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Abstract The diverse utility of acyclic vinylsilanes has driven the interest in the synthesis of enantioenriched vinylsilanes bearing a Si-stereogenic center. However, the predominant approaches for catalytic asymmetric generation of Si-stereogenic vinylsilanes have mainly relied on transition metal-catalyzed reactions of alkynes with different silicon sources. Here we successfully realize the enantioselective synthesis of linear silicon-stereogenic vinylsilanes with good yields and enantiomeric ratios from simple alkenes under rhodium catalysis. The significance of this transformation lies in its ability to achieve regioconvergent and enantioconvergent conversion, efficiently transforming petroleum-derived isomeric mixtures of olefin feedstocks into a single regio- and stereoisomer product. The practicality of this method is further exemplified by the diverse downstream transformations of these enantioenriched silicon-stereogenic vinylsilanes leveraging the olefin functionality and the leaving group nature of the aryl substituent on silicon as well as the development of chiral π-conjugated double bond systems.

Abstract In the financial sector, alternatives to traditional datasets, such as financial statements and Securities and Exchange Commission filings, can provide additional ways to describe the running status of businesses. Nontraditional data sources include individual behaviors, business processes, and various sensors. In recent years, alternative data have been leveraged by businesses and investors to adjust credit scores, mitigate financial fraud, and optimize investment portfolios because they can be used to conduct more in-depth, comprehensive, and timely evaluations of enterprises. Adopting alternative data in developing models for finance and business scenarios has become increasingly popular in academia. In this article, we first identify the advantages of alternative data compared with traditional data, such as having multiple sources, heterogeneity, flexibility, objectivity, and constant evolution. We then provide an overall investigation of emerging studies to outline the various types, emerging applications, and effects of alternative data in finance and business by reviewing over 100 papers published from 2015 to 2023. The investigation is implemented according to application scenarios, including business return prediction, business risk management, credit evaluation, investment risk prediction, and stock prediction. We discuss the roles of alternative data from the perspective of finance theory to argue that alternative data have the potential to serve as a bridge toward achieving high efficiency in financial markets. The challenges and future trends of alternative data in finance and business are also discussed.

In this paper, we focus on studying a specific type of equations called backward stochastic Volterra integral equations (BSVIEs). Our approach to approximating an unknown function involved using collocation approximation. We used Newton's technique to solve a particular BSVIE by employing block pulse functions (BPFs) and the related stochastic operational matrix of integration. Additionally, we developed considerations for Lipschitz and linear growth, along with linearity conditions, to illustrate error and convergence analysis. We compared the solutions we obtain the values of exact and approximate solutions at selected points with a defined absolute error. The computations were performed using MATLAB R2018a.

Background: Immunotherapy has emerged as a novel strategy for cancer treatment following surgery, radiotherapy, and chemotherapy. Immune checkpoint blockade and Chimeric antigen receptor (CAR)-T cell therapies have been successful in clinical trials. Cancer cells evade immune surveillance by hijacking inhibitory pathways via overexpression of checkpoint genes. The Cluster of Differentiation 47 (CD47) has emerged as a crucial checkpoint for cancer immunotherapy by working as a “don’t eat me” signal and suppressing innate immune signaling. Furthermore, CD47 is highly expressed in many cancer types to protect cancer cells from phagocytosis via binding to SIRPα on phagocytes. Targeting CD47 by either interrupting the CD47-SIRPα axis or combing with other therapies has been demonstrated as an encouraging therapeutic strategy in cancer immunotherapy. Antibodies and small molecules that target CD47 have been explored in pre- and clinical trials. However, formidable challenges such as the anemia and palate aggregation cannot be avoided because of the wide presentation of CD47 on erythrocytes. Aim of view: This review summarizes the current knowledge on the regulation and function of CD47, and provides a new perspective for immunotherapy targeting CD47. It also highlights the clinical progress of targeting CD47 and discusses challenges and potential strategies. Key scientific concepts of review: This review provides a comprehensive understanding of targeting CD47 in cancer immunotherapy, it also augments the concept of combination immunotherapy strategies by employing both innate and adaptive immune responses.

Roses (Rosa rugosa) are a famous flower with high ornamental and economic value. But the petals of roses are usually pink and purple, which restricted its application in garden settings. Flavonols and anthocyanins are crucial secondary metabolites related to flower pigmentation in plants. While MYB transcription factors involved in the biosynthesis pathway of anthocyanins have been identified in roses, the functional characterization of the MYB transcription factor regulating flavonol synthesis in R. rugosa remains unexplored. In this study, we isolated and characterized the R2R3-MYB transcription factors RrMYB12 and RrMYB111 involved in regulation of the flavonol biosynthetic pathway from R. rugosa. The bioinformatics analysis indicated that both the RrMYB12 and RrMYB111 belong to the R2R3-MYB subgroup 7 family. qRT-PCR analysis showed that RrMYB12 and RrMYB111 were expressed at low levels in roots and flowers. And transactivation activity assay indicated that RrMYB12 and RrMYB111 were transcriptional activators. The overexpression of RrMYB12 and RrMYB111 in tobacco resulted in an elevation of flavonol levels and a reduction in anthocyanin levels in flowers due to the upregulation of structural genes involved in flavonol synthesis, while the biosynthesis genes for the anthocyanin pathway were significantly downregulated. The transient reporter assay demonstrated that RrMYB12 exhibited strong activation of the promoters of RrCHS and RrFLS in Nicotiana benthamiana leaves following transient transformation. Furthermore, it was observed that RrMYBs displayed binding specificity to the promoter region of CsFLS.The functional characterization of the flavonol synthesis regulatory factors RrMYB12 and RrMYB111 offers a deeper understanding of the regulatory mechanism governing flavonol biosynthesis in roses, while also presenting an effective tool for genetic manipulation aimed at creating new varieties.

