Tf2O-Mediated P(O)-N Bond Formation of Either P(O)-OH or P(O)-H Reagents with Multitype Amines.

We have developed a Tf2O-mediated approach for the direct amination of either P(O)-OH or P(O)-H reagents with a variety of aliphatic or aromatic amines. Without the requirement of precious metals and toxic reagents, this protocol provides an alternative route to various phosphinamides and phosphoramides. The reaction proceeds under simple and mild conditions and can be effectively scaled up with similar efficiency.

Unsymmetrical Benzothieno-Fused BODIPYs as Efficient NIR Heavy-Atom-Free Photosensitizers.

Heavy-atom-free photosensitizers are potentially suitable for use in photodynamic therapy (PDT). In this contribution, a new family of unsymmetrical benzothieno-fused BODIPYs with reactive oxygen efficiency up to 50% in air-saturated toluene was reported. Their efficient intersystem crossing (ISC) resulted in the generation of both 1O2 and O2-• under irradiation. More importantly, the PDT efficacy of a respective 4-methoxystyryl-modified benzothieno-fused BODIPY in living cells exhibited an extremely high phototoxicity with an ultralow IC50 value of 2.78 nM. The results revealed that the incorporation of an electron-donating group at the α-position of the unsymmetrical benzothieno-fused BODIPY platform might be an effective approach for developing long-wavelength absorbing heavy-atom-free photosensitizers for precision cancer therapy.

[Multi-scale medical image segmentation based on pixel encoding and spatial attention mechanism].

In response to the issues of single-scale information loss and large model parameter size during the sampling process in U-Net and its variants for medical image segmentation, this paper proposes a multi-scale medical image segmentation method based on pixel encoding and spatial attention. Firstly, by redesigning the input strategy of the Transformer structure, a pixel encoding module is introduced to enable the model to extract global semantic information from multi-scale image features, obtaining richer feature information. Additionally, deformable convolutions are incorporated into the Transformer module to accelerate convergence speed and improve module performance. Secondly, a spatial attention module with residual connections is introduced to allow the model to focus on the foreground information of the fused feature maps. Finally, through ablation experiments, the network is lightweighted to enhance segmentation accuracy and accelerate model convergence. The proposed algorithm achieves satisfactory results on the Synapse dataset, an official public dataset for multi-organ segmentation provided by the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), with Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD95) scores of 77.65 and 18.34, respectively. The experimental results demonstrate that the proposed algorithm can enhance multi-organ segmentation performance, potentially filling the gap in multi-scale medical image segmentation algorithms, and providing assistance for professional physicians in diagnosis.

Cinchonine-induced cell death in pancreatic cancer cells by downregulating RRP15.

Pancreatic cancer is characterized by poor prognosis and high mortality, while its treatment remains unsatisfactory. Cinchonine, a natural compound present in cinchona bark, is a potential anticancer drug. Whether cinchonine is of relevance to pancreatic cancer therapeutics is unclear. This research showed that the ribosomal RNA-processing 15 homolog (RRP15) expression is decreased in the pancreatic cancer, and RRP15 knockdown inhibited autophagy, and caused apoptosis in pancreatic cancer cells. Cinchonine treatment inhibits the expression of RRP15 and autophagy, and caused apoptosis by leading to the activation of Nrf2 axis in pancreatic cancer cells. Taken together, the above results indicate that cinchonine treatment inhibited autophagy and induced apoptosis through activating Nrf2 axis by downregulating RRP15 in pancreatic cancer cells.

Blockade of IL-11 Trans-Signaling or JAK2/STAT3 Signaling Ameliorates the Profibrotic Effect of IL-11.

