Time course of changes in the transcriptome during russet induction in apple fruit.

BACKGROUND: Russeting is a major problem in many fruit crops. Russeting is caused by environmental factors such as wounding or moisture exposure of the fruit surface. Despite extensive research, the molecular sequence that triggers russet initiation remains unclear. Here, we present high-resolution transcriptomic data by controlled russet induction at very early stages of fruit development. During Phase I, a patch of the fruit surface is exposed to surface moisture. For Phase II, moisture exposure is terminated, and the formerly exposed surface remains dry. We targeted differentially expressed transcripts as soon as 24 h after russet induction. RESULTS: During moisture exposure (Phase I) of 'Pinova' apple, transcripts associated with the cell cycle, cell wall, and cuticle synthesis (SHN3) decrease, while those related to abiotic stress increase. NAC35 and MYB17 were the earliest induced genes during Phase I. They are therefore linked to the initial processes of cuticle microcracking. After moisture removal (Phase II), the expression of genes related to meristematic activity increased (WOX4 within 24 h, MYB84 within 48 h). Genes related to lignin synthesis (MYB52) and suberin synthesis (MYB93, WRKY56) were upregulated within 3 d after moisture removal. WOX4 and AP2B3 are the earliest differentially expressed genes induced in Phase II. They are therefore linked to early events in periderm formation. The expression profiles were consistent between two different seasons and mirrored differences in russet susceptibility in a comparison of cultivars. Furthermore, expression profiles during Phase II of moisture induction were largely identical to those following wounding. CONCLUSIONS: The combination of a unique controlled russet induction technique with high-resolution transcriptomic data allowed for the very first time to analyse the formation of cuticular microcracks and periderm in apple fruit immediately after the onset of triggering factors. This data provides valuable insights into the spatial-temporal dynamics of russeting, including the synthesis of cuticles, dedifferentiation of cells, and impregnation of cell walls with suberin and lignin.

Point-of-Care Ultrasonography Helped to Rapidly Detect Pneumomediastinum in a Vomiting Female.

Vomiting-induced pneumomediastinum is a rare presentation and can be a result of alveolar rupture (Mackler effect) or Boerhaave syndrome. Patients diagnosed with Boerhaave syndrome may present with the classic Mackler triad of vomiting, chest pain, and subcutaneous emphysema. However, there exists a large overlap of symptoms accompanying Boerhaave syndrome and the Macklin effect, including retrosternal chest pain, neck discomfort, cough, sore throat, dysphagia, dysphonia, and dyspnea. Boerhaave syndrome is a dangerous condition. Delayed diagnosis of Boerhaave syndrome may worsen sepsis and cause mortality. Therefore, early diagnosis and timely management are important to prevent further complications. Here, we present a case of vomiting-induced pneumomediastinum, which supports the use of bedside ultrasonography to aid in the diagnosis and rapid differentiation of etiology of pneumomediastinum.

Deciphering Molecular Mechanism Underlying Self-Flocculation of Zymomonas mobilis for Robust Production.

