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3D superstructures (3DSs) have attracted increasing interest because of the collective synergistic effects of individual building units, but their customization relies on tedious multistep strategy or high‐end nanofabrication technology. Herein, for the first time, a facile block copolymer micelle‐mediated anisotropic growth approach is reported to fabricate gold 3DSs consisting of tunable and intersecting lamellae with sawtooth‐like edges. The preparation of the 3DSs depends on the mediation of reduction kinetics of gold precursors and adsorption of block copolymer micelles on gold crystal surfaces using disulfiram as ligands. The thickness of lamellae in the 3DSs is controllable from ≈21 to 102 nm by adjusting the weight fraction of the micellar hydrophobicity blocks and the composed lamellar number is regulated from ≈3 to ≈30. Additional morphologies, such as a dendritic mesoporous structure and meatball‐like shapes, are obtained through controlling the extent of micelle swelling. Finite‐difference time‐domain simulations demonstrate that the unique 3DSs of gold lamellae with sawtooth‐like edges form abundant hotspots giving rise to surface‐enhanced Raman scattering (SERS). The 3DSs exhibit strong electromagnetic field enhancement and excellent performance as SERS substrates for detecting 4‐mercaptobenzoic acid. [ABSTRACT FROM AUTHOR]

Numerous nanomedicines have been developed to improve the efficiency and safety of conventional anticancer drugs. However, the carrier materials and intricate nature of multifunctional design always hindered the clinical transformation of nanomedicines. Herein, a novel carrier‐free anticancer nanomedicine (CFDC) with tailored morphologies including nanodots, nanorod and nanosheet were prepared using the clinically approved anti‐alcoholism drug disulfiram (DSF) via supramolecular assembly process. Our study reveals that CFDC induces the production of reactive oxygen species and activates the downstream apoptosis‐related c‐Jun N‐terminal kinase (JNK) and p‐38 pathway. In addition, the CFDC effectively counteract the inhibitory effect of NF‐κB expression on ROS‐induced cellular cytotoxicity, ultimately resulting in enhanced cell apoptosis, which is not achievable by pure DSF and the simply mixing of DSF and Cu2+ (DSF+Cu). Notably, the CFDC exhibits 3.1‐, 3.0‐folds increased on cancer cell DNA damage compared with the DSF, and DSF+Cu groups. In vivo experiments conducted on breast‐ or prostate‐bearing mice modals demonstrated that the CFDC exhibits a higher efficacy in suppressing the tumor growth. The remarkable drug delivery efficiency and better anticancer effect of CFDC nanodrug provide promising prospects for the clinical transformation of DSF based nanodrug in cancer therapy. [ABSTRACT FROM AUTHOR]

O3 was applied as an efficient oxidant in the pre-oxidation of cellulose under the mild conditions for oxidation-hydrolysis of cellulose without additional catalyst. After treated by O3 at 120 °C for 4 h, some hydroxymethyl groups on cellulose structure were oxidized to carboxyl groups which act as the active sites for the hydrolysis under the hydrothermal conditions to break the glycoside bonds of cellulose. Much lower oxidation temperature and short treatment time make this method more competitive than the conventional oxidation-hydrolysis strategy (210 °C, 48 h) where O2 was used as the oxidant. Furthermore, in this oxidation-hydrolysis strategy, efficient hydrolysis of cellulose to glucose can be realized with a high cellulose/water mass ratio (40 wt%). Correspondingly, a glucose aqueous solution with high concentration (50.9 g L−1) can be obtained. High concentration of glucose is favorable for the further application in fermentation or chemical conversion. This work provides a new, mild, and green oxidation strategy for oxidation-hydrolysis of cellulose without additional catalyst. [ABSTRACT FROM AUTHOR]