OBJECTIVES: Systemic sclerosis (SSc) is a rare rheumatic disease characterized by vascular damage, dysregulated immune response, and fibrosis. Interleukin-11 (IL-11) is upregulated in SSc. This study aimed to investigate the pathological and therapeutic role of the IL-11 trans-signaling pathway in SSc. METHODS: Plasma IL-11 level was evaluated in 32 patients with SSc and 15 healthy controls, while the expression levels of ADAM10, ADAM17, IL-11, IL-11 Rα, or IL-11 co-stained with CD3 or CD163 in the skin of SSc patients and healthy controls were analyzed. Fibroblasts were treated with IL-11 and ionomycin to evaluate the profibrotic effect of IL-11 trans-signaling pathway. TJ301 (sgp130Fc) and WP1066 (a JAK2/STAT3 inhibitor) intervention groups were set up to investigate the antifibrotic effect of targeting IL-11. RESULTS: Levels of plasma IL-11 were extremely low in most SSc patients and healthy controls. In contrast, levels of IL-11, IL-11 Rα, and ADAM10, but not ADAM17, were significantly elevated in the skin of SSc patients. Moreover, the numbers of IL-11+ CD3+ cells and IL-11+ CD163+ cells were increased in the skin of SSc patients. Besides, IL-11 and ADAM10 were also elevated in the skin and pulmonary of bleomycin-induced SSc mouse. Fibroblasts co-stimulated with IL-11 and ionomycin showed increased expression of COL3 and phosphorylation of STAT3, which could be inhibited by TJ301 or WP1066. TJ301 also ameliorated skin and lung fibrosis in BLM-induced SSc mouse. CONCLUSIONS: IL-11 induces fibrosis in SSc by regulating the trans-signaling pathway. Blockage of sgp130Fc or inhibition of the JAK2/STAT3 pathway could ameliorate the profibrotic effect of IL-11.

Prediction Efficacy for Clinical Outcome of Prognostic Nutritional Index in Patients with Resectable Biliary Tract Cancer Depends on Sex and Obstructive Jaundice Status.

BACKGROUND: The Prognostic Nutritional Index (PNI), a marker of nutritional status and systemic inflammation, is a proven prognostic biomarker in some cancers. The predictive value of PNI in biliary tract cancer (BTC) has not been established. OBJECTIVE: The aim of this study was to determine the relationship between the PNI and outcomes of resectable BTC. METHODS: In total, 430 patients with stage I-III resectable BTC [gallbladder cancer (GBC), n = 212; cholangiocarcinoma (CHO), n = 218] who had attended Fudan University Zhongshan Hospital were enrolled. The relationship between the PNI and clinical outcomes was evaluated both in the whole cohort and in selected subgroups. RESULTS: Eligible patients were classified into PNI-low (PNI < 45) and PNI-high (PNI ≥ 45) groups. The PNI-low group had significantly worse overall survival (OS) in both the whole cohort (p = 0.002) and in the GBC subgroup (p = 0.001), but had similar OS as the PNI-high group in the CHO subgroup (p = 0.328). Multivariate analysis revealed that low PNI is an independent risk factor for worse survival in GBC (hazard ratio 1.623, 95% confidence interval 1.063-2.480, p = 0.026). PNI was found to predict clinical outcome in women (p < 0.001) and patients without obstructive jaundice (p = 0.017) with GBC, but was not a prognostic factor in any subgroup with CHO. The estimated area under the time-dependent receiver operating characteristic curve was significantly greater when TNM stage was combined with PNI in women with GBC. CONCLUSIONS: PNI is an independent predictor of OS in GBC, but not in CHO. It has no prognostic value in men with GBC or patients with obstructive jaundice.

A facile synthesis of CoMn2O4 nanosheets on reduced graphene oxide for non-enzymatic glucose sensing.

