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Abstract Delta opioid receptor (δOR) plays a pivotal role in modulating human sensation and emotion. It is an attractive target for drug discovery since, unlike Mu opioid receptor, it is associated with low risk of drug dependence. Despite its potential applications, the pharmacological properties of δOR, including the mechanisms of activation by small-molecule agonists and the complex signaling pathways it engages, as well as their relation to the potential side effects, remain poorly understood. In this study, we use cryo-electron microscopy (cryo-EM) to determine the structure of the δOR-Gi complex when bound to a small-molecule agonist (ADL5859). Moreover, we design a series of probes to examine the key receptor-ligand interaction site and identify a region involved in signaling bias. Using ADL06 as a chemical tool, we elucidate the relationship between the β-arrestin pathway of the δOR and its biological functions, such as analgesic tolerance and convulsion activities. Notably, we discover that the β-arrestin recruitment of δOR might be linked to reduced gastrointestinal motility. These insights enhance our understanding of δOR’s structure, signaling pathways, and biological functions, paving the way for the structure-based drug discovery.

Abstract Background Simultaneous bilateral total hip arthroplasty (SI-THA) results in more blood loss and a greater need for postoperative allogeneic blood transfusion (ABT). Previous studies have reported that multimodal patient blood management (PBM) strategies were associated with a smaller effect of intraoperative cell salvage (ICS) in unilateral total hip arthroplasty. However, there are few studies on the role of ICS in SI-THA. This study aims to explore the effect of ICS with multimodal PBM strategies on SI-THA and to identify risk factors associated with ABT. Methods This retrospective matched cohort study included 72 patients in the ICS group and 72 patients in the control group who were matched according to age, sex, and year of hospitalization. Demographic data, hematological indicators, blood loss, and ABT were compared between the two groups. Logistic regression analysis was performed to identify independent risk factors for postoperative ABT. Postoperative outcomes were also recorded. Results In the cohort of 144 patients, 27 patients (37.5%) in the ICS group while 45 patients (62.5%) in the control group received postoperative ABT after SI-THA. Compared with the control group, the ICS group showed significant differences in terms of blood loss, postoperative hemoglobin and hematocrit. The transfused volume of allogeneic red blood cells per ABT patient was also lower in the ICS group. Multivariate logistic regression analysis indicated that sex, the utilization of ICS, and preoperative hematocrit level were identified as independent factors associated with postoperative ABT. The utilization of ICS significantly shortened off-bed time and length of hospital stay, but had no effect on early pain and functional outcomes. Conclusion The utilization of ICS can significantly affect postoperative ABT in SI-THA patients with multimodal PBM strategies. Sex, the utilization of ICS and preoperative hematocrit level were identified as independent factors associated with postoperative ABT. The utilization of ICS promoted weight-bearing functional exercises, but had no effect on early outcomes.

Aiming at the influence of hard and thick roof fracture and structural evolution on the impact of working face, taking the hard and thick roof condition of 63 upper 05 working face in Dongtan Coal Mine as the engineering background, the critical condition and structural evolution process of hard and thick roof fracture and instability are studied by theoretical analysis and numerical simulation, and the dangerous area of working face impact is divided. It is concluded that the thickness and strength of the roof are proportional to the vertical load at the end of the block breaking. The structure of immediate roof and main roof gradually evolved from “V” type to “U” type. The first and periodic steps of the double hard thick roof increase obviously compared with the conventional condition, and the evolution of the basic roof structure is more retarded than that of the direct roof. The vertical stress of the roof evolves in the form of stress arch, and many stress concentration phenomena are formed in the mined-out area during mining. Based on the above research results, the impact danger area of 63 upper 05 working face was divided and the accuracy was verified by microseismic monitoring technology.

Multifunctional therapeutics have emerged as a solution to the constraints imposed by drugs with singular or insufficient therapeutic effects. The primary challenge is to integrate diverse pharmacophores within a single-molecule framework. To address this, we introduced DeepSA, a novel edit-based generative framework that utilizes deep simulated annealing for the modification of articaine, a well-known local anesthetic. DeepSA integrates deep neural networks into metaheuristics, effectively constraining molecular space during compound generation. This framework employs a sophisticated objective function that accounts for scaffold preservation, anti-inflammatory properties, and covalent constraints. Through a sequence of local editing to navigate the molecular space, DeepSA successfully identified AT-17, a derivative exhibiting potent analgesic properties and significant anti-inflammatory activity in various animal models. Mechanistic insights into AT-17 revealed its dual mode of action: selective inhibition of NaV1.7 and 1.8 channels, contributing to its prolonged local anesthetic effects, and suppression of inflammatory mediators via modulation of the NLRP3 inflammasome pathway. These findings not only highlight the efficacy of AT-17 as a multifunctional drug candidate but also highlight the potential of DeepSA in facilitating AI-enhanced drug discovery, particularly within stringent chemical constraints.

BackgroundIn patients with tibial plateau bone cysts undergoing total knee arthroplasty (TKA), bone defects commonly occur following tibial plateau resection. Current strategies for addressing these defects include bone grafting, bone cement filling, and the cement-screw technique. However, there remains no consensus on the optimal approach to achieve the best surgical outcomes. This study aims to evaluate the most effective repair method for residual bone defects following tibial plateau bone cyst repair during TKA from a biomechanical perspective.MethodsThe treatment options for tibial plateau bone defects were classified into four categories: no treatment, cancellous bone filling, bone cement filling, and the cement-screw technique. Finite-element analysis (FEA) was employed to evaluate stress distribution and displacement across the models for each treatment group. In addition, static compression mechanical tests were used to assess the displacement of the models within each group.ResultsFEA results indicate that when employing the cement-screw technique to repair tibial plateau bone defects, the maximum stress on the prosthesis and the cement below the prosthesis is minimized, while the maximum stress on the cancellous bone is maximized. And the displacement of each component is minimized. Biomechanical tests results further demonstrate that the displacement of the model is minimized when utilizing the cement-screw technique for tibial plateau bone defects.ConclusionUsing cement-screw technique in treating residual tibial bone defects due to bone cysts in TKA offers optimal biomechanical advantages.

Breast cancer (BRCA) is the most common cancer among women. Adriamycin (ADR), also known as doxorubicin (Dox), is a commonly used chemotherapeutic agent for BRCA patients, however, the susceptibility of tumor cells to develop resistance to Dox has severely limited its clinical use. One new promising therapeutic target for breast cancer patients is exosomes. The objective of this study was to investigate the role of exosomes in regulating Dox resistance in BRCA.In this study, the exosomes from both types of cells were extracted by differential centrifugation. The effect of exosomes on drug resistance was assessed by laser confocal microscopy, MTT assay, and qRT-PCR. The miRNA was transfected into cells using Lipofectamine 2000, which was then evaluated for downstream genes and changes in drug resistance.Exosomes from MCF-7 cells (MCF-7/exo) and MCF-7/ADR cells (ADR/exo) were effectively extracted in this study. The ADR/exo was able to endocytose MCF-7 cells and make them considerably more resistant to Dox. Moreover, we observed a significant difference in miR-34a-5p expression in MCF-7/ADR and ADR/exo compared to MCF-7 and MCF-7/exo. Among the miR-34a-5p target genes, NOTCH1 displayed a clear change with a negative correlation. In addition, when miR-34a-5p expression was elevated in MCF-7/ADR cells, the expression of miR-34a-5p in ADR/exo was also enhanced alongside NOTCH1, implying that exosomes may carry miRNA into and out of cells and perform their function.In conclusion, exosomes can influence Dox resistance in breast cancer cells by regulating miR-34a-5p/NOTCH1. These findings provide novel insights for research into the causes of tumor resistance and the enhancement of chemotherapy efficacy in breast cancer.

