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The deintercalation of weakly bonded A element affects the microstructure and properties of MAX phases and their reinforced composites. In this work, the effect of M-site element on the interaction of Al-containing M2AlC (M = V, Cr) phase and Ag, and the induced properties of Ag/M2AlC electrical contact materials (ECMs) were investigated. Though Ag and Al are soluble to each other and can form intermetallics, the variation of M element significantly affected the vacancy formation of Al, and thereby the interfacial reaction of Ag/M2AlC. The difficult formation of Al vacancy in V2AlC contributed to no obvious interfacial reaction in Ag/V2AlC. But the easy deintercalation of Al atoms in Cr2AlC led to their massive replacement by Ag, which generated Ag nano-twins and Cr3C2 with the same crystallographic relationship in one original Cr2AlC, and Cr7C3 and Ag3Al as well. Due to the distinct interactions, the resistivities of Ag/V2AlC and Ag/Cr2AlC increased by roughly 1 and 5 times after sintering, respectively. The low resistivity and proper hardness of the sintered Ag/V2AlC, which were very close to those of the “all-purpose” commercial Ag/CdO, contributed to its superior arc erosion resistance.

Background and objective In China, lung cancer remains the cancer with the highest incidence and mortality rate. Among early-stage lung adenocarcinomas (LUAD), the micropapillary (MPP) component is prevalent and typically exhibits high aggressiveness, significantly correlating with early metastasis, lymphatic infiltration, and reduced five-year survival rates. Therefore, the study is to explore the similarities and differences between MPP and non-micropapillary (non-MPP) components in malignant pulmonary nodules characterized by GGOs in early-stage LUAD, identify unique mutational features of the MPP component and analyze the relationship between the ZNF469 gene, a member of the zinc-finger protein family, and the prognosis of early-stage LUAD, as well as its correlation with immune infiltration. Methods A total of 31 malignant pulmonary nodules of LUAD were collected and dissected into paired MPP and non-MPP components using microdissection. Whole-exome sequencing (WES) was performed on the components of early-stage malignant pulmonary nodules. Mutational signatures analysis was conducted using R packages such as maftools, Nonnegative Matrix Factorization (NMF), and Sigminer to unveil the genomic mutational characteristics unique to MPP components in invasive LUAD compared to other tumor tissues. Furthermore, we explored the expression of the ZNF469 gene in LUAD using The Cancer Genome Atlas (TCGA) database to investigate its potential association with the prognosis. We also investigated gene interaction networks and signaling pathways related to ZNF469 in LUAD using the GeneMANIA database and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Lastly, we analyzed the correlation between ZNF469 gene expression and levels of immune cell infiltration in LUAD using the TIMER and TISIDB databases. Results MPP components exhibited a higher number of genomic variations, particularly the 13th COSMIC (Catalogue of Somatic Mutations in Cancer) mutational signature characterized by the activity of the cytidine deaminase APOBEC family, which was unique to MPP components compared to non-MPP components in tumor tissues. This suggests the potential involvement of APOBEC in the progression of MPP components in early-stage LUAD. Additionally, MPP samples with high similarity to APOBEC signature displayed a higher tumor mutational burden (TMB), indicating that these patients may be more likely to benefit from immunotherapy. The expression of ZNF469 was significantly upregulated in LUAD compared to normal tissue, and was associated with poor prognosis in LUAD patients (P

Frequency agile technology provides full play to the advantage of radars for adopting electronic countermeasures actively, which can effectively enhance the antinoise suppression jamming performance of radars. However, with the increasing complexity of the interference environment, developing an online decision-making method for frequency-agile radar with dynamic adaptability and without foresight of the nature of the environment is a demanding task. According to the features of the jamming strategy, suppression jamming scenarios are divided into three categories, and an online decision-making method for frequency-agile radar based on Multi-Armed Bandit (MAB) is developed to maximize the radar’s detection probability. This approach is an online learning algorithm that does not need to interfere with the foresight of the environment and offline training process and realizes remarkable learning performance from noninterference scenarios to adaptive interference scenarios. The simulation results and theoretical analysis demonstrate that compared with the classical algorithm and stochastic agile strategy, the proposed method has stronger flexibility and can effectively improve the antijamming and target detection performances of the frequency-agile radar for various jamming scenarios.

AbstractBackground Circadian rhythm involved with physiology has been reported to affect pharmacokinetics or pharmacodynamics. We hypothesized that circadian variations in physiology disturb anesthesia and eventually affect recovery after anesthesia.Methods A retrospective cohort study initially included 107,406 patients (1 June 2016–6 June 2021). Patients were classified into morning or afternoon surgery groups. The primary outcome was daytime variation in PACU (post-anesthesia care unit) recovery time and Steward score. Inverse probability weighting (IPW) approach based on propensity score and univariable/multivariable linear regression were used to estimate this outcome.Results Of 28,074 patients, 13,418 (48%) patients underwent morning surgeries, and 14,656 (52%) patients underwent afternoon surgeries. LOWESS curves and IPW illustrated daytime variation in PACU recovery time and Steward score. Before adjustment, compared to morning surgery group, afternoon surgery group had less PACU recovery time (median [interquartile range], 57 [46, 70] vs. 54 [43, 66], p

Postoperative cognitive dysfunction (POCD) is a common neurological complication in elderly patients after surgery and general anesthesia. The occurrence of POCD seriously affects the postoperative recovery of patients, and leads to prolonged hospital stay, reduced quality of life, increased medical costs, and even higher mortality. There is no definite and effective drug treatment for POCD. More evidence shows that perioperative non-pharmacological intervention can improve postoperative cognitive function and reduce the incidence of POCD. Therefore, our studies summarize the current non-pharmacological interventions of POCD from the aspects of cognitive training, physical activity, transcutaneous electrical acupoint stimulation, noninvasive brain stimulation, non-pharmacological sleep improvement, music therapy, environment, and multimodal combination Interventions, to provide more data for clinical application and research.

