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Abstract The precise mechanisms regulating inflammatory and prorepair macrophages have not been fully elucidated, despite the pivotal role played by innate immunity in wound healing. We first employed a denervation wound model to validate the crosstalk between neurons and macrophages. Compared to normal wound healing, the denervation wound healing process involved fewer macrophages, decreased angiogenesis, and delayed wound healing. Consistent with the results of the scRNA-seq libraries, the number of early-phase wound proinflammatory and late-phase wound prorepair macrophages were decreased during the denervation wound healing process. We profiled early-phase and late-phase skin wounds in mice at the transcriptional and functional levels and compared them to those of normal wounds. We revealed a neuroimmune regulatory pathway driven by peripheral nerve-derived CSF1 that induces BMP2 expression in prorepair macrophages and enhances nerve regeneration. Crosstalk between neurons and macrophages facilitates the healing process of wounds and provides a potential strategy for wound healing therapy.

The texture of polycrystalline material is the preferred orientation distribution of its crystallites. As an intrinsic feature of metals, alloys, ceramics and polymers, texture strongly affects many properties of polycrystalline materials. It will make the material exhibit significant anisotropy in properties, consequently affecting its service performance. Therefore, texture is regarded as one of the essential parameters for describing a full microstructural characterization of polycrystalline materials. Texture determination is usually based on the pole figure measurements by X-ray, synchrotron radiation, electron back-scatter diffraction and neutron diffraction. Among these techniques, neutron diffraction offers many advantages in texture characterization due to the low absorption coefficient of neutrons. For example, it enables the use of sample environment devices to investigate texture evolution during in-situ high temperature or loading processes of materials. The first neutron texture diffractometer in China has been built at the China Advanced Research Reactor (CARR), due to strong demand for texture measurement with neutrons from the domestic user community. This instrument is mainly applied to study texture in commonly used industrial materials and engineering components. As the study of texture evolution during in-situ loading processes is extremely important for a deeper understanding of the deformation modes and performance evolution mechanisms of materials under various deformation processes and service environment. A specialized in-situ loading device was designed and developed based on the neutron texture diffractometer of CARR, capable of applying a maximum loading force of 10 kN, with a continuously adjustable loading rate ranging from 0.01 to 3 mm/min. In order to realize real-time measurement of the microstructure and bulk texture evolution in polycrystalline materials during in-situ tensile and compression processes, this loading device can be rotated around neutron texture diffractometer Euler cradle χ angle from 0° to 90° and along the tensile axis rotated from 0° to 360°. The texture evolution of hot-extruded Mg-1.2Al-0.3Ca-0.47Mn (MMK1) alloy during in-situ tensile process was studied using this device, and it was found that the intensity of the (0002) basal texture continuously increased with increasing of tensile displacement, indicating that the device’s capability to measure texture evolution of polycrystalline materials during in-situ loading processes. The design and development of this in-situ loading device at the CARR neutron texture diffractometer provide crucial technical support for investigating the relationship between microstructure and mechanical properties of polycrystalline materials, especially the laws and mechanisms of material structure evolution under external load condition.

Abstract Bamboo corals are promising archives of paleoceanographic conditions. Existing calibrations for element‐to‐calcium ratio (El/Ca) proxies of bamboo corals, however, are not necessarily calibrated to contemporaneous environmental parameters, thus weakening the reliability of the proxies. Here, we aim at calibrating the proxies by comparing El/Ca in the outermost surface of the calcareous skeletons of live‐collected bamboo corals from the South China Sea (SCS) with modern environmental records. Statistical analysis suggests that Mg/Ca and Ba/Ca can be expressed as a function of in situ seawater temperature and silicate concentration, respectively, that is, Mg/Ca (mmol/mol) = 2.17 ± 0.51 * T (°C) + 74.90 ± 2.66 and Ba/Ca (μmol/mol) = 0.070 ± 0.020 * Silicate (μmol/kg) + 7.27 ± 2.42. The slope of the Mg/Ca‐T equation from this study is slightly different from that in a previous study on bamboo corals, likely due to taxonomic and/or geographic differences of the corals and/or differences in sampling strategy and pre‐treatment method. Intra‐ and inter‐coral variations have small effects on Mg/Ca, yielding an uncertainty of 2.04 mmol/mol in Mg/Ca (95% confidence interval), equivalent to 0.94°C in estimated temperature. The slope of the Ba/Ca‐silicate equation is the same as that in a previous study, suggesting little effect of geographic difference on Ba/Ca. Intra‐ and inter‐coral variations in Ba/Ca are larger than those in Mg/Ca, possibly reflecting incorporation of multiple Ba‐rich particulate phases and/or highly variable nutrient concentrations in the micro‐environment near corals. These new calibrations allow reconstructions of paleo‐temperature and nutrient concentration in the SCS on decadal and longer timescales.

