ZNF384-ZEB1 feedback loop regulates breast cancer metastasis.

BACKGROUND: Breast cancer has become the most frequently diagnosed cancer worldwide. Increasing evidence indicated that zinc finger proteins (ZNFs), the largest family of transcription factors, contribute to cancer development and progression. Although ZNF384 is overexpressed in several types of human cancer, the role of ZNF384 in breast cancer remains unknown. Therefore, our research focused on ZNF384 regulation of the malignant phenotype of breast cancer and the underlying molecular mechanisms. METHODS: CCK-8 and colony formation assays were used to evaluate cell proliferation. Transwell and scratch assays were used to evaluate the cell migration and invasion. Chromatin immunoprecipitation (ChIP)-qPCR and luciferase reporter assays were used to confirm the target relationship between ZNF384 and zinc finger E-box binding homeobox 1 (ZEB1). Xenografts were used to monitor the targets in vivo effects. RESULTS: We noted that ZNF384 was significantly overexpressed in breast cancer and highlighted the oncogenic mechanism of ZNF384. ZNF384 transactivated ZEB1 expression and induced an epithelial and mesenchymal-like phenotype, resulting in breast cancer metastasis. Furthermore, ZNF384 may be a target of miR-485-5p, and ZEB1 can up-regulate ZNF384 expression by repressing miR-485-5p expression. Together, we unveiled a feedback loop of ZNF384-ZEB1 in breast cancer metastasis. CONCLUSIONS: The findings suggest that ZNF384 can serve as a prognostic factor and a therapeutic target for breast cancer patients.

Study on the single-mode condition for x-cut LNOI rib waveguides based on leakage losses.

Lithium niobate-on-insulator (LNOI) has recently emerged as a promising material platform for high-density and advanced photonics integrated circuits (PICs). And single-mode waveguides (SMW) are the most basic building blocks for structuring various PICs. In this paper, single-mode conditions (SMCs) for shallowly etched LNOI rib waveguides in x-cut LNOI wafer are investigated with the finite element method (FEM) in consideration of the lateral leakage and the magic width for the first time, to our best knowledge. Our results indicate that due to the lateral leakage and the magic width these shallowly etched x-cut LNOI rib waveguides have unique and complex SMCs. Our method and results provide a guidance in designing low-loss LNOI SMW and high-performance PICs.

Restraint of FAM60A has a cancer-inhibiting role in pancreatic carcinoma via the effects on the Akt/GSK-3ß/ß-catenin signaling pathway.

Family with sequence similarity 60A (FAM60A) has been reported as a new cancer-related protein that affects the malignant progression of some cancers. However, whether FAM60A plays a part in pancreatic carcinoma is undetermined. This work was designed to examine the impact of FAM60A in pancreatic carcinoma. Abundant expression of FAM60A was observed in the primary tumor tissue of pancreatic carcinoma. Moreover, a high FAM60A level was related to a poor overall survival in pancreatic carcinoma patients. Malignant behaviors of pancreatic carcinoma cells, such as proliferation and invasiveness, were markedly affected by FAM60A depletion. In addition, FAM60A depletion enhanced the drug sensitivity of pancreatic carcinoma cells to gemcitabine. Further study revealed that FAM60A depletion impaired the activities of Akt and ß-catenin. Inhibiting the activity of Akt abolished FAM60A-mediated ß-catenin activation. Re-expression of ß-catenin partially diminished the FAM60A-depletion-mediated cancer suppressive effect in pancreatic carcinoma cells. In vivo experiments demonstrated that FAM60A depletion prohibited the xenograft formation of pancreatic carcinoma cells, with concurrent reductions of Akt and ß-catenin activities. Collectively, our findings indicate that FAM60A exerts a cancer-promoting role in pancreatic carcinoma through affection of the Akt/ß-catenin pathway. This work indicates that FAM60A acts as a tumor promoter in pancreatic carcinoma and can be utilized as a potential target for anti-pancreatic carcinoma therapy development.