According to the World Health Organization's world report on hearing, nearly 2.5 billion people worldwide will suffer from hearing loss by 2050, which may contribute to a severe impact on individual life quality and national economies. Sensorineural hearing loss (SNHL) occurs commonly as a result of noise exposure, aging, and ototoxic drugs, and is pathologically characterized by the impairment of mechanosensory hair cells of the inner ear, which is mainly triggered by reactive oxygen species accumulation, inflammation, and mitochondrial dysfunction. Though recent advances have been made in understanding the ability of cochlear repair and regeneration, there are still no effective therapeutic drugs for SNHL. Chinese herbal medicine which is widely distributed and easily accessible in China has demonstrated a unique curative effect against SNHL with higher safety and lower cost compared with Western medicine. Herein we present trends in research for Chinese herbal medicine for the treatment of SNHL, and elucidate their molecular mechanisms of action, to pave the way for further research and development of novel effective drugs in this field.

Lignin is one of the building blocks of plant cell walls, and the study of the spectral characterization of its cleavage process can help to monitor the production and reuse of straw after decay. In this paper, four theoretical model structures of lignin formed by lignin G monomers and connected by β-O-4 bonding type were optimized and calculated based on the density functional theory using the B3LYP/3-21g and B3LYP/6-311g basis sets. The results showed that the theoretical infrared spectra of lignin increased sequentially in the absorption peaks of 1500 cm−1 blue shift and 2932 cm−1 and 1200 cm−1 red shift, while the latter three theoretical models showed new infrared absorption peaks of 716 cm−1 and 823 cm−1 due to the presence of the β-O-4 structure, which is of great value for the theoretical spectral study of organic macromolecules and also provides data support for the spectral change in lignin in the degradation of graminaceous plants.

The storage time of rice determines its quality and nutritional value, and the longer the storage time, the greater the impact. In this study, different excitation wavelengths (405 nm, 365 nm, 310 nm) were used to detect the fluorescence spectrum of “Dongdao 12” brown rice. Support vector machine (SVM), K-nearest neighbor (KNN), and wide neural network (WNN) were used for modeling and analysis. Under the excitation of 310 nm, the accuracy of WNN classification is up to 99.2%. In order to reduce the scattering effect and other interference in the data, multiplicative scatter correction (MSC), standard normal variable (SNV), and Savitzky–Goray smoothing (SG) preprocessing methods were used. The results showed that SG + KNN classification achieved an accuracy of 99.3% under 310 nm excitation. In order to further improve the classification accuracy, the original spectrum and the preprocessed spectrum under different excitation light sources were fused. The classification accuracy of all methods was improved, and the original data fusion was combined with the WNN model to reach 100%. It shows that fluorescence spectroscopy has excellent potential in identifying rice storage years.

Abstract The brain consists of the left and right cerebral hemispheres and both are connected by callosal projections. Less is known about the basic mechanism of this cortical-cortical connection and its functional importance. Here we investigate the cortical-cortical connection between the bilateral anterior cingulate cortex (ACC) by using the classic electrophysiological and optogenetic approach. We find that there is a direct synaptic projection from one side ACC to the contralateral ACC. Glutamate is the major excitatory transmitter for bilateral ACC connection, including projections to pyramidal cells in superficial (II/III) and deep (V/VI) layers of the ACC. Both AMPA and kainate receptors contribute to synaptic transmission. Repetitive stimulation of the projection also evoked postsynaptic Ca2+ influx in contralateral ACC pyramidal neurons. Behaviorally, light activation of the ACC-ACC connection facilitated behavioral withdrawal responses to mechanical stimuli and noxious heat. In an animal model of neuropathic pain, light inhibitory of ACC-ACC connection reduces both primary and secondary hyperalgesia. Our findings provide strong direct evidence for the excitatory or facilitatory contribution of ACC-ACC connection to pain perception, and this mechanism may provide therapeutic targets for future treatment of chronic pain and related emotional disorders.

The origin of agricultural products significantly influences their quality and safety. Fluorescence spectroscopy was used to analyse Japonica rice 830, grown in different areas of Jilin Province, by examining rice seed, brown rice, and rice flour from 12 origins. Fluorescence spectra were pre-processed through normalisation and smoothing to remove noise. These processed spectra were input into decision trees, support vector machines (SVMs), K-nearest neighbour (KNN), and neural network models for classification. The analysis revealed that the combined four models achieved an average classification accuracy of 98.05% with a computation time of 180 s, while the reduced-scale models improved accuracy to 98.36% and reduced computation time to 11.25 s. Additionally, prediction models using standard rice starch content values across different states achieved R² values over 0.8. This method provides a rapid, precise approach for assessing rice quality and origin, demonstrating significant potential for application in rice analysis.

Abstract Rare earth element ore deposits associated with carbonatite derived from Earth’s mantle supply half of the world’s rare earth element. However, the formation of carbonatite and initial enrichment and transport of rare earth element in the mantle, is unclear. Here, we image the lithospheric architecture of a Cenozoic rare earth element ore belt in southwestern China by integrating seismic tomography with geochemical data. The subduction of the Indian continent caused vertical upwelling and lateral flow of the asthenosphere, which triggered the melting of the overlying subcontinental lithospheric mantle to generate carbonatites. Such a mantle source that previously metasomatized by fluids from recycled marine sediments is a precursor process critical for forming a giant rare earth element system. For the studied ore belt, three key factors are prerequisites to generating ore-forming carbonatites: thick lithosphere with a continental root; prior fertilization of the subcontinental lithospheric mantle; and trans-lithospheric weakness for magma ascent.

In order to study the mechanical response and crack evolution law of different lithologic rock bodies under different stress environments in deep stress mines, based on the deviator stress theory, the actual triaxial disturbance unloading rock test system was used to simulate the stress occurrence environment of the original rock. The mechanical characteristics of different σ2 coal rock masses were studied, and the crack evolution law of coal and sandstone under different stress environments was analyzed. The results show that the increase of σ2 inhibits the deformation in the σ2 direction of coal and sandstone, promotes the expansion and deformation in the σ3 direction, and enhances its peak strength and elastic modulus. The development characteristics of internal cracks in rock mass are directly related to the stress environment, and the increase of σ2 promotes the increase of the proportion of coal RA value, weakens the proportion of sandstone RA value, aggravates the development of coal internal shear cracks, and inhibits the development of internal shear cracks in sandstone. The larger σ2, the greater the initial AE ringing count of coal and sandstone, and the greater the AE cumulative energy when the rock mass is finally damaged. At the same time, due to the self-organizing behavior in the process of crystal failure in sandstone, the cumulative energy curve of sandstone fluctuates in a step-like manner. The ringing count and cumulative energy increase suddenly, which can predict the imminent instability and failure of the rock, and the research results can provide an experimental basis for the sudden instability of deep high-stress roadways.

