Mechanistic examination of causes for narrow distribution in an endangered shrub: a comparison of its responses to drought stress with a widespread congeneric species

Although deep rooting is usually considered a drought-tolerant trait, we found that Syringapinnatifolia, a deep rooting and hydrotropic shrub, has a limited distribution in arid areas. To elucidate the mechanisms for its narrow distribution, we conducted two experiments to examine the physiological and morphological responses to water availability and heterogeneity in S. pinnatifolia and a widespread congeneric species, S. oblata. We measured gas exchange, water use efficiency, and plasticity index in plants of these two species grown at different levels of soil water regimes and in containers with patched water distribution. Our results showed that high photosynthetic capacity in the narrowly distributed S. pinnatifolia was an important factor enabling its survival in the harsh sub-alpine environment. High photosynthetic capacity in S. pinnatifolia, however, was obtained at the expense of high transpiratory water loss, resulting in lower integrative water use efficiency. Biomass allocation to roots in S. pinnatifolia increased by 73 % when soil water increased from 75 to 95 % field capacity, suggesting that S. pinnatifolia could be less competitive for above-ground resources under favorable water regimes. The horizontal root hydrotropism and vertical root hydrotropism of S. pinnatifolia in soil with patched water patterns were likely related to compensation for leaf water loss at low soil water level, indicating a limited capacity for homeostasis within the plant for water conservation and lower level of inherent drought-tolerance. In summary, greater degree of morphological plasticity but lower degree of physiological adjustment may be the main causes for the hydrotropism and narrow distribution of S. pinnatifolia in the sub-alpine habitats

Genetically modified adenoviral vector with the protein transduction domain of Tat improves gene transfer to CAR-deficient cells

The transduction efficiency of Ad (adenovirus) depends, to some extent, on the expression level of CAR (coxsackievirus and Ad receptor) of a target cell. The low level of CAR on the cell surface is a potential barrier to efficient gene transfer. To overcome this problem, PTD.AdeGFP (where eGFP is enhanced green fluorescent protein) was constructed by modifying the HI loop of Ad5 (Ad type 5) fibre with the Tat (trans-activating) PTD (protein transduction domain) derived from HIV. The present study showed that PTD.AdeGFP significantly improved gene transfer to multiple cell types deficient in expression of CAR. The improvement in gene transfer was not the result of charge-directed binding between the virus and the cell surface. Although PTD.AdeGFP formed aggregates, it infected target cells in a manner different from AdeGFP aggregates precipitated by calcium phosphate. In addition, PTD.AdeGFP was able to transduce target cells in a dynamin-independent pathway. The results provide some new clues as to how PTD.AdeGFP infects target cells. This new vector would be valuable in gene-function analysis and for gene therapy in cancer

FSCN1 Promotes Epithelial-Mesenchymal Transition Through Increasing Snail1 in Ovarian Cancer Cells

Background/Aims: Epithelial-mesenchymal transition (EMT) is one of the key mechanisms mediating cancer progression. Snail1 has a pivotal role in the regulation of EMT, involving the loss of E-cadherin and concomitant upregulation of vimentin, among other biomarkers. We have found FSCN1 promoted EMT in ovarian cancer cells, but the precise mechanism of FSCN1 in EMT process has not been clearly elucidated. Methods: The levels of FSCN1 and snail1 were determined in epithelial ovarian cancer(EOC) specimen and in ovarian cancer cells by RT-qPCR. The changes of EMT makers and effects on snail1 by FSCN1 were examined by overexpression or depletion of FSCN1 in EOC cells by RT-qPCR and western blotting. The invasiveness of the FSCN1-modified EOC cells was examined in transwell assay. Co-immunoprecipitation (IP) was performed to detect the interaction between snail1 and FSCN1 in EOC cells. Results: We found FSCN1 and snail1 significantly increased in EOC, and especially in EOC with metastasis. FSCN1 was positively correlated with snail1 expression at the cellular/histological levels. Moreover, we further showed that FSCN1 physiologically interacted with and increased the levels of snail1 to promote ovarian cancer cell EMT. Conclusion: FSCN1 promote EMT through snail1 in ovarian cancer cells. FSCN1 is an attractive novel target for inhibiting invasion and metastasis of EOC cells

A Two-stage Method with a Shared 3D U-Net for Left Atrial Segmentation of Late Gadolinium-Enhanced MRI Images

