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Background: Nasopharyngeal carcinoma (NPC) is a subtype of head and neck cancer with dismal prognosis and high relapse rate. The role of long non-coding RNAs (lncRNAs) in NPC has become a research hotspot in recent years. This study aimed to interrogate the function and mechanism of lncRNA MSC antisense RNA 1 (MSC-AS1) in NPC. Methods: MSC-AS1 level in NPC tissues and cells were detected by RT-qPCR. Function of MSC-AS1 in NPC cells was assessed by CCK-8, EdU, TUNEL, caspase-3 activity, and transwell invasion assay. Interaction of microRNA-524-5p (miR-524-5p) with MSC-AS1 and nuclear receptor subfamily 4 group A member 2 (NR4A2) was determined by RIP and luciferase reporter assays. Results: MSC-AS1 was upregulated in NPC tissues and cells. Functional assays indicated that MSC-AS1 exacerbated cell proliferation, hindered apoptosis, and facilitated invasion and epithelial-to-mesenchymal transition (EMT) in NPC. Mechanistically, MSC-AS1 sequestered miR-524-5p to upregulate NR4A2 expression in NPC cells. Finally, NR4A2 was conformed as an oncogene in NPC, and overexpressed NR4A2 could restore MSC-AS1 knockdown-mediated inhibition on NPC progression. Conclusions: Our study firstly showed that lncRNA MSC-AS1 aggravated NPC progression by sponging miR-524-5p to increase NR4A2 expression, indicating MSC-AS1 as a novel target for the lncRNA-targeted therapy in NPC. [ABSTRACT FROM AUTHOR]

[Display omitted] • Methotrexate can quench the fluorescence of the MoS 2 quantum dots based on inner filter effect. • The limit of detection of this prosed method is 42 nM. • This proposed method is applicable for the detection of methotrexate in real samples. Herein, we developed a unique fluorescence biosensor for methotrexate assay based on MoS 2 quantum dots, which were synthesized in one step using sodium molybdate and cysteine as raw materials. The fluorescence of MoS 2 QDs could be quenched when encountered with methotrexate, which was attributed to the inner filter effect (IFE). Furthermore, this present IFE-based method showed the linearity between the MoS 2 QDs fluorescence intensity and the methotrexate concentration in the range of 0.05–1 μM with the LOD of 42 nM. The practical applicability of this strategy was successfully demonstrated by detecting methotrexate in real samples. Results indicated that the proposed method could be a promising sensing platform for methotrexate analysis. [ABSTRACT FROM AUTHOR]

In this study, a novel highly sensitive colorimetric platform has been designed for malathion assay based on Fe-N/C SAzyme. The as-synthesized SAzyme can directly oxidize 3,3´,5,5´-tetramethylbenzidine (TMB) to generate blue colored oxidized TMB. L-ascorbic acid-2-phosphate (AA2P), a substrate of acid phosphatase (ACP), could be hydrolyzed to AA, thereafter inhibit the oxidization reaction of TMB, leading to a conspicuous blue color fading. With the addition of malathion hindered the ACP activity and limited the AA production, resulting in the recovery of the catalytic activity of single-atom nanozyme. Under optimized operational conditions, a novel colorimetric assay has been designed for malathion detection with LOD of 0.42 nM. Besides, quantification of malathion in environmental and food samples was achieved based on the proposed strategy. In addition, the successfully integrated paper/smartphone sensor provided sensitive, and rapid, reliable detection of malathion with a LOD of 1 nM. [Display omitted] • Fe-N/C single-atom nanozyme possesses high oxidase mimetics activity. • Malathion can be sensitively detected. • This proposed strategy can be well applied in actual samples. • A paper-based colorimetric biosensor was established for portable detection. [ABSTRACT FROM AUTHOR]

