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Gastric cancer (GC) is a prevalent form of cancer worldwide and has a high death rate, with less than 40% of patients surviving for 5 years. GC demonstrates a vital characteristic of evading regulatory cell death (RCD). However, the extent to which RCD patterns are clinically significant in GC has not been well investigated. The study created a regulatory cell death index (RCDI) signature by employing 101 machine-learning algorithms. These algorithms were based on the expression files of 1292 GC patients from 6 multicenter cohorts. RCDI is a reliable and robust determinant of the likelihood of surviving in general. Furthermore, the precision of RCDI surpasses that of the 20 signatures that have been previously disclosed. The presence of RCDI signature is closely linked to immunological characteristics, such as the infiltration of immune cells, the presence of immunotherapy markers, and the activation of immune-related functions. This suggests that there is a higher level of immune activity in cases with RCDI signature. Collectively, the use of RCDI has the potential to be a strong and encouraging method for enhancing the clinical results of individual individuals with GC.

Abstract Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-specific antigen, exposing “danger signals” to stimulate the body’s immune response. Given the recent development of immunotherapy in lung adenocarcinoma, we explored the role of tumor immunogenic cell death-related lncRNAs in lung adenocarcinoma for prognosis and immunotherapy benefit, which has never been uncovered yet. Based on the lung adenocarcinoma cohorts from the TCGA database and GEO database, the study developed the immunogenic cell death index signature by several machine learning algorithms and then validated the signature for prognosis and immunotherapy benefit of lung adenocarcinoma patients, which had a more stable performance compared with published signatures in predicting the prognosis, and demonstrated predictive value for benefiting from immunotherapy in multiple cohorts of multiple cancers, and also guided the utilization of chemotherapy drugs.

Abstract Tumor-associated macrophages (TAMs) are a specific subset of macrophages that reside inside the tumor microenvironment. The dynamic interplay between TAMs and tumor cells plays a crucial role in the treatment response and prognosis of lung adenocarcinoma (LUAD). The study aimed to examine the association between TAMs and LUAD to advance the development of targeted strategies and immunotherapeutic approaches for treating this type of lung cancer. The study employed single-cell mRNA sequencing data to characterize the immune cell composition of LUAD and delineate distinct subpopulations of TAMs. The “BayesPrism” and “Seurat” R packages were employed to examine the association between these subgroups and immunotherapy and clinical features to identify novel immunotherapy biomarkers. Furthermore, a predictive signature was generated to forecast patient prognosis by examining the gene expression profile of immunotherapy-associated TAMs subsets and using 104 machine-learning techniques. A comprehensive investigation has shown the existence of a hitherto unidentified subgroup of TAMs known as RGS1 + TAMs, which has been found to have a strong correlation with the efficacy of immunotherapy and the occurrence of tumor metastasis in LUAD patients. CD83 was identified CD83 as a distinct biomarker for the expression of RGS1 + TAMs, showcasing its potential utility as an indicator for immunotherapeutic interventions. Furthermore, the prognostic capacity of the RTMscore signature, encompassing three specific mRNA (NR4A2, MMP14, and NPC2), demonstrated enhanced robustness when contrasted against the comprehensive collection of 104 features outlined in the published study. CD83 has potential as an immunotherapeutic biomarker. Meanwhile, The RTMscore signature established in the present study might be beneficial for survival prognostication.

With the development of the power system, power users begin to use their own power supply in order to improve the power economy, but this also leads to the occurrence of the risk of self-provided power supply. The actual distribution network has few samples of power supply risk and it is difficult to identify the power supply risk by using conventional deep learning methods. In order to achieve high accuracy of self-provided power supply risk identification with small samples, this paper proposes a combination of transfer learning, convolutional block attention module (CBAM), and convolutional neural network (CNN) to identify the risk of self-provided power supply in an active distribution network. Firstly, in order to be able to further identify whether or not a risk will be caused based on completing the identification of the faulty line, we propose that it is necessary to identify whether or not the captive power supply on the faulty line is in operation. Second, in order to achieve high-precision identification and high-efficiency feature extraction, we propose to embed the CBAM into a CNN to form a CBAM-CNN model, so as to achieve high-efficiency feature extraction and high-precision risk identification. Finally, the use of transfer learning is proposed to solve the problem of low risk identification accuracy due to the small number of actual fault samples. Simulation experiments show that compared with other methods, the proposed method has the highest recognition accuracy and the best effect, and the risk recognition accuracy of active distribution network backup power is high in the case of fewer samples.

