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The traditional groundwater overexploitation restoration only considers the impact on groundwater, on the basis of which, this paper also comprehensively considers the impact on economic society and the ecological environment. Based on analyzing the effect of groundwater overexploitation restoration on the groundwater–economic society–ecological environment (GESEE) system, an evaluation indicator system covering the GESEE system was constructed, an evaluation method for the effect of groundwater overexploitation restoration was established, and the effects were evaluated for Hebei Province, China, from 2014 to 2019. The results showed that the effect of groundwater overexploitation restoration in Hebei Province was obvious, and the grade of the groundwater overexploitation restoration effect improved from fair to good. The grade of the groundwater overexploitation restoration effect in most cities was improved to good. The measures that most affected the effect of groundwater overexploitation restoration in Hebei Province are strict control of extraction and reduction of consumption, while measures such as the replacement of water sources also play a significant role. An evaluation indicator system constructed in this paper can help to promote sophisticated effect evaluation of groundwater overexploitation restoration and improve the understanding and management of groundwater overexploitation restoration. HIGHLIGHTS An evaluation indicator system covering the groundwater–economic society–ecological environment system is constructed.; An evaluation method for the effect of groundwater overexploitation restoration is established.; The evaluation method is applied at both provincial and municipal levels in Hebei Province, one of the most severe groundwater overexploitation areas in the world.;

Abstract Our previous studies have showed that C-C motif chemokine ligand 20 (CCL20) advanced tumor progression and enhanced the chemoresistance of cancer cells by positively regulating breast cancer stem cell (BCSC) self-renewal. However, it is unclear whether CCL20 affects breast cancer progression by remodeling the tumor microenvironment (TME). Here, we observed that polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) were remarkably enriched in TME of CCL20-overexpressing cancer cell orthotopic allograft tumors. Mechanistically, CCL20 activated the differentiation of granulocyte-monocyte progenitors (GMPs) via its receptor C-C motif chemokine receptor 6 (CCR6) leading to the PMN-MDSC expansion. PMN-MDSCs from CCL20-overexpressing cell orthotopic allograft tumors (CCL20-modulated PMN-MDSCs) secreted amounts of C-X-C motif chemokine ligand 2 (CXCL2) and increased ALDH+ BCSCs via activating CXCR2/NOTCH1/HEY1 signaling pathway. Furthermore, C-X-C motif chemokine receptor 2 (CXCR2) antagonist SB225002 enhanced the docetaxel (DTX) effects on tumor growth by decreasing BCSCs in CCL20high-expressing tumors. These findings elucidated how CCL20 modulated the TME to promote cancer development, indicating a new therapeutic strategy by interfering with the interaction between PMN-MDSCs and BCSCs in breast cancer, especially in CCL20high-expressing breast cancer.

DDX4, a conserved germline factor and RNA helicase, increases small cell lung cancer cell survival by regulating DNA damage and immune response pathways and contributes to cisplatin-mediated drug resistance.

Background Although the antitumor efficacy of docetaxel (DTX) has long been attributed to the antimitotic activities, its impact on the tumor microenvironment (TME) has recently gained more attention. Macrophages are a major component of the TME and play a critical role in DTX efficacy; however, the underlying action mechanisms remain unclear.Methods DTX chemotherapeutic efficacy was demonstrated via both macrophage depletion and C–C motif chemokine ligand 3 (Ccl3)-knockout transgenic allograft mouse model. Ccl3-knockdown and Ccl3-overexpressing breast cancer cell allografts were used for the in vivo study. Combination therapy was used to evaluate the effect of Ccl3 induction on DTX chemosensitivity. Vital regulatory molecules and pathways were identified using RNA sequencing. Macrophage phagocytosis of cancer cells and its influence on cancer cell proliferation under DTX treatment were assessed using an in vitro coculture assay. Serum and tumor samples from patients with breast cancer were used to demonstrate the clinical relevance of our study.Results Our study revealed that Ccl3 induced by DTX in macrophages and cancer cells was indispensable for the chemotherapeutic efficacy of DTX. DTX-induced Ccl3 promoted proinflammatory macrophage polarization and subsequently facilitated phagocytosis of breast cancer cells and cancer stem cells. Ccl3 overexpression in cancer cells promoted proinflammatory macrophage polarization to suppress tumor progression and increase DTX chemosensitivity. Mechanistically, DTX induced Ccl3 by relieving the inhibition of cAMP-response element binding protein on Ccl3 via reactive oxygen species accumulation, and Ccl3 then promoted proinflammatory macrophage polarization via activation of the Ccl3–C-C motif chemokine receptor 5–p38/interferon regulatory factor 5 pathway. High CCL3 expression predicted better prognosis, and high CCL3 induction revealed better DTX chemosensitivity in patients with breast cancer. Furthermore, both the Creb inhibitor and recombinant mouse Ccl3 significantly enhanced DTX chemosensitivity.Conclusions Our results indicate that Ccl3 induced by DTX triggers proinflammatory macrophage polarization and subsequently facilitates phagocytosis of cancer cells. Ccl3 induction in combination with DTX may provide a promising therapeutic rationale for increasing DTX chemosensitivity in breast cancer.