A non-enzymatic sensor nanomaterial which is composed of ultra-thin scaly CoMn2O4 nanosheets grown on the surface of reduced graphene oxide sheets (CoMn2O4 NSs/rGO) has been successfully synthesized by a simple method for glucose sensing. The morphology and elemental composition of CoMn2O4 NSs/rGO are researched by means of x-ray diffraction, field emission scanning electron microscope, and transmission electron microscope. Cyclic voltammetry and amperometry are used to analyse the glucose oxidation characteristics of the material. The test results show that the non-enzymatic glucose sensor based on CoMn2O4 NSs/rGO has excellent glucose sensing performance, exhibiting a wide linear range of 0.1-30 mM with high sensitivity of 6830.5 µA mM-1 cm-2, which is better than other glucose sensors. In addition, the CoMn2O4 NSs/rGO sensor has superior anti-interference and stability. More importantly, the sensor can be applied to the measurement of real sample, which makes it have the potential to become a reliable clinical glucose sensor.

3D laparoscopic common bile duct exploration versus 2D in choledocholithiasis patients: a propensity score analysis.

BACKGROUND: This study was designed to investigate whether 3D laparoscopic common bile duct (LCBDE) could improve surgical outcomes in choledocholithiasis patients compared with 2D LCBDE. METHOD: Propensity score-matched analysis was performed to balance the bias in baseline characteristic between two groups. RESULTS: 213 patients underwent 3D LCBDE and 212 patients receiving 2D LCBDE were enrolled in this study. The operation time and blood loss in 3D group were significantly less than that in 2D group. After propensity score matching, a total of 114 paired cases were selected from the two groups. The operation time and blood loss in 3D group remain significantly lower than in 2D group. In the end, the subgroup analysis based on abdominal adhesion level was performed and it was observed that for patients with adhesion level 1 and level 2, 3D surgery could obviously decrease the operation time and intraoperative blood loss. CONCLUSIONS: 3D LCBDE would significantly reduce operation time, blood loss, and conversion rate to laparotomy in choledocholithiasis patients versus 2D LCBDE. For patients with abdominal adhesions level 1 and level 2, 3D LCBDE could provide better surgical outcomes than 2D LCBDE.

High infiltration of mast cells is associated with improved response to adjuvant chemotherapy in gallbladder cancer.

Recent studies have reported that tumor-infiltrating mast cells (TIM) play an important role in tumor regression, but the effect of TIM in gallbladder cancer (GBC) remains unclear. The present study aims to investigate the prognostic value of TIM in GBC patients and its responsiveness to gemcitabine-based adjuvant chemotherapy (ACT). A total of 298 GBC patients from Zhongshan Hospital were recruited for this study. TIM infiltration was measured by immunohistochemical staining. Accumulation of TIM is significantly associated with prolonged overall survival in GBC patients. The benefit from gemcitabine-based ACT was superior among patients with high infiltration of TIM with GBC. Multivariate analysis identified TIM infiltration as an independent prognostic factor for overall survival. A heatmap showed that TIM-activated gene signatures were positively correlated with CD8+ T cells' gene signatures. Gene set enrichment analysis (GSEA) suggested that TIM was related to multiple T cell-related processes and signaling pathways, including the interferon gamma signaling pathway and the leukocyte migration signaling pathway. It was confirmed that CD8+ T cell infiltration was positively correlated with high TIM infiltration in tissue microarray (TMA), suggesting that TIM infiltration was linked to the immune surveillance in GBC. TIM can be used as an independent prognostic factor and a predictor of therapeutic response of gemcitabine-based ACT in GBC patients, which may mediate immune surveillance by recruiting and activating CD8+ T cells in GBC.

Low immune index correlates with favorable prognosis but with reduced benefit from chemotherapy in gallbladder cancer.