As the second most common cancer in the world, the development of lung cancer is closely related to factors such as heredity, environmental exposure, and lung microenvironment, etc. Early screening and diagnosis of lung cancer can be helpful for the treatment of patients. Currently, CT screening and histopathologic biopsy are widely used in the clinical detection of lung cancer, but they have many disadvantages such as false positives and invasive operations. Microbes are another genome of the human body, which has recently been shown to be closely related to chronic inflammatory, metabolic processes in the host. At the same time, they are important players in cancer development, progression, treatment, and prognosis. The use of microbes for cancer therapy has been extensively studied, however, the diagnostic role of microbes is still unclear. This review aims to summarize recent research on using microbes for lung cancer detection and present the current shortcomings of microbes in collection and detection. Finally, it also looks ahead to the clinical benefits that may accrue to patients in the future about screening and early detection.

As an advanced technology that efficiently aggregates and optimizes renewable energy, controllable loads, and energy storage systems, virtual power plants (VPPs) can effectively promote the green and low-carbon transformation of power systems. A comprehensive assessment of VPPs is important for VPP investment and operation. However, most of the existing evaluation methods focus on the reliability, economy, and mobilizability of VPPs. In this paper, in order to better address the characteristics of demand response-oriented VPPs, three aspects of VPP operation indices, new energy indices, and demand response indices are analyzed. In this manner, it is possible to meet the principles of the construction of VPP evaluation system and also to measure the effect of demand response of the VPP. Then, on the basis of AdaBoost algorithm, combined with back propagation (BP) neural network for the evaluation and classification of demand response-oriented VPPs. The entropy value method and gray correlation are also compared to validate the superiority of the proposed method.

Motion control of robots is a high-dimensional, nonlinear control problem that is often difficult to handle using traditional dynamical path planning means. Reinforcement learning is currently an effective means to solve robot motion control problems, but reinforcement learning has disadvantages such as high number of trials and errors and sparse rewards, which restrict the application efficiency of reinforcement learning. The Hindsight Experience Replay(HER) algorithm is a reinforcement learning algorithm that solves the reward sparsity problem by constructing virtual target values. However, the HER algorithm still suffers from the problem of long time in the early stage of training, and there is still room for improving its sample utilization efficiency. Augmentation by existing data to improve training efficiency has been widely used in supervised learning, but is less applied in the field of reinforcement learning. In this paper, we propose the Hindsight Experience Replay with Transformed Data Augmentation (TDAHER) algorithm by constructing a transformed data augmentation method for reinforcement learning samples, combined with the HER algorithm. And in order to solve the problem of the accuracy of the augmented samples in the later stage of training, the decaying participation factor method is introduced. After the comparison of four simulated robot control tasks, it is proved that the algorithm can effectively improve the training efficiency of reinforcement learning.