BackgroundNerve blocks are widely used in various surgeries to alleviate postoperative pain and promote recovery. However, the impact of nerve block on delirium remains contentious. This study aims to systematically evaluate the influence of Thoracic Paravertebral Nerve Block (TPVB) on the incidence of delirium in patients post Video-Assisted Thoracoscopic Surgery (VATS).MethodsWe conducted a systematic search of PubMed, Embase, Web of Science, Cochrane Library, and Scopus databases in June 2023. The search strategy combined free-text and Medical Subject Headings (MeSH) terms, including perioperative cognitive dysfunction, delirium, postoperative cognitive dysfunction, paravertebral nerve block, thoracic surgery, lung surgery, pulmonary surgery, and esophageal/esophagus surgery. We utilized a random effects model for the analysis and synthesis of effect sizes.ResultsWe included a total of 9 RCTs involving 1,123 participants in our study. In VATS, TPVB significantly reduced the incidence of delirium on postoperative day three (log(OR): −0.62, 95% CI [−1.05, −0.18], p = 0.01, I2 = 0.00%) and postoperative day seven (log(OR): −0.94, 95% CI [−1.39, −0.49], p

Abstract Background Postoperative delirium (POD) is an important complication for older patients and recent randomised controlled trials have showed a conflicting result of the effect of deep and light anesthesia. Methods We included randomised controlled trials including older adults that evaluated the effect of anesthetic depth on postoperative delirium from PubMed, Embase, Web of Science and Cochrane Library. We considered deep anesthesia as observer’s assessment of the alertness/ sedation scale (OAA/S) of 0–2 or targeted bispectral (BIS) 50. The primary outcome was incidence of POD within 7 days after surgery. And the secondary outcomes were mortality and cognitive function 3 months or more after surgery. The quality of evidence was assessed via the grading of recommendations assessment, development, and evaluation approach. Results We included 6 studies represented 7736 patients aged 60 years and older. We observed that the deep anesthesia would not increase incidence of POD when compared with the light anesthesia when 4 related studies were pooled (OR, 1.40; 95% CI, 0.63–3.08, P = 0.41, I2 = 82%, low certainty). And no significant was found in mortality (OR, 1.12; 95% CI, 0.93–1.35, P = 0.23, I2 = 0%, high certainty) and cognitive function (OR, 1.13; 95% CI, 0.67–1.91, P = 0.64, I2 = 13%, high certainty) 3 months or more after surgery between deep anesthesia and light anesthesia. Conclusions Low-quality evidence suggests that light general anesthesia was not associated with lower POD incidence than deep general anesthesia. And High-quality evidence showed that anesthetic depth did not affect the long-term mortality and cognitive function. Systematic review registration CRD42022300829 (PROSPERO).

Abstract Background Current chemotherapy-induced peripheral neuropathy (CIPN) assessment tools mostly have poor sensitivity and weak anti-interference, so that it is sometimes difficult to provide substantive guidance for clinical intervention. This study aimed to develop an assessment tool dedicated for oxaliplatin to address these limitations. Methods This study screened 445 OIPN-related literatures for producing a symptom list, and developed the questionnaire module through expert supplement, item generation, content correlation analysis, pre-testing, and item improvement. The validation phase used a Chinese population-based prospective cohort study from June 2021 to July 2022. Patients were requested to complete the tested questionnaire, QLQ-CIPN20 and the CTCAE grading one day before cycles 2–6 of chemotherapy. Cronbach’s α coefficient and intraclass correlation coefficient (ICC) were calculated for the internal consistency and stability analysis, respectively. Exploratory factor analysis was conducted to investigate the construct validity. The correlations among the tested questionnaire, QLQ-CIPN20 and CTCAE were compared for the criterion validity analysis. Wilcoxon signed-rank sum test was utilized to compare the sensitivity between the tested questionnaire and QLQ-CIPN20. Result A 20-item CIPN assessment tool named chemotherapy-induced peripheral neuropathy integrated assessment – oxaliplatin subscale (CIPNIA-OS) was developed. The validation phase included 186 patients. Cronbach's α coefficient of CIPNIA-OS was 0.764 (> 0.7), and ICC was 0.997 (between 0.9 and 1). The structure of CIPNIA-OS containing seven factors was examined. The correlation coefficient between CIPNIA-OS and CTCAE was 0.661 (95%CI 0.623 to 0.695), which was significantly higher than that between QLQ-CIPN20 and CTCAE (0.417, 95%CI 0.363 to 0.469, p