Abstract Creatine kinases are essential for maintaining cellular energy balance by facilitating the reversible transfer of a phosphoryl group from ATP to creatine, however, their role in mitochondrial ATP production remains unknown. This study shows creatine kinases, including CKMT1A, CKMT1B, and CKB, are highly expressed in cells relying on the mitochondrial F1F0 ATP synthase for survival. Interestingly, silencing CKB, but not CKMT1A or CKMT1B, leads to a loss of sensitivity to the inhibition of F1F0 ATP synthase in these cells. Mechanistically, CKB promotes mitochondrial ATP but reduces glycolytic ATP production by suppressing mitochondrial calcium (mCa2+) levels, thereby preventing the activation of mitochondrial permeability transition pore (mPTP) and ensuring efficient mitochondrial ATP generation. Further, CKB achieves this regulation by suppressing mCa2+ levels through the inhibition of AKT activity. Notably, the CKB‐AKT signaling axis boosts mitochondrial ATP production in cancer cells growing in a mouse tumor model. Moreover, this study also uncovers a decline in CKB expression in peripheral blood mononuclear cells with aging, accompanied by an increase in AKT signaling in these cells. These findings thus shed light on a novel signaling pathway involving CKB that directly regulates mitochondrial ATP production, potentially playing a role in both pathological and physiological conditions.

We present a method for computing the stochastic operational matrix of integration to advance the study of stochastic Volterra-Fredholm integral equations (SVFIEs) based on delay arguments. First, the method evaluates the combined effects of the delay and its parameters on the accuracy improvement of the convergence rate. Our results can be applied to SVFIEs, with the operational delay matrices of the block pulse function simplified to algebraic ones. Numerical calculations were performed on a PC using Python 3 programs. Results also demonstrate the accuracy of approximate solutions; arithmetic operations are carried out without the need for derivation or integration.

Abstract Background Glioma is a lethal brain cancer and lacking effective therapies. Challenges include no effective therapeutic target, intra- and intertumoral heterogeneity, inadequate effective drugs, and an immunosuppressive microenvironment, etc. Deciphering the pathogenesis of gliomas and finding out the working mechanisms are urgent and necessary for glioma treatment. Identification of prognostic biomarkers and targeting the biomarker genes will be a promising therapy. Methods From our RNA-sequencing data of the oxidative phosphorylation (OXPHOS)-inhibition sensitive and OXPHOS-resistant cell lines, we found that the scaffolding protein caveolin 1 (CAV1) is highly expressed in the resistant group but not in the sensitive group. By comprehensive analysis of our RNA sequencing data, Whole Genome Bisulfite Sequencing (WGBS) data and public databases, we found that CAV1 is highly expressed in gliomas and its expression is positively related with pathological processes, higher CAV1 predicts shorter overall survival. Results Further analysis indicated that (1) the differentiated genes in CAV1-high groups are enriched in immune infiltration and immune response; (2) CAV1 is positively correlated with tumor metastasis markers; (3) the methylation level of CAV1 promoters in glioma group is lower in higher stage than that in lower stage; (4) CAV1 is positively correlated with glioma stemness; (5) higher expression of CAV1 renders the glioma cells’ resistant to oxidative phosphorylation inhibitors. Conclusion Therefore, we identified a key gene CAV1 and deciphered its function in glioma progression and prognosis, proposing that CAV1 may be a therapeutic target for gliomas. Graphical Abstract

Cracks are a common defect in civil infrastructures, and their occurrence is often closely related to structural loading conditions, material properties, design and construction, and other factors. Therefore, detecting and analyzing cracks in civil infrastructures can effectively determine the extent of damage, which is crucial for safe operation. In this paper, Web of Science (WOS) and Google Scholar were used as literature search tools and “crack”, “civil infrastructure”, and “computer vision” were selected as search terms. With the keyword “computer vision”, 325 relevant documents were found in the study period from 2020 to 2024. A total of 325 documents were searched again and matched with the keywords, and 120 documents were selected for analysis and research. Based on the main research methods of the 120 documents, we classify them into three crack detection methods: fusion of traditional methods and deep learning, multimodal data fusion, and semantic image understanding. We examine the application characteristics of each method in crack detection and discuss its advantages, challenges, and future development trends.

Zhonghua Gate Castle is on the tentative list for Chinese World Cultural Heritage. Due to long-term sunshine, rain erosion, and man-made damage, its surface appears to have different degrees of cracks and other diseases. This paper centers on Zhonghua Gate Castle; terrestrial laser scanning is used to obtain the exterior wall point cloud data. A crack detection method based on point cloud data curved surface reconstruction is proposed. It involves data preprocessing, crack detection, and the analysis of crack features. This method initially uses data preprocessing techniques to improve data quality. These techniques include removing ground points and super-voxel segmentation. Subsequently, local surface reconstruction was employed to address the issue of missing point cloud data within cracks and the Euclidean clustering algorithm was used for precise crack identification. The article provides a detailed analysis of the geometric characteristics of cracks. They involve the calculation of length, width, and area. The results of the experiment demonstrate that the method could successfully identify cracks and extract geometric features and has millimeter-level accuracy compared to actual crack sizes.