Background Aldehyde dehydrogenase 2 (ALDH2) is a crucial enzyme involved in endogenous aldehyde detoxification and has been implicated in tumor progression. However, its role in tumor immune evasion remains unclear.Methods Here, we analyzed the relationship between ALDH2 expression and antitumor immune features in multiple cancers. ALDH2 knockout tumor cells were then established using CRISPR/Cas9 system. In immunocompetent breast cancer EMT6 and melanoma B16-F10 mouse models, we investigated the impact of ALDH2 blockade on cytotoxic T lymphocyte function and tumor immune microenvironment by flow cytometry, mass cytometry, Luminex liquid suspension chip detection, and immunohistochemistry. Furthermore, RNA sequencing, flow cytometry, western blot, chromatin immunoprecipitation assay, and luciferase reporter assays were employed to explore the detailed mechanism of ALDH2 involved in tumor immune evasion. Lastly, the synergistic therapeutic efficacy of blocking ALDH2 by genetic depletion or its inhibitor disulfiram in combination with immune checkpoint blockade (ICB) was investigated in mouse models.Results In our study, we uncovered a positive correlation between the expression level of ALDH2 and T-cell dysfunction in multiple cancers. Furthermore, blocking ALDH2 significantly suppressed tumor growth by enhancing cytotoxic activity of CD8+ T cells and reshaping the immune landscape and cytokine milieu of tumors in vivo. Mechanistically, inhibiting ALDH2-mediated metabolism of aldehyde downregulated the expression of V-domain Ig suppressor of T-cell activation (VISTA) via inactivating the nucleotide oligomerization domain (NOD)/nuclear factor kappa-B (NF-κB) signaling pathway. As a result, the cytotoxic function of CD8+ T cells was revitalized. Importantly, ALDH2 blockade markedly reinforced the efficacy of ICB treatment.Conclusions Our data delineate that ALDH2-mediated aldehyde metabolism drives tumor immune evasion by activating the NOD/NF-κB/VISTA axis. Targeting ALDH2 provides an effective combinatorial therapeutic strategy for immunotherapy.

Abstract Background Breast cancer is a complex disease with a highly immunosuppressive tumor microenvironment, and has limited clinical response to immune checkpoint blockade (ICB) therapy. T-helper 2 (Th2) cells, an important component of the tumor microenvironment (TME), play an essential role in regulation of tumor immunity. However, the deep relationship between Th2-mediated immunity and immune evasion in breast cancer remains enigmatic. Methods Here, we first used bioinformatics analysis to explore the correlation between Th2 infiltration and immune landscape in breast cancer. Suplatast tosilate (IPD-1151 T, IPD), an inhibitor of Th2 function, was then employed to investigate the biological effects of Th2 blockade on tumor growth and immune microenvironment in immunocompetent murine breast cancer models. The tumor microenvironment was analyzed by flow cytometry, mass cytometry, and immunofluorescence staining. Furthermore, we examined the efficacy of IPD combination with ICB treatment by evaluating TME, tumor growth and mice survival. Results Our bioinformatics analysis suggested that higher infiltration of Th2 cells indicates a tumor immunosuppressive microenvironment in breast cancer. In three murine breast cancer models (EO771, 4T1 and EMT6), IPD significantly inhibited the IL-4 secretion by Th2 cells, promoted Th2 to Th1 switching, remodeled the immune landscape and inhibited tumor growth. Remarkably, CD8+ T cell infiltration and the cytotoxic activity of cytotoxic T lymphocyte (CTL) in tumor tissues were evidently enhanced after IPD treatment. Furthermore, increased effector CD4+ T cells and decreased myeloid-derived suppressor cells and M2-like macrophages were also demonstrated in IPD-treated tumors. Importantly, we found IPD reinforced the therapeutic response of ICB without increasing potential adverse effects. Conclusions Our findings demonstrate that pharmaceutical inhibition of Th2 cell function improves ICB response via remodeling immune landscape of TME, which illustrates a promising combinatorial immunotherapy.

Idiopathic pulmonary fibrosis (IPF) is a long-lasting, continuously advancing, and irrevocable interstitial lung disorder with an obscure origin and inadequately comprehended pathological mechanisms. Despite the intricate and uncharted causes and pathways of IPF, the scholarly consensus upholds that the transformation of fibroblasts into myofibroblasts—instigated by injury to the alveolar epithelial cells—and the disproportionate accumulation of extracellular matrix (ECM) components, such as collagen, are integral to IPF’s progression. The introduction of two novel anti-fibrotic medications, pirfenidone and nintedanib, have exhibited efficacy in decelerating the ongoing degradation of lung function, lessening hospitalization risk, and postponing exacerbations among IPF patients. Nonetheless, these pharmacological interventions do not present a definitive solution to IPF, positioning lung transplantation as the solitary potential curative measure in contemporary medical practice. A host of innovative therapeutic strategies are presently under rigorous scrutiny. This comprehensive review encapsulates the recent advancements in IPF research, spanning from diagnosis and etiology to pathological mechanisms, and introduces a discussion on nascent therapeutic methodologies currently in the pipeline.