Objective: This study was aimed at validating the accuracy of a proposed algorithm for fully automatic 3D left atrial segmentation and to compare its performance with existing deep learning algorithms. Methods: A two-stage method with a shared 3D U-Net was proposed to segment the 3D left atrium. In this architecture, the 3D U-Net was used to extract 3D features, a two-stage strategy was used to decrease segmentation error caused by the class imbalance problem, and the shared network was designed to decrease model complexity. Model performance was evaluated with the DICE score, Jaccard index and Hausdorff distance. Results: Algorithm development and evaluation were performed with a set of 100 late gadolinium-enhanced cardiovascular magnetic resonance images. Our method achieved a DICE score of 0.918, a Jaccard index of 0.848 and a Hausdorff distance of 1.211, thus, outperforming existing deep learning algorithms. The best performance of the proposed model (DICE: 0.851; Jaccard: 0.750; Hausdorff distance: 4.382) was also achieved on a publicly available 2013 image data set. Conclusion: The proposed two-stage method with a shared 3D U-Net is an efficient algorithm for fully automatic 3D left atrial segmentation. This study provides a solution for processing large datasets in resource-constrained applications. Significance Statement: Studying atrial structure directly is crucial for comprehending and managing atrial fibrillation (AF). Accurate reconstruction and measurement of atrial geometry for clinical purposes remains challenging, despite potential improvements in the visibility of AF-associated structures with late gadolinium-enhanced magnetic resonance imaging. This difficulty arises from the varying intensities caused by increased tissue enhancement and artifacts, as well as variability in image quality. Therefore, an efficient algorithm for fully automatic 3D left atrial segmentation is proposed in the present study

Relationship between the Composition of Flavonoids and Flower Colors Variation in Tropical Water Lily (Nymphaea) Cultivars

Water lily, the member of the Nymphaeaceae family, is the symbol of Buddhism and Brahmanism in India. Despite its limited researches on flower color variations and formation mechanism, water lily has background of blue flowers and displays an exceptionally wide diversity of flower colors from purple, red, blue to yellow, in nature. In this study, 34 flavonoids were identified among 35 tropical cultivars by high-performance liquid chromatography (HPLC) with photodiode array detection (DAD) and electrospray ionization mass spectrometry (ESI-MS). Among them, four anthocyanins: delphinidin 3-O-rhamnosyl-5-O-galactoside (Dp3Rh5Ga), delphinidin 3-O-(2″-O-galloyl-6″-O-oxalyl-rhamnoside) (Dp3galloyl-oxalylRh), delphinidin 3-O-(6″-O-acetyl-β-glucopyranoside) (Dp3acetylG) and cyanidin 3- O-(2″-O-galloyl-galactopyranoside)-5-O-rhamnoside (Cy3galloylGa5Rh), one chalcone: chalcononaringenin 2′-O-galactoside (Chal2′Ga) and twelve flavonols: myricetin 7-O-rhamnosyl-(1→2)-rhamnoside (My7RhRh), quercetin 7-O-galactosyl-(1→2)-rhamnoside (Qu7GaRh), quercetin 7-O-galactoside (Qu7Ga), kaempferol 7-O-galactosyl-(1→2)-rhamnoside (Km7GaRh), myricetin 3-O-galactoside (My3Ga), kaempferol 7-O-galloylgalactosyl-(1→2)-rhamnoside (Km7galloylGaRh), myricetin 3-O-galloylrhamnoside (My3galloylRh), kaempferol 3-O-galactoside (Km3Ga), isorhamnetin 7-O-galactoside (Is7Ga), isorhamnetin 7-O-xyloside (Is7Xy), kaempferol 3-O-(3″-acetylrhamnoside) (Km3-3″acetylRh) and quercetin 3-O-acetylgalactoside (Qu3acetylGa) were identified in the petals of tropic water lily for the first time. Meanwhile a multivariate analysis was used to explore the relationship between pigments and flower color. By comparing, the cultivars which were detected delphinidin 3-galactoside (Dp3Ga) presented amaranth, and detected delphinidin 3′-galactoside (Dp3′Ga) presented blue. However, the derivatives of delphinidin and cyanidin were more complicated in red group. No anthocyanins were detected within white and yellow group. At the same time a possible flavonoid biosynthesis pathway of tropical water lily was presumed putatively. These studies will help to elucidate the evolution mechanism on the formation of flower colors and provide theoretical basis for outcross breeding and developing health care products from this plant

Leaching Kinetics of Aluminum from Alkali-Fused Spent Cathode Carbon Using Hydrochloric Acid and Sodium Fluoride

Abundant carbon resides in spent cathode carbon (SCC) of aluminum electrolysis and its high-purity carbon powder is conducive to high-value recycling. The alkali-fused SCC was separated and effectively purified using an HCl/NaF solution. Effects of particle size, leaching temperature, time, initial acid concentration, and sodium fluoride dosage, on the purity of carbon powder and aluminum removal rate, were investigated. Using aluminum as the research object, kinetics of aluminum acid leaching were examined by single-factor experiments. Results showed that under an initial 4 M HCl concentration, particle size D(50) = 67.49 μm, liquid-solid ratio of 15:1, 333 K, 120 min, 0.3 M NaF, carbon powder with ash level below 1% were obtained in subsequent purification of SCC. The leaching process was described by Avram equation, the model characteristic parameter was 0.75147 and the apparent activation energy was 22.056 kJ/mol, which indicated a mixed control mechanism between chemical reactivity and diffusion. The kinetic reaction equation of leaching aluminum from alkali-fused SCC in a mixed HCl/NaF system was established

