72.43, slight damage if DI was between 51.57 and 79.83, and serious damage if DI was less than 51.57. The model had the highest prediction precision with the correlation coefficient of prediction of 0.948, and the mean relative error of 3.928%. These results showed a good prediction of the model and indicated that the grasshopper damage could be estimated at the canopy level using hyper-spectral reflectance.

[Application of near-infrared reflectance spectroscopy to the discrimination of salt tolerance of alfalfa cultivars].

Near infrared reflectance spectroscopy is a new developed method able to analyse the content of specific compound in the detected sample quickly and efficiently, and has been wildly used in many fields such as evaluation of nutrition value of forage, cultivar discrimination and so on. In the present paper a new method was developed for the discrimination of salt tolerance of alfalfa cultivars by Fourier transform near infrared reflectance spectroscopy. Firstly absorbance spectrum generated by Fourier transform near infrared spectrometry was used to classify twenty alfalfa cultivars. These cultivars were obviously clustered into two groups: salt tolerant and salt sensitive, similar to the result, screened by the traditional methods. Based on these results, a discrimination model was built for identification of salt tolerant cultivars. And then, six other cultivars were used to verify the function of the discriminating model. Result showed that the distinguishing rate of 100% was achieved with the performance index of 85.7%. It is concluded that Fourier transform near infrared spectrum is useful for classification and discrimination of salt tolerance of alfalfa cultivars. The method can be applied to estimate salt tolerance of alfalfa cultivars, and works more quickly and efficiently than the traditional screening methods. Application of Fourier transform near infrared spectrum to discriminating salt tolerance of alfalfa cultivars is significant in both academic and technical areas.

[Research on predicting the qualities of stem of alfalfa hay by near infrared reflectance spectroscopy].

The present research was attempted to predict the qualities of stem of alfalfa (Medicago sativa L. ) without separation from the whole plant by near infrared reflectance spectroscopy and discussed the feasibility of using the near infrared reflectance spectra information of the whole object to predict the qualities of a certain part. Sixty six whole alfalfa hay samples of separated stems from leaves were collected and they were distinguishing by years, cultivars, cuts and growing periods. There were 138 calibration samples and 60 validation samplers. Fourier transform-near infrared reflectance spectroscopy (FT-NIRS) and partial least square (PLS) were used to set up the calibration models of stem's crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), crude ash (CA) and in vitro digestible dry matter (IVDDM) contents. All models showed great calibration and prediction performances except the one of stem's NDF content. The correlation coefficients of cross-validation (rCV) were between 0.8523 and 0.9007, the root mean square errors of cross-validation (RMSECV) were between 0.72% and 3.96% and the correlation coefficients of NIRS values and chemical values (r) were between 0.9255 and 0.9512. However, rCV, RMSECV and r of the model of stem's NDF content were 0.8214, 3.70% and 0.9020, respectively. It wasn't exact enough and would be used for rough predicting only. All of the results showed that near infrared reflectance spectra information of whole alfalfa hay could be used to predict some components of its stem exactly. It was the maiden attempt of using near infrared reflectance spectra information of the whole objects to evaluated the qualities of a certain part.

[Application of near-infrared spectroscopy in golf turfgrass management].

The management of golf course is different from other turfs. Its particularity lies in its higher and more precise requirement during maintenance compare with other turfs. In case something happened to turf of golf course, more effective and higher speed detecting and resolution are required. Only the data about turf growth and environment were mastered precisely in time, the friendly environmental and scientific management goal could be completed effectively and economically. The near infrared spectroscopy is a new kind of effective, convenient and non-destructive analytical method in the turfgrass management of golf course in recent years. Many factors of turf-soil system in golf course could be determined by near infrared spectroscopy at the same time. In this paper, the existing literature that use of near infrared spectroscopy to study turfgrass and soil nutrient content, soil hygroscopic moisture, feasible fertilizer application time and rate, to fix the time and volume of irrigation, turfgrass visual quality evaluation, turfgrass disease prediction and prevention were reviewed. Most researchers considered the nutrition condition of turf impacted the visual and playing quality of golf course directly and then indirectly influenced most of assistant cultivation such as fertilization, mowing and irrigation and so on. The using of NIRS can detect the nutrient content of turfgrass effectively and estimate the nutrient is excessive or deficient quickly. And then the feasible time and rate of fertilizers can be decided. Comparing with the common judgment ways based on the season fertilization and visual estimation, the using of NIRS can reduce the application of fertilizers on the base of keeping the same turf quality simultaneously. NIRS can analysis many items of soil such as moisture, elements concentration, textures on the spot by the thousands. This method can get lots of cover-all data non-destructively. What's more, NIRS can analysis soil betimes quickly. NIRS is cheap and simply to operate. Many spectral data of many chemical constituents can be determined only through scanning once. Except for detecting the nutrient concentration of turf or soil, NIRS can analysis the textures and pH of soil and so on. NIRS can analysis the moisture content of soil on the spot quickly and be helpful to decide the right time and mass of irrigation. NIRS can also be used of appraising visual quality of turf including turf color, density, uniformity and cover and so on. And then the quantitative indexes of visual quality of turf can be drawn. NIRS can help analysis the condition of the plant diseases and insect pests and adopt some prevention and cure measure effectively. As a consequence, the negative reaction on environment is avoided because of spraying bactericide and pesticide blindly. The using of near infrared spectroscopy could be helpful of obtaining the data about the turgrass and environment in golf course and contributed to improve turfgrass management and decision-making effectively. Nowadays some problems baffled the far and wide use of near infrared spectroscopy in golf course. Its widely use needs to accumulate the basic chemical analytical data about the golf course. In addition, another problem need to solve is how to ascertain the ground biomass of turfgrass. It is required for NIRS use widely to invent more portable and 'on-the-go' golf course using near infrared spectroscopy apparatus. Together with the more and deeper research on NIRS, new NIRS apparatuses will come up and the application software of NIRS will be upgraded. NIRS will play a more important role in turf management of golf course.