Zymomonas mobilis metabolizes sugar anaerobically through the Entner-Doudoroff pathway with less ATP generated for lower biomass accumulation to direct more sugar for product formation with improved yield, making it a suitable host to be engineered as microbial cell factories for producing bulk commodities with major costs from feedstock consumption. Self-flocculation of the bacterial cells presents many advantages, such as enhanced tolerance to environmental stresses, a prerequisite for achieving high product titers by using concentrated substrates. ZM401, a self-flocculating mutant developed from ZM4, the unicellular model strain of Z. mobilis, was employed in this work to explore the molecular mechanism underlying this self-flocculating phenotype. Comparative studies between ZM401 and ZM4 indicate that a frameshift caused by a single nucleotide deletion in the poly-T tract of ZMO1082 fused the putative gene with the open reading frame of ZMO1083, encoding the catalytic subunit BcsA of the bacterial cellulose synthase to catalyze cellulose biosynthesis. Furthermore, the single nucleotide polymorphism mutation in the open reading frame of ZMO1055, encoding a bifunctional GGDEF-EAL protein with apparent diguanylate cyclase/phosphodiesterase activities, resulted in the Ala526Val substitution, which consequently compromised in vivo specific phosphodiesterase activity for the degradation of cyclic diguanylic acid, leading to intracellular accumulation of the signaling molecule to activate cellulose biosynthesis. These discoveries are significant for engineering other unicellular strains from Z. mobilis with the self-flocculating phenotype for robust production. IMPORTANCE Stress tolerance is a prerequisite for microbial cell factories to be robust in production, particularly for biorefinery of lignocellulosic biomass to produce biofuels, bioenergy, and bio-based chemicals for sustainable socioeconomic development, since various inhibitors are released during the pretreatment to destroy the recalcitrant lignin-carbohydrate complex for sugar production through enzymatic hydrolysis of the cellulose component, and their detoxification is too costly for producing bulk commodities. Although tolerance to individual stress has been intensively studied, the progress seems less significant since microbial cells are inevitably suffering from multiple stresses simultaneously under production conditions. When self-flocculating, microbial cells are more tolerant to multiple stresses through the general stress response due to enhanced quorum sensing associated with the morphological change for physiological and metabolic advantages. Therefore, elucidation of the molecular mechanism underlying such a self-flocculating phenotype is significant for engineering microbial cells with the unique multicellular morphology through rational design to boost their production performance.

[The Change Detection of High Spatial Resolution Remotely Sensed Imagery Based on OB-HMAD Algorithm and Spectral Features].

The high spatial resolution remotely sensed imagery has abundant detailed information of earth surface, and the multi-temporal change detection for the high resolution remotely sensed imagery can realize the variations of geographical unit. In terms of the high spatial resolution remotely sensed imagery, the traditional remote sensing change detection algorithms have obvious defects. In this paper, learning from the object-based image analysis idea, we proposed a semi-automatic threshold selection algorithm named OB-HMAD (object-based-hybrid-MAD), on the basis of object-based image analysis and multivariate alternative detection algorithm (MAD), which used the spectral features of remotely sensed imagery into the field of object-based change detection. Additionally, OB-HMAD algorithm has been compared with other the threshold segmentation algorithms by the change detection experiment. Firstly, we obtained the image object by the multi-solution segmentation algorithm. Secondly, we got the object-based difference image object using MAD and minimum noise fraction rotation (MNF) for improving the SNR of the image object. Then, the change objects or area are classified using histogram curvature analysis (HCA) method for the semi-automatic threshold selection, which determined the threshold by calculated the maximum value of curvature of the histogram, so the HCA algorithm has better automation than other threshold segmentation algorithms. Finally, the change detection results are validated using confusion matrix with the field sample data. Worldview-2 imagery of 2012 and 2013 in case study of Beijing were used to validate the proposed OB-HMAD algorithm. The experiment results indicated that OB-HMAD algorithm which integrated the multi-channel spectral information could be effectively used in multi-temporal high resolution remotely sensed imagery change detection, and it has basically solved the "salt and pepper" problem which always exists in the pixel-based change detection, and has mitigated the impact of building shadows and geometric registration error, and has improved the overall accuracy and kappa coefficient than other change detection algorithm, but it has more undetected error. By compared with the SNR of image object, we know that the MNF transformation could effectively improve to concentrate the change information.

[Spectral characteristics and identification research of soybean under different disease stressed].