Black spot, one of the major diseases of kiwifruit, is caused by Alternaria alternata. A comprehensive investigation into its pathogenicity mechanism is imperative in order to propose a targeted and effective control strategy. The effect of L-arginine on the pathogenicity of A. alternata and the underlying mechanisms were investigated. The results showed that treatment with 5 mM L−1 of L-arginine promoted spore germination and increased the colony diameter and lesion diameter of A. alternata in vivo and in vitro, which were 23.1% and 9.3% higher than that of the control, respectively. Exogenous L-arginine treatment also induced endogenous L-arginine and nitric oxide (NO) accumulation by activating nitric oxide synthase (NOS), arginine decarboxylase (ADC) and ornithine decarboxylase (ODC). In addition, exogenous L-arginine triggered an increase in reactive oxygen species (ROS) levels by activating the activity and inducing gene expression upregulation of NADPH oxidase. The hydrogen peroxide (H2O2) and superoxide anion (O2.−) levels were 15.9% and 2.2 times higher, respectively, than in the control group on the second day of L-arginine treatment. Meanwhile, antioxidant enzyme activities and gene expression levels were enhanced, including superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), glutathione peroxidase (GPX), and glutathione reductase (GR). In addition, exogenous L-arginine stimulated cell wall-degrading enzymes in vivo and in vitro by activating gene expression. These results suggested that exogenous L-arginine promoted the pathogenicity of A. alternata by inducing the accumulation of polyamines, NO, and ROS, and by activating systems of antioxidants and cell wall-degrading enzymes. The present study not only revealed the mechanism by which low concentrations of L-arginine increase the pathogenicity of A. alternata, but also provided a theoretical basis for the exclusive and precise targeting of A. alternata in kiwifruit.

Black spot caused by Alternaria alternata is one of the most common postharvest diseases in fruit and vegetables. A comprehensive investigation into its pathogenicity mechanism is imperative in order to propose a targeted and effective control strategy. The effect of nitric oxide (NO) on the pathogenicity of A. alternata and its underlying mechanism was studied. The results showed that treatment with 0.5 mM L−1 of sodium nitroprusside (SNP) (NO donor) increased the lesion diameter of A. alternata in vivo and in vitro, which was 22.8% and 13.2% higher than that of the control, respectively. Exogenous NO treatment also induced endogenous NO accumulation by activating nitric oxide synthase (NOS). In addition, NO triggered an increase in reactive oxygen species (ROS) levels. NO enhanced activities and gene expression levels of NADPH oxidase (NOX), superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), glutathione peroxidase (GPX), and glutathione reductase (GR). Moreover, NO stimulated cell wall degrading enzymes by activating the corresponding gene expression in vivo and in vitro. These results suggested that exogenous NO promoted the pathogenicity of A. alternata by inducing ROS accumulation and activating antioxidants and cell wall degrading enzymes. The present results could establish a theoretical foundation for the targeted control of the black spot disease in pear fruit.