Ceramic-copper substrates, as high-power, load-bearing components, are widely used in new energy vehicles, electric locomotives, high-energy lasers, integrated circuits, and other fields. The service length will depend on the substrate’s copper-coated surface quality, which frequently achieved by utilising an abrasive strip polishing procedure on the substrate’s copper-coated surface. Precision diamond fly-cutting processing machine tools were made because of the low processing accuracy and inability to match the production line’s efficiency. An analysis of the fly-cutting machining principle and the structural makeup of the ceramic-copper substrate is the first step in creating a roughness prediction model based on a tool tip trajectory. This model demonstrates that a shift in the tool tip trajectory due to spindle runout error directly impacts the machined surface’s roughness. The device’s structural optimisation design is derived from the above analyses and implemented using finite element software. Modal and harmonic response analysis validated the machine’s gantry symmetrical structural layout, a parametric variable optimisation design optimised the machine tool’s overall dimensions, and simulation validated the fly-cutterring’s constituent parts. Enhancing the machine tool’s stability and motion accuracy requires using the LK-G5000 laser sensor to measure the guideway’s straightness. The result verified the machine tool’s design index, with the Z- and Y-axes’ straightness being better than 2.42 μm/800 mm and 2.32 μm/200 mm, respectively. Ultimately, the device’s machining accuracy was confirmed. Experiments with flying-cut machining on a 190 × 140 mm ceramic-copper substrate yielded a roughness of Sa9.058 nm. According to the experimental results, the developed machine tool can fulfil the design specifications.

Bacterial biofilms are complex microbial communities encased in extracellular polymeric substances. Their formation is a multi-step process. Biofilms are a significant problem in treating bacterial infections and are one of the main reasons for the persistence of infections. They can exhibit increased resistance to classical antibiotics and cause disease through device-related and non-device (tissue) -associated infections, posing a severe threat to global health issues. Therefore, early detection and search for new and alternative treatments are essential for treating and suppressing biofilm-associated infections. In this paper, we systematically reviewed the formation of bacterial biofilms, associated infections, detection methods, and potential treatment strategies, aiming to provide researchers with the latest progress in the detection and treatment of bacterial biofilms.

ABSTRACT Foodborne botulism is a rare but life-threatening illness resulting from the action of a potent toxin mainly produced by Clostridium botulinum. It grows in an oxygen-deficient environment and is extremely viable in meat and soy products, making it one of the most virulent bacteria. How to track foodborne botulism events quickly and accurately has become a key issue. Here, we investigated two foodborne botulism events that occurred in Xinjiang in 2019 based on whole-genome sequencing and also successfully traced the relationship between clinical and food C. botulinum isolates using whole-genome core gene markers. All 59 isolates were classified as group I strains. Of the strains isolated in this study, 44 were found to be botulinum toxin A(B), and 15 isolates contained only the toxin B locus. Both the toxin A and B gene segments were located on the chromosome and organized in an ha cluster. Antibiotic resistance and virulence factors were also investigated. A set of 329 universal core gene markers were established using C. botulinum strains from a public database. These core gene markers were applied to the published C. botulinum genomes, and three outbreaks were identified. This work demonstrates that universal core gene markers can be used to trace foodborne botulism events, and we hope that our work will facilitate this effort in future. IMPORTANCE In this study, we analyzed 59 foodborne botulism (FB)-related strains isolated in Xinjiang Province, China. Our findings not only reveal the group classification, neurotoxin locus organization, antibiotic resistance and virulence factors of these strains but also establish a set of core gene markers for tracing foodborne botulism events, which was verified using published genomes. These findings indicate that these gene markers might be used as a potential tracing tool for FB events caused by C. botulinum group I strains, which have relatively stable genomic components.