In recent years, with the progress of new energy conversion technology, especially an increasing number of gas turbine units applied to the market, the connection between the natural gas system and the electric system has become increasingly close. Initially the gas and electricity markets operated relatively independently. Therefore, it is necessary to establish the coupling architecture of natural gas market and electricity market to meet the energy demand of users. This paper attempts to propose a power and gas coupling system based on clearing market structure. Firstly, the difference between natural gas–electricity coupling market and joint settlement market is discussed. The combined market considered in this paper is somewhat different from the associated electricity market and natural gas market. The calculations are easier and the results more reliable than those of the traditional linked gas markets and electric power market. Then, a mathematical model of joint clearing market is established based on bilateral energy contracts. Then, the piecewise linearization approximation (PLA) algorithm is proposed to solve the nonlinear problem. The locational piecewise price (LMEP) and locational marginal gas price (LMGP) are identified respectively, and the bilateral contracts are processed. The solution proposed in this paper guarantees strong duality and clear meaning of dual variables, making PLA easy to apply and solve market clearing problems based on dual variables or Lagrange multiplier pricing, as well as easy to deal with bilateral contract problems. Finally, the proposed joint clearing market is verified by an improved 3-electric bus and 6-gas node system.

In recent years China has committed to energy saving and emission reduction. Chinese Government has proposed a strategic policy of carbon neutrality. In the context of energy shortage, the development of sustainable cities and green buildings is a major trend. An important part of energy consumption in cities is the energy consumed by temperature regulation in buildings, and reducing this part of energy consumption can be of great help to the development of sustainable cities. In this paper, our team propose a scheme for temperature regulation with large permanent magnet direct drive fans system and air conditioners. Compare the conventional room temperature regulation scheme which only uses air conditioners with the new room temperature regulation scheme which uses the large permanent magnet direct drive fan and air conditioners by simulating the indoor temperature regulation process. The results of simulation show that the new scheme’s temperature regulation effects are more uniform than the conventional scheme. The new scheme can reach the target Comfort Index of Human Body faster than the conventional scheme, and the energy consumption can be reduced by more than 8%. The paper concludes that the new room temperature control solution is more energy efficient, reduces carbon emissions and helps to achieve the carbon neutrality target.

Highlights Cerium methacrylate was prepared and ingeniously used as curing agent for epoxy, surface modifier for BN, and effective corrosion inhibitor. The coating integrates high thermal conductivity (4.29 W m−1 K−1), corrosion resistance (low-frequency impedance is 5.1 × 1011 Ω cm2 at 181 day), hydrophobicity (WCA: ~ 148.35° and WSA: ~ 20°), temperature resistance and adhesion. The coating can extend service life of metal materials without sacrificing their inherent heat conduction property.

Objective This research aimed to assess the levels of cognitive function and its contributing factors among individuals experiencing cancer pain (CP) in mainland China.Design A descriptive, cross-sectional study.Setting The investigation was undertaken within three tertiary oncology hospitals.Participants We included 220 hospitalised individuals who reported experiencing cancer-related pain and consented to complete the research questionnaires.Outcome measures The collected data encompassed sociodemographic and clinical variables, augmented by results from validated questionnaires. Cognitive impairment (CI) was evaluated using the Functional Assessment of Cancer Therapy-Cognitive (FACT-Cog) scale, with scores ranging from 0 to 148. Sleep quality, depression and anxiety were assessed through the Pittsburgh Sleep Quality Index, the Patient Health Questionnaire-9 and the Generalised Anxiety Disorder-7, respectively. A binary logistic regression model was used to identify factors associated with CI in individuals with CP.Results Of the 225 individuals approached, 220 (97.8%) participated in the study. The mean FACT-Cog score for those with CP was 101.29 (SD=25.24; range=25–148). The prevalence of CI among these individuals was 35.90%. Sleep quality was rated below medium in 45% of participants with CP. More than moderate pain was reported by 28.2%, with 64.6% experiencing depression and 38.6% experiencing anxiety. Increased odds of developing CI were observed in those with CP (OR 1.422, 95% CI 1.129 to 1.841), depression (OR 1.119, 95% CI 1.029 to 1.2117), anxiety (OR 1.107, 95% CI 1.005 to 1.220), advancing age (OR 1.042, 95% CI 1.013 to 1.073), poor sleep quality (OR 1.126, 95% CI 1.013 to 1.252) and a history of smoking (OR 3.811, 95% CI 1.668 to 8.707).Conclusions CI associated with CP is notably prevalent in China. Those older, with a smoking history, inadequate sleep, more severe pain, depression and anxiety, have a heightened risk of CI. Consequently, interventions need to be personalised, addressing these key determinants.

Amid escalating energy crises and environmental pressures, electric vehicles (EVs) have emerged as an effective measure to reduce reliance on fossil fuels, combat climate change, uphold sustainable energy and environmental development, and strive towards carbon peaking and neutrality goals. This study introduces a nonlinear integer programming model for the deployment of dynamic wireless charging lanes (DWCLs) and EV charging strategy joint optimization in highway networks. Taking into account established charging resources in highway service areas (HSAs), the nonlinear charging characteristics of EV batteries, and the traffic capacity constraints of DWCLs. The model identifies the deployment of charging facilities and the EV charging strategy as the decision-making variables and aims to minimize both the DWCL construction and user charging costs. By ensuring that EVs maintain an acceptable state of charge (SoC), the model combines highway EV charging demand and highway EV charging strategy to optimize the DWCL deployment, thus reducing the construction cost of wireless charging facilities and user charging expenses. The efficacy and universality of the model are demonstrated using the classical Nguyen–Dupius network as a numerical example and a real-world highway network in Guangdong Province, China. Finally, a sensitivity analysis is conducted to corroborate the stability of the model. The results show that the operating speed of EVs on DWCLs has the largest impact on total cost, while battery capacity has the smallest. This comprehensive study offers vital insights into the strategic deployment of DWCLs, promoting the sustainable and efficient use of EVs in highway networks.