Abstract Few‐shot learning (FSL) attempts to learn and optimise the model from a few examples on image classification, which is still threatened by data scarcity. To generate more data as supplements, data augmentation is considered as a powerful and popular technique to enhance the robustness of few‐shot models. However, there are still some weaknesses in applying augmentation methods. For example, all augmented samples have similar semantic information with respect to different augmented transformations, which makes these traditional augmentation methods incapable of learning the property being varied. To address this challenge, we introduce multi‐task learning to learn a primary few‐shot classification task and an auxiliary self‐supervised task, simultaneously. The self‐supervised task can learn transformation property as auxiliary self‐supervision signals to improve the performance of the primary few‐shot classification task. Additionally, we propose a simple, flexible, and effective mechanism for decision fusion to further improve the reliability of the classifier, named model‐agnostic ensemble inference (MAEI). Specifically, the MAEI mechanism can eliminate the influence of outliers for FSL using non‐maximum suppression. Extensive experiment results demonstrate that our method can outperform other state‐of‐the‐art methods by large margins.

ABSTRACT: The comprehensive use and efficient management of straw are significant for agriculture's green and low-carbon transformation. This paper uses literature research and comparative analysis to systematically review the literature on comprehensive straw utilization and governance policy research in China over the past five years. The current literature has explored two major directions: regional and industrial policies and the main actors involved in the comprehensive use of straw. The research is complementary and fruitful concerning both micro and macro perspectives; however, the extant literature suffers from a lack of attention to straw intermediaries and enterprises and a lack of research across time. Therefore, this paper provides an outlook for future research. In the future, scholars should pay more attention to straw intermediaries and enterprises, conduct continuous observations of multiple regions over time to obtain panel data, and further test the heterogeneity of factors to obtain more scientific and valid results.

The AlGaN photocathode with a superlattice emission layer was grown by metal organic chemical vapor deposition. The existence of the superlattice structure was confirmed using a transmission electron microscope, and its optical and electrical properties were measured. The results showed that the introduction of a superlattice emission layer can reduce the transmittance and reflectance at 275 nm and improve the absorption of incident light. In particular, the Hall measurement results indicate that the introduction of a superlattice structure can significantly increase the concentration of holes in the AlGaN photocathode material. The activation experiment demonstrated that the photocurrent of the AlGaN photocathode subassembly with a superlattice structure increased significantly after Cs/O activation and that it showed better photoemission performance. The increase in the incident light absorption to produce more photoelectrons, the enhancement of photoelectron transport capacity by the polarized electric field generated by the superlattice structure, and the reduction in the surface barrier caused by the higher hole concentration were responsible for the significant improvement in photoemission performance.

Breast cancer is the most prevalent malignancy among women. Doxorubicin (Dox) resistance was one of the major obstacles to improving the clinical outcome of breast cancer patients. The purpose of this study was to investigate the relationship between the FABP signaling pathway and Dox resistance in breast cancer. The resistance property of MCF-7/ADR cells was evaluated employing CCK-8, Western blot (WB), and confocal microscopy techniques. The glycolipid metabolic properties of MCF-7 and MCF-7/ADR cells were identified using transmission electron microscopy, PAS, and Oil Red O staining. FABP5 and CaMKII expression levels were assessed through GEO and WB approaches. The intracellular calcium level was determined by flow cytometry. Clinical breast cancer patient’s tumor tissues were evaluated by immunohistochemistry to determine FABP5 and p-CaMKII protein expression. In the presence or absence of FABP5 siRNA or the FABP5-specific inhibitor SBFI-26, Dox resistance was investigated utilizing CCK-8, WB, and colony formation methods, and intracellular calcium level was examined. The binding ability of Dox was explored by molecular docking analysis. The results indicated that the MCF-7/ADR cells we employed were Dox-resistant MCF-7 cells. FABP5 expression was considerably elevated in MCF-7/ADR cells compared to parent MCF-7 cells. FABP5 and p-CaMKII expression were increased in resistant patients than in sensitive individuals. Inhibition of the protein expression of FABP5 by siRNA or inhibitor increased Dox sensitivity in MCF-7/ADR cells and lowered intracellular calcium, PPARγ, and autophagy. Molecular docking results showed that FABP5 binds more powerfully to Dox than the known drug resistance-associated protein P-GP. In summary, the PPARγ and CaMKII axis mediated by FABP5 plays a crucial role in breast cancer chemoresistance. FABP5 is a potentially targetable protein and therapeutic biomarker for the treatment of Dox resistance in breast cancer.

Ultrasound cycloplasty(UCP)procedure using high intensity focused ultrasound(HIFU)is a new non-invasive glaucoma treatment based on miniaturized transducers. In recent years, the safety and efficacy of UCP on various types of glaucoma have been well verified, and it has shown broad application prospects in the treatment of glaucoma. This article collects and reviews the relevant literature on glaucoma treatment by UCP, and summarizes the information on the development of equipment, composition and operation, treatment mechanisms, indications, efficacy and safety, with the purpose to provide relevant basis for clinical applications and future research.

Titanite is a widespread accessory mineral in igneous, metamorphic, and hydrothermal rocks, but few comply with gem-grade requirements. Previous studies on Moroccan titanite focused on elementary composition and U-Pb dating. In this study, two gem-grade titanites (MA-1 and MA-2) from the Moroccan Central High Atlas were investigated through gemological and chemical studies, including infrared spectrum, Raman spectrum, SEM-EDS, and LA-ICP-MS. Two titanite samples are yellow, transparent–translucent with a greasy luster, 3.5 and 2.5 mm long. MA-1 and MA-2 have similar gemological properties, the refractive index (RI) is beyond the range of the refractometer (>1.78), the specific gravity (SG) values fall in the range of 3.52~3.54 and both are inert to short-wave and long-wave UV radiation. The spectral characteristics have high consistency with the RRUFF database. The major elements’ composition shows a negative correlation between Al, Fe, V, and Ti, suggesting the titanites underwent substitutions such as (Al, Fe3+) + (F, OH) ↔ Ti + O. The titanite samples, characterized by a low abundance of REE (802~4088 ppm) and enriched in LREE, exhibit positive Eu (δEu: 1.53~7.79) and Ce (δCe: 1.08~1.33) anomalies, indicating their formation in a hydrothermal environment with low oxygen fugacity. The 238U/206Pb and 207Pb/206Pb ratios of the titanites yield lower intercept ages of 152.6 ± 2.2 and 151.4 ± 5.3 Ma (1s), consistent with their weighted average 206Pb/238U ages of 152.3 ± 2.0 and 150.7 ± 3.2 Ma (1s) respectively. The results of U-Pb dating are matched with the second main magmatic activities in the High Atlas intracontinental belt of Morocco during the Mesozoic to Cenozoic period. Moreover, the two titanite samples have almost no radiational damage. All the results show that the titanite from High Atlas, Morocco, has the potential to be a reference material for LA-ICP-MS U–Pb dating, but further experiments are needed to be sure.