Photodynamic therapy (PDT) has received increasing attention for tumor therapy due to its minimal invasiveness and spatiotemporal selectivity. However, the poor targeting of photosensitizer and hypoxia of the tumor microenvironment limit the PDT efficacy. Herein, eccentric hollow mesoporous organic silica nanoparticles (EHMONs) are prepared by anisotropic encapsulation and hydrothermal etching for constructing PDT nanoplatforms with targeting and hypoxia-alleviating properties. The prepared EHMONs possess a unique eccentric hollow structure, a uniform size (300 nm), a large cavity, and ordered mesoporous channels (2.3 nm). The EHMONs are modified with the mitochondria-targeting molecule triphenylphosphine (CTPP) and photosensitizers chlorin e6 (Ce6). Oxygen-carrying compound perfluorocarbons (PFCs) are further loaded in the internal cavity of EHMONs. Hemolytic assays and in vitro toxicity experiments show that the EHMONs-Ce6-CTPP possesses very good biocompatibility and can target mitochondria of triple-negative breast cancer, thus increasing the accumulation of photosensitizers Ce6 at mitochondria after entering cancer cells. The EHMONs-Ce6-CTPP@PFCs with oxygen-carrying ability can alleviate hypoxia after entering in the cancer cell. Phantom and cellular experiments show that the EHMONs-Ce6-CTPP@PFCs produce more singlet oxygen reactive oxygen species (ROSs). Thus, in vitro and in vivo experiments demonstrated that the EHMONs-Ce6-CTPP@PFCs showed excellent treatment effects for triple-negative breast cancer. This research provides a new method for a targeting and oxygen-carrying nanoplatform for enhancing PDF effectiveness. [ABSTRACT FROM AUTHOR]

Given a directed graph G, the directed densest subgraph (DDS) problem refers to finding a subgraph from G, whose density is the highest among all subgraphs of G. The DDS problem is fundamental to a wide range of applications, such as fake follower detection and community mining. Theoretically, the DDS problem closely connects to other essential graph problems, such as network flow and bipartite matching. However, existing DDS solutions suffer from efficiency and scalability issues. In this paper, we develop a convex-programming-based solution by transforming the DDS problem into a set of linear programs. Based on the duality of linear programs, we develop efficient exact and approximation algorithms. Particularly, our approximation algorithm can support flexible parameterized approximation guarantees. We further investigate using GPU to speed up the solution of convex programs in parallel and achieve hundreds of times speedup compared to the original Frank–Wolfe computation. We have performed an extensive empirical evaluation of our approaches on eight real large datasets. The results show that our proposed algorithms are up to five orders of magnitude faster than the state of the art. [ABSTRACT FROM AUTHOR]

As the energy crisis continues to intensify and with increasing awareness of global climate change, the issue of high energy consumption and emissions in buildings is garnering more attention. Windows have significant research value and importance as pivotal components in the development of ultra-low-energy buildings. This study presents a proposal for a passive exterior window considering the climatic conditions prevalent in the hot summer and cold winter zone of China. Firstly, an experimental platform was established outside a standard office to conduct tests and analyze the indoor thermal environment for four different scenarios in the summer and winter by comparing a passive room (PR) and non-passive room (NPR), respectively. The human apparent temperature was calculated based on the collected thermal environment data and subsequently evaluated. Lastly, the indoor environmental temperature (IET), window surface temperature (WST), and apparent temperature (AT) data were subjected to non-linear fitting regression analysis using Origin software. The primary aim of this analysis was to examine the impact of the passive exterior window on the indoor thermal environment and establish the feasibility of implementing such a window in the hot summer and cold winter zone of China. The results showed that: (1) in the summer, the IET and WST in the PR exhibited reductions of 0.8 °C and 0.6 °C, respectively, under ventilated conditions compared to the NPR; (2) in the winter, the IET and WST of the PR remained lower compared to those of the NPR (however, the temperature differential between the IET and WST in the PR amounted to 6.8 °C and 7.7 °C, respectively, while the corresponding disparity in the NPR was 8.1 °C and 9.3 °C); and (3) regarding the AT, during summer ventilation, the PR exhibited a substantial reduction of up to 3.5 °C in comparison to the NPR. Moreover, in the context of winter, the time for indoor human thermal perception to reach a comfortable level was extended by 0.5 h. Future investigations will delve into the influence of passive exterior windows on building energy consumption, and this research can provide a practical reference for energy-efficient design and retrofitting of exterior windows in the region. [ABSTRACT FROM AUTHOR]

