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Clear cell renal cell carcinoma (ccRCC) is the most common histological and devastating subtype of renal cell carcinoma. Necroptosis is a form of programmed cell death that causes prominent inflammatory responses. miRNAs play a significant role in cancer progression through necroptosis. However, the prognostic value of necroptosis-related miRNAs remains ambiguous. In this study, 39 necroptosis-related miRNAs (NRMs) were extracted and 17 differentially expressed NRMs between normal and tumor samples were identified using data form The Cancer Genome Atlas (TCGA). After applying univariate Cox proportional hazard regression analysis and LASSO Cox regression model, six necroptosis-related miRNA signatures were identified in the training cohort and their expression levels were verified by qRT-PCR. Using the expression levels of these miRNAs, all patients were divided into the high- and low-risk groups. Patients in the high-risk group showed poor overall survival ( P < 0.0001 ). Time-dependent ROC curves confirmed the good performance of our signature. The results were verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression models demonstrated that the risk score was an independent prognostic factor. Additionally, a predictive nomogram with good performance was constructed to enhance the implementation of the constructed signature in a clinical setting. We then employed miRBD, miRTarBase, and TargetScan to predict the target genes of six necroptosis-related miRNAs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that 392 potential target genes were enriched in cell proliferation-related biological processes. Six miRNAs and 59 differentially expressed target genes were used to construct an miRNA–mRNA interaction network, and 11 hub genes were selected for survival and tumor infiltration analysis. Drug sensitivity analysis revealed potential drugs that may contribute to cancer management. Hence, necroptosis-related genes play an important role in cancer biology. We developed, for the first time, a necroptosis-related miRNA signature to predict ccRCC prognosis.

BackgroundCuproptosis is a newly discovered unique non-apoptotic programmed cell death distinguished from known death mechanisms like ferroptosis, pyroptosis, and necroptosis. However, the prognostic value of cuproptosis and the correlation between cuproptosis and the tumor microenvironment (TME) in lower-grade gliomas (LGGs) remain unknown.MethodsIn this study, we systematically investigated the genetic and transcriptional variation, prognostic value, and expression patterns of cuproptosis-related genes (CRGs). The CRG score was applied to quantify the cuproptosis subtypes. We then evaluated their values in the TME, prognostic prediction, and therapeutic responses in LGG. Lastly, we collected five paired LGG and matched normal adjacent tissue samples from Sun Yat-sen University Cancer Center (SYSUCC) to verify the expression of signature genes by quantitative real-time PCR (qRT-PCR) and Western blotting (WB).ResultsTwo distinct cuproptosis-related clusters were identified using consensus unsupervised clustering analysis. The correlation between multilayer CRG alterations with clinical characteristics, prognosis, and TME cell infiltration were observed. Then, a well-performed cuproptosis-related risk model (CRG score) was developed to predict LGG patients’ prognosis, which was evaluated and validated in two external cohorts. We classified patients into high- and low-risk groups according to the CRG score and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (PConclusionCollectively, we demonstrated a comprehensive overview of CRG profiles in LGG and established a novel risk model for LGG patients’ therapy status and prognosis. Our findings highlight the potential clinical implications of CRGs, suggesting that cuproptosis may be the potential therapeutic target for patients with LGG.

Melanose disease caused by Diaporthe citri is considered as one of the most important and destructive diseases of citrus worldwide. In this study, isolates from melanose samples were obtained and analyzed. Firstly, the internal transcribed spacer (ITS) sequences were used to measure Diaporthe-like boundary species. Then, a subset of thirty-eight representatives were selected to perform the phylogenetic analysis with combined sequences of ITS, beta-tubulin gene (TUB), translation elongation factor 1-α gene (TEF), calmodulin gene (CAL), and histone-3 gene (HIS). As a result, these representative isolates were identified belonging to D. citri, D. citriasiana, D. discoidispora, D. eres, D. sojae, and D. unshiuensis. Among these species, the D. citri was the predominant species that could be isolated at highest rate from different melanose diseased tissues. The morphological characteristics of representative isolates of D. citri were investigated on different media. Finally, a molecular tool based on the novel species-specific primer pair TUBDcitri-F1/TUBD-R1, which was designed from TUB gene, was developed to detect D. citri efficiently. A polymerase chain reaction (PCR) amplicon of 217 bp could be specifically amplified with the developed molecular tool. The sensitivity of the novel species-specific detection was upon to 10 pg of D. citri genomic DNA in a reaction. Therefore, the D. citri could be unequivocally identified from closely related Diaporthe species by using this simple PCR approach.