Abstract The pharmacological interventions aimed at activating pathways inducing chondrocyte autophagy or reversing extracellular matrix degradation may be promising approaches for the management of osteoarthritis (OA). Evidence exists suggesting that sirtuin 1 (SIRT1) is involved in the pathogenesis of OA. The present study aimed to explore the regulatory role and downstream mechanisms of SIRT1 in OA. Bioinformatics predictions identified downstream factors phosphatase and tensin homolog (PTEN) and epidermal growth factor receptor (EGFR) in OA. We validated poorly expressed SIRT1 and EGFR and highly expressed PTEN in cartilage tissues of OA patients. OA was induced in vitro by exposing human primary chondrocytes to IL-1β and in vivo by destabilization of the medial meniscus (DMM) in a mouse model. SIRT1 knockdown was found to augment IL-1β-stimulated inflammation and chondrocyte metabolic imbalance. Knockdown of SIRT1 diminished PTEN acetylation and then enhanced PTEN expression. PTEN inactivation decreased EGFR ubiquitination and promoted EGFR expression by destabilizing the EGFR-Cbl complex, which in turn inhibited extracellular matrix degradation in cartilage tissues and activated chondrocyte autophagy. In the DMM mouse model, knockdown of SIRT1 inhibited chondrocyte autophagy, promoted metabolic imbalance, thus accelerating osteoarthritic process. In conclusion, SIRT1 represses the ubiquitination of EGFR by down-regulating PTEN, inhibits extracellular matrix degradation and activates chondrocyte autophagy, thereby performing an OA-alleviating role.

Objective To determine the effect of overworking on vascular smooth muscle cells (VSMC) in rats. Methods Clean SD rats were randomly divided into control group (CON), overworking group (OW) and overworking and sleep deficiency group (OW+SD). The rat model of overworking was established by exhaustive swimming in the latter 2 groups, and the rats of the last group was subjected to sleep deprivation with an underwater platform. In 15 d later, the abdominal aorta of rats was collected for pathological observation by HE staining, and the thickness of media was measured with aid of Image J software. The intracellular ultrastructure was observed by transmission electron microscopy. The apoptotic rate of VSMC was detected by TUNEL, the mRNA expression of Caspsae-3, Bax, Bcl-2 and Ki67 in the VSMC were detected by RT-qPCR, and the content of apoptotic protein Caspase-3 was measured by immunohistochemical assay. Results ① The results of HE staining showed that VSMC were in disordered arrangment and formed vacuole-like cells in the OW and OW+SD groups, and the vascular intima-media thickness was significantly thicker in the OW and OW+SD groups than the CON group (P < 0.05). ② Electron microscopy displayed the apoptotic bodies in the VSMC of the OW and OW+SD groups. ③TUNEL results showed that the apoptotic rate of VSMC was significantly higher in the OW and OW+SD groups than the CON group (P < 0.05). ④RT-qPCR showed that the expression levels of Bax and Ki67 were significantly increased (P < 0.05), while those of Caspase-3 and Bcl-2 were not obviously changed in OW and OW+SD groups (P>0.05) when compared with the CON group. ⑤ Immunohistochemical results showed that the protein content of Caspase-3 in vascular middle membrane of the OW and OW+SD groups was increased significantly than that in the CON group (P < 0.05). Conclusion Overworking aggravates the apoptosis of VSMC and induces the proliferation and repair of VSMC, which form the pathological basis of early arterial lesions. During the experimental time, sleep could not alleviate the injury of VSMC caused by overworking.

Based on adopting the global super-efficiency slacks-based measure (GSSBM) model to calculate green innovation efficiency (GIE), this paper systematically investigates GIE’s overall difference, distribution dynamics and convergence trends in eight national urban agglomerations (UAs) of China from 2004 to2018 by combining the methods of Dagum Gini Coefficient (DGC), Kernel Density Estimation (KDE), Variation Coefficient (VC), fixed-effect model (FEM) and spatial Durbin model (SDM). The results show that: (1) the average GIE of eight UAs was 0.632 during 2004–2018, which is generally low and has substantial potential for improvement, and seven of them achieved positive growth with an annual average growth rate of 2.70%. (2) The overall difference of GIE within eight UAs was significant with the inter-UA difference as the main contributor. (3) The distribution curves of GIE in eight UAs were distinct in terms of location, form, ductility and polarization trend. (4) Besides five UAs presenting significant σ convergence characteristics, all eight UAs displayed significant absolute or conditional β convergence trends with different speeds and cycles. The findings of this paper can provide important insights on the promotion of green innovation-driven development for UAs in China.

Based on employing the global super efficiency epsilon-based measure (GSE-EBM) model to evaluation the green innovation efficiency (GIE) of 285 prefecture-level or above cities in China during the period 2004–2018, this paper combines the approaches of kernel density estimation, cold hot spot analysis and standard deviation ellipse to intuitively describe GIE’s spatiotemporal pattern evolution features, and then utilizes the geographical weighted regression (GWR) model to explore the spatial heterogeneity of GIE’s affecting factors. The results show that: (1) China’s urban GIE displayed a fluctuating increasing trend, revealing clearly regional disparities, and gradually decreased from the Eastern coastal region to the Central, the Western and the Northeast region. (2) The spatial difference of China’s urban GIE exhibited the characteristics of expansion, polarization, and spatial agglomeration with the center of gravity gradually shifting to the Southeast region. (3) In the analysis of socio-economic factors of China’s urban GIE, the GWR model effectively identified the spatial heterogeneity, and improved the explanatory ability compared to ordinary least squares (OLS) model. (4) The GWR model analysis indicate that population density, economic development, transportation infrastructure, openness and industrial structure played significant impacts on China’s urban GIE, and there exists significant spatial heterogeneity in the impact of each influencing factor. The findings of this study can provide valuable references for urban green transformation and high-quality development in China.

Abstract Objective High tibial osteotomy (HTO) has been used for the treatment of patients with knee osteoarthritis. However, the successful implementation of HTO requires precise intraoperative positioning, which places greater requirements on the surgeon. In this study, we aimed to design a new kind of 3D-printed patient-specific instrument (PSI) for HTO, including a positioning device and an angle bracing spacer, and verify its effectiveness using cadaveric specimens. Methods This study included ten fresh human lower-limb cadaveric specimens. Computed tomography (CT) and X-ray examinations were performed to make preoperative plans. PSI was designed and 3D-printed according to the preoperative plan. Then, the PSI was used to guide HTO. Finally, we performed X-ray and CT after the operation to verify its validity and accuracy. Results The PSI using process was adjusted according to the pre-experimental procedure in 1 case. Hinge fracture occurred in 1 case. According to X-rays of the remaining eight cadaveric specimens, no statistically significant difference was noted between the preoperative planning medial proximal tibial angle (MPTA) and postoperative MPTA (P > 0.05) or the preoperative and postoperative posterior slope angle (PSA) (P > 0.05). According to the CT of 10 cadaveric specimens, no statistically significant difference was noted between the design angle and actual angle, which was measured according to the angle between the osteotomized line and the cross section (P > 0.05). The gap between the designed osteotomy line and the actual osteotomy line was 2.09 (0.8 ~ 3.44) mm in the coronal plane and 1.58 (0.7 ~ 2.85) mm in the sagittal plane. Conclusion This 3D-printed PSI of HTO accurately achieves the angle and position of the preoperative plan without increasing the stripping area. However, its use still requires a certain degree of proficiency to avoid complications, such as hinge fracture.