The effectiveness of training-based object detection heavily depends on the amount of sample data. But in the field of remote sensing, the amount of sample data is difficult to meet the needs of network training due to the non-cooperative imaging modes and complex imaging conditions. Moreover, the imbalance of the sample data between different categories may lead to the long-tail problem during the training. Given that similar sensors, data acquisition approaches, and data structures could make the targets in different categories possess certain similarities, those categories can be modeled together within a subspace rather than the entire space to leverage the amounts of sample data in different subspaces. To this end, a subspace-dividing strategy and a subspace-based multi-branch network is proposed for object detection in remotely sensed images. Specifically, a combination index is defined to depict this kind of similarity, a generalized category consisting of similar categories is proposed to represent the subspace, and a new subspace-based loss function is devised to address the relationship between targets in one subspace and across different subspaces to integrate the sample data from similar categories within a subspace and to balance the amounts of sample data between different subspaces. Furthermore, a subspace-based multi-branch network is constructed to ensure the subspace-aware regression. Experiments on the DOTA and HRSC2016 datasets demonstrated the superiority of our proposed method. [ABSTRACT FROM AUTHOR]

A novel Fe–Mn binary oxide (FMBO)/bone char composite (FMBC) was synthesized and utilized to simultaneously adsorb Sb(III) and Cd(II) from aqueous phase in this study. The successful loading of Fe–Mn binary oxide on the bone char surface was revealed by the results of scanning electron microscope, X-ray diffraction patterns, and energy dispersive spectroscopy of FMBC. The FMBC exhibited remarkable ability of simultaneous removing Sb(III) and Cd(II) from aqueous, and the presence of Cd(II) enhanced Langmuir theoretical maximum adsorption capacity for Sb(III) significantly from 67.8 to 209.0 mg/g. Besides, FMBC could efficiently remove Sb(III) and Cd(II) in the wide initial pH range of 2–7. The influences of ionic strength, co-existing anions, humic acid, and temperature on the adsorption of Sb(III) and Cd(II), and the application potential of FMBC in actual groundwater were investigated. The main mechanisms of Sb(III) and Cd(II) adsorption onto FMBC involved redox, electrostatic interaction, surface complexation, ion exchange, and precipitation. The result of X-ray photoelectron spectroscopy and mapping spectrum analysis revealed that Mn(III) on FMBC played the key role in the Sb(III) oxidation, while FeOOH worked as the adsorption sites of FMBC. Meanwhile, the hydroxyapatite on FMBC also contributed to the removal of Cd(II). The presence of Cd(II) not only increased the positive charge on the surface of FMBC but also formed the Fe–Sb–Cd ternary complex, promoting the removal of Sb. This work provides valuable information for the application of FMBO/bone char as a cost-effective adsorbent to remediate co-pollution of Sb(III) and Cd(II) in aqueous environment. [ABSTRACT FROM AUTHOR]

Corncob is one of the main by-products of agricultural biomass in corn-producing area. Here, the valorization of corncob polysaccharide components to produce furfural and glucose was studied. Firstly, corncob was treated by high-pressure CO2-H2O; the in situ formed-carbonic acid catalyzed the selective hydrolysis of hemicellulose component with xylo-oligosaccharide and xylan as the main products. The obtained liquid fraction was further upgraded to furfural with H2SO4 as catalyst. After reaction at 140 °C for 1 h, 7.0 g L−1 of furfural was given. The conversion of C5 sugar and the selectivity of furfural was 56% and 72%, respectively. Then, the cellulose component of the residual solid fraction was depolymerized by oxidation-hydrolysis method. The hydroxymethyl group on the cellulose unit was partially oxidized to carboxyl group, which catalyzed the following hydrolysis of the cellulose component to glucose. 17.2 g of glucose per 100 g oxidized solid fraction was given at 170 °C for 6 h with water as the solvent. Additionally, the oxidation-hydrolysis strategy was also performed for the hydrolysis of the industrial furfural residues. [ABSTRACT FROM AUTHOR]