End wall contraction is an effective approach to reduce the substantial secondary loss in the cascade with low aspect ratio. This paper proposed a series convolutional neural network architecture (SCNN) to improve the design optimization problem of end wall profile of a turbine stator blade. The specific implementation of the architecture is discussed in detail. The effect of the train size and sensitivity analysis of design variables are carried out. Finally, the optimization is completed by the gradient descent method, and the aerodynamic performance of end wall profile before and after optimization is compared. It shows that the SCNN architecture performs outstandingly with 30% training data. It can quickly and accurately provide rich flow field information and performance parameters within 3 ms after training. When the train size is 0.3, the mean prediction errors of mass flow rate and efficiency of each sample are lower than 0.1%, which performs significantly better than the Artificial Neural Network and Gaussian Process Regression model. When the stator blade adopts optimized contracted end wall profile, the power and efficiency are raised by 4.43% and 1.39% respectively with the mass flow rate only changing by 1.48%, which verifies the feasibility of the SCNN architecture. • The SCNN model is established to reconstruct flow field and predict performance. • High prediction accuracy and fast solving speed are achieved by SCNN model. • The sensitivity analysis of the design variables is carried out. • The optimization of end wall profile is completed with gradient descent method. [ABSTRACT FROM AUTHOR]

Aiming at the problems of a long design period and imperfect surrogate modeling in the field of airfoil design optimization, a convolutional neural network framework for airfoil design and performance prediction (DPCNN) is established based on the deep learning method. The airfoil profile parameterization, physical field prediction, and performance prediction are achieved. The results show that the DPCNN framework can generate substantial perfect airfoil profiles with only three geometric parameters. It has significant advantages such as good robustness, great convergence, fast computation speed, and high prediction accuracy compared with the conventional machine learning method. When the train size is 0.1, the predicted results can be obtained within 5 ms. The prediction absolute errors of physical field of most sample points are lower than 0.002, and the relative errors of aerodynamic performance parameters are lower than 2.5%. Finally, the optimization attempt of operating parameters is completed by gradient descent method, which shows good stability and convergence. Overall, the DPCNN framework in this paper has outstanding advantages in time cost and prediction accuracy. [ABSTRACT FROM AUTHOR]

Solid edible fat obtained by hydrogenation of vegetable oils is widely used in food market. However, the produced partially hydrogenated oils usually contain trans-fatty acids, which are harmful to health. It is meaningful to develop effective ways to directly structure edible liquid oil into gel-like state with good stability. Herein, we presented Pickering emulsions cooperatively stabilized by gelatin nanoparticles (GNPs) and dialdehyde starch nanoparticles (DASNPs) to structure liquid vegetable oils into gel state. It is interesting that Schiff's base reactions happened between GNPs and DASNPs on the surface of Pickering emulsion droplets as well as the interface among droplets, which effectively improved the stability of Pickering emulsions. The enhanced stability of Pickering emulsions contributed to the good solidification capacity to liquid oils. As a result, the emulsions could keep structure well after 6 months of storage. Moreover, the dense interfacial layer of Pickering emulsion droplets could protect β-carotene from being diffused out of the internal phase, indicating the potential of Pickering emulsions as container for encapsulating nutrients. In sum, the developed Pickering emulsion is a good strategy to structure liquid oils. [ABSTRACT FROM AUTHOR]

Urban ecological forestry is one of the analyses leading to high global mortality. Urban ecological forestry is based on the destruction of forest habitats and the loss of biodiversity. It is the growth of animals and plants in the world. It is characterized by a single irregular urban forest all over the world. Therefore, it is necessary to detect the affected area according to the application, find out and deal with it early. It is generally believed that urban ecosystem forests are essential indicators of destruction. The previous method used Support Vector Machine (SVM) and Short Time Fourier Transform Algorithm (STFT) to reduce the accuracy and efficiency of C.T. (Computed Tomography) images. The image processing system based on urban ecological forest analysis and detection is being processed. The conversion method is prolonged, and it is impossible to verify the image using advanced risk architecture. The proposedProgrammable Gate Array) is used to develop image processing and easily interface data without complexity. Programmable Gate Array is mainly realized by ASIC (Application Specific Integrated Circuit). This system accelerates forest detection and loss detection and can be used as a single processing system or as a component of an image detection system. Image processing systems rely on double-sided filtering, edge detection, multiple thresholds, image segmentation, morphological image processing, and image labeling to solve urban ecological forestry analysis symptoms. [ABSTRACT FROM AUTHOR]