Few-shot fine-grained image classification aims to solve the learning problem with few limited labeled examples. The existing methods use data augmentation to randomly transform the original examples to get new examples, and then use the new examples to train the model to improve the robustness and generalization ability of the learnt model. Due to each iteration of these methods uses a random transformation to get a new example, it will cause the unstable problem of the class center in the feature measurement stage. To solve this problem, a Multi-view Metric Learning (MML) method is proposed, which is based on a new concept (View Bag) and its effective similarity measurement method to achieve better few-shot fine-grained image classification. Firstly, a new example obtained by a kind of data augmentation is defined as a view, and a set of views generated by multiple data augmentation is defined as a view bag. Then, the view bag is sent into the model to extract the features, and a multi-view metric method with the view bag as the object is proposed to overcome the unstable problem of the class center. Finally, classification is performed by measuring the similarity between view bags. Experiments are conducted on three public datasets, CUB-2011-200, Stanford-Dogs and Stanford-Cars. The proposed method achieves 71.61±0.87%, 57.78±0.96% and 74.02±0.84% for the 5-way 1-shot classification task, and 88.72±0.51%, 76.30±0.68% and 92.94±0.37% for the 5-way 5-shot classification task, which have the state-of-the-art performances. Under the condition of the same backbone network, the proposed multi-view metric method can measure the similarity between examples more effectively, and improve the robustness and generalization ability of the model.

New aquamarine deposits have been found around the world in recent years, and how to compare and distinguish aquamarines of different origin has become a significant problem. Aquamarines from Koktokay, Minas Gerais, and Namaqualand were collected for standard gemology tests, spectroscopy, and chemical analysis in this paper. The spectroscopy experiment included infrared spectroscopy and Raman spectroscopy. Chemical composition analysis comprises electron microprobe and laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS). The results show that infrared absorption peaks related to [Fe2(OH)4] and NaH are found in Koktokay and Minas Gerais aquamarines, respectively. Compared with other two origins, Namaqualand aquamarine have strongest type II water Raman peak related to alkali metal content. Compared with aquamarines from other sources, aquamarines from Xinjiang and Minas Gerais are characterized by relatively high aluminum and low alkali contents in chemical composition, while Namaqualand aquamarine have a high scandium content.

In the process of in situ zircon U–Pb dating, it is an effective means to overcome the matrix effect by using a matrix-matched external reference material. However, the limited number of available zircon reference materials still makes it difficult to meet the research needs. In this paper, we performed a preliminary analysis of the gemological characteristics, trace elements and U–Pb ages of natural zircon CAM18 to assess its suitability as a reference material for laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) U–Pb dating. This tawny, gem-quality zircon has no visible inclusions and weighs approximately 0.55 g. Its density, full width at half maximum (FWHM) of the Raman peak and alpha flux (Dα) indicate that the sample has suffered mild-to-moderate radiation damage without any thermal treatment. The LA-ICP-MS U–Pb dating results reveal that the trace elements content and U–Pb ages of the sample are fairly homogeneous at the 50 μm scale, and there is no obvious loss of radiogenic Pb. The 206Pb/238U age (571.0 ± 3.0 Ma, 2s) and 207Pb/235U age (573.4 ± 6.0 Ma, 2s) are consistent within the analytical uncertainty, and the calculated concordia age is 571.4 ± 1.4 Ma (2s, n = 20). The variation in the 206Pb/238U ages is small, with a measurement repeatability of 0.46% (RSD), which is within the uncertainty of the age accuracy obtained by LA-ICP-MS. The oscillatory zoning, Th/U ratio (0.2) and chondrite-normalized rare-earth element (REE) pattern imply a magmatic origin of zircon CAM18. The Ti-in-zircon temperature ranges from 714 to 742 °C, and the oxygen fugacity ranges from ΔFMQ−2.87 to ΔFMQ−3.17, suggesting that it is crystallized in a reducing environment. All the results show that zircon CAM18 may has great potential in LA-ICP-MS U–Pb dating.

Abstract Previous studies have demonstrated that brain-derived neurotrophic factor (BDNF) is one of the diffusible messengers for enhancing synaptic transmission in the hippocampus. Less information is available about the possible roles of BDNF in the anterior cingulate cortex (ACC). In the present study, we used 64-electrode array field recording system to investigate the effect of BDNF on ACC excitatory transmission. We found that BDNF enhanced synaptic responses in a dose-dependent manner in the ACC in C57/BL6 mice. The enhancement was long-lasting, and persisted for at least 3 h. In addition to the enhancement, BDNF also recruited inactive synaptic responses in the ACC. Bath application of the tropomyosin receptor kinase B (TrkB) receptor antagonist K252a blocked BDNF-induced enhancement. L-type voltage-gated calcium channels (L-VGCC), metabotropic glutamate receptors (mGluRs), but not NMDA receptors were required for BDNF-produced enhancement. Moreover, calcium-stimulated adenylyl cyclase subtype 1 (AC1) but not AC8 was essential for the enhancement. A selective AC1 inhibitor NB001 completely blocked the enhancement. Furthermore, BDNF-produced enhancement occluded theta burst stimulation (TBS) induced long-term potentiation (LTP), suggesting that they may share similar signaling mechanisms. Finally, the expression of BDNF-induced enhancement depends on postsynaptic incorporation of calcium-permeable AMPA receptors (CP-AMPARs) and protein kinase Mζ (PKMζ). Our results demonstrate that cortical BDNF may contribute to synaptic potentiation in the ACC.

Abstract Background miR-92b is a carcinogenic miRNA that has great potential as a biomarker for disease prognosis, diagnosis, and treatment in the clinic. It is of great significance to analyse the relationship between miR-92b and the clinicopathological characteristics of cancer patients. This paper aimed to investigate the expression levels and clinical values of miR-92b-3p in breast cancer (BC). Methods Altogether, 112 female BC patients who were treated in our hospital were included as a study group, and 108 healthy women who came to our hospital for physical examinations were included as a control group. miR-92b-3p expression in the serum of subjects in both groups was detected by fluorescence quantitative PCR (RT-PCR) to analyse the correlation of this miRNA with the patients’ pathological features and prognoses. The diagnostic value of miR-92b-3p expression for BC was analysed by plotting a receiver operating characteristic (ROC) curve. Results miR-92b-3p expression was remarkably higher in the study group (P

Abstract The ACC is an important brain area for the processing of pain-related information. Studies of synaptic connections within the ACC provide an understanding of basic cellular and molecular mechanisms for brain functions such as pain, emotion and related cognitive functions. Previous study of ACC synaptic transmission mainly focused on presumably thalamic inputs into pyramidal cells. In the present study, we developed a new mapping technique by combining single neuron whole-cell patch-clamp recording with 64 multi-channel field potential recording (MED64) to examine the properties of excitatory inputs into a single neuron in the ACC. We found that a single patched pyramidal neuron or interneuron simultaneously received heterogeneous excitatory synaptic innervations from different subregions (ventral, dorsal, deep, and superficial layers) in the ACC. Conduction velocity is faster as stimulation distance increases in pyramidal neurons. Fast-spiking interneurons (FS-IN) show slower inactivation when compared to pyramidal neurons and regular-spiking interneurons (RS-IN) while pyramidal neurons displayed the most rapid activation. Bath application of non-competitive AMPA receptor antagonist GYKI 53655 followed by CNQX revealed that both FS-INs and RS-INs have AMPA and KA mediated components. Our studies provide a new strategy and technique for studying the network of synaptic connections.