Objectives: This study retrospectively investigated in which cycle measurable residual disease (MRD) is associated with prognosis in patients in first complete remission (CR1) of intermediate-risk acute myeloid leukemia (AML). Methods: The study enrolled 235 younger patients with intermediate-risk AML. MRD was evaluated by multiparameter flow cytometry after the 1st, 2nd, and 3rd chemotherapy cycles (MRD1–3, respectively). Results: No significant association was detected after the 1st and 2nd cycles. However, the 5-year incidence of relapse was higher in the MRD3-positive group (n = 99) than in the negative group (n = 136) (48.7% vs. 13.7%, P = 0.005), while 5-year disease-free survival (DFS) and overall survival (OS) were lower in the MRD3-positive group than in the negative group (43.2% vs. 81.0% and 45.4% vs. 84.1%; P = 0.003 and 0.005, respectively). Allogeneic hematopoietic stem cell transplantation led to a lower 5-year relapse, and higher DFS and OS rates than chemotherapy in the MRD3-positive group (22.3% vs. 71.5%, 65.9% vs. 23.0%, and 67.1% vs. 23.9%; P < 0.001, 0.002, and 0.022, respectively), but did not affect the MRD-negative group. Conclusions: MRD3 could serve as an indicator for post-remission treatment choice and help improve outcomes for intermediate-risk AML in CR1. [ABSTRACT FROM AUTHOR]

Dictionary learning has been widely used in image representation under the framework of sparse theory. However, most of the current dictionary learning strategies can only be used for single-frame image separately, which are insufficient from the perspective of incremental information acquisition and global optimization for the sequential or multiframe satellite images. To this end, this article proposes an incremental dictionary learning method for multiframe satellite images representation in the spectral domain. The incremental dictionary learning is formulated analytically in the framework of sparse representation with low-rank constraint, as a frame-by-frame gradual optimization process of global and local dictionaries, and their corresponding sparse coefficients with the sequence. Specifically, the global dictionary representing the common spectral information of the sequential frames is optimized by two adjacent frames gradually. Meanwhile, the local dictionary representing the specific spectral information of each frame is optimized by the newly added frame itself. In addition, an activity ratio for separating the global dictionary from the local dictionaries, an outlier detection method for initializing the local dictionary are also given, and the alternating direction method of multipliers (ADMMs) is employed to implement the above optimization. Comparison results with the related state-of-the-art methods on different datasets demonstrate that, our proposed method achieves the best representation performance in both spatial and spectral domains, and also helps to improve the performance of dictionary-based tasks using sequential satellite images, such as sea surface anomaly detection. [ABSTRACT FROM AUTHOR]

Anomalies in remote sensing images are generally reflected in two aspects of spatial and spectral ones, as for the anomaly detection of sea surface using multispectral or hyperspectral images, spectral information is more important. To this end, a novel spectral anomaly detection method based on dictionary optimization is proposed in this letter. More specifically, the normal scene is first defined to distinguish the anomaly. Then, without any assumption about the distribution of anomaly, a spectral dictionary is formulated and derived theoretically with optimization to express the normal scenes. Using the sparse and low-rank constraints, the alternating direction method of multiplier (ADMM) is employed to solve the above optimization in the spectral domain. Finally, for a given sea-surface image to be detected, the error matrix that cannot be fully expressed by the optimized spectral dictionary is regarded as anomalies. It shows certain generality for various kinds of spectral anomalies on the sea surface. Taking multispectral images obtained by the HY-1C satellite as an example, comparisons with related state-of-the-art methods demonstrate that our proposed method achieves the best anomaly detection performance not only for oil-spill pollution but also for algae pollution. [ABSTRACT FROM AUTHOR]

