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Abstract Osimertinib is a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (EGFR-TKI) approved for patients with EGFR T790M resistance mutations as first- or second-line treatment of EGFR-positive patients. Resistance to Osimertinib will inevitably develop, and the underlying mechanisms are largely unknown. In this study, we discovered that acquired resistance to Osimertinib is associated with abnormal DNA damage response (DDR) in lung adenocarcinoma cells. We discovered that the polycomb protein Lethal(3) Malignant Brain Tumor-Like Protein 1 (L3MBTL1) regulates chromatin structure, thereby contributing to DDR and Osimertinib resistance. EGFR oncogene inhibition reduced L3MBTL1 ubiquitination while stabilizing its expression in Osimertinib-resistant cells. L3MBTL1 reduction and treatment with Osimertinib significantly inhibited DDR and proliferation of Osimertinib-resistant lung cancer cells in vitro and in vivo. L3MBTL1 binds throughout the genome and plays an important role in EGFR-TKI resistance. It also competes with 53BP1 for H4K20Me2 and inhibits the development of drug resistance in Osimertinib-resistant lung cancer cells in vitro and in vivo. Our findings suggest that L3MBTL1 inhibition is a novel approach to overcoming EGFR-TKI-acquired resistance.

Abstract Natural killer/T cell lymphoma (NKTCL) exhibits highly aggressive clinical behavior, and the outcomes for relapsed/refractory patients are still poor. Recently, the mechanism underlying the effect of Epstein-Barr virus (EBV) infection, which has not been fully defined in NKTCL, has attracted great attention. We explored how LMP1 promoted aerobic glycolysis via metabolic sequencing combined with mRNA sequencing and immunoprecipitation coupled to mass spectrometry. Experimental assays were used to determine the effects of LMP1 and its downstream pathway on the function and glucose metabolism of NKTCL cells. The correlations between LMP1 expression in patients and their clinical features, treatment response, and prognosis were analyzed. Results show that LMP1 enhances NKTCL cell proliferation in vitro and in vivo, inhibits apoptosis, and decreases gemcitabine sensitivity. In addition, LMP1 also enhances aerobic glycolysis in NKTCL cells, as indicated by increases in glucose uptake, lactate production, and extracellular acidification rate. Clinically, LMP1 expression is correlated with risk stratification, treatment response, and prognosis, and higher LMP1 expression indicates greater SUVmax for NKTCL patients. Mechanistically, LMP1 competitively binds to TRAF3 to promote cell proliferation and aerobic glycolysis by regulating the noncanonical NF-κB pathway. The application of an NF-κB pathway inhibitor or reactivation of the NF-κB pathway affects aerobic glycolysis and the biological function of NKTCL cells. In summary, this study is the first to describe and define in detail how LMP1 affects glucose metabolism in NKTCL and might provide a novel perspective for further treatment.

With the continuous development of the internet, an increasing number of images have been tampered with on the network, accompanied by a growing range of techniques to cover up tampering traces.However, most current detection models neglect the impact of image post-processing on tamper detection algorithms, limiting their real-life applications.To address these issues, a general image tampering location model based on enhanced samples and the pseudo-twin network was proposed.The pseudo-twin network enabled the model to learn tampering features in real images.On one hand, by applying convolution constraints, the image content was suppressed, allowing the model to focus more on residual trace information of tampering.The two-branch structure of the network facilitated the comprehensive utilization of image feature information.By utilizing enhanced samples, the model could dynamically generate the most crucial pictures for learning tamper types, enabling targeted training of the model.This approach ensured that the model converged in all directions, ultimately obtaining the global optimal model.The idea of data enhancement was employed to automatically generate abundant tampered images and corresponding masks, effectively resolving the limited tampering dataset issue.Extensive experiments were conducted on four datasets, demonstrating the feasibility and effectiveness of the proposed model in pixel-level tamper detection.Particularly on the Columbia dataset, the algorithm achieves a 33.5% increase in F1 score and a 23.3% increase in MCC score.These results indicate that the proposed model harnesses the advantages of deep learning models and significantly improves the effectiveness of tamper location detection.

To solve the problem of reservoir sediment accumulation, this paper intends to study the feasibility of preparing reservoir sediment-cement composite cementitious material by partially replacing cement with reservoir sediment. Using the single factor test method, the replacement rate of reservoir sediment and mechanical activation time were selected as variables to explore the effects of water requirement of normal consistency, setting time, mortar fluidity, and mechanical properties of mortar specimens. The results show that with the increase of sediment replacement rate, the water requirement of normal consistency of composite cementitious material paste increases, the setting time increases, the fluidity of mortar decreases, and the mechanical properties of mortar specimens decrease significantly. With the increase of mechanical activation time, the water requirement of normal consistency decreases, the setting time decreases, the fluidity of mortar increases, and the mechanical properties of the mortar specimen increase. The microcosmic results show that mechanical activation can promote the formation of C-S-H gel in reservoir sediment, and fill each other with unreacted reservoir sediment particles, resulting in a denser microstructure. The purpose of this paper is to provide theoretical support for the preparation of reservoir mud-cement composite cementitious material.