Abstract Cancer immunotherapy, mainly including immune checkpoints-targeted therapy and the adoptive transfer of engineered immune cells, has revolutionized the oncology landscape as it utilizes patients’ own immune systems in combating the cancer cells. Cancer cells escape immune surveillance by hijacking the corresponding inhibitory pathways via overexpressing checkpoint genes. Phagocytosis checkpoints, such as CD47, CD24, MHC-I, PD-L1, STC-1 and GD2, have emerged as essential checkpoints for cancer immunotherapy by functioning as “don’t eat me” signals or interacting with “eat me” signals to suppress immune responses. Phagocytosis checkpoints link innate immunity and adaptive immunity in cancer immunotherapy. Genetic ablation of these phagocytosis checkpoints, as well as blockade of their signaling pathways, robustly augments phagocytosis and reduces tumor size. Among all phagocytosis checkpoints, CD47 is the most thoroughly studied and has emerged as a rising star among targets for cancer treatment. CD47-targeting antibodies and inhibitors have been investigated in various preclinical and clinical trials. However, anemia and thrombocytopenia appear to be formidable challenges since CD47 is ubiquitously expressed on erythrocytes. Here, we review the reported phagocytosis checkpoints by discussing their mechanisms and functions in cancer immunotherapy, highlight clinical progress in targeting these checkpoints and discuss challenges and potential solutions to smooth the way for combination immunotherapeutic strategies that involve both innate and adaptive immune responses.

Abstract To investigate the prevalence and indoor environmental influencing factors of wheeze and asthma among preschool children in Urumqi, Xinjiang, China to provide a strong basis for prevention and control. In August 2019, a cross-sectional study involving 8153 preschool children was conducted in 60 kindergartens in Urumqi. The ALLHOME-2 questionnaire was used for childhood wheeze and asthma survey, and the dampness in buildings and health (DBH) questionnaire was used for the childhood home dwelling and living environment survey. Multivariate unconditional logistic regression was then used to analyze the potential influencing factors of childhood asthma and wheeze. The prevalence of wheeze and asthma in children was 4.7% and 2.0%, respectively. Multivariate unconditional logistic regression results suggested that ethnicity other than the Han Chinese (odds ratio (OR) 1.39, 95% confidence interval (CI) 1.05–1.84), caesarean section (OR 1.24, 95% CI 1.00–1.53), family history of asthma (OR 5.00, 95% CI 3.36–7.44), carpet or floor bedding at home (OR 1.40, 95% CI 1.05–1.87), purchasing new furniture in the mother’s residence during pregnancy (OR 1.58, 95% CI 1.06–2.36), pet keeping in the residence at aged 0–1 year (OR 1.55, 95% CI 1.13–2.13), passive smoking by child in the current residence (OR 1.35, 95% CI 1.01–1.80), and having mould or hygroma in the child's residence at aged 0–1 year (OR 1.72, 95% CI 1.12–2.64) were risk factors for wheeze. In addition, Girls (OR 0.73, 95% CI 0.59–0.90) was a protective factor for wheeze. Caesarean section (OR 1.46, 95% CI 1.06–2.00), family history of asthma (OR 7.06, 95% CI 4.33–11.53), carpet or floor bedding at home (OR 2.20, 95% CI 1.50–3.23), and pet keeping in the residence at aged 0–1 year (OR 1.64, 95% CI 1.04–1.83) were risk factors for asthma, whereas Girls (OR 0.58, 95% CI 0.42–0.80) was a protective factor for asthma. This survey indicates that the purchase of new furniture, the placement of carpet or floor bedding in the child's residence, the pets keeping, room dampness or moldy phenomena, and passive smoking may all contribute to an elevated risk of wheeze or asthma in children.

Roads are the fundamental elements of transportation, connecting cities and rural areas, as well as people’s lives and work. They play a significant role in various areas such as map updates, economic development, tourism, and disaster management. The automatic extraction of road features from high-resolution remote sensing images has always been a hot and challenging topic in the field of remote sensing, and deep learning network models are widely used to extract roads from remote sensing images in recent years. In light of this, this paper systematically reviews and summarizes the deep-learning-based techniques for automatic road extraction from high-resolution remote sensing images. It reviews the application of deep learning network models in road extraction tasks and classifies these models into fully supervised learning, semi-supervised learning, and weakly supervised learning based on their use of labels. Finally, a summary and outlook of the current development of deep learning techniques in road extraction are provided.

In this paper, we consider the general mean-field backward doubly stochastic differential equations (mean-field BDSDEs) whose generator f can be discontinuous in y. We prove the existence theorem of solutions under stochastic linear growth conditions and also obtain the related comparison theorem. Naturally, we present those results under the linear growth condition, which is a special case of the stochastic condition. Finally, a financial claim sale problem is discussed, which demonstrates the application of the general mean-field BDSDEs in finance.

Abstract C − Si Bond cleavage is one of the key elemental steps for a wide variety of silicon-based transformations. However, the cleavage of unstrained Si−C(sp3) bonds catalyzed by transition metal are still in their infancy. They generally involve the insertion of a M − C(sp2) species into the C − Si bond and consequent intramolecular C(sp2)‒Si coupling to exclusively produce siloles. Here we report the Pd-catalyzed sila-spirocyclization, in which the Si−C(sp3) bond is activated by the insertion of a M − C(sp3) species and followed by the formation of a new C(sp3)‒Si bond, allowing the construction of diverse spirosilacycles. This reactivity mode, which is strongly supported by DFT calculations may open an avenue for the Si−C(sp3) bond cleavage and silacycle synthesis.

METTL3 catalyzes mRNA m6A deposition. The authors identify an acetylation-mediated regulation of METTL3 subcellular localization and compartment-specific functions, a process that is fine-tuned by anti-inflammatory and pro-inflammatory signals, which ultimately determine breast cancer metastasis.