Diabetic peripheral neuropathy (DPN) is a chronic complication of diabetes, and its neural mechanisms underlying the pathogenesis remain unclear. Autophagy plays an important role in neurodegenerative diseases and nerve tissue injury. Lipin1 is a phosphatidic acid phosphatase enzyme that converts phosphatidic acid (PA) into diacylglycerol (DAG), a precursor of triacylglycerol and phospholipids which plays an important role in maintaining normal peripheral nerve conduction function. However, whether Lipin1 involved in the pathogenesis of DPN via regulation of autophagy is not elucidated. Here, we show that the Lipin1 expression was downregulated in streptozotocin (STZ)-induced DPN rat model. Interestingly, STZ prevented DAG synthesis, and resulted in autophagic hyperactivity, effects which may increase the apoptosis of Schwann cells and lead to demyelination in sciatic nerve in DPN rats. More importantly, upregulation of lipin1 in the DPN rats ameliorated autophagy disorders and pathological changes of the sciatic nerve, which associated with the increase of the motor nerve conductive velocity (MNCV) in DPN rats. In contrast, knockdown of lipin1 exacerbates neuronal abnormalities and facilitates the genesis of DPN phenotypes in rats. In addition, overexpression of lipin1 in RSC96 cells also significantly decreased the autophagic hyperactivity and apoptosis induced by hyperglycemia. These results suggest that lipin1 may exert neuroprotection within the sciatic nerve anomalies and may serve as a potential therapeutic target for the treatment of DPN. [ABSTRACT FROM AUTHOR]

Photochromism, fluorescence, and ultra‐long room temperature phosphorescence (URTP) are attractive phenomena in photonics. However, achieving multiple optical properties such as photochromism, fluorescence, and URTP on one material still remains a challenge. Here, the authors report a multifunctional optical polymeric film with photochromic, fluorescent, and URTP properties, fabricated by simply doping the naphthopyran molecule into epoxy polymer with 3D network. When the polymer network is loose, the naphthopyran‐doped film exhibits photochromic property but no fluorescence and phosphorescence. When the polymer network becomes dense, the film shows fluorescent and URTP behaviors but no photochromic property. It is noted that the room temperature phosphorescence lifetime is as high as 604 ms. Based on the excellent optical properties of reversible photochromism, fluorescence, and URTP, an advanced sixfold encryption application has been successfully established. This work not only opens up a new direction in design and fabrication of multifunctional optical materials but also offers principles for developing organic optical materials toward multilevel information encryption and data storage. [ABSTRACT FROM AUTHOR]

Spectral or spatial dictionary has been widely used in fusing low-spatial-resolution hyperspectral (LH) images and high-spatial-resolution multispectral (HM) images. However, only using spectral dictionary is insufficient for preserving spatial information, and vice versa. To address this problem, a new LH and HM image fusion method termed OTD using optimized twin dictionaries is proposed in this paper. The fusion problem of OTD is formulated analytically in the framework of sparse representation, as an optimization of twin spectral-spatial dictionaries and their corresponding sparse coefficients. More specifically, the spectral dictionary representing the generalized spectrums and its spectral sparse coefficients are optimized by utilizing the observed LH and HM images in the spectral domain; and the spatial dictionary representing the spatial information and its spatial sparse coefficients are optimized by modeling the rest of high-frequency information in the spatial domain. In addition, without non-negative constraints, the alternating direction methods of multipliers (ADMM) are employed to implement the above optimization process. Comparison results with the related state-of-the-art fusion methods on various datasets demonstrate that our proposed OTD method achieves a better fusion performance in both spatial and spectral domains. [ABSTRACT FROM AUTHOR]

Compressed sensing provides the possibility of efficient compression of massive hyperspectral data. However, the existing methods often use the organization pattern of image blocks in sparse representation, and cannot make full use of inter spectral correlation. The separate retrieval of dictionary and measurement matrix also restricts the processing efficiency. To solve these problems, a novel and efficient hyperspectral image compression method based on compressed sensing and joint optimization is proposed in this paper. In sparse representation, the data organization pattern on spectral dimension is adopted to better express the correlation between spectra and improve the efficiency of operation. On the dictionary and measurement matrix, a joint optimization algorithm is proposed, which synchronously inhibits the sparse representation error and the reconstruction error. Experimental results show that compared with similar methods, the reconstruction error of this method is increased by 3 dB and the number of iterations is reduced by seven times, and the compression rate can reach 1/18. [ABSTRACT FROM AUTHOR]