Use of immune index is a new potential approach for cancer classification and prediction. To investigate the status and clinical effect of immune index in gallbladder cancer (GBC), 238 GBC patients from Zhongshan Hospital affiliated to Fudan University were involved in the present study, including 113 patients in a training set and 125 patients in a validation set. Five immune cells (macrophages, neutrophils, regulatory T cells, cytotoxic T cells and mast cells) were selected based on a literature review and the immune index for each patient was calculated using the LASSO regression. A low immune index (<1) was defined as immunotype A and a high immune index (≥1) was defined as immunotype B. The 5-year overall survival rate for immunotype A was higher than that for immunotype B in the training set and the validation set (70.0% vs 37.0%, P < 0.001; 68.9% vs 47.5%, P = 0.002; respectively). Moreover, the immune index showed higher prediction efficiency compared with all the single immune cells which we selected. When combined with the immune index, the areas under the curve (AUC) of the TNM staging system in both sets were elevated from 0.677 to 0.787 and from 0.631 to 0.694, respectively. Interestingly, gemcitabine-based chemotherapy only benefits stage II patients of immunotype B and stage III patients of both immunotype A and immunotype B (P = 0.015, P = 0.030, P = 0.011, respectively) but does not work in stage II patients of immunotype A (P = .307). Taken together, the immune index could effectively predict prognosis and the benefits of gemcitabine-based chemotherapy and might improve on the TNM staging system.

Polarimetric Stationarity Omnibus Test (PSOT) for Selecting Persistent Scatterer Candidates with Quad-Polarimetric SAR Datasets.

In the traditional single polarimetric persistent scatterers interferometric (PSI) technology, the amplitude dispersion index (ADI) is usually used to select persistent scatterer candidates (PSC). Obviously, based on single polarimetric information, it is difficult to use the statistical characteristics for comprehensively describing the temporal stability of scatterers, which leads to a decrease in persistent scatterer (PS) density. Considering that the temporal polarimetric stationarity of PS, the paper is based on complex Wishart distribution and proposes the polarimetric stationarity omnibus test (PSOT) for identifying PSC. The nonstationary pixels can be removed by the preset significance threshold, which reduces the subsequent processing error and the calculation cost. Then, the exhaustive search polarimetric optimization (ESPO) method is selected for improving the phase quality of PSCs while suppressing the sidelobe of the strong scatterer effectively. For validating the effectiveness of the proposed method, we select a time-series quad-polarimetric ALOS PALSAR-1 images in an urban area as experimental data and mainly perform five group experiments for detailed analysis, including the PSOT+ESPO, ADI+ESPO, ADI+HH, ADI+HV, and ADI+VV. The results show that the proposed PSOT+ESPO method has a better performance on both PSC selection and interferometric phase optimization aspects than that of other methods. Specifically, compared to the last four methods, both the PSCs and PSs identified by the proposed PSOT+ESPO are more concentrated in the high-coherence region. The PSs with the standard deviation (STD) less than 5mm in the PSOT+ESPO method account for 94% of all PSs, which is greater than that of the ADI+ESPO, ADI+HH, ADI+HV, and ADI+VV methods, respectively.

Sub-Canopy Topography Estimation from TanDEM-X DEM by Fusing ALOS-2 PARSAR-2 InSAR Coherence and GEDI Data.

This paper develops a framework for extracting sub-canopy topography from the TanDEM-X digital elevation model (DEM) by fusing ALOS-2 PARSAR-2 interferometric synthetic aperture radar (InSAR) coherence and Global Ecosystem Dynamics Investigation (GEDI) data. The main idea of this method is to estimate the forest height signals caused by the limited penetration of the X-band into the canopy from the TanDEM-X DEM. To achieve this goal, a spaceborne repeat-pass InSAR coherent scattering model is first used to estimate the forest height by the ALOS-2 PARSAR-2 InSAR coherence (APIC), taking the GEDI canopy height as the reference. Then, a linear regression model of the TanDEM-X DEM Vegetation Bias (TDVB) depending on the forest height and the fraction of vegetation cover (FVC) is established and used to estimate the sub-canopy topography. The proposed method was validated by the data of the Amazon rainforest and a boreal forest in Canada. The results showed that the proposed method extracted the sub-canopy topography at the study sites in the tropical forest and boreal forest with the root mean square error of 4.0 m and 6.33 m, respectively, and improved the TanDEM-X DEM accuracy by 75.7% and 39.7%, respectively.