This study aimed to explore the differences between the effectiveness of using a combination of rehabilitation and acceptance commitment therapy (ACT), and rehabilitation therapy alone for the treatment of spinal cord injury (SCI). The newly admitted patients with spinal cord injury whose post-traumatic stress disorder (PTSD) score was higher than 38 points were randomly categorized into the treatment group and control group, with 30 patients in each group. One group underwent ACT and rehabilitation treatment, while the other underwent rehabilitation treatment only. PTSD and functional independence measure (FIM) scores were evaluated. Changes in scores were compared between the two groups before, one month, two months, and three months after treatment. The total PTSD score in SCI patients who were treated with ACT was significantly different before and after treatment (P

Maize is among the most important economic corps in China while moisture content is a critical parameterin the process of storage and breeding. To measure the moisture content in maize kernel, a near-infrared hyperspectral imaging system has been built to acquire reflectance images from maize kernel samples in the spectral region between 1 000 and 2 500 nm. Near-infrared hyperspectral information of full surface and embryo of maize kernel were firstly extracted based on band ratio coupled with a simple thresholding method and the spectra analysis between moisture content in maize kernel and embryo was performed. The characteristic bands were then selected with the help of Competitive Adaptive Reweighted Sampling (CARS), Genetic Algorithm (GA) and Successive Projection Algorithm (SPA). Finally, these selected variables were used as the inputs to build Partial Least Square (PLS) models for determining the moisture content of maize kernel. In this study, a significant relation, which the spectral reflectance decreases as moisture content increase, between moisture content and spectral of embryo in maize kernel was observed. For the investigated independent test samples, all the proposed regression models, namely CARS-PLS, GA-PLS and SPA-PLS, achieved a good performance by using the information of embryo region. The correlation coefficient (Rp) and Root Mean Squared Error of Prediction (RMSEP) and number of characteristic wavelength for the prediction set were 0.931 2, 0.315 3, 9 and 0.917 6, 0.336 9, 14 and 0.922 7, 0.336 6, 16 for CARS-PLS, GA-PLS and SPA-PLS models, respectively. And, compared with models obtained by full surface spectral information, less characteristic wavelengths is used for development of CARS-PLS, GA-PLS and SPA-PLS models, while similar results were obtained. Comprehensively analyzing to both model accuracy and model complexity, SPA-PLS model by using embryo region information achieved the best result. Wavelengths at 1 197，1 322 and 1 495 nm were applied to extracted the information of embryo region, and the bands at 1 322, 1 342, 1 367, 1 949, 2 070 and 2 496 nm were used to establish the SPA-PLS model. These results demonstrated that near-infrared hyperspectral information from embryo region is more effective for determination of moisture nondestructive in maize kernel.

Renshen Yangrong Decoction has been used to treat asthenic disease symptoms, such as exhaustion, and qi and blood deficiency diseases. It not only promotes hematopoietic function and improve immune functions, but also alleviates coronary heart diseases, diabetic complications, malignant tumor, and brain injury. It has satisfactory curative effect on sleep disorders and fatigue. Herein, we provide an overview of fundamental research on Renshen Yangrong Decoction focusing on its hematopoietic and immune functions and the status of clinical research with regard to the above-mentioned diseases in recent years.

