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Methane is considered as a clean energy that is widely used in places with high environmental requirements. The increasing demand for methane exploration in polar and deep sea extreme environments has a positive role in carbon neutrality policies. As a result, there will be a gradual increase in exploration activities for deep sea methane resources. Methane sensors require high reliability but are prone to faults, so fault diagnosis and forecasting of gas sensors are of vital practical significance. In this work, a Gaussian-linearized transformer model with a tranquilized time-series decomposition method is proposed for fault diagnosis and forecasting tasks. Since the traditional transformer model requires more computational expense with time complexity of O (N2) and is not applicable to continuous-sequence prediction tasks, two blocks of the transformer are improved. First, a Gaussian-linearized attention block is modified for fault-diagnosis tasks so that its time complexity can be changed to O (N), which can reduce computational resources. Second, a model with proposed attention for fault forecasting replaces the traditional embedding block with a decomposed block, which can input the continuous sequence data to the model completely and preserve the continuity of the methane data. Results show that the Gaussian-linearized transformer improves the accuracy of fault diagnosis to 99% and forecasting with low computational cost, which is superior to that of traditional methods. Moreover, the least mean-square-error loss of fault forecasting is 0.04, which is lower compared with the traditional time series prediction models and other deep learning models, highlighting the great potential of the proposed transformer for fault diagnosis and fault forecasting of gas sensor arrays. [ABSTRACT FROM AUTHOR]

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Duckweed (Lemna aoukikusa), a common aquatic plant found worldwide, was used to treat a solution polluted with the model antibiotics, ciprofloxacin (fluoroquinolone group) and sulfamethoxazole (sulfonamide group), which were selected because they were frequently present in pharmaceutical wastewater. The plant could grow even in an aqueous solution with a high concentration of both antibiotics, and illumination enhanced its growth. The presence of antibiotics in the solution inhibited the growth, and the inhibitory effect of sulfamethoxazole was greater than that of ciprofloxacin. Ciprofloxacin was effectively reduced by hydrolysis, photolysis, and uptake by the duckweed. Although sulfamethoxazole was resistant to hydrolysis and photolysis, its uptake by duckweed under illumination conditions could remove both antibiotics from the solution, even at high concentrations. Regarding the contribution of the respective types of antibiotic removal rates to total antibiotic removal, the uptake rate of antibiotics was the highest, and the treatment of wastewater using duckweed was proposed as a promising treatment method. [ABSTRACT FROM AUTHOR]

Image segmentation plays an essential role in medical imaging analysis such as tumor boundary extraction. Recently, deep learning techniques have dramatically improved performance for image segmentation. However, an important factor preventing deep neural networks from going further is the information loss during the information propagation process. In this article, we present AX-Unet, a deep learning framework incorporating a modified atrous spatial pyramid pooling module to learn the location information and to extract multi-level contextual information to reduce information loss during downsampling. We also introduce a special group convolution operation on the feature map at each level to achieve information decoupling between channels. In addition, we propose an explicit boundary-aware loss function to tackle the blurry boundary problem. We evaluate our model on two public Pancreas-CT datasets, NIH Pancreas-CT dataset, and the pancreas part in medical segmentation decathlon (MSD) medical dataset. The experimental results validate that our model can outperform the state-of-the-art methods in pancreas CT image segmentation. By comparing the extracted feature output of our model, we find that the pancreatic region of normal people and patients with pancreatic tumors shows significant differences. This could provide a promising and reliable way to assist physicians for the screening of pancreatic tumors. [ABSTRACT FROM AUTHOR]

Jiawei Foshou San (JFS) is the new formula originated from classic Foshou San formula, composed with ligustrazine, ferulic acid, and tetrahydropalmatine. Previously JFS inhibited the growth of endometriosis (EMS) with unclear mechanism, especially in metastasis, invasion, and epithelial–mesenchymal transition. In this study, network pharmacology was performed to explore potential mechanism of JFS on EMS. Through compound–compound target and compound target–EMS target networks, key targets were analyzed for pathway enrichment. MMP–TIMP were uncovered as one cluster of the core targets. Furthermore, autologous transplantation of EMS rat’s model were used to evaluate in vivo effect of JFS on invasion, metastasis and epithelial–mesenchymal transition. JFS significantly suppressed the growth, and reduced the volume of ectopic endometrium, with modification of pathologic structure. In-depth study, invasion and metastasis were restrained after treating with JFS through decreasing MMP-2 and MMP-9, increasing TIMP-1. Meanwhile, JFS promoted E-cadherin, and attenuated N-cadherin, Vimentin, Snail, Slug, ZEB1, ZEB2, Twist. In brief, anti-EMS effect of JFS might be related to the regulation of epithelial–mesenchymal transformation, thereby inhibition of invasion and metastasis. These findings reveal the potential mechanism of JFS on EMS and the benefit for further evaluation. [ABSTRACT FROM AUTHOR]