Planar oxide atomic clusters are of considerable scientific interest because of their potential for enhanced catalytic activity versus their three‐dimensional counterparts. This enhancement is the result of the substrate stabilizing novel planar configurations that have an extensive periphery where catalytic reactions can occur. A class of planar NbnOm atomic clusters that are synthesized by the evaporation of metallic Nb onto an Au(111) substrate in an ultrahigh vacuum environment and subsequent oxidation at elevated temperatures is reported. The atomic structures of the clusters are determined using a combination of scanning tunneling microscopy and density functional theory. The clusters are composed of structural units with four‐, five‐, and sixfold rotational symmetry and these units can assemble to form larger planar clusters. The theoretical comparison of supported structures with their hypothetical freestanding counterparts shows that the atomic and electronic structures of the oxide clusters are significantly altered by the interaction with the Au substrate. The substrate effects include interfacial charge transfer and structural relaxation to relieve the strain in the Nb‐O bonds. The substrate interactions also reduce the energy differences between clusters of different configurations and this enables the coexistence of a large variety of cluster configurations.

As major producers in the national economy, industrial enterprises bear great responsibility for carbon emissions. A smart city pilot policy (SCPP) with innovative advantages and environmentally friendly features provides a feasible way to scientifically achieve carbon emission reduction targets while maintaining industrial growth. However, there is a lack of specific understanding of the microscopic carbon reduction mechanisms of the policy. Thus, based on the data of A-share listed industrial firms from 2009 to 2018 in China, this study explores the impact mechanism of the SCPP on the CO2 emissions from industrial firms with the time-varying DID methodology and the mediating effect model. The results demonstrate that the SCPP can curb CO2 emissions from industrial firms in China by 23% by strengthening the intensity of environmental regulation and promoting green technological innovation. Further analysis indicates that the mediating effect of resource allocation efficiency only works in industrial firms in low-carbon industries, not high-carbon industries. In addition, the heterogeneity test suggests a pronounced reduction effect of the SCPP on non-state-owned enterprises (non-SOEs), and industrial enterprises in low-carbon industries, resource-based cities and eastern China. This paper is of great significance for providing theoretical and practical implications for making rational use of smart city policies to improve the carbon reduction performance of enterprises.

Abstract In recent years, air pollution has become a factor that cannot be ignored, affecting human lives and health. The distribution of high-density populations and high-intensity development and construction have accentuated the problem of air pollution in China. To accelerate air pollution control and effectively improve environmental air quality, the target of our research was cities with serious air pollution problems to establish a model for air pollution prediction. We used the daily monitoring data of air pollution from January 2016 to December 2020 for the respective cities. We used the long short term memory networks (LSTM) algorithm model to solve the problem of gradient explosion in recurrent neural networks, then used the particle swarm optimization algorithm to determine the parameters of the CNN-LSTM model, and finally introduced the complete ensemble empirical mode decomposition of adaptive noise (CEEMDAN) decomposition to decompose air pollution and improve the accuracy of model prediction. The experimental results show that compared with a single LSTM model, the CEEMDAN-CNN-LSTM model has higher accuracy and lower prediction errors. The CEEMDAN-CNN-LSTM model enables a more precise prediction of air pollution, and may thus be useful for sustainable management and the control of air pollution.

Hypertrophic scar (HS) is a chronic inflammatory skin disease characterized by excessive deposition of extracellular matrix, but the exact mechanisms related to its formation remain unclear, making it difficult to treat. This study aimed to investigate the potential role of cuproptosis in the information of HS. To this end, we used single-cell sequencing and bulk transcriptome data, and screened for cuproptosis-related genes (CRGs) using differential gene analysis and machine learning algorithms (random forest and support vector machine). Through this process, we identified a group of genes, including ATP7A, ULK1, and MTF1, as novel therapeutic targets for HS. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to confirm the mRNA expression of ATP7A, ULK1, and MTF1 in both HS and normal skin (NS) tissues. We also constructed a diagnostic model for HS and analyzed the immune infiltration characteristics. Additionally, we used the expression profiles of CRGs to perform subgroup analysis of HS. We focused mainly on fibroblasts in the transcriptional profile at single-cell resolution. By calculating the cuproptosis activity of each fibroblast, we found that cuproptosis activity of normal skin fibroblasts increased, providing further insights into the pathogenesis of HS. We also analyzed the cell communication network and transcription factor regulatory network activity, and found the existence of a fibroblast-centered communication regulation network in HS, where cuproptosis activity in fibroblasts affects intercellular communication. Using transcription factor regulatory activity network analysis, we obtained highly active transcription factors, and correlation analysis with CRGs suggested that CRGs may serve as potential target genes for transcription factors. Overall, our study provides new insights into the pathophysiological mechanisms of HS, which may inspire new ideas for the diagnosis and treatment.