Summary: How mechanical allodynia following nerve injury is encoded in patterns of neural activity in the spinal cord dorsal horn (DH) remains incompletely understood. We address this in mice using the spared nerve injury model of neuropathic pain and in vivo electrophysiological recordings. Surprisingly, despite dramatic behavioral over-reactivity to mechanical stimuli following nerve injury, an overall increase in sensitivity or reactivity of DH neurons is not observed. We do, however, observe a marked decrease in correlated neural firing patterns, including the synchrony of mechanical stimulus-evoked firing, across the DH. Alterations in DH temporal firing patterns are recapitulated by silencing DH parvalbumin+ (PV+) interneurons, previously implicated in mechanical allodynia, as are allodynic pain-like behaviors. These findings reveal decorrelated DH network activity, driven by alterations in PV+ interneurons, as a prominent feature of neuropathic pain and suggest restoration of proper temporal activity as a potential therapeutic strategy to treat chronic neuropathic pain.

Under the challenges of global crises such as climate warming, ESG performance, which represents sustainable development, has received widespread attention at home and abroad. Using the panel data from 2011 to 2020, comprising 726 high energy-consuming companies listed on the Shanghai and Shenzhen A-shares, this paper takes Energy Internet demonstration project in 2016 as a quasi-natural experiment and builds a difference-in-difference model to study its microscopic policy effects. The study found that, firstly, Energy Internet can markedly enhance ESG performance of high energy-consuming companies. Secondly, the mechanism test finds that Energy Internet can facilitate high energy-consuming enterprises to enhance their ESG performance through three mechanisms: increasing government subsidies for enterprises in energy conservation and environmental protection, absorbing talent employment and improving information environment within the enterprises. Finally, the heterogeneity analysis proves that Energy Internet's policy effects are more pronounced in regions with higher financial expenditures on local science undertakings and among state-owned enterprises. China ought to persist in advancing the development of Energy Internet and provide companies with adequate support on finance, talent and technology. Meanwhile, during the construction of Energy Internet, attention should be paid to adapting to local conditions and enterprises.

Abstract Immune checkpoint blockades are the most promising therapy in lung adenocarcinoma (LUAD). However, the response rate remains limited, underscoring the urgent need for effective sensitizers. Interleukin 4 induced 1 (IL4I1) is reported to have immunoinhibitory and tumor‐promoting effects in several cancers. However, the targetable value of IL4I1 in sensitizing the immunotherapy is not clear, and there is a lack of effective small molecules that specifically target IL4I1. Here, we show that silencing IL4I1 significantly remodels the immune microenvironment via inhibiting aryl hydrocarbon receptor (AHR) signaling, thereby enhancing the efficacy of anti‐PD‐1 antibody in LUAD, which suggests that IL4I1 is a potential drug target for the combination immunotherapy. We then identify thymol as the first small molecule targeting IL4I1 transcription through a drug screening. Thymol inhibits the IL4I1 expression and blocks AHR signaling in LUAD cells. Thymol treatment restores the antitumor immune response and suppresses the progression of LUAD in an orthotopic mouse model. Strikingly, the combination treatment of thymol with anti‐PD‐1 antibody shows significant tumor regression in LUAD mice. Thus, we demonstrate that thymol is an effective small molecule to sensitize the PD‐1 blockade in LUAD via targeting IL4I1, which provides a novel strategy for the immunotherapy of LUAD.

Alectinib has been approved as first-line treatment for anaplastic lymphoma kinase (ALK)-positive non-small cell lung carcinoma. Oncologists are also exploring the possibility of applying alectinib in the perioperative period. Here, we present a patient with locally advanced lung adenocarcinoma associated with EML4-ALK fusion mutation, who received neoadjuvant chemotherapy and alectinib treatment, and then underwent thoracoscopic left lower lung lobectomy. The patient initially received eight chemotherapy cycles and achieved partial remission. After eight cycles of chemotherapy, the lymph nodes in the hilar region again enlarged. The patient was then switched to 4 months of alectinib therapy, but no significant lesion changes were detected on imaging during this period. This raised the question of whether the patient developed alectinib resistance. The pathological findings of the postoperative lung lobe specimens indicated extensive necrosis in the tumor area with no residual tumor cells and massive chronic inflammatory cell infiltration around the tumor area, confirming inconsistency between the imaging findings and pathological results. Multi-point tumor specimen sampling was postoperatively performed. Tumor immune-related gene expression was detected in the sample with the help of the PanCancer IO360™ panel based on the nCounter platform. This is a rare case of a patient who was treated with neoadjuvant alectinib and had paradoxical radiographic findings and pathological responses. The possibility that intratumoral immune heterogeneity was responsible for this phenomenon has been discussed. Based on the findings, it is argued that the pathological response should be an important basis for assessing the effectiveness of neoadjuvant alectinib therapy.