Shandong Province (SDP) experienced serious land subsidence from March 2017 to December 2020. Exploring the response relationships between land subsidence and its inducing factors plays an important role in ensuring the development of the economy and residential safety. Firstly, we applied Persistent Scatterers Interferometric Aperture Radar (PS-InSAR) technology to 558 Sentinel-1 images to determine the land subsidence in SDP from March 2017 to December 2020. Secondly, we mosaicked the land subsidence monitoring results of five tracks to obtain a land subsidence map covering the whole SDP and validated the land subsidence monitoring results using Global Positioning System (GPS) monitoring results and leveling benchmark monitoring results observed in the same period. Finally, the response relationships between the land subsidence and its inducing factors in SDP were analyzed. The findings are as follows: (1) the PS-InSAR outcomes showed that the land subsidence was widely distributed in SDP and that the maximum land subsidence rate was −298.9 mm/year during the study period. (2) The PS-InSAR monitoring results coincide well with the GPS monitoring results and leveling benchmark monitoring results; the Pearson correlation coefficient (PCC) values between the PS-InSAR monitoring results and the GPS measurement results and leveling benchmark monitoring results were 0.97 and 0.98, respectively. We found that Spearman’s rank correlation coefficient (SRCC) values between any two adjacent tracks of the mosaic PS-InSAR monitoring results were greater than 0.95, indicating good consistency. (3) The long-term overexploitation of groundwater in middle and deep aquifers and mining of underground mineral resources are the main inducing factors of land subsidence in SDP when considering this problem on a large geographical scale. Moreover, the type of bridge material is an important inducing factor causing the large variation in the land subsidence of the bridge body within a small geographical range. These findings may provide scientific support for land subsidence control measures in SDP.

In metropolitan areas, the static load of high-rise buildings may result in uneven settlement, which seriously threatens residents’ living safety. Studying the response relationship between the additional stress of high-rise buildings and foundation settlement plays an important role in ensuring the safe development of metropolitan cities. Firstly, based on Persistent Scatterers Interferometric Aperture Radar (PS-InSAR) technology, we used 68 descending TerraSAR-X images to obtain the surface settlement in the study area from April 2010 to October 2018, which were validated with leveling benchmark monitoring results. Secondly, we calculated the additional stress of the building loads to quantify its effect on the uneven settlement in the Central Business District (CBD) of Beijing. Finally, two sets of characteristic points were selected to analyze the response relationships between foundation settlement and additional stress generated by building loads. The findings show: (1) The surface settlement rate varied from −145.2 to 24 mm/year in the Beijing Plain. The InSAR results agree well with the monitoring results derived from the leveling benchmark; the Pearson correlation coefficients were 0.98 and 0.95 in 2011–2013 and 2015–2016, respectively. (2) The stress results show that the depth of the influence of the static load of high-rise buildings was 74.9 m underground in the CBD. (3) The spatial distribution pattern of the additional stress is consistent with the foundation settlement. A characteristic point with greater additional stress in the same group has a higher foundation settlement rate. This relationship has also been found between the uneven foundation settlement and additional stress gradients. These findings provide scientific support for mitigating economic losses due to foundation settlement caused by additional stresses derived from building loads.

Cancer stem cells (CSCs) refer to a subpopulation of cancer cells responsible for tumorigenesis, metastasis, and drug resistance. Increasing evidence suggests that CSC-associated tumor neovascularization partially contributes to the failure of cancer treatment. In this review, we discuss the roles of CSCs on tumor-associated angiogenesis via trans-differentiation or forming the capillary-like vasculogenic mimicry, as well as the roles of CSCs on facilitating endothelial cell-involved angiogenesis to support tumor progression and metastasis. Furthermore, we discuss the underlying regulation mechanisms, including the intrinsic signals of CSCs and the extrinsic signals such as cytokines from the tumor microenvironment. Further research is required to identify and verify some novel targets to develop efficient therapeutic approaches for more efficient cancer treatment through interfering CSC-mediated neovascularization.