Responses to sedatives, analgesics and muscle relaxants vary among patients under general anesthesia, which could be ascribed to the disparities of clinical characteristics and genetic factors of individuals. Accumulating researches have indicated that gene polymorphisms of the receptors, transporters and metabolizing enzymes associated with anesthetics play a considerable role in their efficacy. However, a systematically summarized study on the mechanisms of gene polymorphisms on pharmacodynamics and pharmacokinetics of anesthetics is still lacking. In this paper, the recent researches on pharmacogenomics of sedatives, analgesics and muscle relaxants are comprehensively reviewed, and the contributions and mechanisms of polymorphisms to the differences of individual efficacy of these drugs are discussed, so as to provide guidance for the formulation of a rational anesthesia regimen for patients with various genotypes.

Background and objective The morbidity and mortality rates of lung cancer remain high worldwide, and lung adenocarcinoma is one of the most important tissue subtypes of lung cancer. Epidermal growth factor receptor (EGFR) mutation is an important driver gene mutation for lung adenocarcinoma. In recent years, immune checkpoint inhibitors (ICIs), such as programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) inhibitors, have achieved remarkable efficacy in some lung cancer patients. Patients with EGFR mutations enjoyed limited benefits from immunotherapy according to recent studies. This study aimed to explore the relationship between EGFR mutation status and the spatial distribution as well as infiltration number of various immune cells in patients with EGFR mutant lung adenocarcinoma. Methods This study included 62 lung adenocarcinoma patients who underwent surgery. Through multi-point sampling of surgically removed tumor tissues in different areas, 223 tumor tissue samples were finally obtained. We aquired EGFR mutations status including variant allele frequency (VAF) and mutation subtype in each tumor tissue by genetic test. Afterwards, hematoxylin-eosin (HE) staining, immunohistochemical staining and multiplex fluorescence immunohistochemistry staining have been performed, therefore the infiltration of various immune cells and the distribution of tertiary lymphoid structure (TLS) in tumor tissues were obtained by calculating the immunohistochemical score. Results Compared with EGFR wild-type patients, patients with EGFR-mutant lung adenocarcinoma had more infiltration of CD68+ macrophages and major histocompatibility complex (MHC) class II antigen-presenting cells and higher spatial distribution heterogeneity of MHC class II antigen presenting cells in tumor tissues, while CD56+ natural killer cells and CD8+ T cells had lower infiltration. Tumor tissues with higher EGFR VAF were associated with lower cell infiltration such as CD3+ T cells, CD20+ B cells, CD56+ natural killer cells, CD68+ macrophages, CD8+ T cells, and only CD3+ T cells showed a lower spatial distribution heterogeneity. For the two common subtypes of EGFR mutations in Chinese population, tumor tissues with EGFR exon 19 deletion mutations have lower immune cell infiltration but higher spatial distribution heterogeneity of CD3+ T cells, CD56+ natural killer cells, CD68+ macrophages, and CD8+ T cells than that in EGFR exon 21 L858R mutant tumor tissues. Prognostic analysis found that patients with EGFR mutations with high degree of CD3+ T cells, CD20+ B cell infiltration and larger numbers of TLS formation and high spatial distribution heterogeneity of CD8+ T cell had longer disease-free survival. Conclusion EGFR-mutated lung adenocarcinoma had a unique "non-inflammatory" tumor microenvironment with low infiltration of immune cells, and there was also heterogeneity in the tumor microenvironment among the tumors with different mutation subtypes and mutation abundance. These differences were not only reflected in the number but also the spatial distribution of immune cell infiltration. Hence, further studies on the immune microenvironment of EGFR-mutant lung adenocarcinoma were of great significance for improving the efficacy of immunotherapy in EGFR-mutant lung adenocarcinoma patients in the future.

Weak bonds usually make macromolecules stronger; therefore, they are often used to enhance the mechanical strength of polymers. Not enough studies have been reported on the use of weak bonds in flame retardants. A water-soluble polyelectrolyte complex composed of polyethyleneimine (PEI), sodium tripolyphosphate (STPP) and melamine (MEL) was designed and utilized to treat bio-based polyamide 56 (PA56) by a simple three-step process. It was found that weak bonds cross-linked the three compounds to a 3D network structure with MEL on the surface of the coating under mild conditions. The thermal stability and flame retardancy of PA56 fabrics were improved by the controlled coating without losing their mechanical properties. After washing 50 times, PA56 still kept good flame retardancy. The cross-linking network structure of the flame retardant enhanced both the thermal stability and durability of the fabric. STPP acted as a catalyst for the breakage of the PA56 molecular chain, PEI facilitated the char formation and MEL released non-combustible gases. The synergistic effect of all compounds was exploited by using weak bonds. This simple method of developing structures with 3D cross-linking using weak bonds provides a new strategy for the preparation of low-cost and environmentally friendly flame retardants.