BackgroundCutaneous melanoma (CM) is one of the malignant tumors with a relative high lethality. Necroptosis is a novel programmed cell death that participates in anti-tumor immunity and tumor prognosis. Necroptosis has been found to play an important role in tumors like CM. However, the necroptosis-associated lncRNAs’ potential prognostic value in CM has not been identified.MethodsThe RNA sequencing data collected from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Project (GTEx) was utilized to identify differentially expressed genes in CM. By using the univariate Cox regression analysis and machine learning LASSO algorithm, a prognostic risk model had been built depending on 5 necroptosis-associated lncRNAs and was verified by internal validation. The performance of this prognostic model was assessed by the receiver operating characteristic curves. A nomogram was constructed and verified by calibration. Furthermore, we also performed sub-group K-M analysis to explore the 5 lncRNAs’ expression in different clinical stages. Function enrichment had been analyzed by GSEA and ssGSEA. In addition, qRT-PCR was performed to verify the five lncRNAs’ expression level in CM cell line (A2058 and A375) and normal keratinocyte cell line (HaCaT).ResultsWe constructed a prognostic model based on five necroptosis-associated lncRNAs (AC245041.1, LINC00665, AC018553.1, LINC01871, and AC107464.3) and divided patients into high-risk group and low-risk group depending on risk scores. A predictive nomogram had been built to be a prognostic indicator to clinical factors. Functional enrichment analysis showed that immune functions had more relationship and immune checkpoints were more activated in low-risk group than that in high-risk group. Thus, the low-risk group would have a more sensitive response to immunotherapy.ConclusionThis risk score signature could be used to divide CM patients into low- and high-risk groups, and facilitate treatment strategy decision making that immunotherapy is more suitable for those in low-risk group, providing a new sight for CM prognostic evaluation.

Keloid is a pathological scar formed by abnormal wound healing, characterized by the persistence of local inflammation and excessive collagen deposition, where the intensity of inflammation is positively correlated with the size of the scar formation. The pathophysiological mechanisms underlying keloid formation are unclear, and keloid remains a therapeutic challenge in clinical practice. This study is the first to investigate the role of glycosphingolipid (GSL) metabolism pathway in the development of keloid. Single cell sequencing and microarray data were applied to systematically analyze and screen the glycosphingolipid metabolism related genes using differential gene analysis and machine learning algorithms (random forest and support vector machine), and a set of genes, including ARSA,GBA2,SUMF2,GLTP,GALC and HEXB, were finally identified, for which keloid diagnostic model was constructed and immune infiltration profiles were analyzed, demonstrating that this set of genes could serve as a new therapeutic target for keloid. Further unsupervised clustering was performed by using expression profiles of glycosphingolipid metabolism genes to discover keloid subgroups, immune cells, inflammatory factor differences and the main pathways of enrichment between different subgroups were calculated. The single-cell resolution transcriptome landscape concentrated on fibroblasts. By calculating the activity of the GSL metabolism pathway for each fibroblast, we investigated the activity changes of GSL metabolism pathway in fibroblasts using pseudotime trajectory analysis and found that the increased activity of the GSL metabolism pathway was associated with fibroblast differentiation. Subsequent analysis of the cellular communication network revealed the existence of a fibroblast-centered communication regulatory network in keloids and that the activity of the GSL metabolism pathway in fibroblasts has an impact on cellular communication. This contributes to the further understanding of the pathogenesis of keloids. Overall, we provide new insights into the pathophysiological mechanisms of keloids, and our results may provide new ideas for the diagnosis and treatment of keloids.