As a common geological hazard, land subsidence is widely distributed in the Eastern Beijing Plain. The pattern of evolution of this geological phenomenon is controlled by many factors, including groundwater level change in different aquifers, compressible layers of different thicknesses, and static and dynamic loads. First, based on the small baseline subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique, we employed 47 ENVISAT ASAR images and 48 RADARSAT-2 images to acquire the ground deformation of the Beijing Plain from June 2003 to November 2015 and then validated the results using leveling benchmark monitoring. Second, we innovatively calculated additional stress to obtain static and dynamic load information. Finally, we evaluated the contribution rate of the influencing factors to land subsidence by using the Spearman’s rank correlation coefficient (SRCC) and extremely randomized trees (ERT) machine learning methods. The SBAS-InSAR outcomes revealed that the maximum deformation rate was 110.7 mm/year from 2003 to 2010 and 144.4 mm/year from 2010 to 2015. The SBAS-InSAR results agreed well with the leveling benchmark monitoring results; the correlation coefficients were 0.97 and 0.96 during the 2003–2010 and 2013–2015 periods, respectively. The contribution rate of the second confined aquifer to the cumulative land subsidence was 49.3% from 2003 to 2010, accounting for the largest proportion; however, its contribution rate decreased to 23.4% from 2010 to 2015. The contribution rate of the third confined aquifer to the cumulative land subsidence increased from 2003 to 2015. Although the contribution of additional stress engendered from static and dynamic loads to the cumulative land subsidence was slight, it had a significant effect on the uneven land subsidence, with a contribution rate of 33.8% from 2003 to 2010 and 23.1% from 2010 to 2015. These findings provide scientific support for mitigating hazards associated with land subsidence.

Medullary thyroid cancers (MTCs) are derived from calcitonin-producing cells (C cells) of neuroendocrine origin. Rb heterozygous mice develop low-grade C cell adenocarcinoma following biallelic inactivation of the Rb tumor suppressor gene loci. Additional inactivation of another tumor suppressor gene such as Trp53, Arf or Cdkn1a allows Rb-deficient mice to generate more aggressive C cell adenocarcinoma (Takahashi et al., 2006; Shamma et al., 2009; Kitajima et al., 2015). To characterize C cell adenocarcinoma cells derived from Rb-deficient mice of different genetic backgrounds, we attempted to extract C cell adenocarcinoma cells from primary thyroid tumor tissue. Since primary mouse small cell lung cancer (SCLC) cells those originate in neuroendocrine cells that also stems C cells, can be established both as non-adhesive and adhesive cells (Calbo et al., 2011), we applied their method to MTCs. Here we describe our isolation technique for non-adhesive and adhesive cell cultures from primary medullary thyroid tumor tissue. We found that the molecular markers of C cell such as Calcitonin and Ascl1 are predominantly enriched in the non-adhesive population (Kitajima et al., 2015). This is in line with the fact that one of most commonly distributed human MTC cell line TT is non-adhesive.

Targets faced by inverse synthetic aperture radar (ISAR) are often non-cooperative, with target maneuvering being the main manifestation of this non-cooperation. Maneuvers cause ISAR imaging results to be severely defocused, which can create huge difficulties in target identification. In addition, as the ISAR bandwidth continues to increase, the impact of migration through resolution cells (MTRC) on imaging results becomes more significant. Target non-cooperation may also result in sparse aperture, leading to the failure of traditional ISAR imaging algorithms. Therefore, this paper proposes an algorithm to realize MTRC correction and sparse aperture ISAR imaging for maneuvering targets simultaneously named whale optimization algorithm–fast iterative shrinkage thresholding algorithm (WOA-FISTA). In this algorithm, FISTA is used to perform MTRC correction and sparse aperture ISAR imaging efficiently and WOA is adopted to estimate the rotational parameter to eliminate the effects of maneuvering on imaging results. Experimental results based on simulation and measured datasets prove that the proposed algorithm implements sparse aperture ISAR imaging and MTRC correction for maneuvering targets simultaneously. The proposed algorithm achieves better results than traditional algorithms under different signal-to-noise ratio conditions.

Abstract In ISAR imaging, echo signals of complex manoeuvring targets have to be modelled as multi‐component cubic phase signals (m‐CPS). In this condition, the Doppler diffusion will seriously affect the quality of ISAR imaging. Herein, a complex manoeuvring target imaging method based on local polynomial transform‐fast chirp Fourier transform (LPT‐FCFT) is proposed. In this method, the instantaneous frequency and the quadratic chirp rate of the echo signal are estimated by local polynomial transformation, then the chirp rate and the amplitude are estimated by fast chirp Fourier transform, and finally the high‐resolution ISAR image of the complex manoeuvring target is obtained by CLEAN technology. Compared with the traditional method, the proposed method has the advantages of less computational complexity, clearer imaging results and better anti‐noise performance. Simulation results indicate the effectiveness and superiority of the proposed method.