The objective of this paper is to identify disease and its severity of soybean by using single leaf spectral data in the field. The soybean spectral were measured in the Sutton Bonington Campus of University of Nottingham (52.8 degrees N, 1.2 degrees W), which infected rust disease (RD) and common mosaic disease (CMD), respectively, and continuum removal method was used to process the original spectral data, and sensitive bands were selected for disease and disease severity, and vegetation index was designed for identifying RD and CMD of soybean. The result showed spectral reflectance of soybean under CMD stressed is more than that of health in the visible region. However, spectral reflectance of soybean under RD stressed will decrease in the green region and that will increase in the red region with disease severity increasing. According to the spectral changing features, a new index R500 x R550/R680 was designed for identifying the disease of soybean. In order to test the index identifying disease ability, the J-M distances were calculated among health, RD and CMD. The result indicated index R500 x R550/R680 can better identify RD and CMD, at the same time, the index has good ability for discriminating the disease severity of soybean. The research results of this paper has important theoretical value for crops disease monitoring and prevention and practical application meanings.

[Research on the spectral feature and identification of the surface vegetation stressed by stored CO2 underground leakage].

With the global climate warming, reducing greenhouse gas emissions becomes a focused problem for the world. The carbon capture and storage (CCS) techniques could mitigate CO2 into atmosphere, but there is a risk in case that the CO2 leaks from underground. The objective of this paper is to study the chlorophyll contents (SPAD value), relative water contents (RWC) and leaf spectra changing features of beetroot under CO2 leakage stress through field experiment. The result shows that the chlorophyll contents and RWC of beetroot under CO2 leakage stress become lower than the control beetroot', and the leaf reflectance increases in the 550 nm region and decreases in the 680nm region. A new vegetation index (R550/R680) was designed for identifying beetroot under CO2 leakage stress, and the result indicates that the vegetation index R550/R680 could identify the beetroots after CO2 leakage for 7 days. The index has strong sensitivity, stability and identification for monitoring the beetroots under CO2 stress. The result of this paper has very important meaning and application values for selecting spots of CCS project, monitoring and evaluating land-surface ecology under CO2 stress and monitoring the leakage spots by using remote sensing.

Rapid Identification of Patients Eligible for Direct Emergent Computed Tomography Angiography during Acute Ischemic Stroke: The DARE-PACE Assessment.

BACKGROUND: We investigated the clinical signs to establish a method for rapid identification of patients with the National Institute of Health Stroke Scale (NIHSS) score ≥ 8 eligible for direct brain CTA study; Methods: We retrospectively enrolled 2895 in patients with acute ischemic stroke (AIS). Four items in the NIHSS were selected as the main clinical signs of stroke; Results: A total of 922 (31.8%) patients had an initial NIHSS score of ≥8. The average door-to-CT time and door-to-CTA time were 13.4 ± 1.8 and 75.5 ± 44.5 min, respectively. Among 658 patients who had the priority signs, namely dense hemiplegia (D), aphasia with right arm drop (AR), and eyeball forced deviation (E), 634 patients (96.4%) with an NIHSS score ≥ 8 were identified. By using a classification and regression tree analysis, 153 patients with an NIHSS ≥ 8 were identified among 175 patients (87.4%) who had the secondary signs, namely hemiparesis with limb falls (P), aphasia (A), drowsy or worse consciousness (C), and eyeball limitation (E). The sensitivity, specificity, and accuracy were 85.4%, 97.7%, and 95.3%, respectively. CONCLUSIONS: The DARE-PACE assessment involving a checkbox list provides excellent accuracy for rapid identification of AIS patients with an NIHSS score ≥ 8 for direct CTA study to reduce the time delay for endovascular thrombectomy.

Apple fruit periderms (russeting) induced by wounding or by moisture have the same histologies, chemistries and gene expressions.