Abstract Due to the advantages in efficacy and safety compared with traditional chemotherapy drugs, targeted therapeutic drugs have become mainstream cancer treatments. Since the first tyrosine kinase inhibitor imatinib was approved to enter the market by the US Food and Drug Administration (FDA) in 2001, an increasing number of small-molecule targeted drugs have been developed for the treatment of malignancies. By December 2020, 89 small-molecule targeted antitumor drugs have been approved by the US FDA and the National Medical Products Administration (NMPA) of China. Despite great progress, small-molecule targeted anti-cancer drugs still face many challenges, such as a low response rate and drug resistance. To better promote the development of targeted anti-cancer drugs, we conducted a comprehensive review of small-molecule targeted anti-cancer drugs according to the target classification. We present all the approved drugs as well as important drug candidates in clinical trials for each target, discuss the current challenges, and provide insights and perspectives for the research and development of anti-cancer drugs.

Abstract A single‐layer dipole antenna array with quasi‐Yagi configuration has been proposed and demonstrated, which provides a dual radiation pattern with the same sense. This antenna is mainly composed of a substrate‐supported parallel strip line (PSL) and several periodic dipole elements. Fed by PSL, dipole elements can be stimulated with a uniform power, forming a linear dipole antenna array. By adjusting the elements separation appropriately, the step phase of array factor can be tuned to achieve the same directivity as the element dipole. When an SubMiniature version A (SMA) coaxial connector is connected at the beginning of PSL, the fundamental mode TEM in the PSL is excited and the radiation electromagnetic wave from the dipole elements is achieved. A taper line between the SMA and PSL can be used to reduce the discontinuity, minimizing the reflection coefficient of the port. According to the theory of classical Yagi antenna, the gain can be further improved by introducing multiple directors, achieving the gain increment of about 3 dBi in the proposed design. Considering 5 GHz frequency band applications (4.85–5.2 GHz), the experimental and simulated results show the proposed antenna array has a working bandwidth (|S11|≤−10dB) from 4.85 to 12 GHz.

Purpose: The LIM (Lin-11, Isl1, MEC-3) domain protein AJUBA is involved in multiple biological functions, and its aberrant expression is related to the occurrence and progression of various cancers. However, there are no analytical studies on AJUBA in pan-cancer.Methods: We performed a comprehensive pan-cancer analysis and explored the potential oncogenic roles of AJUBA, including gene expression, genetic mutation, protein phosphorylation, clinical diagnostic biomarker, prognosis, and AJUBA-related immune infiltration based on The Cancer Genome Atlas and Genotype-Tissue Expression databases.Results: The results revealed that the expression of AJUBA highly correlated with poor clinical outcomes in patients with different types of cancer. Meanwhile, AJUBA expression was positively correlated with cancer-associated fibroblasts in many human cancers, such as breast invasive carcinoma, colon adenocarcinoma, brain lower-grade glioma, lung adenocarcinoma (LUAD), and ovarian serous cystadenocarcinoma (OV). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that AJUBA is mainly involved in protein serine/threonine kinase activity, cell–cell junction, covalent chromatin modification, and Hippo signaling pathway.Conclusion: The pan-cancer study reveals the oncogenic roles of AJUBA and provides a comprehensive understanding of the molecular biological genetic information of AJUBA in various tumors.

N6-methyladenosine (m6A) RNA methylation is identified as the most common, abundant and reversible RNA epigenetic modification in messenger RNA (mRNA) and non-coding RNA, especially within eukaryotic messenger RNAs (mRNAs), which post-transcriptionally directs many important processes of RNA. It has also been demonstrated that m6A modification plays a pivotal role in the occurrence and development of tumors by regulating RNA splicing, localization, translation, stabilization and decay. Growing number of studies have indicated that natural products have outstanding anti-cancer effects of their unique advantages of high efficiency and minimal side effects. However, at present, there are very few research articles to study and explore the relationship between natural products and m6A RNA modification in tumorigenesis. m6A is dynamically deposited, removed, and recognized by m6A methyltransferases (METTL3/14, METTL16, WTAP, RBM15/15B, VIRMA, CBLL1, and ZC3H13, called as “writers”), demethylases (FTO and ALKBH5, called as “erasers”), and m6A-specific binding proteins (YTHDF1/2/3, YTHDC1/2, IGH2BP1/2/3, hnRNPs, eIF3, and FMR1, called as “readers”), respectively. In this review, we summarize the biological function of m6A modification, the role of m6A and the related signaling pathway in cancer, such as AKT, NF-kB, MAPK, ERK, Wnt/β-catenin, STAT, p53, Notch signaling pathway, and so on. Furthermore, we reviewed the current research on nature products in anti-tumor, and further to get a better understanding of the anti-tumor mechanism, thus provide an implication for nature products with anti-cancer research by regulating m6A modification in the future.

Although smart construction tools are already assisting the construction sector, still major reforms are considerably seen in the coming years with Artificial Intelligence of Things (AIoT). The purpose of this work was to develop a down-to-earth reliable edge-computing design and plan, which can be utilized to bolster savvy development situations with high quality of service. The number of devices connected to industrial processes is growing in tandem with the advancement of sophisticated technologies and the use of the AIoT. Big data are created as gadgets grow more integrated and need more computing power. However, as the amount of big data generated grows, processing and analytical issues arise. Cloud computing technologies are now being used to solve processing and analytical challenges. However, by using edge computing technologies, greater emphasis is placed on executing calculations as near to the device as feasible. As a result of these facts, this article suggests the arrangement plan, which depends on the most recent cloud and computer program designing approaches and advances, and gives flexibility, interoperability, and adjustment to construction companies' particular needs.

As one of the largest global emitters of sulfur dioxide (SO2), China faces increasing pressure to achieve sustainable economic and social development. Using panel data of 58 prefecture-level cities in North China between 2003 and 2017, this paper considers the dynamic spatio-temporal characteristics of industrial SO2 emissions in the “2 ​+ ​26” in North China and extended cities in North China and decomposes the determinants of industrial SO2 emissions into eight effects using the Generalized Divisia Index Model (GDIM). The contributions of each effect on changes in emissions are assessed on regional, provincial, and prefectural levels, as well as according to various stages. The results indicate the following. First, industrial SO2 emissions in the “2 ​+ ​26” cities in North China and extended cities in North China exhibit spatial autocorrelation and agglomeration effects. Cities with high-high (HH) and low-low (LL) agglomeration patterns were concentrated in Shanxi and Henan provinces, respectively. Second, industrialization, energy consumption, and economic development were the main factors that increased industrial SO2 emissions, while technology, energy sulfur intensity, and economic sulfur intensity were the key factors that reduced them. Third, 13 cities, including Tangshan, were the most important regions where further emissions regulations need to be implemented. These cities were divided into three types and different corresponding measures for reducing their emissions are suggested. Based on the conclusions of this study, this paper puts forward some targeted policy recommendations for reducing industrial SO2 emissions according to different categories of cities.