Dimers formed with the mixed-type G-quadruplex binder pyridostatin specifically recognize human telomere G-quadruplex dimers.

By choosing pyridostatin (PDS) with high thermal stabilization towards mixed-type G-quadruplexes as the monomer in dimers, three novel polyether-tethered PDS dimers (1a-c) were first synthesized and their interaction with human telomere G-quadruplex dimers (G2T1) was studied. Through the regulation of the linker length in PDS dimers, the dimer with a medium-length polyether linker (1b) showed higher binding selectivity and thermal stabilization (ΔTm = 29.5 °C) towards antiparallel G2T1 over G-quadruplex monomers (G1). Furthermore, the dimer with the longest-length polyether linker (1c) showed higher binding selectivity and thermal stabilization towards mixed-type G2T1 over mixed-type G1, c-kit 1, c-kit 2, c-myc and ds DNA. This work provides new insights into the development of G2T1 binders, especially mixed-type G2T1 binders, which could be promoted by a polymer formed with a mixed-type G-quadruplex binder. In addition, dimer 1c exhibited stronger telomerase inhibition than dimers 1a and 1b.

Upregulation of LASP2 inhibits pancreatic cancer cell migration and invasion through suppressing TGF-ß-induced EMT.

LASP2 (LIM and SH3 protein 2), a member of the LIM-protein subfamily of the nebulin group, was first identified as a splice variant of the nebulin gene. In the past, investigators mainly focused on the impact of LASP2 on cardiac diseases because of its identification in the myocardium. Recently, several studies have reported that LASP2 is associated with the progression of various cancers. However, there have been no investigations on the expression and function of LASP2 in pancreatic cancer (PC). In this study, we performed the quantitative real-time polymerase chain reaction and Western blot analysis to detect the expression of LASP2 in PC tissues and cell lines. PC cells were transfected with LASP2 overexpression plasmid or the negative control in the presence or absence of tumor growth factor-ß (TGF-ß). The transwell assays were used to measure the effects of LASP2 on PC cell migration and invasion. The protein expression of epithelial-mesenchymal transition (EMT) markers was detected using Western blot assay. Our results demonstrated that LASP2 was downregulated in PC tissues and cell lines. In addition, upregulation of LASP2 inhibited the PC cell migration and invasion. We also found that LASP2 upregulation reversed TGF-ß-induced EMT in PC cells. Taken together, we provided novel evidence supporting the tumor-suppressor role of LASP2 in PC and suggested it as a potential therapeutic target in PC treatment.

Effects of dietary inclusion levels of palm oil on growth performance, antioxidative status and serum cytokines of broiler chickens.

This study was conducted to investigate the effects of dietary palm oil inclusion levels on growth performance, serum antioxidative status and cytokines in Sanhuang broiler chickens. A total of 208 one-day-old female Sanhuang chickens were randomly allocated to four treatment groups with four replicates per group and of 13 birds each for a 42-day feeding trial. Dietary treatments were basal diet without palm oil (control) and diets containing 2%, 4% or 6% palm oil. During days 22 to 42 and the overall experimental period, chickens fed diets supplemented with 4% and 6% palm oil had a lower average daily feed intake (ADFI) (p = 0.019) and feed to gain ratio (F/G) (p = 0.031). Average daily gain (ADG) tended to be higher (p = 0.089) for palm oil inclusion treatments compared with the control treatment from days 1 to 42. Dietary 2% and 4% palm oil treatments significantly lowed serum malondialdehyde concentration on day 21 when compared to the control and 6% palm oil treatments (p = 0.027). Dietary 6% palm oil treatment significantly reduced the catalase (CAT) activity (p = 0.018) and total antioxidant capacity (T-AOC) (p = 0.027) in serum in comparison with the control treatment on day 21. No significant differences were observed in superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities in serum among dietary treatments on day 21. There were no significant differences in T-AOC, CAT, SOD and GSH-Px activities among dietary treatments on day 42. Dietary inclusion of 4% and 6% palm oil significantly increased (p = 0.01) serum interleukin-1ß (IL-1ß) content, but improved transforming growth factor-ß (TGF-ß) content in serum on both days 21 and 42 (p = 0.032 and 0.022 respectively) as well as IL-10 content on day 42 (p = 0.022) when compared with the control treatment. Furthermore, dietary inclusion of 6% palm oil significantly reduced tumour necrosis factor-α (TNF-α) content on days 21 and 42 (p = 0.021 and 0.001 respectively) compared with the control treatment. These results suggest that dietary inclusion of 4% and 6% palm oil could improve the growth performance, modulate the balance between pro- and anti-inflammatory cytokines, and show limited effect on antioxidative status in Sanhuang broiler chickens.