Russeting is a cosmetic defect of some fruit skins. Russeting (botanically: induction of periderm formation) can result from various environmental factors including wounding and surface moisture. The objective was to compare periderms resulting from wounding with those from exposure to moisture in developing apple fruit. Wounding or moisture exposure both resulted in cuticular microcracking. Cross-sections revealed suberized hypodermal cell walls by 4 d, and the start of periderm formation by 8 d after wounding or moisture treatment. The expression of selected target genes was similar in wound and moisture induced periderms. Transcription factors involved in the regulation of suberin (MYB93) and lignin (MYB42) synthesis, genes involved in the synthesis (CYP86B1) and the transport (ABCG20) of suberin monomers and two uncharacterized transcription factors (NAC038 and NAC058) were all upregulated in induced periderm samples. Genes involved in cutin (GPAT6, SHN3) and wax synthesis (KCS10, WSD1, CER6) and transport of cutin monomers and wax components (ABCG11) were all downregulated. Levels of typical suberin monomers (ω-hydroxy-C20, -C22 and -C24 acids) and total suberin were high in the periderms, but low in the cuticle. Periderms were induced only when wounding occurred during early fruit development (32 and 66 days after full bloom (DAFB)) but not later (93 DAFB). Wound and moisture induced periderms are very similar morphologically, histologically, compositionally and molecularly.

[Comparison among remotely sensed image fusion methods based on spectral response function].

Remotely sensed image fusion is a critical issue, and many methods have been developed to inject features from a high spatial resolution panchromatic sensor into low spatial resolution multi-spectral images, trying to preserve spectral signatures while improving spatial resolution of multi-spectral images. However, no explicit physical information of the detection system has been taken into account in usual methods, which might lead to undesirable effects such as severe spectral distortion. Benefiting from the proper decomposition of the image fusion problem by a concise image fusion mathematical model, the present paper focuses on comparing reasonable modulation coefficient of spatial details based on analysis of the spectral response function (SRF). According to the classification of former methods, three modulation coefficients based on SRF of sensors were concluded, which lead to three image fusion methods incorporating spatial detail retrieved by Gaussian high-pass filter. All these methods were validated on Ikonos data compared to GS and HPM method.

[Using canopy hyperspectral ratio index to retrieve relative water content of wheat under yellow rust stress].

The aim of this paper is to estimate canopy relative water contents (RWC) of winter wheat under yellow rust stress by using hyperspectral remote sensing. The canopy reflectance of winter wheat that infected different severity yellow rust was collected and the disease index (DI) of the wheat was investigated respectively in the fields, whereafter the wheat was sampled corresponding to the canopy reflectance measurements and the RWC of the whole wheat were measured in the Laboratory. The research showed that the canopy spectra reflectance gradually decreased in the near-infrared (NIR) region (900-1,300 nm) with RWC reduction, however, canopy spectra reflectance gradually increased in the short-wave-infrared (SWIR) region (1,300-2,500 nm), and there was just higher minus correlation between RWC and DI. Smoothing the canopy spectra, the ratio indices were built by using the sensitive bands for water in NIR and SWIR, and then the estimation RWC linear models were built by using ratio indices as variables, and the model inversion precision and stability were analyzed and compared for estimation RWC. The result indicated that the inversion precision and the stability of the model with ratio index R1,300/R1,200 as variable excel other models, the linear model's RMSE is 3.43, and the relative error is 4.78%. So, this study results not only can provide assistant information for diagnosing wheat disease but also can supply theories and methods for inversion vegetation RWC by using hyperspectral images in the future.

[Using the distance between hyperspectral red edge position and yellow edge position to identify wheat yellow rust disease].

The objective of the present paper is to identify healthy wheat and disease wheat by using hyeprspectral remote sensing as soon as possible. The canopy spectral reflectance of winter wheat infected by different severity yellow rust was measured and the disease indices (DI) were investigated in the field respectively. Smoothing the canopy spectra and calculating the first derivative values, the two methods were used to calculate the red edge position (REP) and yellow edge position (YEP) of the first derivative values: (a) maximum of the first derivative value; (b) Cho and Skidmore method. The result showed that REP gradually shifted to short-wave band, and the YEP gradually shifted to long-wave band with disease severity increasing, however, REP-YEP quickly became smaller. Analyzing and comparing the prediction precision of REP, YEP and REP-YEP for DI, the result indicated that the model REP-YEP as variable has the best estimation precision for DI than REP and YEP, the model estimation error is 6.22, and relative error is 14.3%, and it could identify healthy and disease wheat 12 days before the disease symptom apparently appeared. Therefore, this study not only can provide theory and technology for large areas monitoring of wheat disease by using hyperspectral remote sensing in the future, but also has the important meaning and practical application value for implementing precision agriculture.