Abstract 7-Met, a derivative of soybean isoflavone, is a natural flavonoid compound that has been reported to have multiple signaling pathways regulation effects. This study investigated the therapeutic effects of 7-Met on mice with atopic dermatitis induced by fluorescein isothiocyanate (FITC), or oxazolone (OXZ). 7-Met ameliorated FITC or OXZ-induced atopic dermatitis symptoms by decreasing ear thickness, spleen index, mast cell activation, neutrophil infiltration and serum IgE levels in female BALB/c mice. In FITC-induced atopic dermatitis mice, 7-Met reduced Th1 cytokines production and regulated Th1/Th2 balance by downregulating the secretion of thymic stromal lymphopoietin (TSLP) via inactivation of the NF-κB pathway. In OXZ-induced atopic dermatitis, 7-Met functioned through the reduction of Th17 cytokine production. Our study showed that 7-Methoxyisoflavone alleviated atopic dermatitis by regulating multiple signaling pathways and downregulating chemokine production.

BackgroundGlioma is the most lethal and most aggressive brain cancer, and currently there is no effective treatment. Cancer immunotherapy is an advanced therapy by manipulating immune cells to attack cancer cells and it has been studied a lot in glioma treatment. Targeting the immune checkpoint CD47 or blocking the CD47-SIRPα axis can effectively eliminate glioma cancer cells but also brings side effects such as anemia. Glutaminyl-peptide cyclotransferase-like protein (QPCTL) catalyzes the pyroglutamylation of CD47 and is crucial for the binding between CD47 and SIRPα. Further study found that loss of intracellular QPCTL limits chemokine function and reshapes myeloid infiltration to augment tumor immunity. However, the role of QPCTL in glioma and the relationship between its expression and clinical outcomes remains unclear. Deciphering the role of QPCTL in glioma will provide a promising therapy for glioma cancer immunotherapy.MethodsQPCTL expression in glioma tissues and normal adjacent tissues was primarily analyzed in The Cancer Genome Atlas (TCGA) database, and further validated in another independent cohort from the Gene Expression Omnibus (GEO) database, Chinese Glioma Genome Atlas (CGGA), and Human Protein Atlas (HPA). The relationships between QPCTL expression and clinicopathologic parameters and overall survival (OS) were assessed using multivariate methods and Kaplan-Meier survival curves. And the proteins network with which QPCTL interacted was built using the online STRING website. Meanwhile, we use Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA) databases to investigate the relationships between QPCTL expression and infiltrated immune cells and their corresponding gene marker sets. We analyzed the Differentially Expressed Genes (DEGs) including GO/KEGG and Gene Set Enrichment Analysis (GSEA) based on QPCTL-high and -low expression tumors.ResultsIn contrast to normal tissue, QPCTL expression was higher in glioma tumor tissue (p

Abstract Lacking a clear understanding of the molecular mechanism determining cancer cell sensitivity to oxidative phosphorylation (OXPHOS) inhibition limits the development of OXPHOS‐targeting cancer treatment. Here, cancer cell lines sensitive or resistant to OXPHOS inhibition are identified by screening. OXPHOS inhibition‐sensitive cancer cells possess increased OXPHOS activity and silenced nicotinamide N‐methyltransferase (NNMT) expression. NNMT expression negatively correlates with OXPHOS inhibition sensitivity and functionally downregulates the intracellular levels of S‐adenosyl methionine (SAM). Expression of DNA methyltransferase 1 (DNMT1), a SAM consumer, positively correlates with OXPHOS inhibition sensitivity. NNMT overexpression and DNMT1 inhibition render OXPHOS inhibition‐sensitive cancer cells resistant. Importantly, treatments of OXPHOS inhibitors (Gboxin and Berberine) hamper the growth of mouse tumor xenografts by OXPHOS inhibition sensitive but not resistant cancer cells. What's more, the retrospective study of 62 tumor samples from a clinical trial demonstrates that administration of Berberine reduces the tumor recurrence rate of NNMTlow/DNMT1high but not NNMThigh/DNMT1low colorectal adenomas (CRAs). These results thus reveal a critical role of the NNMT‐DNMT1 axis in determining cancer cell reliance on mitochondrial OXPHOS and suggest that NNMT and DNMT1 are faithful biomarkers for OXPHOS‐targeting cancer therapies.

Pre-supported pipe roof grouting is difficult to be satisfied due to various influences, which may have an impact on its bearing characteristics. In order to determine the impact of grouting plumpness on the bearing behavior of pipe roof, based on the preliminary experimental research a refined numerical model that takes into account the bonding between the steel pipe and cement mortar was established in this paper. It was used to analyze the bending moment-deflection curve, variation laws of ultimate bearing capacity coefficient, and disengagement rate of pipe roof under different grouting plumpness. Meanwhile, the working conditions of reinforcement and casing in the pipe were conducted. The results show that compared with full grouting, the ultimate bearing capacity of the grouting pipe roof, pipe roof with reinforcement bundles and casing pipe decreases by 4.6%, 5.2%, and 4.8% respectively when grouting incompleteness is 2%, and decreases by 35.3%, 40.4%, and 37.1% respectively, when grouting incompleteness rises to 25%; The ultimate bearing capacity of the pipe roof can be greatly enhanced by adding reinforcement bundles and casing pipe, and the increases of this case is 7.7%–18.3%, 31.4%–51.6%, respectively; The disengagement rate of pipe roof and mortar under the same load increases with the increase of grouting incompleteness, which growing relatively slowly when the grouting incompleteness is less than 2%, and develops rapidly when it is 2%–30%, while growing little when it is more than 30%. Under the same grouting incompleteness, adding reinforcement bundles and casing pipe in the pipe roof can effectively reduce its debonding rate and the latter has a better effect, and the corresponding disengagement rate is 62.8%–97.9% and 29.1%–91.9% of the grouting pipe roof respectively.