Fluctuation of the optical power incident on a photodiode will cause phase variation of the electrical signal. This phenomenon is known as amplitude-to-phase (AM-to-PM) conversion. The effects of bias voltage and test frequency on AM-to-PM conversion are described systematically in this paper. A larger null point of AM-to-PM coefficient and smaller phase variation have been observed when bias voltage increases or test frequency decreases. The variation of transit time which is caused by different carrier velocity is the main reason of the phase variation. The influence mechanism of bias on AM-to-PM conversion has been explained in detail by giving the relationship between the carrier drift velocity and the internal electric field related to bias. When the internal voltage exceeds a certain value, the transit time will be almost unchanged and the phase variation is small because of saturated drift velocity. These results can provide guidance to operate the optoelectronic link under optimal conditions.

Breast cancer (BC) is the most common tumor in women, and the molecular mechanism underlying its pathogenesis remains unclear. In this study, we aimed to investigate gene modules related to the phenotypes of BC, and identify representative candidate biomarkers for clinical prognosis of BC patients. Using weighted gene co-expression network analysis, we here identified NPY5R as a hub gene in BC. We further found that NPY5R was frequently downregulated in BC tissues compared with adjacent tumor-matched control tissues, due to its aberrant promoter CpG methylation which was confirmed by methylation analysis and treatment with demethylation agent. Higher expression of NPY5R was closely associated with better prognosis for BC patients. Gene set enrichment analysis showed that transcriptome signatures concerning apoptosis and cell cycle were critically enriched in specimens with elevated NPY5R. Ectopic expression of NPY5R significantly curbed breast tumor cell growth, induced cell apoptosis and G2/M arrest. Moreover, NPY5R also promoted the sensitivity of BC cells to doxorubicin. Mechanistically, we found that NPY5R restricted STAT3 signaling pathway activation through interacting with IL6, which may be responsible for the antitumor activity of NPY5R. Collectively, our findings indicate that NPY5R functions as a tumor suppressor but was frequently downregulated in BC.

Organic ultraviolet absorbents (OUVAs) in the environment have been of increasing concern because of their potential hazards. However, the OUVAs in waters is far from being well studied and little is known about their occurrence in small urban rivers. This study investigated the concentrations and distribution of eleven OUVAs in the sediments from five small urban rivers of Tianjin, China, and found total concentrations in the range of 11.6–189 ng/g dry weight. Relative to other rivers and lakes, no high concentrations of sediment OUVAs were observed in the small rivers. Benzophenone, homosalate and octocrylene were the dominant OUVAs, representing medians of 13.3%, 12.4% and 12.3% of the total concentrations, respectively. Our observed composition profiles of these chemicals were different from those found in most of other waters. The sediment OUVAs may originate more from industrial activities than the use of cosmetics and personal care products in this area. The risk to aquatic organisms from exposure to the sediment OUVAs in these small urban rivers was considered low, except for benzophenone. However, more researches are needed to investigate the pollution and associated risks of these chemicals in urban rivers due to the complexity of their toxicity to aquatic organisms.

Multi-project parallelism is an important feature of open source communities (OSCs), and multi-project collaboration among users is a favorable condition for an OSC’s development. This paper studies the robustness of this type of community. Based on the characteristics of knowledge collaboration behavior and the large amount of semantic content generated from user collaboration in open source projects, we construct a directed, weighted, semantic-based multi-project knowledge collaboration network. Using analysis of the KCN’s structure and user attributes, nodes are divided into knowledge collaboration nodes and knowledge dissemination nodes that participate in either multi- or single-project collaboration. From the perspectives of user churn and behavior degradation, two types of failure modes are constructed: node failure and edge failure. Based on empirical data from the Local Motors open source vehicle design community, we then carry out a dynamic robustness analysis experiment. Our results show that the robustness of our constructed network varies for different failure modes and different node types: the network has (1) a high robustness to random failure and a low robustness to deliberate failure, (2) a high robustness to edge failure and a low robustness to node failure, and (3) a high robustness to the failure of single-project nodes (or their edges) and a low robustness to the failure of multi-project nodes (or their edges). These findings can be used to provide a more comprehensive and targeted management reference, promoting the efficient development of OSCs.