University students are young, open to new technologies, and their perceptions of the Shared Autonomous Vehicles (SAVs) may indicate their travel behaviors in the future. College towns in small urban or suburban areas offer researchers a unique environment to understand the travel behaviors of future commuters, and test emerging mobility services, such as SAVs. The study performs a survey with the aim of understanding university student perception regarding SAVs. The survey was conducted among the University of Alabama students in Tuscaloosa. The key survey questions include their knowledge and attitudes about AV and shared mobility. The results showed 97% of respondents are aware of AVs, but only 41% know specific automation technologies. As for shared mobility services, 98% of respondents are familiar with Uber and Lyft services. The survey also asked survey participants to indicate their Willingness-To-Pay (WTP) for hypothetical SAV services in three price scenarios. The prices were assumed as relative to the cost of using ride-hailing services with human drivers such as Uber and Lyft. Random parameter ordered logit models were developed to uncover the correlates of the WTP for SAV services. The models identified significant relationships between the WTP and various factors related to respondents’ socio-demographics, awareness of AV companies, and experiences with human-driver ride-hailing services. The awareness of AV companies and ride-hailing services is positively related to the WTP for SAV services. Students who know more AV companies appear to have a greater WTP, and students who are heavy users of Uber or Lyft services are also likely to SAV users in the future. Significant variations were also found in model estimates, indicating that some relationships could vary significantly across observations due to the unobserved heterogeneity. The findings offer insights to decision-makers and investors trying to estimate the market potential of emerging mobility services with AVs.

Abstract Background Patients with non‐small cell lung cancer (NSCLC) are diagnosed in advanced stages and with a poor 5‐year survival rate. There is a critical need to identify novel biomarkers to improve the therapy and overall prognosis of this disease. Methods Differentially expressed genes (DEGs) were identified from three profiles of GSE101586, GSE101684 and GSE112214 using Venn diagrams. hsa_circ_0043256 were validated using quantitative real‐time polymerase chain reaction (RT‐qPCR). The circular RNA–microRNA–messenger RNA (circRNA–miRNA–mRNA) regulatory network was constructed with Cytoscape 3.7.0. Hub genes were identified with protein interaction (PPI) and validated with the Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA) databases, and immunohistochemistry. Survival analyses were also performed using a Kaplan–Meier (KM) plotter. The effects of hsa_circ_0043256 on cell proliferation and cell cycles were evaluated by EdU staining and flow cytometry, respectively. Results hsa_circ_0043256, hsa_circ_0029426 and hsa_circ_0049271 were obtained. Following RT‐qPCR validation, hsa_circ_0043256 was selected for further analysis. In addition, functional experiment results indicated that hsa_circ_0043256 could inhibit cell proliferation and cell‐cycle progression of NSCLC cells in vitro. Prediction by three online databases and combining with DEGs identified from The Cancer Genome Atlas (TCGA), a network containing one circRNAs, three miRNAs, and 209 mRNAs was developed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated DEGs might be associated with lung cancer onset and progression. A PPI network based on the 209 genes was established, and five hub genes (BIRC5, SHCBP1, CCNA2, SKA3, and GINS1) were determined. Following verification of five hub genes using GEPIA database, HPA database, and immunohistochemistry. High expression of all five hub genes led to poor overall survival. Conclusion Our study constructed a circRNA–miRNA–mRNA network of hsa_circ_0043256. hsa_circ_0043256 may be a potential therapeutic target for lung cancer.

Assessing the relationships between ecosystem services supply and demand is crucial to support sustainable planning and human well-being. In the present study, we analyzed the ecosystem services supply and demand, synergies and trade-offs among services, as well as the spatial relationships between supply and demand, for four services in a desert steppe of Inner Mongolia. In terms of the balance between supply and demand, the grass production and carbon stock supply exceeded the demand, whereas the demand of water yield and windbreak and sand fixation services surpassed the supply. The degree of demand in windbreak and sand fixation service was met increased from 14.7% in 2000 to 20.6% in 2017, versus a decrease from 18.0% to 8.2% in water yield. The spatial distributions of the water yield and carbon stock demand were similar, and there was a significant synergy between them. The grass production supply and demand were not spatially matched, with higher supply in the eastern part of the study area and higher demand in the western part. Areas with high demand for the windbreak and sand fixation service also had a high supply. The water supply and demand in the low-coverage grassland were relatively balanced, and the deficiency of carbon stock supply was mainly found in construction land. In summary, for the sustainable development of animal husbandry and to reduce wind erosion, each county should establish an appropriate livestock density standard based on local constraints. Furthermore, it is also crucial for policymakers to develop water-saving industries to improve water utilization efficiency, and to set targets for CO2 emissions to reduce the impact on climate change.