This paper presents a model for finding optimal pandemic control policy considering cross-region human mobility. We extend the baseline susceptible-infectious-recovered (SIR) epidemiology model by including the net human mobility from a severely-impacted region to a mildly-affected region. The strategic optimal mitigation policy combining testing and lockdown in each region is then obtained with the goal of minimizing economic cost under the constraint of limited resources. We parametrize the model using the data of the COVID-19 pandemic and show that the optimal response strategy and mitigation outcome greatly rely on the mitigation duration, available resources, and cross-region human mobility. Furthermore, we discuss the economic impact of travel restriction policies through a quantitative analysis.

Abstract Surgery is the common treatment for early lung cancer with multiple pulmonary nodules, but it is often accompanied by the problem of significant malignancy of other nodules in non-therapeutic areas. In this study, we found that a combined treatment of local radiofrequency ablation (RFA) and melatonin (MLT) greatly improved clinical outcomes for early lung cancer patients with multiple pulmonary nodules by minimizing lung function injury and reducing the probability of malignant transformation or enlargement of nodules in non-ablated areas. Mechanically, as demonstrated in an associated mouse lung tumor model, RFA not only effectively remove treated tumors but also stimulate antitumor immunity, which could inhibit tumor growth in non-ablated areas. MLT enhanced RFA-stimulated NK activity and exerted synergistic antitumor effects with RFA. Transcriptomics and proteomics analyses of residual tumor tissues revealed enhanced oxidative phosphorylation and reduced acidification as well as hypoxia in the tumor microenvironment, which suggests reprogrammed tumor metabolism after combined treatment with RFA and MLT. Analysis of residual tumor further revealed the depressed activity of MAPK, NF-kappa B, Wnt, and Hedgehog pathways and upregulated P53 pathway in tumors, which was in line with the inhibited tumor growth. Combined RFA and MLT treatment also reversed the Warburg effect and decreased tumor malignancy. These findings thus demonstrated that combined treatment of RFA and MLT effectively inhibited the malignancy of non-ablated nodules and provided an innovative non-invasive strategy for treating early lung tumors with multiple pulmonary nodules. Trial registration: www.chictr.org.cn , identifier ChiCTR2100042695, http://www.chictr.org.cn/showproj.aspx?proj=120931 .

Abstract: This research describes the evolution of the spatial effects of foundation pits considering internal support and external loads. Based on the existing concept of “plane strain ratio”, the term “plane strain ratio considering maximum surface settlement” is proposed to characterize the spatial effects of an asymmetric foundation pit. A series of finite element model calculations were carried out using the Nanchang Aixi Lake foundation pit, including 1) the calculation of simulated actual conditions, 2) the calculation of simulated full symmetric load, and 3) the calculation of simulated asymmetric load. The results indicate that for the symmetric condition at 20 kPa and below, the spatial effect range increases as the load increases. For the symmetric condition above 20 kPa, the load has a negligible impact on the spatial effect range. On the side with a larger load under asymmetric loading conditions, the spatial effect of the working condition below 30 kPa is smaller than the corresponding symmetric load. On the side with a smaller load, the spatial effect of the working condition above 80 kPa increases compared with that of the corresponding symmetrical load. Given and verified are the modified fitting equations that take into account the influence range of spatial effect on both sides of the foundation pit under symmetrical and asymmetrical loads.

Abstract Mitochondria are biosynthetic, bioenergetic, and signaling organelles existing in almost all eukaryotic cells, and their dysregulated function has been proved to be essential for tumorigenesis, tumor development, and tumor metastasis. In this short review, first, we briefly summarize the historic misunderstanding of mitochondria in tumors, and then come up with a current view that mitochondria play a pivotal role in tumor cells; second, we review how tumor cells rewind mitochondrial function for their oncogenic purpose via known or unknown mechanisms by key oncogenes or tumor suppressors; third, we go through reagents and strategies currently available targeting mitochondria when treating tumors. Recently, merging data suggest that slow cycling cancer cells/cancer stem cells have distinctive mitochondrial metabolism comparing to bulk tumor cells and mitochondria inhibitors seem to be promising to target them, which are resistant to traditional radio and chemotherapies. We thus discuss role of mitochondria in these cancer stem cells and summarize mitochondria as a target from different aspects.

Y-box–binding protein 1 (YB-1) is a multifunctional RNA binding protein involved in virtually every step of RNA metabolism. However, the functions and mechanisms of YB-1 in one of the most aggressive cancers, glioblastoma, are not well understood. In this study, we found that YB-1 protein was markedly overexpressed in glioblastoma and acted as a critical activator of both mTORC1 and mTORC2 signaling. Mechanistically, YB-1 bound the 5′UTR of CCT4 mRNA to promote the translation of CCT4, a component of the CCT chaperone complex, that in turn activated the mTOR signaling pathway by promoting mLST8 folding. In addition, YB-1 autoregulated its own translation by binding to its 5′UTR, leading to sustained activation of mTOR signaling. In patients with glioblastoma, high protein expression of YB-1 correlated with increased expression of CCT4 and mLST8 and activated mTOR signaling. Importantly, the administration of RNA decoys specifically targeting YB-1 in a mouse xenograft model resulted in slower tumor growth and better survival. Taken together, these findings uncover a disrupted proteostasis pathway involving a YB-1/CCT4/mLST8/mTOR axis in promoting glioblastoma growth, suggesting that YB-1 is a potential therapeutic target for the treatment of glioblastoma.