Outcome of children with newly diagnosed acute lymphoblastic leukemia treated with CCLG-ALL 2008: The first nation-wide prospective multicenter study in China.

Acute lymphoblastic leukemia (ALL) is the most common malignancy among children. The trial Chinese Children Leukemia Group (CCLG)-ALL 2008 was a prospective clinical trial designed to improve treatment outcome of childhood ALL through the first nation-wide collaborative study in China. Totally 2231 patients were recruited from ten tertiary hospitals in eight cities. The patients were stratified according to clinical-biological characteristics and early treatment response. Standard risk (SR) and intermediate risk (IR) groups were treated with a modified BFM based protocol, and there was 25%-50% dose reduction during intensification phases in the SR group. Patients in high risk (HR) group received a more intensive maintenance treatment. Minimal residual disease (MRD) monitoring with treatment adjustment was performed in two hospitals (the MRD group). Complete remission (CR) was achieved in 2100 patients (94.1%). At five years, the estimate for overall survival (OS) and event-free survival (EFS) of the whole group was 85.3% and 79.9%, respectively. The cumulative incidence of relapse (CIR) was 15.3% at five years. The OS, EFS and CIR for the SR group were 91.5%, 87.9%, and 9.7%, respectively. The outcome of the MRD group is better than the non-MRD group (5y-EFS: 82.4% vs 78.3%, P = .038; 5y-CIR: 10.7% vs 18.0%, P < .001). Our results demonstrated that the large-scale multicenter trial for pediatric ALL was feasible in China. Dose reduction in the SR group could achieve high EFS. MRD-based risk stratification might improve the treatment outcome for childhood ALL.

Depolymerization of Fucosylated Chondroitin Sulfate with a Modified Fenton-System and Anticoagulant Activity of the Resulting Fragments.

Fucosylated chondroitin sulfate (fCS) from sea cucumber Isostichopus badionotus (fCS-Ib) with a chondroitin sulfate type E (CSE) backbone and 2,4-O-sulfo fucose branches has shown excellent anticoagulant activity although has also show severe adverse effects. Depolymerization represents an effective method to diminish this polysaccharide's side effects. The present study reports a modified controlled Fenton system for degradation of fCS-Ib and the anticoagulant activity of the resulting fragments. Monosaccharides and nuclear magnetic resonance (NMR) analysis of the resulting fragments indicate that no significant chemical changes in the backbone of fCS-Ib and no loss of sulfate groups take place during depolymerization. A reduction in the molecular weight of fCS-Ib should result in a dramatic decrease in prolonging activated partial thromboplastin time and thrombin time. A decrease in the inhibition of thrombin (FIIa) by antithromin III (AT III) and heparin cofactor II (HCII), and the slight decrease of the inhibition of factor X activity, results in a significant increase of anti-factor Xa (FXa)/anti-FIIa activity ratio. The modified free-radical depolymerization method enables preparation of glycosaminoglycan (GAG) oligosaccharides suitable for investigation of clinical anticoagulant application.