High-spatial hyperspectral (HH) image reconstruction using both high-spatial multispectral (HM) image and low-spatial hyperspectral (LH) image over the same scene is widely used in many real applications. Nevertheless, the pair of HM image and LH image over the same scene is hard to obtain. To solve this problem, a new HH image reconstruction method using spectral library-based dictionary learning (named as HIRSL) is proposed in this paper, only from one HM image. The above reconstruction problem is formulated in the framework of sparse representation, as an estimation of the band matching matrix, the spectral dictionary, and the sparse coefficients. More specifically, a band matching method is proposed for mapping the common spectral library to a specific spectral library corresponding to the reconstructed HH image in spectral domain. Then, an efficient spectral dictionary learning method is proposed for the construction of spectral dictionary using the matched specific spectral library, which avoids the dependence of the LH image over the same scene. Finally, the sparse coefficients of the HM image with respect to the learned spectral dictionary are estimated using the alternating direction method of multipliers without nonnegative constraint. Comparison results on simulated and real data sets with the relative state-of-the-art methods demonstrate that even only using one HM image, our proposed method achieves a comparable reconstruction quality of high-spatial hyperspectral image both in spatial and spectral domains. [ABSTRACT FROM AUTHOR]

In this study, we compared the removal kinetics and Ni release styles of 1,1,1-trichloroethane (1,1,1-TCA), trichloroethylene (TCE), and tetrachloroethene (PCE) that result from the use of Ni/Fe nanoparticles in water. Compared to TCE and PCE, 1,1,1-TCA was more readily removed, and the concentration profiles of the three chlorinated aliphatic hydrocarbons (CAHs) during the reduction processes fit pseudo-first-order reaction rate models well. The surface area-normalized rate constants show that the 11% Ni Ni/Fe nanoparticles, which has the largest Brunauer–Emmett–Teller surface area, has the highest capacity for 1,1,1-TCA removal per unit surface area and that the 6% Ni sample was the best for removing TCE and PCE. The observed by-products suggested that hydrogenolysis was responsible for the dechlorination of CAHs in the presence of Ni/Fe nanoparticles. More Ni2+ was released during the degradation of 1,1,1-TCA than that of TCE and PCE because Ni will reduce the CAHs directly as a zerovalent metal does when hydrogen atoms in the Ni lattice are not sufficient due to the rapid incomplete dechlorination of 1,1,1-TCA. The different modes of adsorption of chloroalkane and chloroalkene onto the surfaces of Ni/Fe particles might play an important role in their dechlorination process. [ABSTRACT FROM AUTHOR]

The nicotinamide adenine dinucleotide-dependent protein deacetylase silent information regulator 2 (Sir2) regulates cellular lifespan in several organisms. Histone deacetylase 4 (HDAC4) belongs to the class IIa group of HDACs; this class of HDACs is composed of proteins that are important regulators of gene expression that control pleiotropic cellular functions. However, the role of HDAC4 in cellular senescence is still unknown. This study shows that the expression patterns of HDAC4 and Sirtuin 1 (SIRT1; the mammalian homolog of Sir2) are positively correlated during cellular senescence. Moreover, the overexpression of HDAC4 delays senescence, whereas the knockdown of HDAC4 leads to premature senescence in human fibroblasts. Furthermore, it is demonstrated that HDAC4 increases endogenous SIRT1 expression by enhancing its sumoylation modification levels, thereby stabilizing its protein levels. This study, therefore, provides a new molecular mechanism for the regulation of cellular senescence. [ABSTRACT FROM AUTHOR]