Ancient architecture, with its long history, has a high cultural value, artistic achievement, and scientific value. The Nanjing City Wall was constructed in the mid-to-late 14th century, and it ranks first among the world’s city walls in terms of both length and size, whether historically or in the contemporary era. However, these sites are subject to long-term degradation and are sensitive to disturbances from the surrounding landscape, resulting in the potential deterioration of the architecture. Therefore, it is urgent to detect the defects and repair and protect Nanjing City Wall. In this paper, a novel method is proposed to detect the surface defects of the city walls by using the unmanned aerial vehicle (UAV) oblique photogrammetry and terrestrial laser scanning (TLS) data. On the one hand, the UAV oblique photogrammetry was used to collect the image data of the city wall, and a three-dimensional (3D) model of the wall was created using the oblique images. With this model, 43 cracks with lengths greater than 30 cm and 15 shedding surfaces with an area greater than 300 cm2 on the wall can be effectively detected. On the other hand, the point cloud data obtained by TLS were firstly preprocessed, and then, the KNN algorithm was used to construct a local neighborhood for each sampling point, and the neighborhood was fitted using the least squares method. Next, five features of the point cloud were calculated, and the results were visualized. Based on the visualization results, surface defects of the wall were identified, and 18 cracks with lengths greater than 30 cm and 5 shedding surfaces with an area greater than 300 cm2 on the wall were detected. To verify the accuracy of these two techniques in measuring cracks, the coordinates of some cracks were surveyed using a prism-free total station, and the lengths were calculated. The root mean square error (RMSE) of crack lengths based on the UAV oblique photogrammetry model and TLS point cloud model were calculated to be 0.73 cm and 0.34 cm, respectively. The results of the study showed that both techniques were able to detect the defects on the wall surface, and the measurement accuracy could meet the accuracy requirements of the surface defect detection of the city wall. Considering their low cost and high efficiency, these two techniques provide help for the mapping and conservation of historical buildings, which is of great significance for the conservation and repair of ancient buildings.

Flavonoids, including flavonol derivatives, are the main astringent compounds of tea and are beneficial to human health. Many researches have been conducted to comprehensively identify and characterize the phenolic compounds in the tea plant. However, the biological function of tea flavonoids is not yet understood, especially those accumulated in floral organs. In this study, the metabolic characteristics of phenolic compounds in different developmental stages of flower buds and various parts of the tea flower were investigated by using metabolomic and transcriptomic analyses. Targeted metabolomic analysis revealed varying accumulation patterns of different phenolic polyphenol compounds during flowering; moreover, the content of flavonol compounds gradually increased as the flowers opened. Petals and stamens were the main sites of flavone and flavonol accumulation. Compared with those of fertile flowers, the content of certain flavonols, such as kaempferol derivatives, in anthers of hybrid sterile flowers was significantly low. Transcriptomic analysis revealed different expression patterns of genes in the same gene family in tea flowers. The CsFLSb gene was significantly increased during flowering and was highly expressed in anthers. Compared with fertile flowers, CsFLSb was significantly downregulated in sterile flowers. Further functional verification of the three CsFLS genes indicated that CsFLSb caused an increase in flavonol content in transgenic tobacco flowers and that CsFLSa acted in leaves. Taken together, this study highlighted the metabolic properties of phenolic compounds in tea flowers and determined how the three CsFLS genes have different functions in the vegetative and reproductive organs of tea plants. Furthermore, CsFLSb could regulated flavonol biosynthesis in tea flowers, thus influencing fertility. This research is of great significance for balancing the reproductive growth and vegetative growth of tea plants.

With the gradual maturity of the terrestrial laser scanners (TLS) technology, it is widely used in the field of deformation monitoring due to its fast, automated, and non-contact data acquisition capabilities. The TLS technology has changed the traditional deformation monitoring mode which relies on single-point monitoring. This paper analyzes the application of TLS in deformation monitoring, especially in the field of ground surface, dam, tunnel, and tall constructions. We divide the methods for obtaining ground surface deformation into two categories: the method based on point cloud distance and the method based on displacement field. The advantages and disadvantages of the four methods (M2M, C2C, C2M, M3C2) based on point cloud distance are analyzed and summarized. The deformation monitoring methods and precisions based on TLS for dams, tunnels, and tall constructions are summarized, as well as the various focuses of different monitoring objects. Additionally, their limitations and development directions in the corresponding fields are analyzed. The error sources of TLS point cloud data and error correction models are discussed. Finally, the limitations and future research directions of TLS in the field of deformation monitoring are presented in detail.

Mitochondria are not only the main energy supplier but are also the cell metabolic center regulating multiple key metaborates that play pivotal roles in epigenetics regulation. These metabolites include acetyl-CoA, α-ketoglutarate (α-KG), S-adenosyl methionine (SAM), NAD+, and O-linked beta-N-acetylglucosamine (O-GlcNAc), which are the main substrates for DNA methylation and histone post-translation modifications, essential for gene transcriptional regulation and cell fate determination. Tumorigenesis is attributed to many factors, including gene mutations and tumor microenvironment. Mitochondria and epigenetics play essential roles in tumor initiation, evolution, metastasis, and recurrence. Targeting mitochondrial metabolism and epigenetics are promising therapeutic strategies for tumor treatment. In this review, we summarize the roles of mitochondria in key metabolites required for epigenetics modification and in cell fate regulation and discuss the current strategy in cancer therapies via targeting epigenetic modifiers and related enzymes in metabolic regulation. This review is an important contribution to the understanding of the current metabolic-epigenetic-tumorigenesis concept.