[Determination of main fiber compositions of alfalfa hay by near infrared reflectance spectroscopy].

Sixty alfalfa samples, with different growth stage, cultivars, and preparing method (drying by oven, shade and sun), were selected to study the potential of determination of cellulose, hemicellulose and lignin content in the present research. The result showed that the correlation coefficient of cross-validation (R(cv)), determination coefficient of external validation(r2) and the ratio of standard deviation to root mean square error of prediction (RPD) of cellulose and lignin were 0.97, 0.97 and 4.44, and 0.94, 0.94 and 4.08, respectively. This indicated the feasibility of determining cellulose and lignin content of alfalfa using near infrared reflectance spectroscopy. Hemicellulose was not predicted accurately by NIRS in this study, due to the lowest accuracy (R(cv) = 0.39, r2 = 0.29, RPD = 1.09). The exact determination of cellulose and lignin using near infrared reflectance spectroscopy will be useful to quality control in alfalfa production and quickly analyzing the fiber composition of alfalfa samples breeding research.

[The application of near-infrared reflectance spectroscopy in seeds quality certification].

Near infrared reflectance spectroscopy is a newly developed method capable of analyzing the content of specific compound in the detected sample quickly and efficiently. Near infrared reflectance spectroscopy has been wildly used in many fields such as agriculture science, food industry, medical industry, chemical engineering and protection of environment and so on. In the present paper firstly the principle, technique method and merits of near infrared reflectance spectroscopy were described. Then the application of near infrared reflectance spectroscopy to the seeds of many crops, i.e. wheat, rice, rape and apple, was reviewed and discussed in brief. Based on this introduction, the potential value of the application of near infrared reflectance spectroscopy to the grass seeds quality certification was discussed in the four areas, i.e. the grass seed variety discrimination, the standard percentage rate of grass seed germination testing, the scale of the content of grass seed moisture, and the evaluation of the grass seed vigor and the purity of grass seed. Finally, it was concluded that the application of near infrared reflectance spectroscopy to the grass seed quality certification is significant both in the academic and the technical areas because near infrared reflectance spectroscopy will not only improve the efficiency of grass seed certification, saving manual work and testing time, but also help expand the extent and application of routine quality certification of grass seeds.

[Application of near-infrared reflectance spectroscopy in grass breeding with space flight mutagenesis].

Near infrared reflectance spectroscopy is a new fast and efficient analysis method. It has been wildly used in many areas such as evaluation of feedstuff, assessment of soil fertilizer and so on. In the present paper, the principle, technique method and merits of NIRS were introduced. The potential application of NIRS in grass breeding with space flight mutagenesis was discussed in areas such as analysis of grass nutrition, estimate of secondary metabolism compounds, forecast of disease and insects resistance, and evaluation of abiotic stress. The conclusion is that application of NIRS in grass breeding with space mutagenesis is significant in both academic and technical areas because it not only improves the efficiency of mutation selection but helps uncover the mechanism of space mutation breeding.

[Prediction of leaf concentration in alfalfa using near infrared reflectance spectroscopy].