[Using hyperspectral remote sensing to estimate canopy chlorophyll density of wheat under yellow rust stress].

The canopy reflectance of winter wheat infected with different severity yellow rust was collected in the fields and canopy chlorophyll density (CCD) of the whole wheat was measured in the laboratory. The correlation was analyzed between hyperspectral indices and CCDs, the indices with relationship coefficients more than 0. 7 were selected to build the inversion models, and comparing the predicted results and measured results to test the models, the results showed the first derivative index (D750-D550)/(D750+D550) has higher prediction precision than other indices, while the next is first derivative index (D725-D702)/(D725+D702). Saturation analysis was performed for the above indices, the result indicated that when CCD was more than 12 microg x cm(-2), the first derivative index (D750-D550)/(D750+D550) was easiest to get to saturation level. Therefore, when CCD was less than 12 microg x cm(-2), the first derivative index (D750-D550)/(D750+D550) could be used to estimate wheat CCD and had higher prediction precision than other indices; and when CCD was more than 12 microg x cm(-2), the first derivative index (D725-D702)/(D725+D702) was not easiest to reach saturation level and could be used to estimate wheat CCD. There is a significant minus cor relation between CCD and disease index (DI), moreover, accurate estimation of CCD by using hyperspectral remote sensing not only can monitor wheat growth, but also can provide assistant information for identification of wheat disease. Therefore, this study has important meaning for prevention and reduction of disaster in agricultural field.

Russeting in Apple Is Initiated After Exposure to Moisture Ends-I. Histological Evidence.

Russeting (periderm formation) is a critical fruit-surface disorder in apple (Malus × domestica Borkh.). The first symptom of insipient russeting is cuticular microcracking. Humid and rainy weather increases russeting. The aim was to determine the ontogeny of moisture-induced russeting in 'Pinova' apple. We recorded the effects of duration of exposure to water and the stage of fruit development at exposure on microcracking, periderm formation and cuticle deposition. Early on (21 or 31 days after full bloom; DAFB) short periods (2 to 12 d) of moisture exposure induced cuticular microcracking-but not later on (66 or 93 DAFB). A periderm was not formed during moisture exposure but 4 d after exposure ended. A periderm was formed in the hypodermis beneath a microcrack. Russeting frequency and severity were low for up to 4 d of moisture exposure but increased after 6 d. Cuticle thickness was not affected by moisture for up to 8 d but decreased for longer exposures. Cuticular ridge thickness decreased around a microcrack. In general, moisture did not affect cuticular strain release. We conclude that a hypodermal periderm forms after termination of moisture exposure and after microcrack formation. Reduced cuticle deposition may cause moisture-induced microcracking and, thus, russeting.

Russeting in Apple is Initiated after Exposure to Moisture Ends: Molecular and Biochemical Evidence.

Exposure of the fruit surface to moisture during early development is causal in russeting of apple (Malus × domestica Borkh.). Moisture exposure results in formation of microcracks and decreased cuticle thickness. Periderm differentiation begins in the hypodermis, but only after discontinuation of moisture exposure. Expressions of selected genes involved in cutin, wax and suberin synthesis were quantified, as were the wax, cutin and suberin compositions. Experiments were conducted in two phases. In Phase I (31 days after full bloom) the fruit surface was exposed to moisture for 6 or 12 d. Phase II was after moisture exposure had been discontinued. Unexposed areas on the same fruit served as unexposed controls. During Phase I, cutin and wax synthesis genes were down-regulated only in the moisture-exposed patches. During Phase II, suberin synthesis genes were up-regulated only in the moisture-exposed patches. The expressions of cutin and wax genes in the moisture-exposed patches increased slightly during Phase II, but the levels of expression were much lower than in the control patches. Amounts and compositions of cutin, wax and suberin were consistent with the gene expressions. Thus, moisture-induced russet is a two-step process: moisture exposure reduces cutin and wax synthesis, moisture removal triggers suberin synthesis.

