Search

The limited bioavailability of PAHs in non-aqueous phase liquid (NAPL) limits their degradation. The biodegradation of phenanthrene in n-tetradecane by hydrophilic bacterium Moraxella sp. CFP312 was studied with the assistance of two polymers, chitosan and carboxymethyl cellulose (CMC). Both chitosan and CMC improved the cell hydrophobicity of CFP312 and increased the contact angle of CFP312 cells from 30.4 to 78.5 and 88.5, respectively. However, CMC increased the degradation ratio of phenanthrene from 45 to nearly 100%, while chitosan did not cause any improvement. We found that CMC was more effective than chitosan in promoting CFP312 to stabilize Pickering emulsion. In the bacteria-CMC complex system, oil was dispersed into small droplets to obtain a high emulsification index and large specific surface area. Moreover, according to the microscopic image of the bacteria-CMC emulsion droplet, we observed that the droplet surface was tightly covered by the CFP312 cells. Therefore, CFP312 cells joined with CMC can utilize phenanthrene in oil phase at the oil-water interface. This study will offer a new strategy for effective microbial degradation of hydrophobic compounds in NAPLs by hydrophilic bacteria. KEY POINTS: • Biodegradation of phenanthrene in Pickering emulsions • Pickering emulsions stabilized by hydrophilic CFP312 joined with CMC. • Phenanthrene was degraded by CFP312 at oil-water interface.

PAH biodegradation aided by surfactants and cyclodextrins has been widely studied because the former's micelles and the latter's hydrophobic cavities can increase the apparent solubility of PAHs. In this work, the effects of Triton X-100 (TX-100) and β-cyclodextrin (β-CD) on the bioavailability and biodegradation of phenanthrene (PHE) were investigated. The degrading microorganism used was Moraxella osloensis CFP312, a new strain screened from polluted soil and could form biofilms on crystalline PHE. At the same concentrations, β-CD solubilized less PHE than TX-100 but promoted PHE biodegradation. The two solubilizers had almost no different effects on CFP312 hydrophobicity; however, β-CD significantly eluted fewer cells from biofilms on crystalline PHE than TX-100. Microscopy observation revealed that the residual structure of the biofilm treated with β-CD was more complete than that of the biofilm treated with TX-100. This effect is beneficial to the function of biofilms and conducive to mass transfer from the exposed area in the crystalline PHE to the aqueous phase. Although TX-100 and β-CD could enhance the mass transfer of PHE to the aqueous phase, the latter significantly improved the bioavailability and biodegradation of PHE mainly because its solubilization was accompanied by easy desorption and retention of the biofilm functional integrity.

The lack of true color and the presence of background clutter reduce the accuracy rate of the saliency analysis for oil tank extraction in the synthetic aperture radar (SAR) images. This letter proposes a specially designed unsupervised method to extract oil tanks using the joint-spatial saliency analysis (JSSA) for multiple SAR images. First, the intrasaliency analysis is established on a saliency driven iterative clustering. This considers the spatial intensity and texture feature within a single image and suppresses most backgrounds. Second, the cospatial residual and the local grayscale statistics are considered independently in the intersaliency analysis. The common salient parts among the input series are extracted and used to overcome the problem of the lack of true color. Third, to make the fusion of the two kinds of saliency maps, the low-rank matrix is introduced. The weights of different maps are calculated and the saliency cues are integrated efficiently. Finally, after the statistics of the highlight points within the candidates, the location of the oil tanks is refined. The experiments show the superiority of the proposed method in both the pixel level and the geometric segmentation. The result of the JSSA model appears to improve the accuracy with fewer missing objects compared with the competing algorithms.

Polycyclic aromatic hydrocarbons (PAHs) are a class of common environmental pollutants that pose threats to human health. In this study, a mesophilic bacterial strain CFP312 (grown at 15-37 °C, optimal at 30 °C) was isolated from PAHs-contaminated soil samples. It was identified as Moraxella sp. by morphological observation, physiological and biochemical test, and 16S rRNA gene phylogeny analysis. This is the first reported PAHs degrading strains in Moraxella. Degradation analysis showed that 84% and 90% of the loaded phenanthrene (400 mg/L) were degraded within 48 h and 60 h, and the degradation rates reached 1.21 and 1.29 mg/(L·h), respectively. During the degradation of phenanthrene, phenanthrene-3,4-dihydrodiol was detected as an intermediate. Based on this, it was proposed that double oxygenation at the positions 3 and 4 of phenanthrene was the first step of biodegradation. Adaptability of strain CFP312 to different enhanced phenanthrene-degradation systems was tested in aqueous-organic system, micellar aqueous system, and cloud point system. Strain CFP312 showed good adaptability to different systems. In addition, the bacterium can rapidly degrade the phenanthrene in contaminated soil in slurry-aqueous system, indicating great potential in environmental remediation.

A novel saliency-driven oil tank detection method based on multidimensional feature vector clustering (MFVC) is proposed in this letter for synthetic aperture radar (SAR) images. There are three major contributions: 1) a specially designed MFVC method, which is suitable for SAR images without true colors, is employed to detect oil tanks roughly by saliency analysis. Five important complementary features, including intensity, texture, structure, and 2-D coordinates, form a 5-D vector, and then an unsupervised strategy is employed for clustering the 5-D feature vectors to acquire the saliency map; 2) For accurate location, the shape limit coefficient is added to the original active contour model to extract contours of top surfaces; and 3) according to the relations of top, bottom, and the brightest arch, bottoms of oil tanks are computed precisely. Experiments are conducted in two aspects: evaluation for saliency analysis, and for bottom location. Results show that the MFVC method outperforms competing methods in maintaining complete oil tanks and accurate boundaries, and removing the background clutter as much as possible.