Long noncoding RNA NEAT1-modulated miR-506 regulates gastric cancer development through targeting STAT3.

Accumulating evidence has indicated that long noncoding RNA NEAT1 exerts critical roles in cancers. So far, the detailed biological role and mechanisms of NEAT1, which are responsible for human gastric cancer (GC), are still largely unknown. Here, we observed that NEAT1 and STAT3 expressions were significantly upregulated in human GC cells including BGC823, SGC-7901, AGS, MGC803, and MKN28 cells compared with normal gastric epithelial cells GES-1, while miR-506 was downregulated. We inhibited NEAT1 and observed that NEAT1 inhibition was able to repress the growth, migration, and invasion of GC cells. Conversely, overexpression of NEAT1 exhibited an increased ability of GC progression in BGC823 and SGC-7901 cells. Bioinformatics analysis, dual luciferase reporter assays, RIP assays, and RNA pull-down tests validated the negative binding correlation between NEAT1 and miR-506. In addition, it was found that miR-506 can modulate the expression of NEAT1 in vitro. STAT3 was predicted as a messenger RNA (mRNA) target of miR-506, and miR-506 mimics can suppress STAT3 mRNA expression. Subsequently, it was observed that downregulation of NEAT1 can restrain GC development by decreasing STAT3, which can be reversed by miR-506 inhibitors. Therefore, it was hypothesized in our study that NEAT1 can be recognized as a competing endogenous RNA to modulate STAT3 by sponging miR-506 in GC. In conclusion, we implied that NEAT1 can serve as an important biomarker in GC diagnosis and treatment.

CoNi2S4 nanosheets on nitrogen-doped carbon foam as binder-free and flexible electrodes for high-performance asymmetric supercapacitors.

Flexible electrode materials show many advantages and hold great prospects for energy storage application. But, the synthesis processes of these kind of materials are always complicated, are low in efficiency and high in cost. Here, we propose a facile and cost-effective two-step synthesis strategy of a flexible electrode by growing ultrathin and vertical CoNi2S4 nanosheets on nitrogen-doped carbon foam (CoNi2S4 NSs@NCF). The NCF is obtained by direct carbonization of the melamine foam. When evaluated as binder-free electrode material for supercapacitor in three-electrode system, the CoNi2S4 NSs@NCF exhibits an excellent specific capacitance of 1576.8 F g-1 and a superior cycling stability (91.5% capacitance retention at the 5000th cycle). Then, an asymmetrical supercapacitor was fabricated using the as-synthesized material as the positive electrode and activated carbon as the negative electrode, which delivers a high energy density of 42.8 Wh kg-1 at a power density of 399.7 W kg-1, remarkable rate capability and satisfactory cycling stability (85.3% capacitance retention at the 5000th cycle). In brief, our work offers a low-cost and facile approach to prepare promising flexible electrode materials for high-performance supercapacitors.

Four differentially methylated gene pairs to predict the prognosis for early stage hepatocellular carcinoma patients.

Hepatocellular carcinoma (HCC) was the second most common malignant tumor with a poor prognostic condition. We aimed to identify novel methylation signatures to predict HCC patients at their early stages. Differentially expressed methylated genes between HCC patients and normal liver tissues retrieved from TCGA were screened out by SAM. Genes highly related to patients' survival were figured out by COX. The signatures that could identify relapse HCC patients were identified by the forwarding search algorithm. Besides, functional enrichment analysis was performed on the methylation genes in the signature. A total of 5,392 CPG sites that differentially methylated expressed were found out and 4,294 differentially expressed genes were obtained. A total of 197 genes among were associated with RFS of HCC patients at both stage I and stage II. Signature composed of 21 pairs was obtained to predict the prognostic situation by C-index forward search method. The function of these genes was figured out by functional enrichment analysis. To summary, the signature composed of 21 gene pairs that can predict the prognostic situation of HCC patients at both stage I and stage II, provided a reference standard for the adjuvant therapy of HCC patients after surgery.