Background Nesfatin-1 plays a role in the regulation of emotional states like depression. The aim of this study was to investigate the plasma nesfatin-1levels in Chinese patients with depression and healthy subjects, and to determine the possible association between the plasma nesfatin-1 level and the severity of depression. Methods A total of 103 depressive patients and 32 healthy subjects were assessed. According to HAMD-17scores, 51, 18, and 34 patients were enrolled in the mild depression, moderate depression, and severe depression groups, respectively. Plasma nesfatin-1 levels were determined by the ELISA method. Differences between groups were compared and associations between plasma nesfatin-1 and other variables were analyzed. Results The plasma nesfatin-1 was significantly positively correlated with HAMD-17 score (r = 0.651). Compared with healthy controls (8.11 ± 3.31 ng/mL), the plasma nesfatin-1 level significantly increased in patients with mild depression (11.17 ± 3.58 ng/mL), with moderate depression (16.33 ± 8.78 ng/mL), and with severe depression (27.65 ± 8.26 ng/mL) respectively. Plasma nesfatin-1 level (Odds ratio [OR] = 1.269) was an independent indicator for severe depression by multivariate logistic regression analysis. Conclusion The plasma nesfatin-1 level is positively correlated with the severity of depression. Plasma nesfatin-1 level may be a potential indicator for depression severity.

Gastric and adipose tissue secrete a number of hormones that are involved in energy metabolism. The biological functions of these hormones, including their effects on aging, are currently under investigation. Adiponectin was shown to be directly involved in appetite and the control of body weight. However, the effects of aging of nesfatin-1, an appetite-suppressing peptide that was recently identified, have not yet been fully elucidated. The aim of this study was to determine the effects of aging on the plasma levels of nesfatin-1 and adiponectin. Our results demonstrated no significant differences in the nesfatin-1 plasma levels among three age groups (2, 6 and 24 months) of female BALB/c mice. The plasma nesfatin-1 levels/visceral fat (VF) ratio in the 24-month-old mice was significantly lower compared to that in the 2- and 6-month-old mice. In addition, there were no significant differences in the plasma adiponectin levels among the three age groups. The plasma adiponectin levels/VF ratio in the 24-month-old mice was significantly lower compared to that in the 2- and 6-month-old mice. In conclusion, there were no age-related changes in the plasma levels of nesfatin-1 and adiponectin, although the ratio of plasma levels of nesfatin-1 and adiponectin per VF was decreased with advancing age. Our results indicated that nesfatin-1 and adiponectin may be involved in controlling energy balance during aging.

In order to test the correctness of modification parameters, this paper designs respectively test schemes to measure transmission error and geometric rotary error in accordance with the performance requirements of the FA cycloid-pin gear planetary drive reducer. And we design the drive chain connecting parts which accord to the physical size of this prototype. Then the two tests have been done to prove the correctness of the theory.

In order to develop a potential way to reduce the stagnation pressure and heat flux of the blunt body in hypersonic flow, single pulsed and high rated laser energy are deposited respectively to control the bow shock in Mach 5 flow. Process of the interaction of 100mJ single pulsed laser energy with bow shock is studied by schlieren experiment in Mach 5 shock tunnel. The results indicate that the schlieren photographs and stagnation pressure at different times fit well with the simulation. Bow shock is distorted by the laser induced blast wave. During a single laser pulse, the average stagnation pressure and temperature are reduced by 6.5% and 3.4%. High rated laser energy is used to sustain the low pressure and heat flux region to increase the control efficiency. With the power of 6.6% of the enthalpy flux, when the distance of deposition point and blunt body is 1.1 times of the diameter of the blunt body, the pressure and heat flux of the stagnation point is reduced to 49% and 75%, respectively. The mechanism of interaction of laser and bow shock is disclosed.

All sorts of design variables and parameters are often regarded as fixed values in the traditional design, it cannot describe quantitatively how well the products are safe. It is necessary to make a reliability analysis of cycloidal gear, which is the key part of FA pin-cycloidal transmission, this paper uses Monte-Carlo method to simulate and test the distribution laws of the contact stress and the contact fatigue strength of cycloidal gear, which indicates that the contact stress obeys the normal distribution and the contact fatigue strength obeys the lognormal distribution, besides, makes a sensitivity analysis of the random parameters, all these work lay the foundation for the reliability analysis of the whole reducer.

A simulation study of the parallax effect of gaseous detectors using the Garfield program is reported. A method that mainly uses non-uniform cathode potentials to reduce the parallax error of planar type gas detectors is described. By applying it to MWPC and Micro-pattern gas detectors, the method reduces the parallax broadening with very good results. For a 13° incidence track, the width (FWHM) of the parallax broadening is reduced to less than 20% of the normal one after using the special cathode potentials.