Aerodynamic design optimization of the blade profile is a critical approach to improve performance of turbomachinery. This paper aims to achieve the performance prediction with deep learning method and realize fast design optimization of a turbine blade. Two parameterization methods based on geometric relationships (PGR) and neural network (PNN) are proposed, which can generate smooth and complete blade profiles. A dual convolutional neural network (DCNN) is constructed to predict the physical fields and aerodynamic performance. The implementations of DCNN are accomplished based on the datasets generated by the two parameterization methods respectively, which are called PGR-DCNN and PNN-DCNN model. Results show that the prediction accuracy increases and then keeps stable as train size increases. The two models can offer the detailed physical field distribution within 3 ms and accurately predict the aerodynamic performance. The prediction errors of performance parameters for 99% samples in validation set are less than 0.5% with PGR-DCNN model, which are significantly better than conventional machine learning methods. Finally, based on the accurate predictive models, the gradient-based design optimization for rotor blade profile is completed in 38 s. The efficiency of the two optimal blades reaches 89.29% and 88.92% respectively, which verifies the feasibility of our method. • Two parameterization methods based on geometric relationships and neural network are proposed. • The DCNN model is constructed to reconstruct physical fields and predict performance. • High prediction accuracy and fast calculation speed are achieved by DCNN model. • The gradient descent method is adopted to conduct the optimization of the turbine blade profile. [ABSTRACT FROM AUTHOR]

Background: Nasopharyngeal carcinoma (NPC) is a deadly cancer, mainly presenting in southeast and east Asia. Long noncoding RNAs (lncRNAs) play essential roles in cancer progression. Exosomes are critical for intercellular communication. Thus, the aim of this study was to identify the functional lncRNAs in NPC and its relevant mechanisms. Methods: Data from public databases were utilized to screen for functional lncRNAs in NPC. Functional and mechanical experiments were performed to determine the role of lncRNAs in NPC and its relative molecular mechanisms. Exosomes derived from NPC cells were isolated to determine their function in tumor-associated macrophages. Results: LncRNA TP73-AS1 was increased in NPC cells and tissues and was associated with a poor prognosis. TP73-AS1 overexpression promoted proliferation, colony formation, and DNA synthesis of NPC cells while TP73-AS1 knockdown showed opposite roles. TP73-AS1 could directly bind with miR-342-3p. MiR-342-3p overexpression attenuated the effect of TP73-AS1 in NPC cells. Furthermore, TP73-AS1 was transferred by exosomes to promote M2 polarization of macrophages. Lastly, exosomal TP73-AS1 enhanced the motility and tube formation of macrophages. Conclusions: Together, this study suggests that TP73-AS1 promotes NPC progression through targeting miR-342-3p and exosome-based communication with macrophages and that TP73-AS1 might be an emerging biomarker for NPC. [ABSTRACT FROM AUTHOR]

Background: Laryngeal cancer has the highest mortality rate among head and neck tumours. RNA N6-methyladenosine (m6A) is the most plentiful and variable in mammalian mRNA. Yet, the m6A regulatory mechanism underlying the carcinogenesis or progression of LSCC remains poorly understood. Methods: The m6A RNA methylation quantification kit was used to detect tissue methylation levels. m6A microarray analysis, mRNA transcriptomic sequencing (mRNA-seq), and proteomics were used to determine RBM15, TMBIM6, and IGF2BP3. Immunohistochemical (IHC), quantitative real-time PCR (qRT-PCR) and Western blot were used to investigate RBM15, TMBIM6, and IGF2BP3 expression in tissue samples and cell lines. The biological effects of RBM15 were detected both in vitro and in vivo. The combination relationship between RBM15/IGF2BP3 and TMBIM6 was verified by RNA immunoprecipitation (RIP) assay, Methylated RNA immunoprecipitation sequencing (MeRIP-seq), RNase Mazf, and luciferase report assay. RNase Mazf was used to determine the methylation site on TMBIM6 mRNA. Hoechst staining assay was used to confirm the apoptotic changes. The actinomycin D verified TMBIM6 stability. Results: The global mRNA m6A methylation level significantly increased in LSCC patients. RBM15, as a "writer" of methyltransferase, was significantly increased in LSCC and was associated with unfavorable prognosis. The knockdown of RBM15 reduced the proliferation, invasion, migration, and apoptosis of LSCC both in vitro and in vivo. The results were reversed after overexpressing RBM15. Mechanically, TMBIM6 acted as a downstream target of RBM15-mediated m6A modification. Furthermore, RBM15-mediated m6A modification of TMBIM6 mRNA enhanced TMBIM6 stability through IGF2BP3-dependent. Conclusion: Our results revealed the essential roles of RBM15 and IGF2BP3 in m6A methylation modification in LSCC, thus identifying a novel RNA regulatory mechanism. [ABSTRACT FROM AUTHOR]