[Study on the Analysis of the Proportion of Mixed Samples with Near Infrared Spectroscopy and Non-Negative Coefficients Regression].

In the process of practical production, it is important to accurately analyze the proportion of mixed samples with high speed, which plays a great role for quality control and formulation design in food and agricultural processing. Traditional solution is to build statistical model with a large number of representative samples, which is both labor-intensive and time-consuming. In this paper, the proportion of alcohol and acids mixed samples, and their dilute solution mixed samples(used carbon tetrachloride (CCl4) which has no near-infrared absorption characteristics as the solvent medium)，as well as sheet tobacco leaf mixed samples are respectively analyzed by using near infrared spectroscopy, SG smooth and non-negative coefficients regression, which verifies the feasibility of analyzing the proportion of the mixed samples. The results show that, the analytic proportion of transmission spectra of alcohol and acids according to non-negative coefficients regression is closer to actual molar proportion with result error less than 4%. The result of the dilute solution is much better with error less than 4%. The analytic proportion of diffuse reflectance spectra of sheet tobacco leaf according to non-negative coefficients regression is highly accurate with error less than 10%. In the meantime, it has a highly consistency between actual spectra and analytic spectra of mixed samples; and the result of F-test and T-test shows that there is no significant difference between them and the confidence level is 0.01. It has the reliability of analytical proportion in theory. With the spectral data of several pure samples, the proportion of mixed samples can be thus analyzed, which has a good application prospect for quality control and formulation design in food and agricultural processing.

[Study on the Determination of the Maturity Level of Tobacco Leaf Based on In-Situ Spectral Measurement].

Discriminating the maturity levels of tobacco leaf with in-situ measurement can effectively reduce loss rate and quality decline due to misjudgment of the maturity levels of tobacco leaf. In the meantime, the regular way we use to determine the maturity levels of tobacco, which is depend on tobacco leaf age and judgment of tobacco grower, lacks of objectivity. So this paper proposed a method to identify maturity levels of tobacco leaf by using spectral feature parameters combined with the method of support vector machine (SVM). In this paper, a total of 351 tobacco leaf samples collected in 5 maturity levels including immature (M1), unripe (M2), mature (M3), ripe (M4), and mellow (M5) determined by experts were scanned by field spectroscope(ASD FieldSpec3) with in-situ measurement for getting their reflectance spectrum. Through spectral analysis we found that the spectrum of tobacco leaf with different levels of maturity can be distinguished in visible band but not easily be distinguished in near-infrared band, so we use the tobacco leaf spectrum in visible band as the sensitive bands to analyze and model. To find the most suitable input variables for modeling, we use continuous spectrum (350~780 nm), feature band (496~719 nm) and spectral feature parameters (the reflectance of green peak, location of green peak, first order differential value of red-edge and blue-edge, red-edge and blue-edge area, location of red-edge and blue-edge) in visible region as the input variables, and using these three kinds of input variables in the method of SVM to establish a discriminant model for identifying maturity levels of tobacco leaf. The result shows that, the model using spectral feature parameters gains the accuracy rate of 98.85%. While the accuracy rates of other two models were 90.80% and 93.10%, respectively. The conclusion was drawn that using spectral feature parameters in visible spectrum as the input variables in SVM can improve the model performance. It is feasible to use this method to identify maturity level of tobacco leaf with in-situ measurement.

[Determination of Wine Varieties with NIR and Fusion of Multiple Classifiers].