Cancer-Testis Gene Expression in Hepatocellular Carcinoma: Identification of Prognostic Markers and Potential Targets for Immunotherapy.

BACKGROUND: Cancer-testis genes can serve as prognostic biomarkers and valuable targets for immunotherapy in multiple tumors because of their restricted expression in testis and cancer. However, their expression pattern in hepatocellular carcinoma is still not well understood. The purpose is to comprehensively characterize the cancer-testis gene expression in hepatocellular carcinoma as well as identify prognostic markers and potential targets for immunotherapy. METHODS: Cancer-testis database and publicly available data sets reporting new cancer-testis genes were integrated, and then restricted them in a testis and hepatocellular carcinoma expression pattern. Pathway enrichment analysis and survival analysis were conducted to evaluate the biological function and prognostic effect of cancer-testis genes. Clustering analysis and coexpression analysis were performed to illustrate cancer-testis gene expression patterns in hepatocellular carcinoma. The association of gene expression of each cancer-testis gene to the corresponding methylation status was detected. Finally, we explored the associations between cancer-testis genes and CD8+ T-cell infiltration in hepatocellular carcinoma by TISIDB, and then validated it in an independent hepatocellular carcinoma cohort with 72 patients. RESULTS: A total of 59 testis-specific genes were identified highly expressed in hepatocellular carcinoma. Pathway enrichment analysis revealed that cancer-testis genes in hepatocellular carcinoma significantly involves in the process of cell cycle regulation. Most of the cancer-testis genes were coexpressed, and cluster analysis suggested that cancer-testis gene expressed in hepatocellular carcinoma is independent of sex, hepatitis status, and histology type. We also found that demethylation might be a regulatory mechanism of cancer-testis gene expression in hepatocellular carcinoma. Survival analysis indicated that cancer-testis genes could predict the prognosis of patients with hepatocellular carcinoma. Furthermore, BUB1B was identified contributing to the resistance of CD8+ T-cell infiltration in hepatocellular carcinoma and was an independent prognostic factor both for overall survival and disease-free survival. CONCLUSIONS: Our analysis enables better understanding of cancer-testis genes in hepatocellular carcinoma and provides potential targets for hepatocellular carcinoma treatment. Experimental and clinical studies are needed for further validations.

[Improving hyperspectral matching method through feature-selection/weighting based on SVM].

In the present article, feature selection/weighting based on SVM was employed to improve the algorithm of choosing reference spectrum through a multi-objective optimization approach proposed in reference. Based on the sensitive analysis, half of features having low weights in SVM classification model were eliminated iteratively. Two criteria, matching accuracy and classification confidence, were used to select the best-performing feature subset. Three scenarios were designed: (1) only feature subset selected by SVM was used; (2) both feature subset and global weights were used, in which global weights were the coefficients of selected features in the SVM classification model; (3) both feature subset and local weights, which changed with the distance of a sample point to the SVM separation plan, were used. Experiment executed on the popular Indiana AVIRIS data set indicate that under all the three scenarios, spectral matching accuracies were increased by 13%-17% compared to the situation without feature selection. The result obtained under scenario 3 is the most accurate and the most stable, which can be primarily attributed to the ability of local weights to accurately describe local distribution of spectra from the same class in feature space. Moreover, scenario 3 can be regarded as the extension of scenario 2 because when spectra far away from the separation plane are selected as reference spectrums for matching, the features' weights will not be considered. The results obtained under scenario 1 and 2 are very similar, indicating that considering global weights is not necessary. The research presented in this paper advanced the spectrum analysis using SVM to a higher level.

[Comparison of principal component analysis with VI-empirical approach for estimating severity of yellow rust of winter wheat].