In order to improve the human engineering properties for the racing wheelchair, using the CATIA Human Engineering Analysis module, this paper established the human body 3-D model, analyzed the eligibility of the hold and the extend for the racing wheelchair, analyzed and evaluated the comfort of three typical sports postures of human body. The general evaluation results accorded with the human body kinematic theory, and the upper limb comfort gradually became better, in a movement cycle of the upper limbs driving the wheelchair.

Machine thermal equilibrium seriously influences the machining accuracy,a significant amount of research has been dedicated to the task of achieving and reasonablely controlling the thermal equilibrium time.In this paper,based on the analysis of the trait of thermal equilibrium process of machine tool ,the affection of room temperature and spindle speed on this process and the temperature when each point reaches to the heat balance is investigated.A new method of estimating thermal equilibrium time of each measured points based on spindle thermal model theory and multivariate optimization is presented,the results are analysed,further research about the control of machine thermal equilibrium process can be made based on this paper.

When the FA pin-cycloid drive is used in high precision control drive system, especially in the robot drive, there are strict requirements to torsional rigidity .Usually in rated torque, the elastic lost motion produced by the torsional elastic deformation must meet certain precision. This paper analyzes all kinds of elastic factors which affect the rigidity, establishes mathematical model of the machine rigidity and calculates the rigidity for the FA pin-cycloidal drive. Meanwhile ANSYS is applied to build finite element analysis model, and the finite element contact analysis results coincide with the rigidity analysis theory, which confirms the correctness of the machine rigid mathematical model.

Computer vision is a rapid, consistent and objective inspection technique, which has expanded into many diverse industries. Its speed and accuracy provide one alternative for an automated, non-destructive and cost-effective technique to accomplish ever-increasing production and quality requirements. This method of inspection has found applications in the agricultural industry, including the inspection and grading of fruits. This paper provides an introduction to main defection and grading approaches of fruit external defects, including image processing and pattern recognition methods based on fruit two-dimensional (2D) and three-dimensional (3D) information, and hyperspectral and multispectral imaging. In addition, their advantages and disadvantages are also discussed.

Obestatin, a 23-amino-acid peptide, is derived from the preproghrelin precursor. Obestatin was identified in 2005 as a hormone regulating food intake and energy, and having opposite effects to those of ghrelin. However, as studies have progressed, many disputes on the physiological function of obestatin have emerged. The food intake suppressive effects of obestatin have not been replicated in many studies. Nonetheless, many biological roles of obestatin have been revealed, and obestatin is thought to be associated with a variety of biological functions such as feeding, drinking, incretion, memory, and sleep, and with neuropsychiatric manifestations. The biological effects of obestatin will be reviewed in this article.

The objective of this study was to clarify the role of a novel agonist with high selectivity and affinity for Y4 receptors in the regulation of food intake. The Y4 receptor agonist BVD-74D was administered to C57BL/6J mice that were fed with a normal or high-fat diet, and to fatty liver Shionogi (FLS)-ob/ob mice; the food intake, water intake, and body weight gain were measured in these mice. In the mice fed with a normal diet, the cumulative food intake significantly decreased at 20 min and 1 h after the administration of 1 mg/kg of BVD-74D and at 1, 2, 4, 8, and 24 h after the administration of 10 mg/kg of BVD-74D. Moreover, the cumulative water intake and body weight gain significantly decreased in these mice. Among the mice that were fed with a high-fat diet, the cumulative food intake and water intake significantly decreased 1, 2, and 4 h after BVD-74D (10 mg/kg) administration. Furthermore, the cumulative food intake significantly decreased 2 and 4 h after BVD-74D (10 mg/kg) administration in the FLS-ob/ob mice. Thus, we propose that the novel Y4 receptor agonist BVD-74D has suppressive effects on food intake, water intake, and weight gain in normal mice fed with normal diets and on food intake in normal mice fed with high-fat diets and in FLS-ob/ob mice. These findings indicate that the Y4 receptor and its agonist would be promising targets for obesity.