Leaf concentration in alfalfa is an important factor affecting the nutritive value, forage intake and digestibility. Estimates of leaf concentrations commonly used currently involve a labor intensive process of hand separating leaf and stem fractions. In the present study, a total of 41 artificial alfalfa samples were mixed with different leaf concentrations ranging from 15% to 55%. The object was to develop 3 calibrations for predicting alfalfa leaf concentrations using 15, 25 and 35 calibrated samples by near infrared reflectance spectroscopy. The root mean square error of prediction(RMSEP)was 1.02, 1.97 and 0.51, respectively. External validation had a coefficient of determination (r2) ranging from 0.79 8 to 0.998 9. The ratio of performance to standard deviation (RPD) varied from 2.85 to 25.93. The results showed that 15 samples could develop accurate NIRS model of alfalfa leaf concentrations; the calibration equations got better accuracy with the increase in calibrated samples numbers from 15 to 35.

[Evaluation of fermentation character of alfalfa silage through near infrared reflectance spectroscopy (NIRS)].

It is very important to evaluate the fermentation character of alfalfa silage using near infrared reflectance spectroscopy technology (NIRS) for animal production, including the content of NH3-N, lactic acid, acetic acid and butyric acid in silage. In order to evaluate the feasibility of using NIRS to analyze the formation character of alfalfa silage, the near infrared reflectance spectroscopy models were built for NH3-N, lactic acid, zcetic acid and butyric acid in this experiment. Partial least square regression (PLS), Fourier transform technology and sample preparation with liquid nitrogen technology were used to optimize the model. The analyzed samples were obtained with different cultivars, maturity, cuttings and ensiling method. The determination of cross validation was between 0.6024 and 0.9497. The standard errors of cross validation were between 5.59 x 10(-1) and 3.78 g x kg(-1) fresh weight. The validation samples were used to test the performance of the models. The correlation coefficients between the chemical value and the NIRS value were between 0.8826 and 0.9853, and the root mean square errors of prediction were between 5.71 x 10(-1) and 3.15 g x kg(-1) fresh weight. The results showed the NIRS could evaluate the fermentation of the fresh forage.

[Applications of spectral analysis technique to monitoring grasshoppers].

Grasshopper monitoring is of great significance in protecting environment and reducing economic loss. However, how to predict grasshoppers accurately and effectively is a difficult problem for a long time. In the present paper, the importance of forecasting grasshoppers and its habitat is expounded, and the development in monitoring grasshopper populations and the common arithmetic of spectral analysis technique are illustrated. Meanwhile, the traditional methods are compared with the spectral technology. Remote sensing has been applied in monitoring the living, growing and breeding habitats of grasshopper population, and can be used to develop a forecast model combined with GIS. The NDVI values can be analyzed throughout the remote sensing data and be used in grasshopper forecasting. Hyper-spectra remote sensing technique which can be used to monitor grasshoppers more exactly has advantages in measuring the damage degree and classifying damage areas of grasshoppers, so it can be adopted to monitor the spatial distribution dynamic of rangeland grasshopper population. Differentialsmoothing can be used to reflect the relations between the characteristic parameters of hyper-spectra and leaf area index (LAI), and indicate the intensity of grasshopper damage. The technology of near infrared reflectance spectroscopy has been employed in judging grasshopper species, examining species occurrences and monitoring hatching places by measuring humidity and nutrient of soil, and can be used to investigate and observe grasshoppers in sample research. According to this paper, it is concluded that the spectral analysis technique could be used as a quick and exact tool in monitoring and forecasting the infestation of grasshoppers, and will become an important means in such kind of research for their advantages in determining spatial orientation, information extracting and processing. With the rapid development of spectral analysis methodology, the goal of sustainable monitoring grasshoppers can be developed in the future. First, it is needed to find the relationship between the grasshopper and its environment. Second, the new spectral technology including thermal infrared, microwave, UV detection, and laser technique will be widely practiced in grasshopper monitoring. Finally, it is obvious that the integration of all methods will drive the research into a bright direction of synthetically monitoring grasshoppers. Such approaches will greatly decrease the likelihood of grasshopper outbreaks.

[Research on predicting the nutrition value of pelletized alfalfa by near infrared reflectance spectroscopy].

The present research aimed to predict the qualities of pelletized alfalfa by near infrared reflectance spectroscopy. Sixty pelletized alfalfa samples were collected, including 22 whole plant alfalfa samples, 19 stem samples and 19 leaf samples. They were divided into a calibration sample set (45 samples) and a validation sample set (15 samples). The Fourier transform-near infrared reflectance spectroscopy (FT-NIRS) and the partial least square (PLS) were used to calibrate models of the pelletized alfalfa nutrition value, involving crude protein (CP), neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents. All models had great calibration performances. The correlation coefficients of cross-validation (R(CV)) were between 0.96410 and 0.96887, and the root mean square errors of cross-validation (RMSECV) were between 0.80% and 2.59%. Fifteen validation samples were used to predict the performances of these models, all the correlation coefficients of NIRS value and chemical value (r) were between 0.9669 and 0.9743, and the root mean square errors of prediction (RMSEP) were between 0.85% and 2.07%. The RPD values of cross-validation and prediction were all above 3. The results showed that pelletized alfalfa's CP, NDF, ADF contents were exactly predicted by near infrared reflectance spectroscopy.