Abstract Background The echinoderm microtubule-associated protein-like-4 anaplastic lymphoma kinase (EML4-ALK) fusion gene was identified in a subset of non-small cell lung cancer (NSCLC) patients. They responded positively to ALK inhibitors. This study aimed to characterize the mechanisms triggered by EML4-ALK to induce NSCLC transformation. Methods HEK293 and NIH3T3 cells were transfected with EML4-ALK variant 3 or pcDNA3.1-NC. H2228 cells were transfected with siRNA-EML4-ALK or siRNA-NC. Cell viability and proliferation were measured by the CCK-8 and EdU methods, respectively. Flow cytometry revealed apoptosis. Gene expression profiles were generated from a signaling pathway screen in EML4-ALK-regulated lung cancer cells and verified by qPCR and Western blotting. The co-immunoprecipitation and immunohistochemistry/ immunofluorescence determined the interaction and colocalization of JAK2-STAT pathway components with EML4-ALK. Results Microarray identified several genes involved in the JAK2-STAT pathway. JAK2 and STAT6 were constitutively phosphorylated in H2228 cells. EML4-ALK silencing downregulated phosphorylation of STAT6. Expression of EML4-ALK in HEK293 and NIH3T3 cells activated JAK2, STAT1, STAT3, STAT5, and STAT6. In EML4-ALK-transfected HEK293 cells and EML4-ALK-positive H2228 cells, activated STAT6 and JAK2 colocalized with ALK. STAT3 and STAT6 were phosphorylated and translocated to the nucleus of H2228 cells following IL4 or IL6 treatment. Apoptosis increased, while cell proliferation and DNA replication decreased in H2228 cells following EML4-ALK knockdown. In contrast, HEK293 cell viability increased following EML4-ALK overexpression, while H2228 cell viability significantly decreased after treatment with ALK or JAK-STAT pathway inhibitors. Conclusions Our data suggest that the aberrant expression of EML4-ALK leads to JAK2-STAT signaling pathway activation, which is essential for the development of non-small cell lung cancer.

Background and objective Lung cancer is a malignant with high incidence and mortality and adenocarcinoma is among the most popular subtypes. Epidermal growth factor receptor (EGFR) mutation is one of the most important driver mutations for lung adenocarcinoma and EGFR-tyrosine kinase inhibitor (TKI) will benefit those patients with sensitive EGFR mutations. Recently, immune checkpoint inhibitor (ICI) therapy, provide a new breakthrough treatment for lung cancer patients. Whereas immunotherapy as an emerging treatment does not benefit patients with EGFR mutations, for which mechanistic studies are poorly defined and focused on the link of EGFR mutations and programmed cell death-ligand 1 (PD-L1) expression, we speculate that the different immune microenvironment associated with the two classes of patients. Methods Lung adenocarcinoma datasets were collected from the Cancer Genome Atlas (TCGA) database, and clinical information and gene expression profiles were downloaded. The immune related lymphocyte infiltration in TCGA database were generated through timer 2.0 GSEA was used to analyze the difference of pathway expression between EGFR mutant patients and wild type patients. Results EGFR mutation was more frequently among women and never smokers. Immunoinfiltration analysis showed that patients with EGFR mutation tends to have more tumor associated fibroblasts, common myeloid progenitor cells, hematopoietic stem cells, effector CD4+ T cells and natural killer T cells infiltration, and less memory B cells, naïve B cells, plasma B cells, plasmacytoid dendritic cells, memory CD4+ T cells, CD4+ helper T cells 2, naive CD8+ T cells, CD8+ T cells and central memory CD8+ T cells infiltration. Moreover, patients with more infiltration of CD8+ T cells, natural killer T cells, memory B cells and hematopoietic stem cells, tends have better prognosis (Log-rank test, P=0.017, 0.0093, 0.018, 0.016). However, the patients with more CD4+ T th2 infiltration in the tumor tends to have worse prognosis (Log-rank test, P=0.016). Furthermore, the results of gene set enrichment analysis showed that compared with the lung adenocarcinoma patients with EGFR wild type, the three pathways positive regulation of natural killer (NK) cell-mediated immune response to tumor cells, NK cell activation involved in immune response, and NK cell-mediated immune response to tumor cells related to natural killer cells in patients with EGFR mutation were down regulated, while the pathway the positive regulation of cytokine secretion involved in immune response was up-regulated in EGFR mutation patients. Conclusion The tumour microenvironment of patients with EGFR mutations lacks potent tumour killing effector cells and appears dysfunctional with effector cells. This may be a potential reason for the poor efficacy of immunotherapy in patients with EGFR mutations.