Ghrelin and peptide YY (PYY) are brain-gut peptides that have a variety of physiological functions and are involved in energy regulation. Thus far, abnormalities in the expression and secretion of ghrelin and PYY are known to occur in lifestyle-related diseases, including obesity, and the improvement of these abnormalities has become an important challenge. Exercise has recently been reported to influence ghrelin and PYY concentrations. Exercise increases the PYY secretion. The effects of exercise on ghrelin levels vary with the study subject, timing of exercise, and duration of exercise. Here, we review the findings of recent studies on the association of PYY and ghrelin with obesity, particularly, on the influence of exercise on PYY and ghrelin levels.

Starting from an improved mapping approach and a linear variable separation approach, new families of variable separated solutions (including solitary wave solutions, periodic wave solutions and rational function solutions) with arbitrary functions for the (2+1)-dimensional asymmetric Nizhnik- Novikov-Veselov (ANNV) system are derived. Based on the derived solutions, we obtain some special complex wave excitations.

In this paper, we present a method of special conditional similarity reductions for nonlinear partial differential equations. As an concrete example of its applications in physical problems, we apply this method to the (2 + 1)-dimensional Broer–Kaup–Kupershmidt system with variable coefficients (VCBKK), which has the extensive physics background, and obtain abundant exact solutions derived from some reduction equations.

In using spectroscopy to quantitatively or qualitatively analyze the quality of fruit, how to obtain a simple and effective correction model is very critical for the application and maintenance of the developed model. Strawberry as the research object, this research mainly focused on selecting the key variables and characteristic samples for quantitatively determining the soluble solids content. Competitive adaptive reweighted sampling (CARS) algorithm was firstly proposed to select the spectra variables. Then, Samples of correction set were selected by successive projections algorithm (SPA), and 98 characteristic samples were obtained. Next, based on the selected variables and characteristic samples, the second variable selection was performed by using SPA method. 25 key variables were obtained. In order to verify the performance of the proposed CARS algorithm, variable selection algorithms including Monte Carlo-uninformative variable elimination (MC-UVE) and SPA were used as the comparison algorithms. Results showed that CARS algorithm could eliminate uninformative variables and remove the collinearity information at the same time. Similarly, in order to assess the performance of the proposed SPA algorithm for selecting the characteristic samples, SPA algorithm was compared with classical Kennard-Stone algorithm Results showed that SPA algorithm could be used for selection of the characteristic samples in the calibration set. Finally, PLS and MLR model for quantitatively predicting the SSC (soluble solids content) in the strawberry were proposed based on the variables/samples subset (25/98), respectively. Results show that models built by using the 0.59% and 65.33% information of original variables and samples could obtain better performance than using the ones obtained by using all information of the original variables and samples. MLR model was the best with R(pre)2 = 0.9097, RMSEP=0.3484 and RPD = 3.3278.

In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

The quality and safety of fruits and vegetables are the most concerns of consumers. Chemical analytical methods are traditional inspection methods which are time-consuming and labor intensive destructive inspection techniques. With the rapid development of imaging technique and spectral technique, hyperspectral imaging technique has been widely used in the nondestructive inspection of quality and safety of fruits and vegetables. Hyperspectral imaging integrates the advantages of traditional imaging and spectroscopy. It can obtain both spatial and spectral information of inspected objects. Therefore, it can be used in either external quality inspection as traditional imaging system, or internal quality or safety inspection as spectroscopy. In recent years, many research papers about the nondestructive inspection of quality and safety of fruits and vegetables by using hyperspectral imaging have been published, and in order to introduce the principles of nondestructive inspection and track the latest research development of hyperspectral imaging in the nondestructive inspection of quality and safety of fruits and vegetables, this paper reviews the principles, developments and applications of hyperspectral imaging in the external quality, internal quality and safety inspection of fruits and vegetables. Additionally, the basic components, analytical methods, future trends and challenges are also reported or discussed in this paper.

To improve the precision and robustness of the NIR model of the soluble solid content (SSC) on pear. The total number of 160 pears was for the calibration (n=120) and prediction (n=40). Different spectral pretreatment methods, including standard normal variate (SNV) and multiplicative scatter correction (MSC) were used before further analysis. A combination of genetic algorithm (GA) and successive projections algorithm (SPA) was proposed to select most effective wavelengths after uninformative variable elimination (UVE) from original spectra, SNV pretreated spectra and MSC pretreated spectra respectively. The selected variables were used as the inputs of least squares-support vector machine (LS-SVM) model to build models for de- termining the SSC of pear. The results indicated that LS-SVM model built using SNVE-UVE-GA-SPA on 30 characteristic wavelengths selected from full-spectrum which had 3112 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.956, 0.271 for SSC. The model is reliable and the predicted result is effective. The method can meet the requirement of quick measuring SSC of pear and might be important for the development of portable instruments and online monitoring.