In this study, the mixed diffusion flame soot of methane, ethylene and hydrogen were studied, and the two-dimensional light extinction measurement was applied to investigate the distribution characteristics of the ethylene flame soot concentration with different methane and hydrogen ratios. The soot concentration distribution was analyzed, and the effect of hydrogen addition and methane addition on the soot distribution of a laminar ethylene diffusion flame was investigated. The experiments showed that the flame soot of pure ethylene was mainly distributed in both sides of the flame, which increased first and then decreased in the height direction, and the distribution in the radial direction moved toward the center of the flame as the height increased. The low methane addition in pure ethylene flame will produce a synergistic effect to promote soot formation, and its effect disappeared with the increase of methane addition, and the adding of hydrogen in pure ethylene flame will inhibit soot formation, and the inhibiting effect increased with the increase of hydrogen. When the three gases were blended together, the inhibition effect of hydrogen on soot formation was greater than the promotion effect of methane on soot formation at this ratio.

BackgroudSkin cutaneous melanoma (SKCM) is an extremely metastatic form of skin cancer. However, there are few valuable molecular biomarkers, and accurate diagnosis is still a challenge. Hypercoagulable state encourages the infiltration and development of tumor cells and is significantly associated with poor prognosis in cancer patients. However, the use of a coagulation-related gene (CRG) signature for prognosis in SKCM, on the other hand, has yet to be determined.MethodWe used data from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases to identify differentially expressed CRGs, then designed a prognostic model by using the LASSO algorithm, univariate and multivariate Cox regression analysis, and constructed a nomogram which was evaluated by calibration curves. Moreover, the Gene Expression Omnibus (GEO), GSE54467 was used as an independent validation. The correlation between risk score and clinicopathological characteristics, tumor microenvironment (TME), and immunotherapy was further analyzed.ResultsTo develop a prognostic model, seven CRGs in SKCM patients related to overall survival (OS) were selected: ANG, C1QA, CFB, DUSP6, KLKB1, MMP7, and RABIF. According to the Kaplan-Meier survival analysis, an increased OS was observed in the low-risk group than in the high-risk group (P

Based on the existing research on environmental regulation (ER) and enterprise innovation, this paper separates green innovation ability from general technological innovation and divides it, from the perspective of motivation, into substantive green innovation (SUBGI) and symbolic green innovation (SYMGI). This paper employs panel data of China's A-share listed enterprise from 2008 to 2018 in a difference-in-difference-in-difference model to construct a quasinatural experiment on the impacts of ER and the green innovation strategy of enterprises. Government subsidies and regulatory capture are used to explore the mechanism between ER and innovation behavior. The results show that ER has a significantly positive effect on green innovation, but its impact on SYMGI and SUBGI decreases. Under the constraints of the ER policy, government subsidies incentivize the green innovation of enterprises, but they are not the main reason for the difference between the two innovation behaviors. Regulatory capture plays a negative moderating role in ER promoting enterprises’ SUBGI and has no significant impact on SYMGI, which is the key factor leading to the difference between the two innovation behaviors. The heterogeneity test suggests a pronounced promotion effect of ER on state-owned enterprises, large enterprises, and growing enterprises. This study provides momentous policy implications for making rational use of environmental policies in promoting enterprises’ green innovation capability, especially high-quality green innovation behavior aimed at promoting enterprises’ green technology progress and gaining competitive advantages.

Objective To investigate the impact of COVID-19 social distancing on medical research from the perspective of postgraduate students. Methods A cross-sectional study using an online survey was conducted from October 31 to November 1, 2021. A questionnaire was used to assess the impact of COVID-19 social distancing on medical research among postgraduate students. The questionnaire included basic information, medical research information, and information about social distancing measures. Participants also completed the self-made Research Work Affected Scale of Postgraduates (RWAS-P; qualitative evaluation: very mildly 0–10; mildly 11–20; moderately 21–30; severely 31–40; very severely 41–50). Logistic regression was used to identify factors related to the impact of COVID-19 social distancing. Results A total of 468 participants were analyzed; 95.2% of the participants adhered to social distancing measures. The median total RWAS-P score was 22. The median RWAS-P scores for earlier research data, current research projects, future research plans, paper publication, and graduation schedule were 2, 6, 6, 6, and 4, respectively (score range 0–10). The higher grade of students, experimental research, and existence of inappetence or sleeplessness were related to negative attitude towards COVID-19 social distancing (odd ratio = 6.35, 9.80, 2.31, 2.15, 1.95, respectively). Conclusions Participants reported that social distancing had a moderate overall impact on their medical research. Social distancing had the greatest impact on current research projects, future research plans, and paper publications among postgraduate students. Higher grade level, experimental research type, inappetence, and sleeplessness were related to the impact of social distancing on their medical research.