Abstract Background With the ongoing development of targeted therapy and immunotherapy in recent years, the overall five‐year survival rate of NSCLC patients has not improved, and the search for novel diagnostic and prognostic markers for lung adenocarcinoma continues. Methods Lung adenocarcinoma (LUAD) gene expression data and relevant clinical information were obtained from the TCGA. Hub genes were identified with weighted gene co‐expression network analysis (WGCNA) and protein–protein interaction network (PPI). Survival analyses were also performed using GEPIA. The 536 LUAD patients were divided into two groups according to the SPRR1B expression level and analyzed by gene set enrichment analysis (GSEA) and verified by immunoblotting. The effects of SPRR1B on cell proliferation and cell metastasis and apoptosis were evaluated by 5‐ethynyl‐2′‐deoxyuridine (EdU) staining, colony formation assay, transwell migration and invasion assay, and flow cytometry, respectively. Results A total of 2269 DEGs were analyzed by WGCNA and five hub genes (CCK, FETUB, PCSK9, SPRR1B, and SPRR2D) were identified. Among them, SPRR1B was selected as one of the most significant prognostic genes in LUAD. SPRR1B was found to be highly expressed in lung adenocarcinoma cells compared with that in normal bronchial epithelial cells. In addition, silencing of SPRR1B could inhibit the cell proliferation, invasion, and migration of lung adenocarcinoma cells, but induced cell apoptosis and G2/M phase arrest in vitro. The result of GSEA and immunoblotting revealed that SPRR1B activated the MAPK signaling pathway involved in the proliferation and metastasis of lung cancer. Conclusions Our findings demonstrate that SPRR1B may function as a prognosis predictor in lung adenocarcinoma.

Abstract Background Lung cancer is the leading cause of cancer-related deaths worldwide. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. In traditional anti-cancer therapy, epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKI) have been proven to be beneficial for patients with EGFR mutations. However, patients with EGFR wild-type NSCLC were usually not respond to EGFR-TKIs. Enhancer of zeste homolog 2 (EZH2) is a key molecular in the PRC2 complex and plays an important role in epigenetic regulation and is overexpressed in variant tumors. EZH2 inhibitors have been reported to sensitize variant tumor cells to anticancer drugs. This study aimed to investigate whether the EZH2 inhibitors, GSK343 and DZNep when combined with gefitinib can reverse EGFR-TKIs resistance in EGFR wild-type NSCLC cells. Methods The RNA-sequencing data of patients with NSCLC [502 patients with lung squamous cell carcinoma, including 49 paracancerous lung tissues and 513 patients with lung adenocarcinoma (LUAD), including 59 paracancerous lung tissues] from the Cancer Genome Atlas (TCGA), were analyzed for EZH2 expression. EZH2 expression was verified in 40 NSCLC tissue cancer samples and their corresponding paracancerous tissues from our institute (TJMUGH) via RT-PCR. A549 and H1299 cells treated with siRNA or EZH2 inhibitors were subjected to cell viability and apoptosis analyses as well to EGFR pathway proteins expression analyses via western blotting. Results EZH2 was upregulated in human NSCLC tissues and correlated with poor prognosis in patients with LUAD based on data from both TCGA and TJMUGH. Both GSK343 and DZNep sensitized EGFR wild-type LUAD cells (A549 and H1299) to gefitinib and suppressed cell viability and proliferation in vitro by downregulating the phosphorylation of EGFR and AKT and by inducing cell apoptosis. Co-administration of EZH2 inhibitors (GSK343 or DZNep) with gefitinib exerted a stronger inhibitory effect on tumor activity, cell proliferation and cell migration than single drug administration in vitro and in vivo. Conclusions These data suggest that the combination of EZH2 inhibitors with EGFR-TKIs may be an effective method for treating NSCLC-patients with EGFR-wild type, who do not want to undergo traditional treatment with chemotherapy.

Background and objective Lung cancer is the most common malignancy world-wide. Small cell lung cancer is the deadliest subtype of lung cancer, which features such as rapid growth, early metastasis, and high vascularization. Apatinib is a vascular endothelial growth factor receptor 2 inhibitor independently developed in China, which has a significant inhibition in a variety of solid tumors. The purpose of this study is to investigate the effects of Apatinib alone or Apatinib combined with mammalian target of rapamycin (mTOR) inhibitor, CCI-779, on small cell lung cancer cell line NCI-H446 in vitro. Methods The small cell lung cancer cell line NCI-H446 was grew in vitro. The effects of Apatinib alone or Apatinib combined with CCI-779 on proliferation, apoptosis, cell cycle and migration of NCI-H446 small cell lung cancer cells were detected by CCK8; FACS and transwell assays were also carried out; Western blot assays were used to detect vascular endothelial growth factor and cell cycle related protein expression. Results CCK8 assays showed that high concentration of Apatinib could inhibit the proliferation of NCI-H446 cells. Apoptosis assays showed that high concentration of Apatinib could induce NCI-H446 cell apoptosis. Transwell assays showed that high concentration of Apatinib could inhibit NCI-H446 cell migration. After combined with mTOR inhibitor CCI-779, low concentration of Apatinib could inhibit the proliferation and migration of NCI-H446 small cell lung cancer cells and induce apoptosis. Conclusion Apatinib has a concentration-dependent effect on the small cell lung cancer cell line NCI-H446. High concentration of Apatinib can inhibit the proliferation and migration of NCI-H446 small cell lung cancer cells, induce apoptosis. Apatinib combined with the mTOR inhibitor CCI-779 can sensitize the NCI-H446 cells to Apatinib.