Rolling bearing fault diagnosis is conventionally performed by vibration-based diagnosis (VBD). However, VBD is restrained in some cases because vibration measurement usually requires the contact with the machine. Acoustical-based fault diagnosis (ABD) has the advantage of non-contact measurement over VBD. However, ABD has received little attention and rarely applied in bearing fault diagnosis. In this paper, a new non-contact ABD method for rolling bearings using acoustic imaging and convolutional neural networks (CNN) is proposed. Firstly, a microphone array is used to acquire the acoustic field radiated by rolling bearings. Then, acoustic imaging is performed with the wave superposition method (WSM). The reconstructed acoustic images can depict the spatial distribution of the acoustic field, which add a new spatial dimension in the acoustic data representation for fault diagnosis and makes it possible to localize the sound sources. Finally, CNN is applied to accomplish bearing fault diagnosis, which can overcome the problems of handcrafted feature extraction in traditional ABD methods. Experimental results verify the effectiveness of the proposed ABD method. Comparisons with peer state-of-the-art ABD methods further validate that the proposed method can mitigate the drawbacks of the existing ABD methods, and obtain more accurate and reliable diagnosis results.

In machinery fault diagnosis, a large amount of monitoring data is often unlabeled, while the number of labeled data is limited. Therefore, learning effective features from massive unlabeled data is a challenging issue for machinery fault diagnosis. In this paper, a simple unsupervised feature learning method, consistency inference-constrained sparse filtering (CICSF), is proposed to learn mechanical fault features with enhanced clustering performance for fault diagnosis. Firstly, inspired by the data augmentation strategy, consistency inference of latent representations for time series (CILRTS) is derived, which infers that training data instances segmented from the same time series should possess consistent latent feature representations. Then, CILRTS is integrated into sparse filtering (SF) as an additional constraint in the latent feature space. The developed CICSF method can optimize the inter-class sparsity and intra-class similarity of the feature distribution simultaneously. Thus, it can learn more effective features from massive unlabeled data. Finally, based on CICSF, a semi-supervised machinery fault diagnosis method is developed. After unsupervised feature learning by CICSF, a softmax regression classifier is trained with limited labeled data to realize machinery fault diagnosis. Experimental results on bearing and gearbox datasets verify the effectiveness of the proposed method. Moreover, comparisons with standard SF and several auto-encoder (AE) variants validate its superiority in unsupervised feature learning and fault diagnosis using limited labeled data.

Translational motion compensation is a prerequisite of inverse synthetic aperture radar (ISAR) imaging. Translational motion compensation for datasets with low signal-to-noise ratio (SNR) is important but challenging. In this work, we proposed a noise-robust translational motion compensation method based on high-order local polynomial transform–generalized scaled Fourier transform (HLPT-GSCFT). We first model the translational motion as a fourth-order polynomial according to order-of-magnitude analysis, and then design HLPT-GSCFT for translation parameter estimation and parametric translational motion compensation. Specifically, HLPT is designed to estimate the acceleration and third-order acceleration of the translational motion and GSCFT is introduced to estimate the second-order acceleration. Both HLPT and GSCFT have a strong ability for cross-term suppression. In addition, we use a minimum weighted entropy algorithm to estimate the velocity of the translational motion, which can improve the noise robustness of the parameter estimation. Experimental results based on a measured dataset prove that the proposed method is effective and noise-robust.

In inverse synthetic-aperture radar (ISAR) imaging, it is essential to deal with the Doppler ambiguity of group targets with complex maneuvers in order to avoid the bias of target position towards the actual value. Simultaneously, migration through resolution cell (MTRC) under the Doppler ambiguity is unable to be compensated for as a preprocessing. Traditional ISAR imaging methods for maneuvering targets, however, are undesirable to handle the severe deformation and defocusing in the imaging results induced by the Doppler ambiguity and MTRC. In this paper, we propose a novel and effective ISAR imaging method to improve the imaging quality by removing the Doppler ambiguity and compensating for the MTRC. Specifically, we first model the echo as a multi-component cubic phase signal (m-CPS) and design a high-order instantaneous autocorrelation function–generalized scaled Fourier transform (HIAF–GSCFT) to process the echo. This is to estimate the rotational parameters without MTRC compensation. Then, a maximum weighted contrast algorithm is used to remove the Doppler ambiguity, followed by reconstructing the echo. Compared with the existing method, the proposed method can accurately estimate the rotational parameters under the existing MTRCs and achieves a high-quality ISAR image for group targets, with complex maneuvers without Doppler ambiguity. Experiments of simulated and measured datasets validate its effectiveness and robustness for single target and group targets.