The present study proposed competitive adaptive reweighted sampling (CARS) algorithm to be used to select the key variables from near-infrared hyperspectral imaging data of "Ya" pear. The performance of the developed model was evaluated in terms of the coefficient of determination(r2), and the root mean square error of prediction (RMSEP) and the ratio (RPD) of standard deviation of the validation set to standard error of prediction were used to evaluate the performance of proposed model in the prediction process. The selected key variables were used to build the PLS model, called CARS-PLS model. Comparing results obtained from CARS-PLS model and results obtained from full spectra PLS, it was found that the better results (r(2)pre = 0. 908 2, RMSEP=0. 312 0 and RPD=3. 300 5) were obtained by CARS-PLS model based on only 15. 6% information of full spectra. Moreover, performance of CARS-PLS model was also compared with PLS models built by using variables got by Monte Carlo-uninformative variable elimination (MC-UVE) and genetic algorithms (GA) method. The result found that CARS variable selection algorithm not only can remove the uninformative variables in spectra, but also can reduce the collinear variables from informative variables. Therefore, this method can be used to select the key variables of near-infrared hyperspectral imaging data. This study showed that near-infrared hyperspectral imaging technology combined with CARS-PLS model can quantitatively predict the soluble solids content (SSC) in "Ya" pear. The results presented from this study can provide a reference for predicting other fruits quality by using the near-infrared hyperspectral imaging.

Bruising is one of the major defects occurring on apple surface inevitably during postharvest handling and processing stage. To detect slight bruises on apples fast and efficiently, a novel bruises detection algorithm based on hyperspectral imaging and minimum noise fraction transform is proposed. First, the hyperspectral images in the visible and near-infrared (400 approximately 1 000 nm) ranges are acquired, and MNF transform based on full ranges could obtain better detection performance compared to PCA transform; Second, five wavebands (560, 660, 720, 820 and 960 nm) are selected as the effective wavebands based on the coefficient curve of I-RELIEF method conducted on spectra extracted from intact and bruise surface; Third, the bruises detection algorithm is developed based on the effective wavebands and MNF transform method. For the investigated 40 sound samples and 40 different time stage bruise samples, the results with a 97. 1% overall detection rate are got. The recognition results indicate that the proposed methods and the effective wavelengths selected in this paper are feasible and efficient. This research lays a foundation for the development of multispectral imaging system based on MNF transform for slight bruises detection on apples.

In order to explore the potential of simultaneously detecting the soluble solid content (SSC) and pH of a variety of pears using visible-near infrared spectra technology, linear and nonlinear predictive models for SSC and pH of three kinds of pears were built using the partial least squares (PLS) and least squares-support vector machine (LS-SVM) methods in this study. One-hundred eighty samples (60 for each variety) were selected as sample set. 150 pear samples (50 for each variety) were selected randomly for the calibration set, and the remaining 30 samples (10 for each variety) for the prediction set. Different preprocessing methods including average smoothing, first and second derivatives were applied to improve the predictive ability of the models. For estimation of SSC and pH values, PLS models with original spectra and LS-SVM models with the first derivative obtained the best performance. Moreover, with a comparation between PLS and LS-SVM models, it was found that PLS model based on original spectra was better than LS-SVM model. The correlation coefficients (r) of SSC and pH were 0.9205 and 0.9318, respectively. The root mean square error of prediction (RMSEP) of SSC and pH were 0.4091 and 0.0729, respectively. Test results showed that it is feasible to detect the SSC and pH of a variety of pears using visible-near infrared spectra technology simultaneously.