Background and ObjectivesCurrently, the location of primary tumor was an independent prognostic factor of breast cancer. Tumors in the central and nipple portion (TCNP) had poor prognosis compared to other peripheral quadrants. The breast-conserving therapy (BCT) is becoming increasingly common worldwide in breast cancer operations. However, whether the availability of BCT was performed for TCNP remained a matter of debate. We sought to investigate whether BCT was suitable for TCNP with respect to survival outcomes, compared with mastectomy therapy.MethodsUtilizing the Surveillance, Epidemiology, and End Results (SEER) database, we obtained TCNP breast cancer patients diagnosed during the period of 2010–2015. One-to-one (1:1) propensity score matching (PSM) was applied to construct a matched sample consisting of pairs of BCT and mastectomy groups. Univariate and multivariate Cox proportional hazard models were applied to estimate the factors associated with breast cancer-specific survival (BCSS) and overall survival (OS). Survival analysis was performed with the Kaplan–Meier method.ResultsIn the overall cohort, a total of 9,900 patients were enrolled. We found that patients with BCT showed significantly better BCSS (log-rank, p < 0.001) and OS (log-rank, p < 0.001) than the mastectomy group before PSM. The same finding was also shown in 5,820 patients after PSM. Additionally, none of the subgroups, including age, sex, race, histological grade, AJCC stage, and molecular subtype undergoing mastectomy therapy, had better BCSS than BCT.ConclusionsOur study was the first research to show that BCT exhibited superior prognosis in the cohort of TCNP from SEER databases than mastectomy therapy. This finding could provide a cue for treatment strategies for suitable TCNP patients, especially those with a strong willingness to conserve their breasts.

A novel optical frequency-hopping system based on distributed feedback laser integrated with an electroabsorption modulator is proposed and demonstrated. In the proposed system, a user's data are split into segments and modulated onto multiple optical frequency shift keying carries, therefore, a single wavelength of optical carrier only carries partial user's data. By this way, the security of optical communication system is improved. In this paper, we demonstrate an error free transmission through 32-km single mode fiber and 8-km dispersion compensation fiber with 2.5 Gb/s hopping rate and 10 Gb/s data rate. Meanwhile, we also compare and analyze the performance of the proposed system with different hopping rate and data rate.

Tumor microenvironment (TME) is vital for the occurrence and development of breast cancer (BRCA). However, it remains challenging to understand the dynamic modulation of the stromal and immune components comprehensively in TME. Herein, we used ESTIMATE and CIBERSORT algorithm to estimate the number of stromal and immune components and the abundance of tumor-infiltrating immune cells (TICs) in 582 BRCA cases from gene expression omnibus (GEO) database. We employed three regression models including univariable Cox proportion, LASSO regression model and multivariate Cox regression, and identified 7 immune-specific genes related to BRCA survival. Of 7 genes, ATPase Secretory Pathway Ca2+ Transporting 2 (ATP2C2) attracts our attention for significantly predicting prognosis of BRCA patients. Further analysis indicated that ATP2C2 expression was closely related to the clinicopathological features (age, T- and N-staging) and negatively correlated with patients’ survival in BRCA. Gene Set Enrichment Analysis (GSEA) was performed to reveal pathway enrichment between ATP2C2high and ATP2C2low groups. The low ATP2C2 expression groups’ genes were mainly enriched for immune-related activities, while those in the ATP2C2 high-expression group were largely enriched in metabolic-related pathways. Notably, Pearson’s correlation analysis identified that ATP2C2 expression was positively correlated with T follicular helper (Tfh) cells, and negatively correlated with gamma delta (γδ) T cell, suggesting that ATP2C2 might be accountable for the maintenance of immune-dominant status for TME. To sum up, this study comprehensively analyzed the TME and shed light on prognostic immune-related biomarkers for BRCA. In particular, ATP2C2 might be helpful for predicting the prognosis of BRCA patients, which provided an extra insight for BRCA treatment.