This paper presents a novel approach to building an interval dynamic model for an industrial plant with uncertainty by an interval neural network (INN). A new type of randomized learner model, named interval random vector functional-link network (IRVFLN), is proposed to take advantages of the inherent RVFLN in rapid modeling. The IRVFLN model is equipped with interval hidden input weights (and biases), which are randomly assigned from certain distribution/range and remain fixed, and the interval output weights can be evaluated by solving a couple of least squares problems. The comparative numerical experiments have verified the good potential of the proposed IRVFLN with the interval learner models produced by the error back-propagation algorithm. In the following modeling application, some measures for building IRVFLN with unknown but bounded (UBB) errors requirements are discussed in depth, in order to modeling an uncertain dynamic plant with IRVFLN by bounded-error data in either known or unknown error bounds. Finally, as a case study, the IRVFLN is applied to modeling a chemical interval dynamic plant with recycling, where the simulation results and generalization ability analysis demonstrate that the proposed method is suitable and effective.

Recently, drone small cells (DSCs) has been brought into significant focus, which is the one key enabler for potentially facilitating terrestrial wireless communication systems. Meanwhile, in ultra-dense unmanned networks, artificial intelligence (AI) has been a useful and efficient tool for control and management of the multi-agents. This paper investigates a downlink interference control problem in ultra-dense unmanned networks with AI-aided approach, that each DSC can adjust its altitude to increase the data-rate. This problem is formulated as a mean field game (MFG) framework, an AI-aided method to make decisions. In this framework, each DSC controls its velocity to minimize the cost over a period, where the cost function is composed by the data-rate and height adjusting consumption. Meanwhile, in this model, we adopt the mean-field approximation (MFA) approach to derive the interference introduced from a large number of DSCs. Besides, the control strategy is described and explained by using the related Hamilton-Jacobi-Bellman (HJB) and Fokker-Planck-Kolmogorov (FPK) equations, respectively. Thus, a finite difference algorithm is proposed to solve the coupled partial differential equations, which can obtain the optimal altitude control strategy. The algorithm outputs show the optimal behaviors of DSCs in different environment scenarios. In additon, the simulation results verify that the proposed control strategy has better average signal to interference plus noise ratio (SINR) compared with the baseline method.

BackgroundPyroptosis is a new type of programmed cell death, accompanied by an intense inflammatory response. Previous studies have shown that pyroptosis can modify long-chain non-coding RNA (lncRNA), thereby affecting the occurrence and progression of tumors. However, the underlying role of pyroptosis-related lncRNA in lung adenocarcinoma (LUAD) remains to be elucidated. Therefore, the purpose of our study was to evaluate the prognostic value of pyrolysis-related lncRNA in patients with LUAD.MethodsA total of 454 LUAD samples were downloaded from The Cancer Genome Atlas (TCGA) database. Pearson’s correlation coefficient was used to identify the pyroptosis-related lncRNAs. Unsupervised consensus clustering was used to identify the various LUAD molecular subtypes. A least absolute shrinkage and selection operator (LASSO) analysis was conducted to construct a prognostic signature.ResultsAn 11-lncRNA prognostic signature out of 19 identified pyroptosis-related prognostic lncRNAs was constructed. The patients with LUAD were divided into low-risk and high-risk groups. Patients in the high-risk group had higher score values and mortality. The immune score, stromal score, and estimate score were lower in the high-risk group. The risk score was an independent predictor for OS in multivariate Cox regression analyses (HR > 1, p < 0.01). BTLA, PD-1, PD-L1, CTLA, and CD47 were lower expressed in the high-risk group.ConclusionsOur study identified an 11-pyroptosis-related lncRNA signature. These findings could further clarify the role of pyroptosis in LUAD and guide the prognosis and individualized treatment of patients.