The metalloprotease lethal factor (LF) from Bacillus anthracis plays a vital role in anthrax toxin action, and thus becomes a target for anti-anthrax therapy. Following the guidelines based on existing metalloprotease inhibitors, we designed a 'first-generation' LF inhibitor R9LF-1. This inhibitor was shown to be very stable by itself in a wide range of pH and temperature and able to inhibit LF activity in vitro. However, as we reported previously in the presence of LF, this inhibitor was degraded to a small molecular weight species, resulting in a significantly decreased ability to protect MAPKK from cleavage by LF as well as to protect murine macrophages from lethal toxin. In order to elucidate this unusual phenomenon to build solid basis for high-efficiency LF inhibitor development, we performed extensive research to study the effect of LF on its peptide-based inhibitor. Effects of temperature and incubation period of time on generation of the smaller peptide (short version R9LF-1) by LF as well as its catalytic domain were analyzed. We found that LF degraded R9LF-1 with maximum efficiency in the pH range of 7.0-8.5, which correlates well with the range of LF enzymatic activity with its native substrate. The degradation showed a deviation from normal hyperbolic kinetics but a similarity to the kinetics profile of an enzyme-catalyzed reaction with positive cooperativity. The short version R9LF-1 had decreased inhibitory activity toward LF; surprisingly, BIAcore results suggested a better affinity for its binding to LF. In addition, R9LF-1 was not hydrolyzed by other common proteases, such as chymotrypsin and pepsin, suggesting hydrolysis of the bond between amino acid and hydroxamate groups is unique to LF. This study calls for caution when designing peptide-based LF inhibitors and when interpreting effects of these types of inhibitors. [ABSTRACT FROM AUTHOR]

Na/K-ATPases are membrane-associated enzymes responsible for the active transport of Na and K ions across cell membranes, generating chemical and electrical gradients. These enzymes' α-subunit provides catalytic function, binding and hydrolyzing ATP, and itself becoming phosphorylated during the transport cycle. In this study, Na/K-ATPase α-subunit cDNA was cloned from gill tissue of the swimming crab Portunus trituberculatus by reverse-transcription polymerase chain reaction (RT-PCR) and rapid amplification of cDNA end methods. Analysis of the nucleotide sequence revealed that the cDNA had a full-length of 3 833 base pairs (bp), with an open reading frame of 3 120 bp, 5′ untranslated region (UTR) of 317 bp, and 3′ UTR of 396 bp. The sequence encoded a 1 039 amino acid protein with a predicted molecular weight of 115.57 kDa and with estimated pI of 5.21. It was predicted here to possess all expected features of Na/K-ATPase members, including eight transmembrane domains, putative ATP-binding site, and phosphorylation site. Comparison of amino acid sequences showed that the P. trituberculatus α-subunit possessed an overall identity of 75%-99% to that of other organisms. Phylogenetic analysis revealed that this α-subunit was in the same category as those of crustaceans. Quantitative real-time RT-PCR analysis indicated that this α-subunit's transcript were most highly expressed in gill and lowest in muscle. RT-PCR analysis also revealed that α-subunit expression in crab gill decreased after 2 and 6 h, but increased after 12, 24, 48, and 72 h. In addition, α-subunit expression in hepatopancreas of crab decreased after 2-72 h. These facts indicated that the crab's Na/K-ATPase α-subunit was potentially involved in the observed acute response to low salinity stress. [ABSTRACT FROM AUTHOR]

Advanced glycation end products (AGEs)-induced vasculopathy, including oxidative stress, inflammation and apoptosis responses, contributes to the high morbidity and mortality of coronary artery diseases in diabetic patients. The present study was conducted to evaluate the protective activity of liquiritin (Liq) on AGEs-induced endothelial dysfunction and explore its underlying mechanisms. After pretreatment with Liq, a significant reduction in AGEs-induced apoptosis, as well as reactive oxygen species generation and malondialdehyde level in human umbilical vein endothelial cells (HUVECs) were observed via acridine orange/ethidium bromide fluorescence staining test. Notably, Liq also significantly increased AGEs-reduced superoxide dismutase activity. Furthermore, the pretreatment with receptor for advanced glycation end products (RAGE)-antibody or Liq remarkably down-regulated TGF-beta1 and RAGE protein expressions and significantly blocked NF-κB activation which were proved by immunocytochemistry or immunofluorescence assays. These results indicated that Liq held potential for the protection on AGEs-induced endothelial dysfunction via RAGE/NF-κB pathway in HUVECs and might be a promising agent for the treatment of vasculopathy in diabetic patients. [ABSTRACT FROM AUTHOR]