Metformin Inhibited Growth, Invasion and Metastasis of Esophageal Squamous Cell Carcinoma in Vitro and in Vivo.

BACKGROUND/AIMS: This study aimed at investigating the effects of metformin on the growth and metastasis of esophageal squamous cell carcinoma (ESCC) in vitro and in vivo. METHODS: Two human ESCC cell lines EC9706 and Eca109 were selected and challenged with metformin in this study. Western blot assay was performed to detect th level of Bcl-2, Bax and Caspase-3. Scratch wound assay, transwell assay and Millicell invasion assay were used to assay the invasion and migration of EC9706 and Eca109 cells. Nude mice tumor models were used to assay the growth and lung metastasis of ESCC cells after metformin treatment. The plasma glucose level was also assayed. RESULTS: We found that metformin significantly inhibited proliferation and induced apoptosis of both ESCC cell lines in a dose- and time-dependent manner, and the expression of Bcl-2 was down-regulated and Bax and Caspase-3 were up-regulated. Metformin significantly inhibited the invasion and migration of EC9706 and Eca109 cells (p < 0.05). mRNA and protein levels of MMP-2 and MMP-9 decreased significantly upon treatment with metformin of 10mM for 12, 24 and 48h in a time-dependent manner (p < 0.05). In line with in vitro results, in vivo experiments demonstrated that metformin inhibited tumorigenicity, inhibited lung metastasis and down-regulated the expression of MMP-2 and MMP-9. Moreover, we showed that metformin treatment did not cause significant alteration in liver and renal functions and plasma glucose level. CONCLUSION: Our study for the first time demonstrated the anti-invasive and anti-metastatic effects of metformin on human ESCC cells both in vitro and in vivo, which might be associated with the down-regulation of MMP-2 and MMP-9. As a whole, our results indicate the potential of metformin to be developed as a chemotherapeutic agent for patients with ESCC and might stimulate future studies on this area.

MiR-300 Serves as Potential Biomarker to Screen Knee Osteoarthritis Patients by Targeting TNFα.

BACKGROUND: This study mainly explored the serum level of miR-300 with the risk of knee OA, thereby evaluating their diagnostic ability for treatment of knee osteoarthritis (KOA) patients. METHODS: In the current study, we evaluated the level of TNFα in KOA patients and HCs. The serum was used to quantify the level of TNF-α by way of a sandwich enzyme-linked immunosorbent assay. Dual luciferase reporter assay was carried out to identify the possible target gene of miR-300. RESULTS: In line with previous studies, our data showed that serum TNFα level was increased along with K/L grades and WOMAC scoring, suggesting TNFα induced inflammatory responses correlating with the severity of KOA. We also showed that serum miR-300 level was increased with the severity of KOA according to X ray examination and K/L grades. Furthermore, we showed that serum miR-300 level positively correlated with K/L grades, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain scoring and WOMAC function scoring. Bioinformatic predictions showed a conserved binding site of miR-300 in the 3'UTR of IκBα. We then carried out a dual luciferase reporter assay and found miR-300 significantly suppressed pmirGLO-IκBα-3'UTR luciferase activity. CONCLUSIONS: Serum miR-300 is increased with the severity of KOA according to X-ray examination and K/L grades, thereby reflecting the severity of KOA and the degree of cartilage damage. Therefore, it could be used as a potential biomarker to screen KOA patients from healthy controls.

A Maximum Likelihood Based Nonparametric Iterative Adaptive Method of Synthetic Aperture Radar Tomography and Its Application for Estimating Underlying Topography and Forest Height.