The existence of cavities behind the shield tunnel lining can cause cracking, broken pieces, water leakage, and other problems, which reduces the durability and safety of the shield tunnel segment structure. In order to clarify the mechanism of cavity damage, a more systematic study of the effects of cavities on the shield tunnel lining structure from the angle, depth, and the number of cavities is carried out using model tests and numerical simulations without considering the effects of the stiffness reduction effect at the tunnel segment joints and groundwater seepage in this paper. The findings show that the bending moment value and the cavity angle value are approximately linear with the increase of single cavity angle, and the bending moment at the vault arch is reversed when the angle of the cavity behind the arch is greater than 30°. With the increase of single cavity depth, the axial force and bending moment at the cavity increase, and the distribution of bending moment remains unchanged, and the bending moment tends to be stable and unchanged beyond a certain depth. With the increase of single cavity angle and depth, the structural safety coefficient of the segment decreases, and the degree of influence is angle value > depth value. The existence of multiple cavities intensifies the influence of each cavity on the segment, especially when there are cavities behind the top and bottom of the vault; the bending moment value of the top of the vault increases by 22.53% compared with that of the single cavity condition.

LiDAR (Light Detection And Ranging) technology is an important means to obtain three-dimensional information of trees and vegetation. However, due to the influence of scanning mode, environmental occlusion and mutual occlusion between tree canopies and other factors, a tree point cloud often has different degrees of data loss, which affects the high-precision quantitative extraction of vegetation parameters. Aiming at the problem of a tree laser point cloud being missing, an individual tree incomplete point cloud restoration method based on local features of the point cloud is proposed. The L1-Median algorithm is used to extract key points of the tree skeleton, then the dominant direction of skeleton key points and local point cloud density are calculated, and the point cloud near the missing area is moved based on these features to gradually complete the incomplete point cloud compensation. The experimental results show that the above repair method can effectively repair the incomplete point cloud with good robustness and can adapt to the individual tree point cloud with different geometric structures and correct the branch topological connection errors.

The 2-oxoglutarate-dependent dioxygenase (2-OGD) superfamily is one of the largest protein families in plants. The main oxidation reactions they catalyze in plants are hydroxylation, desaturation, demethylation, epimerization, and halogenation. Four members of the 2-OGD superfamily, i.e., flavonone 3β-hydroxylase (F3H), flavones synthase I (FNS I), flavonol synthase (FLS), and anthocyanidin synthase (ANS)/leucoanthocyanidin dioxygenase (LDOX), are present in the flavonoid pathway, catalyzing hydroxylation and desaturation reactions. In this review, we summarize the recent research progress on these proteins, from the discovery of their enzymatic activity, to their functional verification, to the analysis of the response they mediate in plants towards adversity. Substrate diversity analysis indicated that F3H, FNS Ⅰ, ANS/LDOX, and FLS perform their respective dominant functions in the flavonoid pathway, despite the presence of functional redundancy among them. The phylogenetic tree classified two types of FNS Ⅰ, one mainly performing FNS activity, and the other, a new type of FNS present in angiosperms, mainly involved in C-5 hydroxylation of SA. Additionally, a new class of LDOXs is highlighted, which can catalyze the conversion of (+)-catechin to cyanidin, further influencing the starter and extension unit composition of proanthocyanidins (PAs). The systematical description of the functional diversity and evolutionary relationship among these enzymes can facilitate the understanding of their impacts on plant metabolism. On the other hand, it provides molecular genetic evidence of the chemical evolution of flavonoids from lower to higher plants, promoting plant adaptation to harsh environments.

Abstract We investigate a stochastic optimal control problem where the controlled system is depicted as a stochastic differential delayed equation; however, at the terminal time, the state is constrained in a convex set. We firstly introduce an equivalent backward delayed system depicted as a time-delayed backward stochastic differential equation. Then a stochastic maximum principle is obtained by virtue of Ekeland’s variational principle. Finally, applications to a state constrained stochastic delayed linear-quadratic control model and a production-consumption choice problem are studied to illustrate the main obtained result.

Background: Alzheimer's disease (AD) is the most common type of dementia. Scientists have discovered that the causes of AD may include a combination of genetic, lifestyle, and environmental factors, but the exact cause has not yet been elucidated. Effective strategies to prevent and treat AD therefore remain elusive. The identified genetic causes of AD mainly focus on individual genes, but growing evidence has shown that complex diseases are usually affected by the interaction of genes in a network. Few studies have focused on the interactions and correlations between genes and how they are gradually destroyed or disappear during AD progression. A differential network analysis has been recognized as an essential tool for identifying the underlying pathogenic mechanisms and significant genes for prediction analysis. We therefore aim to conduct a differential network analysis to reveal potential networks involved in the neuropathogenesis of AD and identify genes for AD prediction.Methods: In this paper, we selected 365 samples from the Religious Orders Study and the Rush Memory and Aging Project, including 193 clinically and neuropathologically confirmed AD subjects and 172 no cognitive impairment (NCI) controls. Then, we selected 158 genes belonging to the AD pathway (hsa05010) of the Kyoto Encyclopedia of Genes and Genomes. We employed a machine learning method, namely, joint density-based non-parametric differential interaction network analysis and classification (JDINAC), in the analysis of gene expression data (RNA-seq data). We searched for the differential networks in the RNA-seq data with a pathological diagnosis of AD. Finally, an optimal prediction model was built through cross-validation, which showed good discrimination and calibration for AD prediction.Results: We used JDINAC to derive a gene co-expression network and to explore the relationship between the interaction of gene pairs and AD, and the top 10 differential gene pairs were identified. We then compared the prediction performance between JDINAC and individual genes based on prediction methods. JDINAC provides better accuracy of classification than the latest methods, such as random forest and penalized logistic regression.Conclusions: The interaction between gene pairs is related to AD and can provide more insight than the individual genes in AD prediction.