Network-group targets are a set of objectives that adhere to a shared communication protocol, perform common tasks, and exhibit relatively coordinated movements. Typically, network-group targets emit radar and communication signals. However, they often employ a silent mode to evade our perception. Despite this, they continue to exchange data through their communication networks. By intercepting the communication signals of these targets, this paper proposes a method for estimating the state and network topology of network-group targets based on random finite set (RFS) theory. This method is based on the modeling of network-group targets using a labeled multi-Bernoulli (LMB) RFS. In state estimation, the usual method involves extracting the localization parameters from the signals in the first step and use these parameters for target tracking in the second step. This study focused on estimating the kinematic states of network-group targets using communication signals containing delay and Doppler information received by multiple mobile sensor platforms. The proposed method considers the coherency between frequency-hopping pulses in the signals, resulting in an improved estimation performance. In addition, considering that network-group targets require network access for information exchange, graph theory concepts were utilized to estimate the network topology of network-group targets by address measurement. The simulation results validated the effectiveness of the proposed method and demonstrated its superior performance.

Summary: EGFRT790M mutation causes resistance to the first-generation tyrosine kinase inhibitors (TKIs) in patients with non-small cell lung cancer (NSCLC). However, the therapeutic options for sensitizing first TKIs and delaying the emergence of EGFRT790M mutant are limited. In this study, we show that quercetin directly binds with glucose-6-phosphate dehydrogenase (G6PD) and inhibits its enzymatic activity through competitively abrogating NADP+ binding in the catalytic domain. This inhibition subsequently reduces intracellular NADPH levels, resulting in insufficient substrate for methionine reductase A (MsrA) to reduce M790 oxidization of EGFRT790M and inducing the degradation of EGFRT790M. Quercetin synergistically enhances the therapeutic effect of gefitinib on EGFRT790M-harboring NSCLCs and delays the acquisition of the EGFRT790M mutation. Notably, high levels of G6PD expression are correlated with poor prognosis and the emerging time of EGFRT790M mutation in patients with NSCLC. These findings highlight the potential implication of quercetin in overcoming EGFRT790M-driven TKI resistance by directly targeting G6PD.

Background/Purpose: Investigating the antitumor effect and intratumor as well as local immune response in breast cancer-bearing mice after MV X-ray ultra-high dose rate radiotherapy (FLASH-RT) and conventional dose rate radiotherapy (CONV-RT). Materials/Methods: Six-week-old female C57BL/6 mice were inoculated subcutaneously with Py8119 and Py230 breast tumor cells in the inguinal mammary gland and administered 10 Gy abdominal 6 MV X-ray FLASH-RT (125 Gy/s) or CONV-RT (0.2 Gy/s) 15 days after tumor inoculation. Tumor and spleen tissues were obtained at different time points post-irradiation (PI) for analysis of immune cell infiltration using flow cytometry and immunohistochemical (IHC) staining. Intestine tissues were collected 3 days PI to evaluate normal tissue damage and immune cell infiltration. Results: Both FLASH-RT and CONV-RT significantly delayed tumor growth. Flow cytometry showed increased CD8+/CD3 + and CD8+/CD4 + ratios, and IHC confirmed a similar increased CD8 + T cell infiltration at 2 weeks PI in Py8119 tumor tissues in both irradiation groups. No statistical difference was observed between the irradiation groups in terms of tumor growth and increased T cell infiltration in the tumor. Unexpectedly, significantly smaller spleen weight and substantially higher CD8+/CD3 + and lower CD4+/CD3 + ratios were observed in the spleens of the FLASH-RT group than in the spleens of the non-irradiated control and CONV-RT groups 4 weeks PI. Pathological analysis revealed severe red pulp expansion in several spleens from the CONV-RT group, but not in the spleens of the FLASH-RT group. Reduced intestinal damage, macrophage and neutrophil infiltration were observed in the FLASH-RT group compared with CONV-RT group. Conclusions: FLASH-RT and CONV-RT effectively suppressed tumor growth and promoted CD8 + T cell influx into tumors. FLASH-RT can induce different splenic immune responses and reduce radiation-induced damage in the spleen and intestine, which may potentially enhance the therapeutic ratio of FLASH-RT.

Abstract Background Little is known about patients’ intention for participation in end-of-life decisions (EOLD) in three coastal provinces in southern China. This study aimed to explore the willingness of patients with cancer pain to participate in EOLD and potential influencing factors. Methods A multi-center cross-sectional study was performed in three coastal provinces in southern China. Two hundred and thirty patients with cancer pain were recruited and consented to fill out the questionnaires. The patients’ willingness to participate in EOLD, demographic and disease-related data was surveyed. Results In total, 223 patients completed and returned the survey (response rate = 96.95%). One hundred four cases (46.64%) were willing to participate in EOLD. 119 (54.36%) cases not willing to participate in EOLD, respectively. Multivariate logistic regression analysis shows that educational level (OR: 0.683, 95% CI: 0.482–0.966), history of alcoholism (OR: 8.353, 95%CI: 2.535–27.525), Eastern Cooperative Oncology Group (ECOG) score (OR: 0.645, 95% CI: 0.450–0.925) and experience of explosive pain (OR: 6.367, 95% CI: 3.103–13.062) and clinical rescue (OR: 3.844, 95% CI: 1.722–8.577) had significant effects on EOLD intention (P

For the sake of increasing the energy efficiency of the city’s energy supply, it is an effective approach to adopt the joint planning of the integrated energy system employing a group of cooling heat and power. However, the coupling matrix in the integrated energy system is quite difficult to formulate. In this paper, a standardized construction method for modeling Energy Hub is proposed. The construction of the model is divided into several steps. In addition, the difficult of solving the coupling matrix of integrated energy system can be availably reduced through this method. Considering the nonlinear problem caused by dispatch factors, this paper proposes a comprehensive energy system optimization strategy by using improved particle swarm optimization algorithm. Finally, using an example of a residential area with cooling, heating and electricity system to verify the effectiveness of the proposed modeling and calculation method . At the same time, the influence of demand response and energy storage on economy during operation is analyzed.