Synthetic aperture radar tomography (TomoSAR) is an important way of obtaining underlying topography and forest height for long-wavelength datasets such as L-band and P-band radar. It is usual to apply nonparametric spectral estimation methods with a large number of snapshots over forest areas. The nonparametric iterative adaptive approach for amplitude and phase estimation (IAA-APES) can obtain a high resolution; however, it only tends to work well with a small number of snapshots. To overcome this problem, this paper proposes the nonparametric iterative adaptive approach based on maximum likelihood estimation (IAA-ML) for the application over forest areas. IAA-ML can be directly used in forest areas, without any prior information or preprocessing. Moreover, it can work well in the case of a large number of snapshots. In addition, it mainly focuses on the backscattered power around the phase centers, helping to detect their locations. The proposed IAA-ML estimator was tested in simulated experiments and the results confirmed that IAA-ML obtains a higher resolution than IAA-APES. Moreover, six P-band fully polarimetric airborne SAR images were applied to acquire the structural parameters of a forest area. It was found that the results of the HH polarization are suitable for analyzing the ground contribution and the results of the HV polarization are beneficial when studying the canopy contribution. Based on this, the underlying topography and forest height of a test site in Paracou, French Guiana, were estimated. With respect to the Light Detection and Ranging (LiDAR) measurements, the standard deviation of the estimations of the IAA-ML TomoSAR method was 2.11 m for the underlying topography and 2.80 m for the forest height. Furthermore, compared to IAA-APES, IAA-ML obtained a higher resolution and a higher estimation accuracy. In addition, the estimation accuracy of IAA-ML was also slightly higher than that of the SKP-beamforming technique in this case study.

An Adaptive Nonlocal Mean Filter for PolSAR Data with Shape-Adaptive Patches Matching.

The traditional nonlocal filters for polarimetric synthetic aperture radar (PolSAR) images are based on square patches matching to obtain homogeneous pixels in a large search window. However, it is still difficult for the regular patches to work well in the complex textured areas, even when the patch size has a small enough setting (e.g., 3 × 3 windows). Therefore, this paper proposes an adaptive nonlocal mean filter with shape-adaptive patches matching (ANLM) for PolSAR images. Mainly, the shape-adaptive (SA) matching patches are constructed by combining the polarimetric likelihood ratio test for coherency matrices (PolLRT-CM) and the region growing (RG), which is called PolLRT-CMRG. It is used to distinguish the homogeneous and heterogeneous pixels in textured areas effectively. Then, to enhance the filtering effect, it is necessary to take the adaptive threshold selection of similarity test (Simi-Test) into consideration. The simulated, low spatial resolution SAR580-Convair and high spatial resolution ESAR PolSAR image datasets are selected for experiments. We make a detailed quantitative and qualitative analysis for the filtered results. The experimental results have demonstrated that the proposed ANLM filter has better performance in speckle suppression and detail preservation than that of the traditional local and nonlocal filters.

A Crop Classification Method Integrating GF-3 PolSAR and Sentinel-2A Optical Data in the Dongting Lake Basin.

With the increasing of satellite sensors, more available multi-source data can be used for large-scale high-precision crop classification. Both polarimetric synthetic aperture radar (PolSAR) and multi-spectral optical data have been widely used for classification. However, it is difficult to combine the covariance matrix of PolSAR data with the spectral bands of optical data. Using Hoekman's method, this study solves the above problems by transforming the covariance matrix to an intensity vector that includes multiple intensity values on different polarization basis. In order to reduce the features redundancy, the principal component analysis (PCA) algorithm is adopted to select some useful polarimetric and optical features. In this study, the PolSAR data acquired by satellite Gaofen-3 (GF-3) on 19 July 2017 and the optical data acquired by Sentinel-2A on 17 July 2017 over the Dongting lake basin are selected for the validation experiment. The results show that the full feature integration method proposed in this study achieves an overall classification accuracy of 85.27%, higher than that of the single dataset method or some other feature integration modes.