Runyang Bridge is a newly built cable-supported bridge that crosses the Yangtze River in China. The bridge is composed of one suspension bridge and one cable-stayed bridge. During the construction of the bridge, a structural health monitoring system (SHMS) was installed, which was designed by the Southeast University. Since the bridge was open to traffic, quantities of structural ambient responses have been recorded by the SHMS. And, it’s really important to extract structrural information from these records for health monitoring. This paper presents the study on modal identification of the bridge. The dynamic properites including modal frequencies, mode shapes and damping ratios are extracted from the ambient responses. Two identification methods are employed including the enhanced frequency domain decomposition and the stochastic subspace identification. The identified modal parameters from the two methods are compared. Results show that modal frequencies and mode shapes from the two methods are almost the same while the damping ratios are different. [ABSTRACT FROM AUTHOR]

Monitoring gait patterns in daily life will provide a lot of biological information related to human health. At present, common gait pressure analysis systems, such as pressure platforms and in-shoe systems, adopt rigid sensors and are wired and uncomfortable. In this paper, a biomimetic porous graphene–SBR (styrene-butadiene rubber) pressure sensor (PGSPS) with high flexibility, sensitivity (1.05 kPa−1), and a wide measuring range (0–150 kPa) is designed and integrated into an insole system to collect, process, transmit, and display plantar pressure data for gait analysis in real-time via a smartphone. The system consists of 16 PGSPSs that were used to analyze different gait signals, including walking, running, and jumping, to verify its daily application range. After comparing the test results with a high-precision digital multimeter, the system is proven to be more portable and suitable for daily use, and the accuracy of the waveform meets the judgment requirements. The system can play an important role in monitoring the safety of the elderly, which is very helpful in today's society with an increasingly aging population. Furthermore, an intelligent gait diagnosis algorithm can be added to realize a smart gait monitoring system. [ABSTRACT FROM AUTHOR]

The floating height of the strip in an air cushion furnace is a key parameter for the quality and efficiency of production. However, the high temperature and high pressure of the working environment prevents the floating height from being directly measured. Furthermore, the strip has multiple floating states in the whole operation process. It is thus difficult to employ a single model to accurately describe the floating height in different states. This paper presents a multi-model soft sensor to estimate the height based on state identification and the soft transition. First, floating states were divided using a partition method that combined adaptive k-nearest neighbors and principal component analysis theories. Based on the identified results, a hybrid model for the stable state, involving a double-random forest model for the vibration state and a soft-transition model, was created to predict the strip floating height. In the hybrid model for the stable state, a mechanistic model combined thick jet theory and the equilibrium equation of force to cope with the lower floating height. In addition, a novel soft-transition model based on data gravitation that further reflects the intrinsic process characteristic was developed for the transition state. The effectiveness of the proposed approach was validated using a self-developed air cushion furnace experimental platform. This study has important value for the process prediction and control of air cushion furnaces. [ABSTRACT FROM AUTHOR]

Fusion of the high-spatial-resolution hyperspectral (HHS) image using low-spatial- resolution hyperspectral (LHS) and high-spatial-resolution multispectral (HMS) image is usually formulated as a spatial super-resolution problem of LHS image with the help of an HMS image, and that may result in the loss of detailed structural information. Facing the above problem, the fusion of HMS with LHS image is formulated as a nonlinear spectral mapping from an HMS to HHS image with the help of an LHS image, and a novel cluster-based fusion method using multi-branch BP neural networks (named CF-BPNNs) is proposed, to ensure a more reasonable spectral mapping for each cluster. In the training stage, considering the intrinsic characteristics that the spectra are more similar within each cluster than that between clusters and so do the corresponding spectral mapping, an unsupervised clustering is used to divide the spectra of the down-sampled HMS image (marked as LMS) into several clusters according to spectral correlation. Then, the spectrum-pairs from the clustered LMS image and the corresponding LHS image are used to train multi-branch BP neural networks (BPNNs), to establish the nonlinear spectral mapping for each cluster. In the fusion stage, a supervised clustering is used to group the spectra of HMS image into the clusters determined during the training stage, and the final HHS image is reconstructed from the clustered HMS image using the trained multi-branch BPNNs accordingly. Comparison results with the related state-of-the-art methods demonstrate that our proposed method achieves a better fusion quality both in spatial and spectral domains. [ABSTRACT FROM AUTHOR]