Arsenic exposure is related to insulin resistance (IR). However, the underlying mechanism is still uncertain. NOD-like receptors containing pyrin domain 3 (NLRP3) inflammasome is a key driving factor of IR. We found that NaAsO2 caused hepatic IR, activated NLRP3 inflammasome, and inhibited glycolysis pathway in vivo. We also found that tricarboxylic acid cycle (TCA cycle) was inhibited, and the content of hepatic lactate was upregulated with the treatment of arsenic. Consistent with these findings, we found that NLRP3 inflammasome and glycolysis were involved in the development of IR in L-02 cells. Besides, inhibiting NLRP3 inflammasome upregulated aerobic glycolysis and inhibited anaerobic glycolysis. Moreover, we demonstrated that NLRP3 inflammasome could bind to pyruvate kinase, liver and RBC (PKLR). Simultaneously, insulin signaling rather than NLRP3 inflammasome activation was altered by overexpressing PKLR. In summary, after treatment with NaAsO2, NLRP3 inflammasome blocked the glycolytic pathway via binding to PKLR, which in turn caused hepatic IR. This study shed new light on the molecular mechanism underlying arsenic-induced IR.

Phosphodiesterase 2 (PDE2A) modulates the levels of cAMP/cGMP and was recently found to be involved in mitochondria function regulation, closely related to multiple types of tumor progression. This study aimed to estimate the prognostic significance and biological effects of PDE2A on hepatocellular carcinoma (HCC). We comprehensively analyzed the PDE2A mRNA expression in HCC based on The Cancer Genome Atlas (TCGA) database and investigated the effects of PDE2A on the proliferation and metastatic capacity of HCC cells. PDE2A was downregulated in 25 cancer types, including HCC. Lower PDE2A expression was a protective factor in HCC and was negatively associated with serum AFP levels, tumor status, vascular invasion, histologic grade, and pathologic stage of HCC. Moreover, tumors with low PDE2A expression displayed a decreased immune function. Then, the ROC curve was used to assess the diagnostic ability of PDE2A in HCC (AUC = 0.823 in TCGA and AUC = 0.901 in GSE76427). Patients with low PDE2A expression exhibited worse outcomes compared with those with high PDE2A expression. Additionally, GO functional annotations demonstrated the involvement of PDE2A in the ECM organization, systems development, and ERK-related pathways, indicating that PDE2A might regulate HCC growth and metastasis. The in vitro experiments confirmed that overexpression of PDE2A inhibited proliferation, colony formation, migration, and invasion in two HCC cell lines (HLF and SNU-368), while inhibition of PDE2A has the opposite results. The mechanism of PDE2A’s effect on HCC cells is attributed to the change of mitochondrial morphology and ATP content. These data demonstrated that PDE2A closely participated in the regulation of HCC proliferation and metastasis and can be used as a predictive marker candidate and a potential therapeutic target for HCC.

The insulin family consists of insulin, insulin-like growth factor 1 (IGF-1), insulin-like growth factor 2 (IGF-2), their receptors (IR, IGF-1R and IGF-2R), and their binding proteins. All three ligands are involved in cell proliferation, apoptosis, protein synthesis and metabolism due to their homologous sequences and structural similarities. Insulin-like growth factor 2, a member of the insulin family, plays an important role in embryonic development, metabolic disorders, and tumorigenesis by combining with three receptors with different degrees of affinity. The main pathological feature of various fibrotic diseases is the excessive deposition of extracellular matrix (ECM) after tissue and organ damage, which eventually results in organic dysfunction because scar formation replaces tissue parenchyma. As a mitogenic factor, IGF-2 is overexpressed in many fibrotic diseases. It can promote the proliferation of fibroblasts significantly, as well as the production of ECM in a time- and dose-dependent manner. This review aims to describe the expression changes and fibrosis-promoting effects of IGF-2 in the skin, oral cavity, heart, lung, liver, and kidney fibrotic tissues.