The conventional qualitative analysis of near infrared spectroscopy (NIR) commonly uses one single classification model. This paper focused on the fusion of multiple classifiers based on different single classifiers by using the fused classifier to determine different varieties of red-wines. NIR spectra of 170 red-wine samples were collected by using Fourier transform near-infrared spectrometer. Red-wine classification models were established respectively, based on PLS-DA, SVM, Fisher and Ada-Boost. Then these models were selected to obtain some different base classifiers according to Diversity Measure Feature Selective (DMFS). The highest accuracy rate of determining different varieties of red-wine test samples of four single base classifiers was up to 88.24%, and at the same time the lowest discriminant accuracy rate was 81.18%. At last, we got the fused classifier, which combined four base classifiers with weighted voting principle, and determined its test set again by using the fused classifier. The final classification accuracy rate for red-wine varieties increased to 92.94%, In contrast with one single classifier, the lowest misjudged number of fused classifiers decreased from 9 to 6.These results suggested that the performance of fused classifier is superior to one single classifier. It is feasible to use fused classifier combined with near infrared spectroscopy to determine different varieties of red-wines.

PPARγ-dependent pathway in the growth-inhibitory effects of K562 cells by carotenoids in combination with rosiglitazone.

BACKGROUND: Carotenoids have been found to play roles in the prevention and therapy of some cancers which PPARγ was also discovered to be involved in. The present studies were directed to determine the inhibitory effects of carotenoids in combination with rosiglitazone, a synthetic PPARγ agonist, on K562 cell proliferation and elucidate the contribution of PPARγ-dependent pathway to cell proliferation suppression. METHODS: The effects of carotenoid and rosiglitazone combination on K562 cell proliferation were evaluated by trypan blue dye exclusion assay and MTT assay. When PPARγ has been inhibited by GW9662 and siRNA, cycle-related regulator expression in K562 cells treated with carotenoid and rosiglitazone combination was analyzed by Western blotting. RESULTS: Rosiglitazone inhibited K562 cell proliferation and augmented the inhibitory effects of carotenoids on the cell proliferation greatly. Specific PPARγ inhibition attenuated the cell growth suppression induced by carotenoid and rosiglitazone combination. GW9662 pre-treatment attenuated the enhanced up-regulation of PPARγ expression caused by the combination treatment. Moreover, GW9662 and PPARγ siRNA also significantly attenuated the up-regulation of p21 and down-regulation of cyclin D1 caused by carotenoids and rosiglitazone. CONCLUSIONS: PPARγ signaling pathway, via stimulating p21 and inhibiting cyclin D1, may play an important role in the anti-proliferative effects of carotenoid and rosiglitazone combination on K562 cells. GENERAL SIGNIFICANCE: Carotenoids in combination with rosiglitazone are hopeful to provide attractive dietary or supplementation-based and pharmaceutical strategies to treat cancer diseases.

[Traceability of Wine Varieties Using Near Infrared Spectroscopy Combined with Cyclic Voltammetry].

To achieve the traceability of wine varieties, a method was proposed to fuse Near-infrared (NIR) spectra and cyclic voltammograms (CV) which contain different information using D-S evidence theory. NIR spectra and CV curves of three different varieties of wines (cabernet sauvignon, merlot, cabernet gernischt) which come from seven different geographical origins were collected separately. The discriminant models were built using PLS-DA method. Based on this, D-S evidence theory was then applied to achieve the integration of the two kinds of discrimination results. After integrated by D-S evidence theory, the accuracy rate of cross-validation is 95.69% and validation set is 94.12% for wine variety identification. When only considering the wine that come from Yantai, the accuracy rate of cross-validation is 99.46% and validation set is 100%. All the traceability models after fusion achieved better results on classification than individual method. These results suggest that the proposed method combining electrochemical information with spectral information using the D-S evidence combination formula is benefit to the improvement of model discrimination effect, and is a promising tool for discriminating different kinds of wines.

[The Study of the Spectral Model for Estimating Pigment Contents of Tobacco Leaves in Field].