Nowadays, lung cancer has the highest mortality worldwide. The emergence of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) has greatly improved the survival of patients with non-small cell lung cancer (NSCLC) having EGFR-TKI-sensitive mutations. Unfortunately, acquired resistance happens for most patients. In the present research, we found that EGFR-TKIs (such as gefitinib and osimertinib) can induce autophagy in NSCLC cell lines. Compared with parental sensitive cells, drug-resistant cells have higher autophagy activity. The use of an autophagy inhibitor could enhance the toxicity of gefitinib and osimertinib, which indicates that the enhancement of protective autophagy might be one of the mechanisms of EGFR-TKI resistance in NSCLC. In addition, increased autophagy activity is associated with decreased enhancer of zeste homolog 2 (EZH2) expression. Knockdown of EZH2 or EZH2 inhibitor treatment could lead to increased autophagy in NSCLC cells, indicating that EZH2 is a negative regulator of autophagy. We revealed that the increase in autophagy caused by the reduction of EZH2 was reversed in vitro and in vivo when combining gefitinib or osimertinib with suberoylanilide hydroxamic acid (SAHA), a broad-spectrum histone deacetylase inhibitor (HDACi). In conclusion, our results indicated that the combination of EGFR-TKIs and SAHA may be a new strategy to overcome EGFR-TKIs acquired resistance.

At present, the growth mechanism of TiO2 nanotubes in different electrolytes is still controversial. Field assisted dissolution (FAD) theory believes that fluoride ion is the main factor affecting the growth of TiO2 nanotubes. In this paper, we conducted a comparative experiment in HBF4 and NH4F electrolytes which containing the same fluoride ion molarity. By comparing the growth morphology of TiO2 nanotubes in two electrolytes, orderly nanotube arrays were obtained in NH4F electrolyte. However, only dense films and nanotube embryos were formed in HBF4 electrolyte. Obviously, FAD theory cannot explain these phenomena. Ionic current and electronic current theories and oxygen bubble model are reasonable for these phenomena. In the NH4F electrolyte, there are high electronic current and intense oxygen evolution, so the nanotube embryos cannot be seen. The low electronic current in the HBF4 electrolyte and the slow evolution of oxygen gas lead to the discovery of the nanotube embryos. This phenomenon also confirms that the formation process of TiO2 nanotubes is that anodic oxides grow upward around the oxygen bubble to form the nanotube walls.

Worldwide, non-small cell lung cancer (NSCLC) has the highest morbidity and mortality of all malignancies. The lack of responsiveness to checkpoint inhibitors is a central problem in the modern era of cancer immunotherapy, with the rapid development of immune checkpoint inhibitors (ICIs) in recent years. The human switch/sucrose nonfermentable (SWI/SNF) chromatin-remodeling complex has been reported to be recurrently mutated in patients with cancer, and those with SWI/SNF mutations have been reported to be sensitive to ICIs. Six reported cohorts, a total of 3416 patients, were used to analyze the mutation status of ARID1A, ARID1B, ARID2 and SMARCA4 in patients with NSCLC and the effect of mutations on prognosis after ICIs. Finally, a nomogram was established to guide the clinical use of ICIs. The results show that patients with NSCLC who have ARID1A, ARID1B, and ARID2 mutations of the SWI/SNF complex were more likely to benefit from ICI therapy.

Abstract Background Grazing is an important land use in northern China. In general, different grazing intensities had a different impact on the morphological and physiological traits of plants, and especially their photosynthetic capacity. We investigated the responses of Leymus chinensis to light, medium, and heavy grazing intensities in comparison with a grazing exclusion control. Results With light grazing, L. chinensis showed decreased photosynthetic capacity. The low chlorophyll and carotenoid contents constrained light energy transformation and dissipation, and Rubisco activity was also low, restricting the carboxylation efficiency. In addition, the damaged photosynthetic apparatus accumulated reactive oxygen species (ROS). With medium grazing, more energy was used for thermal dissipation, with high carotene content and high non-photochemical quenching, whereas photosynthetic electron transport was lowest. Significantly decreased photosynthesis decreased leaf C contents. Plants decreased the risk caused by ROS through increased energy dissipation. With high grazing intensity, plants changed their strategy to improve survival through photosynthetic compensation. More energy was allocated to photosynthetic electron transport. Though heavy grazing damaged the chloroplast ultrastructure, adjustment of internal mechanisms increased compensatory photosynthesis, and an increased tiller number facilitated regrowth after grazing. Conclusions Overall, the plants adopted different strategies by adjusting their metabolism and growth in response to their changing environment.

Summary: Li2MnO3 endows Li-rich layered oxides with a superior energy density; however, its electron transfer mechanism is still unclear. Here, the electronic and thermodynamic behavior of LixMnO3 (x = 0.5–2) is determined using first-principles computations. The cationic redox, anionic redox, and local electron exchange in Mn-O polyhedron are revealed. An obvious electron donation inclination of manganese is demonstrated when the Li+ content is low. Through ab initio molecular dynamics, high valence Mn6+ and Mn7+ are generated in the form of MnO4 tetrahedrons with structural transformation toward a disordered structure, controlled by the Li+ content and dynamic energy barrier. Furthermore, a local redox reaction between Mn6+ or Mn7+ and their surrounding oxygen atoms is elucidated. Consequently, a comprehensive understanding regarding the electron transfer in LixMnO3 is provided. Our results bring insight regarding the electron transfer mechanism in Li-rich layered oxide cathode materials and encourage further reconsideration and investigation into its redox mechanism.