Objective To investigate whether intravenous combined with topical administration of tranexamic acid (TXA) is superior to intravenous administration alone in terms of blood loss, incision complications, functional recovery, and pain relief in high tibial osteotomy (HTO). Methods Clinical data of patients with knee osteoarthritis (OA) treated with unilateral HTO were retrospectively reviewed. The patients were grouped according to the TXA administration method, with 24 patients in the combined group and 21 in the solo group. In the combined group, 100 mL saline containing 1 g TXA was intravenously administered before application of a tourniquet, and 20 mL saline containing 2 g TXA was injected through a drainage tube after closure of the incision. Alternatively, 100 mL of saline containing 1 g TXA was intravenously administered before application of a tourniquet in the solo group. The blood loss and adverse events were compared between the two groups. Results All patients were followed for more than half a year. The drainage volume on the first day and total blood loss on the second day after surgery in the combined and single treatment groups were 130.06 ± 29.22 and 165.35 ± 43.08 mL (P

Application stability and power generation of a conventional cube-type thermoelectric (TE) module were analyzed considering different shapes. It was found that the stress concentration occurred in the copper electrodes of cube-type ones. Further, cube TE legs were re-designed into cylinder ones. And stress concentration in the copper electrodes has reduced. To explore novel designing for enhancing efficiency, the truncated cone-type TE module with a smaller cold end area was designed. The results show that application stability and power generation have been optimized synchronously. The maximum stress has dropped by 1.9% compared with the cube-type TE module, and the maximum deformation is decreased by 1.4%. When the temperature difference is 80K, the output power of the novel TE module is enhanced by 9.3%. The proposed truncated cone-type TE module has high reliability and applicability, and it can be a promising method for heat harvesting.

Understanding the spatiotemporal heterogeneities of PM2.5 reduction efficiency (PRE) and their driving factors are substantially critical for the atmospheric environmental governance. Using the balanced panel data covering 2003–2017 of the three urban agglomerations (UAs) in the Yangtze River Economic Belt (YREB), Yangtze River Delta (YRD), Middle-Reach Yangtze River (MRYR), and Cheng-Yu (CY), as the research sample, this paper quantified the PREs by non-separable input–output SBM-Undesirable model and then investigated the spatiotemporal heterogeneities through Dagum Gini Coefficient, Kernel Density Estimation and Markov Chain, as well as analyzed the driving factors of PRE using panel quantile regression. The results show that: (1) The overall PRE of the three UAs was relatively low, with an average of 0.630, the YRD showed the highest PRE (0.684), followed by the CY (0.615), while the MRYR suffered the lowest (0.588). (2) There existed significant differences in PRE among the three UAs, and the intensity of trans-variation was the main source. The Kernel Density Estimation and Markov Chain analysis showed that the gaps of PRE between cities were narrowing and gradually converged to the middle PRE level. (3) The impacts of seven selected driving factors including fixed asset investment, economic development level, investment in education, transport infrastructure, environmental regulation, information level and trade openness on PRE in the three UAs were significantly heterogenous across cities with different PRE scores. The findings of this paper are helpful to formulate differentiated policies in PM2.5 pollution reduction and promote the coordination between economic development and atmospheric environmental protection for the three UAs in YREB accordingly.

Recently, unsupervised deep hashing has attracted increasing attention, mainly because of its potential ability to learn binary codes without identity annotations. However, because the labels are predicted by their pretext tasks, unsupervised deep hashing becomes unstable when learning with noisy labels. To mitigate this issue, we propose a simple but effective approach to self-supervised hash learning based on dual pseudo agreement. By adding a consistency constraint, our method can prevent corrupted labels and encourage generalization for effective knowledge distillation. Specifically, we use the refined pseudo labels as a stabilization constraint to train hash codes, which can implicitly encode semantic structures of the data into the learned Hamming space. Based on the stable pseudo labels, we propose a self-supervised hashing method with mutual information and noise contrastive loss. Throughout the process of hash learning, the stable pseudo labels and data distributions collaboratively work together as teachers to guide the binary codes learning process. Extensive experiments on three publicly available datasets demonstrate that the proposed method can consistently outperform state-of-the-art methods by large margins.

Making machines learn like humans is the ultimate goal of artificial intelligence. Few-shot learning attempts to simulate the learning mechanism of humans, which is a task that can learn novel concepts from very few labeled samples. Due to the lack of sufficient labeled training data, existing methods often increase the risk of over-fitting or cause a considerable gap between clean and augmented data. To solve these problems, we present a novel compare network to perform robust few-shot learning in a meta-learned end-to-end manner. Specifically, we argue that it is desirable to learn a robust encoder that can draw inferences about other cases from one example. To this end, we improve the accuracy of few-shot learning by mining the internal mechanism of deep networks, which can leverage label information more effectively. By introducing shift-invariant blocks and a self-attention block in our architecture, all these components are seamlessly integrated into our framework, which can give feedback to each other without data augmentation. Furthermore, we provide ablative analyses of different blocks to help understand how each term contributes to performance. Extensive experiments demonstrate that our method can provide more robust results and outperform state-of-the-art few-shot learning methods.

Abstract Background Perioperative immune function plays an important role in the prognosis of patients. Several studies have indicated that low-dose opioid receptor blockers can improve immune function. Methods Sixty-nine patients undergoing video-assisted thoracoscopic resection of the lung cancer were randomly assigned to either the naloxone group (n = 35) or the non-naloxone group (n = 34) for postoperative analgesia during the first 48 h after the operation. Both groups received sufentanil and palonosetron via postoperative analgesia pump, while 0.05 μg·kg− 1·h− 1 naloxone was added in naloxone group. The primary outcomes were the level of opioid growth factor (OGF) and immune function assessed by natural killer cells and CD4+/CD8+ T-cell ratio. Second outcomes were assessed by the intensity of postoperative pain, postoperative rescue analgesia dose, postoperative nausea and vomiting (PONV). Results The level of OGF in the naloxone group increased significantly at 24 h (p

The application of fine-grained image classification can be problematic due to subtle differences between classes. The existing global feature-based methods have worse accuracies than regional feature-based methods, because regional feature-based methods focus on the determination of differentiated features within local regions. To learn more discriminative global features, in this paper, we proposed the use of L2 normalization to tackle a neglected conflict between the widely used metric loss (triplet loss) and classification loss (softmax loss) in global feature-based methods. Furthermore, a multi-level metric learning network (MMLN) is proposed for fine-grained image classification based on global features. In the MMLN, multi-level metric learning objectives and classification objectives are present at multiple high-level layers. The multi-level metric learning objectives work together to supervise the network in order to learn highly discriminative features. In addition, a new probability aggregation strategy (PAS) is proposed to produce a fused prediction by combining the multi-level predictive probabilities. Experiments were conducted on three standard fine-grained classification datasets (CUB-200-2011, Stanford Cars, and FGVC-Aircraft). Results demonstrated that our MMLN achieved accuracies of 88.0%, 94.6% and 92.4% respectively and outperformed state-of-the-art methods, substantially improving fine-grained classification tasks. Besides, gradient-weighted class activation mapping (Grad-CAM) shows that the MMLN is able to pay more attention to the discriminative local regions due to the application of multi-level metric learning.

Dysfunction of vascular smooth muscle cells (VSMCs) mediates intracranial aneurysm (IA). KDR is reported to alleviate IA progression via promoting VSMC proliferation, while the upstream regulators are still unclear. Arterial wall tissues at the aneurysm site from 12 patients were obtained. The real-time PCR result indicated that circRNA_0020397 was down-regulated, but miR-138 was up-regulated in artery wall tissues and cells of IA. Overexpressed circRNA_0020397 promoted proliferation of human umbilical artery SMCs. MiR-138 negatively regulated KDR via binding with 3’UTR of KDR mRNA. The expression of circRNA_0020397 was negatively correlated with miR-138. In conclusion, our findings demonstrated that decreased expression of circRNA_0020397 in IA may contribute to the decreased VSMC proliferation via increasing miR-138 expression and subsequently decreasing KDR expression.