Abstract Background To determine whether adipocyte-derived lipids could be transferred into breast cancer cells and investigate the underlying mechanisms of subsequent lipolysis and fatty acid trafficking in breast cancer cells. Methods A Transwell co-culture system was used in which human breast cancer cells were cultured in the absence or presence of differentiated murine 3 T3-L1 adipocytes. Migration/invasion and proliferation abilities were compared between breast cancer cells that were cultivated alone and those co-cultivated with mature adipocytes. The ability of lipolysis in breast cancer cells were measured, as well as the expression of the rate-limiting lipase ATGL and fatty acid transporter FABP5. ATGL and FABP5 were then ablated to investigate their impact on the aggressiveness of breast cancer cells that were surrounded by adipocytes. Further, immunohistochemistry was performed to detect differential expression of ATGL and FABP5 in breast cancer tissue sections. Results The migration and invasion abilities of cancer cells were significantly enhanced after co-culture with adipocytes, accompanied by elevated lipolysis and expression of ATGL and FABP5. Abrogation of ATGL and FABP5 sharply attenuated the malignancy of co-cultivated breast cancer cells. However, this phenomenon was not observed if a lipid emulsion was added to the culture medium to substitute for adipocytes. Furthermore, epithelial-mesenchymal transaction was induced in co-cultivated breast cancer cells. That may partially due to the stimulation of PPARβ/δ and MAPK, which was resulted from upregulation of FABP5. As evidenced by immunohistochemistry, ATGL and FABP5 also had higher expression levels at the invasive front of the breast tumor, in where the adipocytes abound, compared to the central area in tissue specimens. Conclusions Lipid originating from tumor-surrounding adipocytes could be transferred into breast cancer cells. Adipocyte-cancer cell crosstalk rather than lipids alone induced upregulation of lipases and fatty acid transport protein in cancer cells to utilize stored lipids for tumor progression. The increased expression of the key lipase ATGL and intracellular fatty acid trafficking protein FABP5 played crucial roles in this process via fueling or signaling.

In order to promote the renewal and development of the capital city and avoid the "low-speed development trap" in the economy, the government proposed to use "high-tech" industries as the driving force to accelerate the construction of a "high-tech" industrial economic structure and increase investment in industrial innovation, so as to better guide and support overall and long-term development of economic and social. This article uses the SWOT analysis model, based on the actual development of Beijing’s industry, deeply analyzes the advantages, disadvantages, opportunities and challenges of the city’s development of "high-tech" industries, and proposes four aspects of countermeasure, such as improving fiscal and tax incentive policies, improving financing methods, optimizing industrial layout, promoting dual-chain integration. Beijing Municipal Government should speed up a reasonable "high-tech" industrial structure, give full play to the role of "high-tech" industries in "improving quality and efficiency" in Beijing's economic development, and then optimize and enhance the core functions of the capital.

In order to promote China's economy high-quality development, the country has continuously lowered the certification standards for high-tech enterprises. The existing research literature has not yet reached a clear conclusion about the impact of high-tech qualification certification on enterprise innovation performance. This paper uses the Shanghai and Shenzhen A-share listed companies from 2013 to 2018 as a research sample. Through the propensity score matching method, it is found that the implementation of the high-tech enterprise identification policy has an effect on the innovation performance of the enterprise, especially for strategic innovation represented by the number of non-invention patent applications. The sub-sample results show that the identification policy has a more obvious impact on the innovation performance of non-state-owned enterprises, young enterprises and larger enterprises. Finally, based on the results of the research, it is proposed to continuously improve the identification policy, guide enterprises to make substantial innovations, and implement hierarchical tax rates for different types of enterprises to help improve the identification policies for high-tech enterprises.