Abstract Background Metastasis is the leading cause of cancer mortality and is a major hurdle for lung cancer treatment. Invadopodia, which are cancer-specific protrusive structures, play a crucial role in the metastatic cascade through degradation of the basement membrane and surrounding stroma. Cortactin, a critical component of invadopodia, frequently used as an invadopodia marker, a universally important player in invadopodia function, and is frequently overexpressed in cancer, but the exact mechanism of regulation is not yet fully understood. Methods The expression level of CTTN in human non-small cell lung cancer (NSCLC) tissues was detected by qRT-PCR. Cell migration, invasion and invadopodia formation were assessed in vitro by wound-healing, transwell assay and immunofluorescence, respectively. The dual-luciferase reporter assay was used to identify the direct target of miR-182. Results Hepatocyte growth factor (HGF) and phorbol 12,13-dibutyrate (PDBu) can induce CTTN expression, motility, and invasion ability, as well as invadopodia formation in non-small cell lung cancer (NSCLC). Moreover, miR-182 suppressed metastasis and invadopodia formation by targeting CTTN in NSCLC. Our qRT-PCR results showed that CTTN expression was inversely correlated with miR-182 expression that suppressed invadopodia formation via suppression of the Cdc42/N-WASP pathway. Furthermore, miR-182 negatively regulated invadopodia function, and suppressed extracellular matrix(ECM) degradation in lung cancer cells by inhibiting cortactin. Conclusion Collectively, our results demonstrated that miR-182 targeted CTTN gene in NSCLC and suppressed lung cancer invadopodia formation, and thus suppressed lung cancer metastasis. This suggests a therapeutic application of miR-182 in NSCLC.

Background and objective Rb is an important tumor suppressor gene that regulates cell cycle progression. Rb dysfunction can lead to over proliferation of cells and lead to the occurrence of tumor. Loss or reduced Rb expression as well as over phosphorylation of Rb are important mechanisms of Rb dysfunction. The mutated epidermal growth factor receptor (EGFR) gene is an important driver gene in lung adenocarcinoma, and plays an important role in the development of lung cancer. The purpose of this study was to investigate the status of Rb in lung adenocarcinoma patients with EGFR mutations and define the clinicopathologic features. Methods 23 cases pulmonary adenocarcinoma patients with EGFR mutations were collected. The status of Rb and pRb-780, pRb-795 were determined byimmunohistochemistry. Results Loss or reduced Rb expression were detected in 16 of 23 samples (69.6%). pRb-780 and pRb-795 over-expressed were identified in 17 (73.9%) and 16 (69.6%) of 23 samples respectively. All the 23 patients had showed loss/reduced Rb expression or over-expressed Rb phosphorylation. Further analysis showed that over expression of pRb-780 and pRb-795 occurred more frequently in advanced patients. Conclusion Aberrant expressionof Rb is frequently occurred in lung adenocarcinoma patients with EGFR mutations and may be an important pathogenesis in patients with lung adenocarcinoma.

Landslide susceptibility prediction (LSP) modeling is an important and challenging problem. Landslide features are generally uncorrelated or nonlinearly correlated, resulting in limited LSP performance when leveraging conventional machine learning models. In this study, a deep-learning-based model using the long short-term memory (LSTM) recurrent neural network and conditional random field (CRF) in cascade-parallel form was proposed for making LSPs based on remote sensing (RS) images and a geographic information system (GIS). The RS images are the main data sources of landslide-related environmental factors, and a GIS is used to analyze, store, and display spatial big data. The cascade-parallel LSTM-CRF consists of frequency ratio values of environmental factors in the input layers, cascade-parallel LSTM for feature extraction in the hidden layers, and cascade-parallel full connection for classification and CRF for landslide/non-landslide state modeling in the output layers. The cascade-parallel form of LSTM can extract features from different layers and merge them into concrete features. The CRF is used to calculate the energy relationship between two grid points, and the extracted features are further smoothed and optimized. As a case study, the cascade-parallel LSTM-CRF was applied to Shicheng County of Jiangxi Province in China. A total of 2709 landslide grid cells were recorded and 2709 non-landslide grid cells were randomly selected from the study area. The results show that, compared with existing main traditional machine learning algorithms, such as multilayer perception, logistic regression, and decision tree, the proposed cascade-parallel LSTM-CRF had a higher landslide prediction rate (positive predictive rate: 72.44%, negative predictive rate: 80%, total predictive rate: 75.67%). In conclusion, the proposed cascade-parallel LSTM-CRF is a novel data-driven deep learning model that overcomes the limitations of traditional machine learning algorithms and achieves promising results for making LSPs.