Recent deep models trained on large-scale RGB datasets lead to considerable achievements in visual detection tasks. However, the training examples are often limited for an infrared detection task, which may deteriorate the performance of deep detectors. In this paper, we propose a transfer approach, Source Model Guidance (SMG), where we leverage a high-capacity RGB detection model as the guidance to supervise the training process of an infrared detection network. In SMG, the foreground soft label generated from the RGB model is introduced as source knowledge to provide guidance for cross-domain transfer. Additionally, we design a Background Suppression Module in the infrared network to receive the knowledge and enhance the foreground features. SMG is easily plugged into any modern detection framework, and we show two explicit instantiations of it, SMG-C and SMG-Y, based on CenterNet and YOLOv3, respectively. Extensive experiments on different benchmarks show that both SMG-C and SMG-Y achieve remarkable performance even if the training set is scarce. Compared to advanced detectors on public FLIR, SMG-Y with 77.0% mAP outperforms others in accuracy, and SMG-C achieves real-time detection at a speed of 107 FPS. More importantly, SMG-Y trained on a quarter of the thermal dataset obtains 74.5% mAP, surpassing most state-of-the-art detectors with full FLIR as training data.

Abstract This study proposes a novel algorithm that enhances the distinctiveness of the traditional vector of locally aggregated descriptors (VLAD) using spatial distribution clue of local features. The algorithm introduces a new method to compute the spatial distribution entropy (SDE) of clusters. Unlike conventional methods, this algorithm considers the distribution of full spatial information provided by local feature detectors rather than only utilizing the spatial coordinate statistics. For each cluster, the corresponding spatial distribution is computed using a histogram of spatial locations, scales, and orientations of all local features inside the cluster. Entropy is calculated from the spatial distributions of all clusters of an image to create a distribution function, which is further normalized and concatenated with the VLAD vector to generate the final representation. Image retrieval and classification experiments on public datasets are performed. Experimental results show that the proposed algorithms produce better or comparable retrieval performance than several state-of-the-art algorithms. In addition, we extend our SDE to the convolutional neural network (CNN) feature, which further improves the CNN feature result in image retrieval.

Superpixel segmentation has become a crucial pre-processing tool to reduce computation in many computer vision applications. In this paper, a superpixel extraction algorithm based on a seed strategy of contour encoding (SSCE) for infrared images is presented, which can generate superpixels with high boundary adherence and compactness. Specifically, SSCE can solve the problem of superpixels being unable to self-adapt to the image content. First, a contour encoding map is obtained by ray scanning the binary edge map, which ensures that each connected domain belongs to the same homogeneous region. Second, according to the seed sampling strategy, each seed point can be extracted from the contour encoding map. The initial seed set, which is adaptively scattered based on the local structure, is capable of improving the capability of boundary adherence, especially for small regions. Finally, the initial superpixels limited by the image contour are generated by clustering and refined by merging similar adjacent superpixels in the region adjacency graph (RAG) to reduce redundant superpixels. Experimental results on a self-built infrared dataset and the public datasets BSD500 and 3Dircadb demonstrate the generalization ability in grayscale and medical images, and the superiority of the proposed method over several state-of-the-art methods in terms of accuracy and compactness.

Water body extraction can help eco-environmental policymakers to intuitively grasp surface water resources. Remote sensing technology can accurately and quickly extract surface water information, which is of great significance for monitoring surface water changes. Fengyun satellite images have the advantages of high time resolution and multispectral bands. This provides important image data suitable for high-frequency surface water monitoring. Based on Fengyun 3 medium resolution spectral imager (FY-3/MERSI) data, 7 methods were applied in this study, which include single-band threshold method, water body index method, knowledge decision tree classification method, supervised classification method, unsupervised classification method, spectral matching based on discrete particle swarm optimization (SMDPSO), and improved spectral matching based on discrete particle swarm optimization with linear feature enhancement (SMDPSO+LFE). These methods were used to extract the land surface water of Poyang Lake, check the samples from the Landsat image with similar times to the FY-3 images, and calculate the classification accuracy via the confusion matrix. The results showed that the overall classification accuracy (OA) of the SMDPSO+LFE is 97.64%, and the Kappa coefficient is 0.95. To analyze the stability of the surface water extracted by SMDPSO+LFE in different regions, this paper selected eight test sites with different surface water types, landscapes, and terrains to extract surface water. Based on an analysis of the land surface water results at the eight test sites, every OA in the eight sites was higher than 94.5%, the Kappa coefficient was greater than 0.88. In conclusion, the SMDPSO+LFE is found to be the most suitable method among the 7 methods and effectively distinguish between different surface water bodies and backgrounds with good stability.

In order to respond to rapid urbanization, understanding the relationships between urbanization and ecosystem services (ESs) is of practical importance to move toward sustainable urban development. In this study, an emergy-GIS based method is proposed to evaluate ESs. Spatiotemporal emergy values of water retention (WR), air purification (AP), carbon sequestration (CS), soil conservation (SC), and biodiversity conservation (BC) were quantified and relationships among these ESs were analyzed by taking China’s largest city, Shanghai, as a case. The decoupling analysis was conducted to study the relationship between urbanization and ESs. Results show that the total value of regulating ESs had declined by 8.24% from 2005 to 2010. Chongming had the largest value of ESs, followed by Pudong. There is a synergetic relationship among AP, CS, and SC, while a tradeoff appears between WR and other services. Irregular “U” shape relationships between the decrease of ESs and urbanization indicators were observed. Results from decoupling analysis show that ESs experienced weak decoupling from urbanization in most districts. Finally, policy implications were raised based on the study results.

Biocathode microbial electrochemical systems (MESs) that remove nitrogen compounds out of wastewater are of special interest for practice. High energy-input for aeration is one of the barriers that hinder their application on a wider scope. A trickling-bed biocathode MES (TB-MES) was developed by integrating biotrickling filters with a biocathode MES. By recirculating the catholyte and sprinkling it through a spray nozzle, the system was able to achieve a reoxygenation process, which could facilitate the creation of an aerobic and anoxic environment. At an optimal recirculation rate of 200 mL min−1, the TB-MES removed 87.2 ± 2.7% of ammonium nitrogen and 79.7 ± 2.5% of total nitrogen (TN), and simultaneously achieved a maximum power density of 3.8 ± 0.3 Wm−3. Comparable performances were achieved when treating domestic wastewater, which were 84.6 ± 2.4%, 70.1 ± 4.2%, and 3.2 ± 0.2 W m−3 for ammonium nitrogen removal, TN removal, and maximum power density. Pyrosequencing analysis revealed Nitrosomonas was more abundant in the upper portion of the carbon fiber brush biocathode (CFBup, 20.4%) and Azoarcus was more abundant in the lower portion (CFBbottom, 12.6%), which was probably caused by the difference in dissolved oxygen concentration in different parts of the biocathode. The TB-MES shows great promise for domestic wastewater treatment by employing biotrickling filters for oxygen supply in biocathode MES.