This paper introduces the principle of RF MEMS switch and performs modeling analysis. By analyzing the low control voltage and microwave power of the switch, phenomena such as long response time and susceptibility to mechanical failure appear. Therefore, this paper analyzes the current research on RF MEMS switches, improves the internal structure of the switch by adding support columns, fixes the double ends of the beam, and increases the spring coefficient K to slow down the falling speed of the internal cantilever of the switch. The impact force between the cantilever and the dielectric layer is reduced, which greatly reduces the loss of the switch and the problems of mechanical fatigue failure, thus improving the service life of the switch. The simulation shows that the stability of the model is relatively high when the length of the cantilever is 300 um. After adding a 0.7 um support column at a distance of 25 um from the dielectric layer, the turn-on voltage is increased from 42.5 V to 61 V, and the switching capacitance remains unchanged. Finally, by calculating the percentage error between the simulation value and the model theory of 1.6%, the validity and accuracy of the model are checked.

Industrial development with the growth, strengthening, stability, technical advancement, reliability, selection, and dynamic response of the power system is essential. Governments and companies invest billions of dollars in technologies to convert, harvest, rising demand, changing demand and supply patterns, efficiency, lack of analytics required for optimal energy planning, and store energy. In this scenario, artificial intelligence (AI) is starting to play a major role in the energy market. Recognizing the importance of AI, this study was conducted on seven different energetics systems and their variety of applications, including: i) electricity production; ii) power delivery; iii) electric distribution networks; iv) energy storage; v) energy saving, new energy materials, and devices; vi) energy efficiency and nanotechnology; and vii) energy policy, and economics. The main drivers are the four key techniques used in current AI technologies, including: i) fuzzy logic systems; ii) artificial neural networks; iii) genetic algorithms; and iv) expert systems. In developed countries, the power industry has started using AI to connect with smart meters, smart grids, and the Internet of Things devices. These AI technologies will lead to the improvement of efficiency, energy management, transparency, and the usage of renewable energies. In recent decades/years, new AI technology has brought significant improvements to how power system devices monitor data, communicate with the system, analyze input–output, and display data in unprecedented ways. New applications in the energy system become feasible when these new AI developments are incorporated into the energy industry. But on the contrary, much more investment is needed in global research into AI and data-driven models. In terms of power supply, AI can help utilities provide customers with renewable and affordable electricity from complex sources in a secure manner, while at the same time providing these customers with the opportunity to use their own energy more efficiently. Moreover, policy recommendations, research opportunities, and how industry 4.0 will improve sustainability have been briefly described.

Abstract Background Besides featured glucose consumption, recent studies reveal that cancer cells might prefer “addicting” specific energy substrates from the tumor microenvironment (TME); however, the underlying mechanisms remain unclear. Methods Fibroblast-specific long noncoding RNAs were screened using RNA-seq data of our NJLCC cohort, TCGA, and CCLE datasets. The expression and package of LINC01614 into exosomes were identified using flow cytometric sorting, fluorescence in situ hybridization (FISH), and quantitative reverse transcription polymerase chain reaction (RT-PCR). The transfer and functional role of LINC01614 in lung adenocarcinoma (LUAD) and CAFs were investigated using 4-thiouracil-labeled RNA transfer and gain- and loss-of-function approaches. RNA pull-down, RNA immunoprecipitation, dual-luciferase assay, gene expression microarray, and bioinformatics analysis were performed to investigate the underlying mechanisms involved. Results We demonstrate that cancer-associated fibroblasts (CAFs) in LUAD primarily enhance the glutamine metabolism of cancer cells. A CAF-specific long noncoding RNA, LINC01614, packaged by CAF-derived exosomes, mediates the enhancement of glutamine uptake in LUAD cells. Mechanistically, LINC01614 directly interacts with ANXA2 and p65 to facilitate the activation of NF-κB, which leads to the upregulation of the glutamine transporters SLC38A2 and SLC7A5 and eventually enhances the glutamine influx of cancer cells. Reciprocally, tumor-derived proinflammatory cytokines upregulate LINC01614 in CAFs, constituting a feedforward loop between CAFs and cancer cells. Blocking exosome-transmitted LINC01614 inhibits glutamine addiction and LUAD growth in vivo. Clinically, LINC01614 expression in CAFs is associated with the glutamine influx and poor prognosis of patients with LUAD. Conclusion Our study highlights the therapeutic potential of targeting a CAF-specific lncRNA to inhibit glutamine utilization and cancer progression in LUAD.