[Evaluation of fresh sample of alfalfa silage through near infrared reflectance spectroscopy (NIRS)].

It is very important to evaluate the fresh sample of alfalfa silage using near infrared reflectance spectroscopy technology (NIRS) for animal production. The nutrient content of forage means the contents of dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF) in the forage. Because of the high moisture content, it is difficult to make uniform samples for fresh forage and to get useful information from the spectrum. Therefore, it is hard to use NIRS analysis. In order to evaluate the feasibility of using NIRS to analyse the fresh alfalfa silage, the DM, CP, NDF and ADF contents of fresh alfalfa silage were evaluated by the near infrared reflectance spectroscopy model in this experiment using partial least square regression (PLS), Fourier transform technology and sample preparation with liquid nitrogen technology. The analysis samples were obtained through different cultivars, maturity, cuttings and ensiling method. The cross validation was determined between 0.884 6-0. 989 8. The standard error of cross validation was between 3.9 and 9.7 g x kg(-1) fresh weight. Fifty samples were used to test the performance of the models. The coefficients of correlation between the chemical value and the NIRS value are between 0.939 7 and 0.994 9, and the root mean square errors of prediction are between 1.9 and 8.3 g x kg(-1) fresh weight. The results showed that NIRS could be used to evaluate the nutrition of fresh forage.

[Quality prediction of alfalfa hay using Fourier transform near infrared reflectance spectroscopy].

Alfalfa hay has high nutritive value, and it is one of the most important protein feed for domestic animals. The quality parameters of alfalfa hay, including CP, Ash, NDF, ADF, ADL and IVDMD, were predicted using Fourier transform near infrared reflectance spectroscopy with PLS regression in this test. Then the 6 models were validated by cross-validation and external-validation. The results indicated that FT-NIR models of alfalfa hay quality have considerable accuracy and precision: the correlation coefficient of cross-validation is 0.953 88 to 0. 990 19, and the RMSECV is 1.980-0.345; The correlation coefficient of external-validation is 0.963-0. 990. By using FT-NIR, analysis can rapidly and accurately determine the quality of alfalfa without any chemical reagent. This method is of great significance for analysing the trait of alfalfa production, the quality determination, the estimation of germ plasm resource, and the identifying and selecting of hybridized generations in alfalfa research of China.

[Applications of near infrared reflectance spectroscopy technique (NIRS) to grassland ecology research].

The technology of near infrared reflectance spectroscopy (NIRS) have been widely used in many research areas, owing to its rapidness, high efficiency, low cost and no pollution. The present paper mainly illustrates the significance of the applications of NIRS to grassland ecology research, and explains some innovative implications of near infrared reflectance spectroscopy in the determination of a variety of forage nutrients, minerals, and the components of soil, prediction of the composition of for-age mixtures, animal performance, grass resistance of diseases and insect pests and other complex ecological characters, and doing research on biochemical markers, isotope discrimination and so on. By synthesizing these applications properly, it is concluded that NIRS could be used as a holistic tool in grassland ecology research to determine the chemical components, and analyze the complex dynamic character of grassland ecosystem and the total specialty of the system running. According to this paper, the authors also hope to promote the application conditions of NIRS in the grassland ecology research in China, and accelerate the modernization of research measures in this area.

[Survey of the development of near-infrared spectroscopy instruments].

The technology of near-infrared spectroscopic analysis goes by the name of "superman" in the field of analytical chemistry. It is one of the most attention-attracting spectroscopic analysis technologies, and is developing rapidly nowadays. The first near-infrared spectroscopy (NIRS) instrument in the world is fifty years old. Although the authors only have a history of twenty years in NIRS instrument manufacturing, the achievements are exciting. The NIRS instruments are developing and emerging endlessly with the advancement of science. Firstly, the survey of the development of NIRS instruments is described in the present article. Secondly, the principles and the characteristics of five types of NIRS instruments are discussed, including interference filters, Fourier transform, acousto-optic tunable filter, and so on. In addition, the primary producers and their popular products are enumerated in the table. Finally, the direction of NIRS instrument development is viewed.