Fast and non-destructive measurements of tobacco leaf pigment contents by spectroscopy in situ in the field has great significance in production guidance for nutrient diagnosis and growth monitoring of tobacco in vegetative growth stage, and it is also very important for the quality evaluation of tobacco leaves in mature stage. The purpose of this study is to estimate the chlorophyll and carotenoid contents of tobacco leaves using tobacco leaf spectrum collected in the field. Reflectance spectrum of tobacco leaves in vegetative growth stage and mature stage were collected in situ in the field and the pigment contents of tobacco leaf samples were measured in this study, taking the tobacco leaf samples collected in each and both stages as modeling sets respectively, and using the methods of support vector machine (SVM) and spectral indice to establish the pigment content estimation models, and then compare the prediction performance of the models built by different methods. The study results indicated that the difference of estimation performance by each stage or mixed stages is not significant. For chlorophyll content, SVM and spectral indice modeling methods can both have a well estimation performance, while for carotenoid content, SVM modeling method has a better estimation performance than spectral indice. The coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf chlorophyll content by each stage were 0.867 6 and 0.014 7, while the coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf chlorophyll content by mixed stages were 0.898 6 and 0.012 3; The coefficient of determination and the root mean square error for estimating tobacco leaf carotenoid content by each stage were 0.861 4 and 0.002 5, while the coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf carotenoid content by mixed stages were 0.839 9 and 0.002 5. The innovation point of this study is that on the basis of support vector machine and spectral indice, models established by each stage and mixed stages for estimating the pigment contents of tobacco leaf samples can provide scientific basis and technical support for quality control of tobacco leaf production in field and the ensurance of tobacco leaf recovery quality.

[Identification and classification of disease severity of wheat stripe rust using near infrared spectroscopy technology].

Wheat stripe rust caused by Puccinia striiformis f. sp. tritici, is an economically important disease in the world. It is of great significance to assess disease severity of wheat stripe rust quickly and accurately for monitoring and controlling the disease. In this study, wheat leaves infected with stripe rust pathogen under different severity levels were acquired through artificial inoculation in artificial climate chamber. Thirty wheat leaves with disease severity equal to 1%, 5%, 10%, 20%, 40%, 60%, 80% or 100% were picked out, respectively, and 30 healthy leaves were chosen as controls. A total of 270 wheat leaves were obtained and then their near infrared spectra were measured using MPA spectrometer. According to disease severity levels, 270 near infrared spectra were divided into 9 categories and each category included 30 spectra. From each category, 7 or 8 spectra were randomly chosen to make up the testing set that included 67 spectra. The remaining spectra were treated as the training set. A qualitative model for identification and classification of disease severity of wheat stripe rust was built using near infrared reflectance spectroscopy (NIRS) technology combined with discriminant partial least squares (DPLS). The effects of different preprocessing methods of obtained spectra, ratios between training sets and testing sets, and spectral ranges on qualitative recognition results of the model were investigated. The optimal model based on DPLS was built using cross verification method in the spectral region of 4000-9000 cm(-1) when "centralization" was used as the preprocessing method of spectra and the spectra were divided into the training set and the testing set with the ratio equal to 3:1. Accuracy rate of the training set was 95.57% and accuracy rate of the testing set was 97.01%. The results showed that good recognition performance could be acquired using the model based on DPLS. The results indicated that the method using near infrared reflectance spectroscopy technology proposed in this study is feasible for identification and classification of disease severity of wheat stripe rust. A new method was provided for monitoring and assessment of wheat stripe rust.

[Establishment and Application of Model for Determining Oil Content of Cottonseed Using Near Infrared Spectroscopy].