Abstract Nanozymes' activities could be regulated by a simple and effective pH change in an in situ manner. In this work, for the first time, the peroxidase-like activity of Ni/Co layered double hydroxides (LDHs) was regulated via the alkaline-promoted reaction of fluorogenic substrate homovanillic acid and H 2 O 2 , and a promising tool for pH sensing was developed over the pH range of 8.3–9.6. As peroxidase nanozyme model, Ni/Co LDHs showed ease of preparation, low-cost, and water-solubility, which played an important role in this luminescence system. Based on the pH-dependent regulation of the Ni/Co LDHs activity, we constructed the bioassay platform for the determination urea, urease, penicillin G, and penicillinase with a wide linear range of 17–1000 µM, 3.3–270 mU mL−1, 3.3–1300 µM and 3.3–100 mU mL−1, respectively. This study not only demonstrated the alkaline-promoted modulation the nanozymes' activities, but also established a facile approach to develop novel bioassays. Graphical abstract fx1 Highlights • The alkaline-promoted regulating Ni/Co LDHs' peroxidase-like activity has been explored. • A pH sensor was developed based on the system of Ni/Co LDHs-HVA-H 2 O 2. • A platform for the detection urea, urease, penicillin G, and penicillinase was established. [ABSTRACT FROM AUTHOR]

The development of cost-effective and easy-to-use strategies for the detection of ascorbic acid (AA) and acid phosphatase (ACP) is in high demand but challenging. Thus, we report a novel colorimetric platform based on Fe–N/C single atom nanozyme with efficient oxidase mimicking activity for their highly sensitive detection. The designed Fe–N/C single atom nanozyme can directly oxidize 3,3′,5,5′-tetramethylbenzidine (TMB) to produce a blue oxidation product (oxTMB) in the absence of H 2 O 2. In addition, L-ascorbic acid 2-phosphate can be hydrolyzed to ascorbic acid in the presence of ACP, which inhibits the oxidation reaction and results in a significant bleaching of the blue color. Based on these phenomena, a novel colorimetric assay with high catalytic activity was developed for the determination of ascorbic acid and acid phosphatase with detection limits of 0.092 μM and 0.048 U/L, respectively. Notably, this strategy was successfully applied to the determination of ACP in human serum samples and evaluate ACP inhibitors, indicating its potential as a valuable tool for clinical diagnosis and research. [Display omitted] • A series of Fe–N/C single-atom nanozymes with efficient oxidase-like activity have been developed. • A novel high-sensitivity sensing platform for ascorbic acid (AA) and acid phosphatase (ACP) detection was designed. • The Fe–N/C single-atom nanozyme exhibited good accuracy and reproducibility in the ACP determination of human serum. [ABSTRACT FROM AUTHOR]

In this study, a novel fluorescence sensor for tetracyclines (TCs) detection was designed using WS 2 quantum dots (WS 2 QDs). WS 2 QDs could be quenched by TCs through the inner filter effect (IFE). The limit of detection of this proprosed method is 39 nM, 52 nM, and 28 nM for tetracycline (TC), doxycycline (DC), and oxytetracycline (OTC), respectively. The as-proposed strategy was successfully applied to detect TC in milk samples and human serum samples. The WS 2 QDs were highly biocompatible and showed lower toxicity. Moreover, the WS 2 QDs was successfully applied to imaging TC in HeLa cells owing to its excellent optical performance and great biocompatibility. A simple and sensitive fluorescent sensor for tetracyclines assay was developed based on WS 2 quantum dots. [Display omitted] • WS 2 QDs are prepared by a hydrothermal synthesis with sodium tungstate and cysteine. • Tetracyclines can quench the fluorescence of the WS 2 QDs via inner filter effect. • The sensor shows high sensitivity and rapid response toward tetracyclines. • This proposed strategy is applicable for the detection of tetracyclines in real samples. [ABSTRACT FROM AUTHOR]