The advance in synthetic aperture radar (SAR) technology reduces the difficulty of data acquisition, along with greatly increased computational complexity. This paper cares about this and aims to accomplish oil tank detection in SAR images from the perspective of computer vision. The whole model includes three main steps. The first is a saliency-driven clustering to accomplish the single image saliency analysis according to the intensity specificity and texture distribution. The second step introduces a common visual saliency analysis based on the co-spatial residual and local gradation statistic to extract the common visual salient parts within the input series. The final step considers the distribution of adjacent highlight points obtained from the saliency analysis to accomplish the location of tanks. Three competing methods are established in the experimental part. The evaluation in pixel level and geometric segmentation accuracy both verify the superiority of the proposed model in target detection and interferences exclusion.

The great increase in the resolution of remote sensing images comes with the problem of high computational complexity. Besides, the irregular circular shape of the tanks and the difficulty to establish the dataset make the detection task a big challenge. This paper proposes a co-feature and shape prior based saliency analysis model to extract the candidates. Two kinds of saliency maps are considered including the co-feature spatial residual map which is extracted as the common parts of different feature maps and the shape saliency map which provides the complementary information with the shape prior knowledge of circular targets. Besides, the curvature driven active contour model is used to insure the precise of the extracted contour. The quantitative evaluation of the experiments is conducted considering the detection precision and the geometric error. Results show that the proposed method is superior both in the pixel level performance and the geometric shape.

Salt-and-pepper (SAP) noise is one of the common impulse noises. It is generated mostly during the process of image capture and storage, due to false locations in memory and damaged image sensors. SAP noise seriously degrades the quality of images and affects the performance of subsequent image processing, such as edge detection, image segmentation and object recognition. Thus, it is quite necessary to remove SAP noise from corrupted images efficiently. In this paper, we propose a fast-adaptive Gaussian-weighted mean filter (FAGWMF) for removing salt-and-pepper noises. Our denoising filter consists of four stages. At the first stage, we preprocess the image by enlarging and flipping the image. Then, we detect noisy pixels by comparing the pixel value with the maximum (255) and minimum (0) value. One pixel is regarded as noise if its value is equal to the maximum or minimum value. Otherwise, it is regarded as noisefree pixel. At the third stage, we determine the working window size by enlarging the filter window continuously until the quantity of noise-free pixels it includes reaches to the predetermined threshold or the window radius reaches to the predetermined maximum value. At the last stage, we replace each noise candidate by its Gaussian-weighted mean value of the noise-free pixels in window. Using Gaussian-weighted template, the central candidates will get larger weights than those on edges, which helps to preserve the edge information efficiently. Simulation results show that compared to some state-of-the-art algorithms, our proposed filter has faster execution speed and better restoration quality.

The incidence of depression has previously been correlated to hypertension. The aim of the present study was to explore the mechanisms of depression and hypertension by examining the expression and interaction of renin/prorenin receptor (PRR) and heme oxygenase 1 (HO-1) in vascular endothelial cells. A case-control study was conducted, and general data and serum factors were compared between hypertension patients complicated with depression and patients with hypertension alone. Logistic regression analysis was used to detect risk factors associated with hypertension complicated with depression. In addition, human umbilical vein endothelial cells (HUVECs) were treated with oxidized low-density lipoprotein (ox-LDL) and/or PRR gene silencing, and a Cell Counting Kit-8 (CCK-8) assay was performed to test their proliferation. The concentrations of inflammatory factors and oxidative stress factor were also detected using enzyme-linked immunosorbent assay and chemical colorimetry. Western blot analysis and reverse transcription-quantitative polymerase chain reaction were applied to detect protein and mRNA expression levels, respectively. The results revealed that HO-1 and renin precursor (Rep) were independent factors that affected hypertension complicated with depression. Serum HO-1 levels in patients with hypertension complicated with depression were significantly lower than that in hypertensive patients without depression, while Rep levels in patients with hypertension complicated with depression were significantly higher than that in hypertensive patients without depression. In HUVECs, ox-LDL reduced the cell proliferation in a dose-dependent manner, upregulated the expression of PRR gene and downregulated the expression of HO-1 gene. It was also observed that silencing of the PRR gene promoted the expression of the HO-1 gene. Furthermore, ox-LDL upregulated the inflammatory response and oxidative stress levels, while PRR gene silencing inhibited the ox-LDL-induced inflammatory factor and oxidative stress levels in HUVECs. Thus, regulating the expression levels of HO-1 and PRR to inhibit the oxidative stress and pro-inflammatory effect of ox-LDL may provide new insight for the treatment of hypertension patients with depression.

The present study aimed to evaluate the therapeutic effect of CO-releasing molecule-2 (CORM-2) in an established mouse orthotopic lung cancer model and investigate the underlying mechanism associated with inflammation pathway. A total of 80 mice were randomly divided into two groups with 20 serving as a normal control and 60 used for the orthotopic lung cancer model. The tumor group was either untreated, or administrated with DMSO or CORM-2. The mice were sacrificed at day 7 and 14 post-treatment, and the body weight, and thymus and spleen indices were determined. Pathological analysis was performed with hematoxylin and eosin (HE) staining. Serous inflammatory factors were measured using an ELISA. The expression levels of eukaryotic translation initiation factor 4E, p70S6K and toll-like receptor-4 (TLR4) were quantified by reverse transcription-polymerase chain reaction. The effects of CORM-2 on the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR), TLR4/nuclear factor (NF)-κB signaling pathways were determined by western blotting. The body weight increased over time in the control group, while it significantly declined in tumor-bearing mice (P