This study reports on the performance of sodium alginate (SA)/poly(vinyl alcohol) (PVA)/moxifloxacin hydrochloride (MH) nanofibrous membranes (NFM) capable of providing antibacterial agent delivery for wound-dressing applications. The aim of this work was to prepare antibacterial NFM with good permeability properties by employing PVA and SA as carriers. A group of 12% PVA/2% SA solutions blended in various ratios (8:2, 7:3, 6:4, 5:5 and 4:6, v/v) and containing 0.5, 1, 2 or 4 wt% MH were studied for electrospinning into nanoscale fibermats. The optimum ratio found to form smooth fibers with uniform fibrous features was 6:4. The drug release behavior of the electrospun, the antibacterial effects onPseudomonas aeruginosaandStaphylococcus aureusand the animal wound dressing capabilities were also investigated. As much as 80% of the MH was released from the electrospun after 10 h of incubation at 37 °C. In addition, the NFM with 0.5 MH exhibited less activity, whereas those with higher concentrations of MH exhibited greater antibacterial effect. Furthermore, the MH-loaded electrospun accelerated the rate of wound dressing compared to other groups. The results of thein vitroandin vivoexperiments suggest that MH/PVA/SA nanofibers might be an interesting bioactive wound dressing for clinical applications. [ABSTRACT FROM PUBLISHER]

Abstract Isolevuglandins (IsoLGs) are a family of highly reactive 4-ketoaldehydes formed by lipid peroxidation that modify the lysyl residues of cellular proteins. Modification of proteins by IsoLGs have been shown to contribute to disease processes such as the development of hypertension. Accurate quantitation of the extent of protein modification by IsoLGs is essential for understanding the mechanisms whereby these modifications contribute to disease and the efficacy of interventions designed to prevent this modification. The previously described LC/MS assay to quantitate IsoLG protein adducts was extremely labor-intensive and time consuming, and while it offered reasonably low intra-day variation for replicate samples, variation when replicate samples were processed on separate days was significant. These limitations significantly restricted utilization of this approach. We therefore performed a series of studies to optimize the assay. We now report a significantly simplified LC/MS assay for measurement of IsoLG protein adducts with increased sensitivity and lower intra-day and inter-day variability. Highlights • Improved delipidation eliminates need for preparative HPLC. • Use of new internal standard eliminates variability arising from proteolysis. • Previously used base hydrolysis step shown to degrade analyte and thus eliminated. • Simplified assay reduces total processing time from 5 days to 2.5 days. • Sample needed for analysis reduced to 100 μL plasma or 33 mg wet tissue. [ABSTRACT FROM AUTHOR]

Abstract Objective Prostate cancer (PCa) is one of the most prevalent cancers affecting men worldwide. However, the biological functions of circRNAs in PCa are still largely unknown. Methods Real-time PCR (RT-PCR) and immunohistochemistry were performed to characterize the circ-102004 expression in both human PCa tissues and cell lines. The apoptosis and cell cycle status of prostate immortalized cell lines that were overexpressed with circ-102004 by transfection was analyzed using flow cytometry. The scratch test and the Transwell assay were conducted to evaluate the ability of transfected cells to migrate and invade. RNA sequencing, pathway analysis, and Western blotting were performed to probe the associations of circ-102004 with the classical cancer signaling pathways after functionally evaluating circ-102004 in a xenograft tumor model. Results In the present study, circ-102004 expression was found to be significantly higher in PCa samples than in the matched normal tissues. In functional experiments, circ-102004 is shown to play an oncogenic role in PCa by stimulating cancer cell migration and invasion. Circ-102004 overexpression was also accompanied by significant alterations in many signaling pathways, such as ERK, JNK, and Hedgehog, which are known to cause different types of cancers. Conclusions Circ-102004 is a potential oncogenic gene that regulates the development and progression of PCa. This study provides a scientific basis for targeting circ-102004 for either diagnosis or therapy. [ABSTRACT FROM AUTHOR]