Cotton is one of the important oil crops, and it is great significance for screening and identification of breeding materials to establish a method of the rapid, nondestructive testing of cotton seed oil content. In this study, near-infrared diffuse reflection spectroscopy of 118 high and low oil materials were adopted to establish models for fast nondestructive determining oil content of cottonseed using near infrared spectroscopy (NIR). One hundred and six cottonseed samples as calibration set that covered the range of seed oil content for upland cotton were used in this experiment. The spectral data of cottonseed were processed using the first derivative and multiplicative scatter correction (MSC). The correction NIR model of oil content was built based on partial least squares (PLS) method with the spectral regions 5 446-8 848 cm(-1) and main components (5). The determination coefficient (R2) of calibration model was 0.975, standard error of calibration (SEC) was 0.67. The authors test the model's actual ability to predict using external validation set. The correlation coefficient (r) of predicted values and the chemistry value was 0.978, the range of prediction error was 0.1% - 1.7%. The model established has good predictability. The oil content of 784 breeding stocks were predicted by NIR model, statistical analysis of predictable. results elucidated that the NIR model of oil content developed can be well applied to selective breeding and oil related study in cotton.

Endoscopic ultrasonography for tumor node staging and vascular invasion in pancreatic cancer: a meta-analysis.

BACKGROUND/AIMS: The accurate staging of pancreatic cancer (PanCa) is crucial in the development of a stage-specific treatment plan for PanCa patients. We aimed to perform a meta-analysis of endoscopic ultrasonography (EUS) in the tumor node (TN) staging and evaluation of vascular invasion in PanCa. METHODS: A meta-analysis of diagnostic accuracy parameters was performed to evaluate the EUS-based TN staging, and vascular invasion by PanCa was compared to the results of intraoperative staging or to the histopathology of resected specimens. RESULTS: Twenty studies with 726 PanCa cases were identified from 281 articles. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were 0.72, 0.90, 6.27, 0.28, and 24.69, respectively, for T1-2 staging and 0.90, 0.72, 3.58, 0.16, and 24.69, respectively, for T3-4 staging. The overall sensitivity, specificity, PLR, NLR, and DOR were 0.62, 0.74, 2.54, 0.51, and 6.67, respectively, for N staging (positive vs. negative) and 0.87, 0.92, 7.16, 0.20, and 56.19, respectively, for vascular invasion. The area under the curve was 0.90, 0.90, 0.79, and 0.94 for T1-2 staging, T3-4 staging, N staging, and vascular invasion, respectively. CONCLUSIONS: EUS is a reliable and accurate diagnostic tool for the TN staging and evaluation of vascular invasion in PanCa. The nodal staging accuracy using EUS is less satisfactory.

[Detection of Puccinia strii formis f. sp. tritici latent infections in wheat leaves using near infrared spectroscopy technology].

To realize the early detection of P. strii formis f. sp. tritici latent infections in wheat leaves while no disease symptoms appear, a qualitative model for identification of the wheat leaves in the incubation period of stripe rust was built using near infrared reflectance spectroscopy (NIRS) technology combined with qualitative partial least squares (DPLS). In this study, 30 leaf samples infected with P. strii formis f. sp. tritici were collected each day during the eleven-day incubation period. And 30 healthy leaf samples and 30 leaf samples showing disease symptoms infected with P. strii formis f. sp. tritici, were also collected as controls. In total, there were 390 leaf samples that were divided into thirteen categories. Near infrared spectra of 390 leaf samples were obtained using MPA spectrometer and then a model to identify the categories of wheat leaves was built using cross verification method. The effects of different spectral ranges, samples for building the model, preprocessing methods of spectra and number of principal components on NIRS prediction results for qualitative identification were investigated. The optimal identification results were obtained for the model built in the combined spectral region of 5 400-6 600 and 7 600-8 900 cm(-1) when the spectra were divided into the training set and the testing set with the ratio equal to 4 : 1, "scatter correction" was used as the preprocessing method and the number of principal components was 14. Accuracy rate, misjudgment rate and confusion rate of the training set were 95.51%, 1.28% and 3.21%, respectively. And accuracy rate, misjudgment rate and confusion rate of the testing set were 100.00%, 0.00% and 0.00%, respectively. The result showed that using near infrared reflectance spectroscopy technology, P. strii formis f. sp. tritici latent infections in wheat leaves could be detected as early as one day after inoculation (or 11 days before symptoms appearing) and the number of days when the leaf has been infected could also be identified. The results indicated that the method using near infrared reflectance spectroscopy technology proposed in this study is feasible for the identification of wheat leaves latently infected by P. strii formis f. sp. tritici. A new method based on NIRS was provided for the early detection of wheat stripe rust in this study.