Introduction: Dexmedetomidine (DXM) is widely used as an adjuvant to anesthesia or a sedative medicine, and differences in individual sensitivity to the drug exist. This study aimed to investigate the effect of genetic polymorphisms on these differences.Methods: A total of 112 patients undergoing hand surgery were recruited. DXM 0.5 μg/kg was administered within 10 min and then continuously injected (0.4 μg/kg/h). Narcotrend index, effective dose and onset time of sedation, MAP, and HR were measured. Forty-five single nucleotide polymorphisms (SNPs) were selected for genotype.Results: We observed individual differences in the sedation and hemodynamics induced by DXM. ABCG2 rs2231142, CYP2D6 rs16947, WBP2NL rs5758550, KATP rs141294036, KCNMB1 rs11739136, KCNMA1 rs16934182, ABCC9 rs11046209, ADRA2A rs1800544, and ADRB2 rs1042713 were shown to cause statistically significant (p < 0.05) influence on the individual variation of DXM on sedation and hemodynamics. Moreover, the multiple linear regression analysis indicated sex, BMI, and ADRA2A rs1800544 are statistically related to the effective dose of DXM sedation.Discussion: The evidence suggests that the nine SNPs involved in transport proteins, metabolic enzymes, and target proteins of DXM could explain the individual variability in the sedative and hemodynamic effects of DXM. Therefore, with SNP genotyping, these results could guide personalized medication and promote clinical and surgical management.

Large yellow croaker (Larimichthys crocea) is a commercially important fish species worldwide, but high-density cultivation has led to serious diseases especially by Vibrio harveyi. Understanding the molecular response of large yellow croaker to V. harveyi infection is vital for the development of effective measures to combat the disease. In this study, RNA-Seq was performed on the spleen of uninfected and V. harveyi-infected large yellow croaker. A total of 7527 differentially expressed genes (DEGs) were identified, with 4413 up-regulated and 3114 down-regulated genes. Functional enrichment analysis revealed that several immune-related pathways were highlighted, including Toll-like receptors (TLRs) signaling pathway, apoptosis, p53 signaling pathway, and lysosome. In the TLRs signaling pathway, up-regulated genes included IL1b, bactericidal permeability-increasing protein, and IL12b, while down-expressed genes included tlr3 and irf3. The apoptosis pathway showed up-regulated genes such as casp6, bcl-2-like protein, and cytochrome c, and down-expressed genes such as granzyme B, sptan1, and FADD-Fas (tnfrsf6)-associated via death domain. These results suggest that V. harveyi infection induced inflammatory response and apoptotic cell death in the spleen of large yellow croaker. This study provides valuable insights into the molecular mechanisms underlying the immune response of large yellow croaker to V. harveyi infection

BackgroundRandomized controlled trials (RCTs) have shown conflicting results regarding the effects of perioperative cognitive training (CT) on the incidence of postoperative cognitive dysfunction (POCD) and postoperative delirium (POD). We, therefore, performed a meta-analysis to assess the overall effects of studies on this topic.MethodsWe searched PubMed, Embase, the Cochrane Library, and Web of Science for all RCTs and cohort studies that investigated the effects of perioperative CT on the incidence of POCD and POD. Data extraction and quality assessment were conducted independently by two researchers.ResultsThis study included nine clinical trials with a total of 975 patients. The results showed that perioperative CT significantly reduced the incidence of POCD compared with the control group [risk ratio (RR) = 0.5, 95% CI (confidence interval): 0.28–0.89, P = 0.02]. Nevertheless, for the incidence of POD, the difference between the two groups was not statistically significant (RR = 0.64; 95% CI: 0.29–1.43, P = 0.28). In addition, the CT group had less postoperative decline in the cognitive function scores compared with the control group [mean differences (MD): 1.58, 95% CI: 0.57–2.59, P = 0.002]. In addition, there were no statistically differences in length of hospital stay between the two groups (MD: −0.18, 95% CI: −0.93–0.57, P = 0.64). Regarding CT adherence, the proportion of patients in the cognitive training group who completed the planned duration of CT was 10% (95% CI: 0.05–0.14, P = 0.258).ConclusionOur meta-analysis revealed that perioperative cognitive training is possibly an effective measure to reduce the incidence of POCD, but not for the incidence of POD.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022371306, identifier: CRD42022371306.

Introduction: The nuclear factor kB (NF-κB) pathway emerges as a critical regulator of immune responses and is often dysregulated in human cancers. It consists of a family of transcription factors involved in many biological responses. Activated NF-κB subunits results in the nuclear translocation and activation of transcription, and the NF-κB pathway is known to influence the transcription of many genes. Noncanonical NF-κB and its components have been shown to have effects, usually protumorigenic, in many different cancer types. Besides, NF-κB signaling had diverse and complicated roles in cancer with studies that NF-κB could both contribute to tumor promotion and suppression of oncogenesis relying on the cellular context. RelB, a member of noncanonical NF-κB was abnormally regulated in most cancer types, however the molecular features and clinical signature of RelB expression, as well as its role in cancer immunity in human pan-cancer remains to be elucidated.Methods: We used the open databases to explore RelB expression, clinical features and the association with tumor-infiltration cells in human pan-cancer. In this study, we investigated the aberration expression and prognostic significance of RelB, and the correlation with clinicopathological characters and immune cells infiltration in various cancers. The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to analyze the mRNA expression level in different cancer types. Kaplan-Meier analysis and Cox regression were used to explore the prognostic significance of RelB in human pan-cancer. Then we took advantage of the TCGA database to analyze the relationship between RelB expression and DNA methylation, the infiltration of immune cells, immune checkpoint genes, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MSS).Results: Higher expression of RelB was significantly detected in human cancer tissues and a high level of RelB expression was significantly linked with a worse outcome in LGG, KIPAN, ACC, UVM, LUAD,THYM, GBM, LIHC and TGCT but associated with a favorable overall survival (OS) in SARC, SKCM and BRCA. According to the Human Protein Altas database, RelB was considered as an independent factor in breast cancer and renal cancer prognosis. GSEA results revealed that RelB was involved in many oncogenesisrelated processes and immunity-related pathways. RelB was significantly correlated with DNA methylation in 13 types of cancer. Meanwhile, RelB expression was associated with TMB in 5 types of cancer and MSI in 8 types of cancer. In the final, we analyzed the relationship between RelB expression and immune-infiltration cells in human pan-cancer, which suggested RelB could be a promising therapeutic target for cancer immunotherapy.Discussion: Our study further provided insights into a deeper understanding of RelB as a prognostic biomarker.