The canopy reflectance of winter wheat infected by yellow rust with different severity was measured through artificial inoculation, and the disease index (DI) of the wheat corresponding to the spectra acquired in the field was obtained. Principal component analysis (PCA) was used to compute the first 5 principal components (PCs) of canopy spectra in the 350-1 350 nm range and the first 3 PCs of first-order derivative in blue edge (490-530 nm), yellow edge (550-582 nm) and red edge (630-673 nm), respectively. Step-wise regression was used to build models, the results of those models are compared with that of VI-empirical models, and the result shows that the model based on PCs of first-order derivative is particularly accurate compared to others, with the RMSE of 7.65 and relative error of 15.59%. Comparison was made between the estimated DI and the measured DI, indicating that the model based on SDr'/SDg' is suitable to monitoring early disease and the model based on PCs of first-order derivative is suitable to monitoring the more severe disease of yellow rust of winter wheat. The conclusion has great practical and application value to acquiring and evaluating wheat disease severity using hyperspectral remote sensing, and has an important meaning for increasing yields of crops and ensuring security of food supplies.

Efficacy of cytokine-induced killer cell-based immunotherapy for hepatocellular carcinoma.

In attempts to delay tumor progression after surgery or minimally invasive local treatments, multidisciplinary strategies have been broadly studied in patients with hepatocellular carcinoma (HCC). The objective of this present study was to evaluate the efficacy of autologous transplantations of cytokine-induced killer (CIK) cells as an adjuvant therapy for patients with HCC. A total of 264 patients with HCC were enrolled in this retrospective study. Of these patients, 165 received either CIK cell therapy alone or as adjuvant therapy to surgery, transcatheter arterial chemoembolization (TACE), or TACE-based comprehensive treatments (CT). The remaining 99 patients received only surgery or TACE. Kaplan-Meier analysis and the Chi-squared test were used to analyze the overall survival (OS), progression-free survival (PFS), and clinical characteristics of the patients in the different treatment subgroups. Kaplan-Meier analysis suggested that patients in the Surgery+CIK group had a significantly improved OS compared with those in the other three groups (P < 0.001). Furthermore, patients who developed a fever after the CIK cell treatments manifested a likely better OS (P = 0.028). Subgroup analysis indicated that patients in the Surgery+CIK group likely had an improved PFS but a similar OS compared with the patients in the Surgery-alone group (P = 0.055 for PFS, and P = 0.746 for OS). Further subgroup analysis showed that the OS in both the TACE+CIK and CT+CIK groups was prolonged significantly compared with that in the TACE-alone group (P = 0.015 and P = 0.018, respectively). However, similar OS was observed between the TACE+CIK and CT+CIK groups (P = 0.686). Autologous transplantation of CIK cells as an adjuvant therapy was associated with better survival for patients with HCC, especially for those who had also undergone TACE. A fever reaction might be a potential event for assessing the curative effect of the CIK treatment.

[Study on hyperspectra estimation of pigment contents in canopy leaves of winter wheat under disease stress].

The canopy reflectance of winter wheat infected with stripe rust was measured in the field through artificial inoculation, and the pigment contents of the wheat leaves were determined indoor. The correlation between pigment contents and canopy hyperspectra data and the first derivative data of the disease wheat were analyzed respectively. Using linear and non-linear regression methods, and choosing a part of samples, the estimation models about pigment contents of disease wheat were built. Through the test of the other part samples, the result shows that the model containing the normalized value of the sum of first derivative within green edge (SD(g)) and the sum of first derivative within red edge (SD(r)) is the best one. The model was used to estimate the contents of chlorophyll a and chlorophyll b and carotenoid of the disease wheat, and the relative errors were 17.0%, 16.3% and 12.4%, respectively. This study shows that canopy hyperspectra data can be used to estimate the pigment contents of crops leaves and the estimation precision is high. This conclusion has great practice and application value to monitor the grow-ing way of and disease influence on crops by using hyperspectral remote sensing.