[Application of near infrared spectroscopy to qualitative identification and quantitative determination of Puccinia strii formis f. sp. tritici and P. recondita f. sp. tritici].

To realize qualitative identification and quantitative determination of Puccinia strii formis f. sp. tritici (Pst) and P. recondita f. sp. tritici (Prt), a qualitative identification model was built using near infrared reflectance spectroscopy (NIRS) combined with distinguished partial least squares (DPLS), and a quantitative determination model was built using NIRS combined with quantitative partial least squares (QPLS). In this study, 100 pure samples including 50 samples of Pst and 50 samples of Prt were obtained, and 120 mixed samples including three replicates of mixed urediospores of the two kinds of pathogen in different proportions (the content of Pst was within the range of 2. 5% 100% with 2. 5% as the gradient) were obtained. Then the spectra of the samples were collected using MPA spectrometer, respectively. Both pure samples and mixed samples were divided into training set and testing set with the ratio equal to 2:1. Qualitative identification model and quantitative determination model were built using internal cross-validation method in the spectral region 4,000--10,000 cm(-1) based on the training sets from pure samples and mixed samples, respectively. The results showed that the identification rates of the Pst-Prt qualitative identification model for training set and testing set were both up to 100. 00% when scatter correction was used as the preprocessing method of the spectra and the number of principal components was 3. When 'range normalization + scatter correction' was used as the preprocessing method of the spectra and the number of principal components was 6, determination coefficient (RZ), standard error of calibration (SEC) and average absolute relative deviation(AARD) of the Pst-Prt quantitative determination model for training set were 99.36%, 2.31% and 8.94%, respectively, and R2, standard error of prediction (SEP) and AARD for testing set were 99.37%, 2.29% and 5. 0%, respectively. The results indicated that qualitative identification and quantitative determination of Pst and Prt using near infrared spectroscopy technology are feasible and that the Pst-Prt qualitative identification model and the Pst-Prt quantitative determination model built in this study were reliable and stable. A new method based on NIRS was provided for qualitative identification and quantitative determination of plant pathogen in this study.

[Quality anlysis of the before redrying raw tobacco & after redrying sheet tobacco by using online near infrared spectroscopy].

In this paper, the 7 different origin before redrying raw tobacco & after redrying sheet tobacco's online near infrared spectroscopy were collected from sorting & redrying production line specifically for "ZHONGHUA" brand. By using the projection model bulit by different origin tobacco's online spectroscopy and the method of variance and correlation analysis, we studied the uniformity and similarity quality characteristics change before and after the redrying of tobacco, which can provide support for understanding the quality of the tobacco material and cigarette product formulations. This study show that selecting about 10,000 by equally spaced sampling time from a huge number of online near infrared spectroscopy, for modeling are feasible, and representative. After manual sorting, threshing, and redrying, the uiformity of each origin tobacco near-infrared spectroscopy can be increased by 10%~35%, homogeneity of the tobacco leaf has been significantly improved. After redrying, the similar relationship embodied in the origin also have significant changes, overall it reduce significantly, that shows the quality differences embodied by origin significantly improve, which can provide greater space for formulations, it shows the need for high-quality Chinese cigarette production requires large amounts of financial and human resources to implement cured tobacco processing. The traditional means of chemical analysis, it takes a lot of time and effort, it is difficult to control the entire processing chain, Near Infrared Spectroscopy with its rapid, non-destructive advantage, not only can achieve real-time detection and quality control, but also can take full advantage of near-infrared spectroscopy information created in the production process, which is a very promising online analytical detection technology in many industries especially in the agricultural and food processing industries.