Expression and prognostic relevance of Cyclophilin A and matrix metalloproteinase 9 in esophageal squamous cell carcinoma

AIMS: To guide clinicians in selecting treatment options for esophageal squamous cell carcinoma (ESCC) patients, reliable markers predictive of clinical outcome are desirable. This study analyzed the correlation of cyclophilin A (CypA) and matrix metalloproteinase 9 (MMP9) in ESCC and their relationships to clinicopathological features and survival. METHODS: We immunohistochemically investigated 70 specimens of ESCC tissues using CypA and MMP9 antibodies. Then, the correlations between CypA and MMP9 expression and clinicopathological features and its prognostic relevance were determined. RESULTS: Significant correlations were only found in high level of CypA and MMP9 expression with tumor differentiation and lymph node status. Significant positive correlations were found between the expression status of CypA and that of MMP9. Overexpression of CypA and metastasis were significantly associated with shorter progression free survival times in univariate analysis. Multivariate analysis confirmed that CypA expression was an independent prognostic factor. CONCLUSIONS: CypA might be correlated with the differentiation, and its elevated expression may be an adverse prognostic indicator for the patients of ESCC. CypA/MMP9 signal pathway may be attributed to the malignant transformation of ESCC, and attention should be paid to a possible target for therapy. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1166551968105508

Self-assembly of 3D fennel-like Co3O4 with thirty-six surfaces for high performance supercapacitor

Three-dimensional (3D) fennel-like cobalt oxide (II,III) (Co3O4) particles with thirty-six surfaces on nickel foams were prepared via a simple hydrothermal synthesis method and its growth process was also researched. The crystalline structure and morphology were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), and Raman spectroscopy. The Brunauer-Emmett Teller (BET) analysis revealed that 3D fennel-like Co3O4 particles have high specific surface area. Therefore, the special structure with thirty-six surfaces indicates the good electrochemical performance of the micron-nanometer material as electrode material for supercapacitors. The cyclic voltammetry (CV), galvanostatic charge-discharge, and electrochemical impedance spectroscopy (EIS) were conducted to evaluate the electrochemical performances. Compared with other morphological materials of the similar sizes, the Co3O4 particles on nickel foam exhibit a high specific capacitance of 384.375 F.g(-1) at the current density of 3A.g(-1) and excellent cycling stability of a capacitance retention of 96.54% after 1500 galvanostatic charge-discharge cycles in 6M potassium hydroxide (KOH) electrolyte

Probing Quantum Confinement and Electronic Structure at Polar Oxide Interfaces

Polar discontinuities occurring at interfaces between two different materials constitute both a challenge and an opportunity in the study and application of a variety of devices. In order to cure the large electric field occurring in such structures, a reconfiguration of the charge landscape sets in at the interface via chemical modifications, adsorbates or charge transfer. In the latter case, one may expect a local electronic doping of one material: one sparkling example is the two-dimensional electron liquid (2DEL) appearing in SrTiO$_3$ once covered by a polar LaAlO$_3$ layer. Here we show that tuning the formal polarisation of a (La,Al)$_{1-x}$(Sr,Ti)$_x$O$_3$ (LASTO:$x$) overlayer through chemical composition modifies the quantum confinement of the 2DEL in SrTiO$_3$ and its electronic band structure. The analysis of the behaviour in magnetic field of superconducting field-effect devices reveals, in agreement with $ab\ initio$ calculations and self-consistent Poisson-Schr\"odinger modelling, that quantum confinement and energy splitting between electronic bands of different symmetries strongly depend on interface charge densities. These results not only strongly support the polar discontinuity mechanisms with a full charge transfer to explain the origin of the 2DEL at the celebrated LaAlO$_3$/SrTiO$_3$ interface, but also demonstrate an effective tool for tailoring the electronic structure at oxide interfaces.Comment: 18 pages, 4 figures, 1 ancillary file (Supporting Information

Landscape Pattern Analysis and Quality Evaluation in Beijing Hanshiqiao Wetland Nature Reserve

AbstractTaking the Landsat TM and ASTER images of Hanshiqiao wetland nature reserve in 1988, 1996 and 2004 as data source, based on the landscape types from imagery classification, the reserve landscape pattern and its changes were analyzed, meanwhile, the landscape quality and its changes were evaluated and discussed. Several landscape pattern indices were analyzed, the results indicated that from 1988 to 2004, as the result of natural factors and human disturbances, the landscape structure has been changed, landscape fragmentation has become more and more serious, patches have been tended to regular shape, and connectivity of the natural wetland has been weakened. In addition, the landscape quality was evaluated based on the indicators of pressure, state and response. The results showed that during 1996-2004 periods, the landscape quality for Hanshiqiao wetland nature reserve has degraded obviously, which was mainly influenced by human activities breaking into wetland landscape. Effective wetland management and control is therefore needed to solve the issues of the wetland loss and degradation in Hanshiqiao wetland nature reserve

Low-Rank Representations Meets Deep Unfolding: A Generalized and Interpretable Network for Hyperspectral Anomaly Detection

Current hyperspectral anomaly detection (HAD) benchmark datasets suffer from low resolution, simple background, and small size of the detection data. These factors also limit the performance of the well-known low-rank representation (LRR) models in terms of robustness on the separation of background and target features and the reliance on manual parameter selection. To this end, we build a new set of HAD benchmark datasets for improving the robustness of the HAD algorithm in complex scenarios, AIR-HAD for short. Accordingly, we propose a generalized and interpretable HAD network by deeply unfolding a dictionary-learnable LLR model, named LRR-Net$^+$, which is capable of spectrally decoupling the background structure and object properties in a more generalized fashion and eliminating the bias introduced by vital interference targets concurrently. In addition, LRR-Net$^+$ integrates the solution process of the Alternating Direction Method of Multipliers (ADMM) optimizer with the deep network, guiding its search process and imparting a level of interpretability to parameter optimization. Additionally, the integration of physical models with DL techniques eliminates the need for manual parameter tuning. The manually tuned parameters are seamlessly transformed into trainable parameters for deep neural networks, facilitating a more efficient and automated optimization process. Extensive experiments conducted on the AIR-HAD dataset show the superiority of our LRR-Net$^+$ in terms of detection performance and generalization ability, compared to top-performing rivals. Furthermore, the compilable codes and our AIR-HAD benchmark datasets in this paper will be made available freely and openly at \url{https://sites.google.com/view/danfeng-hong}