Decentralized adaptive output-feedback controller design for stochastic nonlinear interconnected systems

In this paper, the controller design for a class of stochastic interconnected systems with both parametric uncertainties and unknown nonlinear interactions is presented. The diffusion terms considered are dependent on the outputs of local subsystems and allowed to be unbounded. First, by employing decentralized state observers, totally decentralized adaptive tracking controllers with suitable parameter adaptive laws are designed to ensure the boundedness in probability of all the signals in the closed-loop system. It is shown that the tracking errors converge to small residual sets around the origin. Then, for systems with relaxed diffusion vector fields, a decentralized adaptive stabilizing scheme is proposed to ensure the boundedness in probability of all signals in the closed-loop system

Crop Classification Based on GDSSM-CNN Using Multi-Temporal RADARSAT-2 SAR with Limited Labeled Data

Crop classification is an important part of crop management and yield estimation. In recent years, neural networks have made great progress in synthetic aperture radar (SAR) crop classification. However, the insufficient number of labeled samples limits the classification performance of neural networks. In order to solve this problem, a new crop classification method combining geodesic distance spectral similarity measurement and a one-dimensional convolutional neural network (GDSSM-CNN) is proposed in this study. The method consisted of: (1) the geodesic distance spectral similarity method (GDSSM) for obtaining similarity and (2) the one-dimensional convolutional neural network model for crop classification. Thereinto, a large number of training data are extracted by GDSSM and the generalized volume scattering model which is based on radar vegetation index (GRVI), and then classified by 1D-CNN. In order to prove the effectiveness of the GDSSM-CNN method, the GDSSM method and 1D-CNN method are compared in the case of a limited sample. In terms of evaluation and verification of methods, the GDSSM-CNN method has the highest accuracy, with an accuracy rate of 91.2%, which is 19.94% and 23.91% higher than the GDSSM method and the 1D-CNN method, respectively. In general, the GDSSM-CNN method uses a small number of ground measurement samples, and it uses the rich polarity information in multi-temporal fully polarized SAR data to obtain a large number of training samples, which can quickly improve the accuracy of classification in a short time, which has more new inspiration for crop classification

Spatio-Temporal Estimation of Rice Height Using Time Series Sentinel-1 Images

Rice height, as the fundamental biophysical attribute, is a controlling factor in crop phenology estimation and yield estimation. The aim of this study was to use time series Sentinel-1A images to estimate the spatio-temporal distribution of rice height. In this study, a particle filter (PF) was applied for the real-time estimation of rice height compared with a simplified water cloud model (SWCM) on the basis of rice mapping and transplanting date. It was found that the VH backscatter (σvho) can potentially be applied to accurately estimate rice height compared with VV backscatter (σvvo), the σvho/σvv0 ratio, and the Radar Vegetation Index (RVI, 4* σvho/(σvho+σvvo)). The results show that the rice height estimation by PF generated a better result with a root-mean-square error (RMSE) equal to 7.36 cm and a determination factor (R2) of 0.95 compared with SWCM (RMSE = 12.59 cm and R2 = 0.86). Moreover, rice height in the south and east of the study area was higher than in the north and west. The reason for this is that the south and east are near to the South China Sea, and there are higher temperatures and earlier transplanting. Altogether, our results demonstrate the potential of PF and σvho to study the spatio-temporal distribution of crop height estimation. As a result, the PF method can contribute greatly to improvements in crop monitoring

Soil Moisture Inversion Based on Data Augmentation Method Using Multi-Source Remote Sensing Data

Soil moisture is an important land environment characteristic that connects agriculture, ecology, and hydrology. Surface soil moisture (SSM) prediction can be used to plan irrigation, monitor water quality, manage water resources, and estimate agricultural production. Multi-source remote sensing is a crucial tool for assessing SSM in agricultural areas. The field-measured SSM sample data are required in model building and accuracy assessment of SSM inversion using remote sensing data. When the SSM samples are insufficient, the SSM inversion accuracy is severely affected. An SSM inversion method suitable for a small sample size was proposed. The alpha approximation method was employed to expand the measured SSM samples to offer more training data for SSM inversion models. Then, feature parameters were extracted from Sentinel-1 microwave and Sentinel-2 optical remote sensing data, and optimized using three methods, which were Pearson correlation analysis, random forest (RF), and principal component analysis. Then, three common machine learning models suitable for small sample training, which were RF, support vector regression, and genetic algorithm-back propagation neural network, were built to retrieve SSM. Comparison experiments were carried out between various feature optimization methods and machine learning models. The experimental results showed that after sample augmentation, SSM inversion accuracy was enhanced, and the combination of utilizing RF for feature screening and RF for SSM inversion had a higher accuracy, with a coefficient of determination of 0.7256, a root mean square error of 0.0539 cm3/cm3, and a mean absolute error of 0.0422 cm3/cm3, respectively. The proposed method was finally used to invert the regional SSM of the study area. The inversion results indicated that the proposed method had good performance in regional applications with a small sample size