NLRP3 inflammasome has been widely implicated in the development and progression of various hematological diseases. However, how NLRP3 inflammasome contributes to the pathogenesis and clinical features of acute lymphoblastic leukemia (ALL) is still unknown. Here, in ALL patients' bone marrow, we investigated the single-nucleotide polymorphisms (SNPs) and expression of NLRP3 inflammasome related genes, NF-κB, NLRP3, IL-1β, IL-18, Caspase-1, and ASC. A total of 308 ALL patients and 300 healthy participants were included in this study. D allele and DD genotype under codominant model of NF-κB-94ins/del ATTG were showed as a protective factor in susceptibility of ALL. As for CARD8 (rs2043211), AT/TT genotype under dominant model and TT genotype under codominant model greatly increased the ALL susceptibility. We further studied the relationship between NLRP3 inflammasome genetic polymorphisms and clinical relevance. The results showed that DD genotype of NF-κB-94 ins/del ATTG and AT/TT genotype of CARD8 (rs2043211) contributed to lower WBC count and T-cell immunophenotype, respectively. Moreover, we also found that AT and TT genotypes of CARD8 (rs2043211), GT and TT genotypes of IL-1β (rs16944), and TT genotype of IL-18 (rs1946518) were associated with higher mRNA expression of NLRP3 inflammasome related genes and secretion of downstream cytokines. In conclusion, NF-κB-94 ins/del ATTG and CARD8 (rs2043211) genotypes might serve as novel biomarkers and potential targets for ALL.

Obesity, a dysregulation of adipose tissue, is a major health risk factor associated with many diseases. Brown adipose tissue (BAT)-mediated thermogenesis can potentially regulate energy expenditure, making it an attractive therapeutic target to combat obesity. Here, we characterize the effects of cold exposure, thermoneutrality, and high-fat diet (HFD) feeding on mouse supraclavicular BAT (scBAT) morphology and BAT-associated gene expression compared to other adipose depots, including the interscapular BAT (iBAT). scBAT was as sensitive to cold induced thermogenesis as iBAT and showed reduced thermogenic effect under thermoneutrality. While both scBAT and iBAT are sensitive to cold, the expression of genes involved in nutrient processing is different. The scBAT also showed less depot weight gain and more single-lipid adipocytes, while the expression of BAT thermogenic genes, such as Ucp1, remained similar or increased more under our HFD feeding regime at ambient and thermoneutral temperatures than iBAT. Together, these findings show that, in addition to its anatomical resemblance to human scBAT, mouse scBAT possesses thermogenic features distinct from those of other adipose depots. Lastly, this study also characterizes a previously unknown mouse deep neck BAT (dnBAT) depot that exhibits similar thermogenic characteristics as scBAT under cold exposure and thermoneutrality.

This paper presents a novel framework to extract metro tunnel cross sections (profiles) from Terrestrial Laser Scanning point clouds. The entire framework consists of two steps: tunnel central axis extraction and cross section determination. In tunnel central extraction, we propose a slice-based method to obtain an initial central axis, which is further divided into linear and nonlinear circular segments by an enhanced Random Sample Consensus (RANSAC) tunnel axis segmentation algorithm. This algorithm transforms the problem of hybrid linear and nonlinear segment extraction into a sole segmentation of linear elements defined at the tangent space rather than raw data space, significantly simplifying the tunnel axis segmentation. The extracted axis segments are then provided as input to the step of the cross section determination which generates the coarse cross-sectional points by intersecting a series of straight lines that rotate orthogonally around the tunnel axis with their local fitted quadric surface, i.e., cylindrical surface. These generated profile points are further refined and densified via solving a constrained nonlinear least squares problem. Our experiments on Nanjing metro tunnel show that the cross sectional fitting error is only 1.69 mm. Compared with the designed radius of the metro tunnel, the RMSE (Root Mean Square Error) of extracted cross sections’ radii only keeps 1.60 mm. We also test our algorithm on another metro tunnel in Shanghai, and the results show that the RMSE of radii only keeps 4.60 mm which is superior to a state-of-the-art method of 6.00 mm. Apart from the accurate geometry, our approach can maintain the correct topology among cross sections, thereby guaranteeing the production of geometric tunnel model without crack defects. Moreover, we prove that our algorithm is insensitive to the missing data and point density.

We proposed a hybrid compact-CIP scheme to solve the Korteweg-de Vries equation. The algorithm is based on classical constrained interpolation profile (CIP) method, which is coupled with high-order compact scheme for the third derivatives in Korteweg-de Vries equation. Several numerical examples are presented to confirm the high resolution of the proposed scheme.

Mean-field forward-backward doubly stochastic differential equations (MF-FBDSDEs) are studied, which extend many important equations well studied before. Under some suitable monotonicity assumptions, the existence and uniqueness results for measurable solutions are established by means of a method of continuation. Furthermore, the probabilistic interpretation for the solutions to a class of nonlocal stochastic partial differential equations (SPDEs) combined with algebra equations is given.