It is very important to extract effective wavelengths for quantitative analysis of fruit internal quality based on hyperspectral imaging. In the present study, genetic algorithm (GA), successive projections algorithm (SPA) and GA-SPA combining algorithm were used for extracting effective wavelengths from 400-1 000 nm hyperspectral images of Yantai "Fuji" apples, respectively. Based on the effective wavelengths selected by GA, SPA and GA-SPA, different models were built and compared for predicting soluble solids content (SSC) of apple using partial least squares (PLS), least squared support vector machine (LS-SVM) and multiple linear regression (MLR), respectively. A total of 160 samples were prepared for the calibration (n = 120) and prediction (n = 40) sets. Among all the models, the SPA-MLR achieved the best results, where Rp(2), RMSEP and RPD were 0.950 1, 0.308 7 and 4.476 6 respectively. Results showed that SPA can be effectively used for selecting the effective wavelengths from hyperspectral data. And, SPA-MLR is an optimal modeling method for prediction of apple SSC. Furthermore, less effective wavelengths and simple and easily-interpreted MLR model show that the SPA-MLR model has a great potential for online detection of apple SSC and development of a portable instrument.

To effectively extract defective areas in fruits, the uneven intensity distribution that was produced by the lighting system or by part of the vision system in the image must be corrected. A methodology was used to convert non-uniform intensity distribution on spherical objects into a uniform intensity distribution. A basically plane image with the defective area having a lower gray level than this plane was obtained by using proposed algorithms. Then, the defective areas can be easily extracted by a global threshold value. The experimental results with a 94.0% classification rate based on 100 apple images showed that the proposed algorithm was simple and effective. This proposed method can be applied to other spherical fruits.

Hydrogen (H(2)) acts as a therapeutic antioxidant. However, there are few reports on H(2) function in other capacities in diabetes mellitus (DM). Therefore, in this study, we investigated the role of H(2) in glucose transport by studying cultured mouse C2C12 cells and human hepatoma Hep-G2 cells in vitro, in addition to three types of diabetic mice [Streptozotocin (STZ)-induced type 1 diabetic mice, high-fat diet-induced type 2 diabetic mice, and genetically diabetic db/db mice] in vivo. The results show that H(2) promoted 2-[(14)C]-deoxy-d-glucose (2-DG) uptake into C2C12 cells via the translocation of glucose transporter Glut4 through activation of phosphatidylinositol-3-OH kinase (PI3K), protein kinase C (PKC), and AMP-activated protein kinase (AMPK), although it did not stimulate the translocation of Glut2 in Hep G2 cells. H(2) significantly increased skeletal muscle membrane Glut4 expression and markedly improved glycemic control in STZ-induced type 1 diabetic mice after chronic intraperitoneal (i.p.) and oral (p.o.) administration. However, long-term p.o. administration of H(2) had least effect on the obese and non-insulin-dependent type 2 diabetes mouse models. Our study demonstrates that H(2) exerts metabolic effects similar to those of insulin and may be a novel therapeutic alternative to insulin in type 1 diabetes mellitus that can be administered orally.

Rottenness is most prevalent and devastating disease that threats citrus fruit. Automatic detection of early rottenness can enhance the competitiveness and profitability of the citrus industry. However, there is no efficient automatic detection technology at this time that could detect this disease. The navel orange was selected as research objective. Hyperspectral fluorescence imaging was used to detect early rottenness in orange. Optimum index factor (OIF) method was applied to identify the optimal band combination. 100% detection rate was achieved based on the optimal bands ratio image and two threshold values. The research showed that the proposed method can effectively overcome the affect from florescence effect because stem damage area and stem also can produce florescence under ultraviolet light. This study will lay a foundation for developing multispectral detection system used in on-line detection of early rottenness fruit.

Both AM1 semi-empirical quantum chemistry method and HF/3-21g* ab initio method were employed to get related parameters or descriptors, particularly, the parameters of the solvation energy delta G with polarizable continuum model, for 42 anti-HIV 5-phenyl-1-phenylamino-1H-imidazole derivatives with known cytotoxicity. With parameters of quantum chemical calculation and traditional ones, 2 multiple linear regression models were obtained. The better regression equation has a high correlation coefficient (r = 0.938) and a low standard deviation (s = 0.125) and the squared correlation coefficient Q2 of the cross-validation is 0.799 (literaure: 0.740) by leave-one-out method. The results have certain significance for the design of new anti-HIV-1 drugs with lower cytotoxicity.