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The previous study has shown that transcriptional factor MEOX1 could promote proliferation and sphere formation ability of non-small cell lung cancer (NSCLC) cells, however, we found that MEOX1 mRNA was lowly expressed in lung cancer tissues compared to that in normal adjacent tissues, and MEOX1 mRNA expression was positively correlated with the survival of lung cancer patients, especially in lung adenocarcinoma patients. Functional experiments using in vitro and in vivo experiments revealed that stable overexpression of MEOX1 significantly suppressed the proliferation ability, promoted cell cycle arrest in G2 phase, and apoptotic ability of NSCLC cells. Additionally, it was identified that MEOX1 and CCNB1 mRNA expression exhibited a negative correlation in different lung cancer tissues. Mechanistically, we indicated that MEOX1 bound to the transcriptional initiation site of CCNB1 and thus suppressed CCNB1 expression. Notably, CCNB1 overexpression rescued the inhibition of MEOX1 overexpression on NSCLC progression. This study deciphers a novel MEOX1/CCNB1 axis suppressing NSCLC progression.

With the continuous advancement of low-altitude UAV (unmanned air vehicle, UAV) technology for the earth observation and its wide popularity, UAV photogrammetry and SfM (Structure from Motion, SfM) methods have received more and more attention as the latest means to obtain true 3D realistic models of the survey area. As the newest means of measuring geomorphological information, UAV low-altitude photogrammetry and SfM methods can quickly obtain a true 3D realistic model of the survey area, and have been applied to a number of research fields. In this paper, the UAV is used to measure the typical local scene of annular landform at the southern edge of Dinosaur Valley in Lufeng, and the high-resolution geomorphological image data of the investigated area are obtained. Combined with the SFM method, a realistic 3D scene model is constructed, and its geomorphological characteristics are discussed and analyzed. The experimental results show that the DSM (digital surface model, DSM) data based on the SFM method can obtain ground points by filtering, diluting, and classifying the data, and the DEM (digital elevation model, DEM) data with a resolution of 0.2m is constructed by using the progressive encrypted triangular mesh method, which can accurately represent the true geomorphological characteristics of the study area. (2) Construction of three typical elevation profiles of the circular scene “inner-middle-outer,” and comparative analysis of the profiles confirmed that the topography of the study area is characterized by the dome ridge line AA' as the main highland ridge line, showing a circular “basin margin” pattern, with gradually decreasing elevations on the inner and outer sides. (3) In order to reveal the complex tectonic geomorphological features of the external scene between the ridge and trough, the ArcGIS surface analysis method was used to extract the ridge lines J1-J7. Accurate quantitative measurements and analysis were carried out to investigate the slope, slope length, slope direction, ridge area face, and other related parameters. (4) Using the multi-view visual interpretation and typical scene analysis of the three-dimensional 3D model, micro-geomorphological features such as the development of washouts in the survey area and the nodal laminar surface of the geological body can be clearly identified. In addition, the coordinates of the geological body’s spatial location and its production, spreading area, square volume, and other rich geological information can be accurately obtained. Through the above experimental study on the detection of 3D scenes of landforms, the advantages of UAV measurement technology and SFM method to construct DSM data and 3D scene models in fine geological structure detection are demonstrated. This will have an important application prospect and practical value for geological survey, monitoring , prevention and control management in mountainous areas .In addition, the fast, low-cost, high-precision, and non-contact measurement mode can provide accurate data basis and technical support for geological structure detection, geological disaster investigation, risk assessment and prevention and control management.

With the rapid development of AC-DC hybrid microgrid and the widespread application of power electric components, AC-DC hybrid park micro-grid based on the topology of electric energy router application(EERA) emerged. In this paper, the matching of the DC/AC devices and DC/DC devices capacity in the planning stage be optimized based on the port model of the electric energy router application. At the same time, the economic operation of the park microgrid is realized by quantifying the life loss cost of energy storage. Therefore, a bi-level optimization model that takes into account both the economic operation of the park microgrid and the investment of PV-energy storage combined power generation system containing the electric energy routers application is proposed. Given the different characteristics of the operating variables and planning variables, the optimization target is solved by the method of combining improved particle swarm algorithm using the Shannon information entropy model and mixed-integer quadratic programming (MIQP) based on the ideas of hierarchical decoupling. Through simulation calculation in different scenarios, it is verified that the effectiveness of the model and the feasibility of the algorithm. Finally, this model can provide a certain reference for the configuration of the park microgrid capacity based on the electric energy router application.

The nonlinear characteristics of wind power series and random fluctuation characteristics of wind resources have a harmful effect on stability of wind power prediction. This paper proposes a novel hybrid wind power short-term prediction model for improving precision and stability of wind power prediction. Firstly, the non-stationary wind power time series is decomposed by complete ensemble empirical mode decomposition - Lempel-Ziv complexity (CEEMD-LZC). Secondly, local linear embedding (LLE) is used to reduce the dimension of meteorological data with maintaining the essential structure of meteorological data. The integrated meteorological data predigested by LLE are treated as input of the prediction model. Finally, ant lion optimization (ALO) is utilized to optimize the weights and biases of extreme learning machine (ELM) network nodes to improve ELM prediction performance. The results of case studies show that the proposed model has a good forecasting effect and is more advantageous in 48h-ahead wind power forecasting.

Cytochrome P450 monooxygenases (P450s) and UDP-glycosyltransferases (UGTs) are major detoxifying enzymes that metabolize plant toxins and insecticides. In the present study, the synergists of piperonyl butoxide, sulfinpyrazone and 5-nitrouracil significantly increased cyantraniliprole and α-cypermethrin toxicity against the resistant strain. The transcripts of UGT341A4, UGT344B4, UGT344D6, UGT344J2 and UGT344M2 increased significantly in the CyR strain compared with the susceptible strain. Among these upregulated genes (including P450s), CYP6CY7 and UGT344B4 were highly expressed in the midgut. Transgenic expression of the P450 and UGT genes in broad body tissues in Drosophila melanogaster indicated that the expression of CYP380C6, CYP4CJ1, UGT341A4, UGT344B4 and UGT344M2 is sufficient to confer cyantraniliprole resistance, and CYP380C6, CYP6CY7, CYP6CY21, UGT341A4 and UGT344M2 are related to α-cypermethrin cross-resistance. The midgut-specific overexpression of CYP380C6, CYP6CY7, CYP6CY21, CYP4CJ1, UGT341A4, UGT344B4 and UGT344M2 significantly increased insensitivity to cyantraniliprole, and CYP380C6, CYP6CY7, CYP6CY21, UGT344B4 and UGT344M2 confer α-cypermethrin cross-resistance. The expression of CYP380C6, CYP4CJ1, UGT341A4 and UGT344M2 in broad tissues or in midgut has similar effects on insensitivity to insecticides; however, CYP6CY7, CYP6CY21 and UGT344B4 are more effective in the midgut. This result indicates that broad body tissues and midgut tissue are involved in insecticide resistance mediated by the candidate P450s and UGTs examined.