Summary: Dynamic thermal emitters have attracted considerable attention due to their potential in widespread applications such as radiative cooling, thermal switching, and adaptive camouflage. However, the state-of-art performances of dynamic emitters are still far below expectations. Here, customized to the special and stringent requirement of dynamic emitters, a neural network model is developed to effectively bridge the structural and spectral spaces and further realizes the inverse design with coupling to genetic algorithms, which considers the broadband spectral responses in different phase-states and utilizes comprehensive measures to ensure the modeling accuracy and computational speed. Besides achieving an outstanding emittance tunability of 0.8, the physics and empirical rules have also been mined qualitatively through decision trees and gradient analyses. The study demonstrates the feasibility of using machine learning to obtain the near-perfect performance of dynamic emitters, as well as guiding the design of other thermal and photonic nanostructures with multifunctions.

The solar array drive assembly (SADA) slip ring is a critical link that provides electrical power and electric signal transmission between solar arrays and satellite power systems, which is prone to arc faults in the space environment. If these arc faults cannot be detected and eliminated quickly enough, they will seriously threaten the safety of the satellite power system and the satellite. In this paper, a fast arc detection method based on fractal dimension is proposed that adapts to different operating modes of power systems. The detection method collects the current differential signal data flowing through the SADA slip ring, and, according to the trend of the fractal dimension change in this signal, the fault identification algorithm is designed for different operating modes of the power system to achieve real-time and rapid identification of arc faults. Finally, the effectiveness of the proposed method is demonstrated using test data under several different fault conditions.

In marine seismic exploration, seismic signals comprise primaries that undergo first-order scattering, as well as multiples resulting from multi-order scattering events. Surface-related multiples involve multi-order scattering at the free surface interface between seawater and air and exhibit a smaller reflection angle and broader illumination compared to primaries. Internal multiples, originating from multi-order scattering among stratified layers, provide additional illumination compensation beneath the reflecting interface. However, in conventional primary migration, different-order wavefields may result in crosstalk artifacts. To address this issue, we developed a least-squares migration (LSM) method based on the multi-order wavefield global normalization condition. This methodology investigates the illumination effects and crosstalk artifacts associated with different-order surface-related and internal multiples, and then modifies the global normalization condition by incorporating an illumination compensation perspective. Virtual sources, represented by surface-related multiples and internal multiples, are integrated into the source compensation term, ultimately yielding a multi-order wavefield normalization condition. This normalization condition is subsequently combined with least-squares full-wavefield migration (LSFWM). Numerical experiments demonstrate that the normalization condition of multi-order wavefields can resolve the problem of weak deep imaging energy and promote the suppression of multiple crosstalk artifacts in the least-squares algorithm.

Investing in entrepreneurship may be costly, and therefore risky, and entrepreneurship is also an economic endeavor that is highly dependent on entrepreneurial ability and risk appetite. In this study, data from 669 famers in southwest China were used as the sample, and we used three different methods to measure farmers’ risk aversion level, including DOSPRET (Domain-Specific Risk-Taking), SOEP (Simple Self-Report), and BRET (Bomb Risk Elicitation Task). This paper studies the impact of farmers’ risk aversion on entrepreneurial choices and the moderating impact of the migrant work experience (MWE) on the relationship between risk aversion and entrepreneurship. The results can be summarized as follows: Firstly, entrepreneurial farmers have lower average levels of risk aversion than non-entrepreneurial farmers. Secondly, risk aversion has a significant negative impact on farmers’ choice of entrepreneurship, corporate entrepreneurship and portfolio entrepreneurship. Thirdly, MWE can reduces the negative impact of risk aversion on a decision to enter entrepreneurship or portfolio entrepreneurship. Fourth, MWE in local or nearby areas reduces the negative effects of risk aversion on entrepreneurship and portfolio entrepreneurship, while MWE in coastal and developed cities increases the negative effects.

This paper addresses the image-based visual servoing (IBVS) control problem with an uncalibrated camera, unknown dynamics, and constraints. A novel data-driven uncalibrated IBVS (UIBVS) strategy is proposed, incorporated with the Koopman-based model predictive control (KMPC) algorithm and the adaptive robust Kalman filter (ARKF). First, to alleviate the need for calibration of the camera’s intrinsic and extrinsic parameters, the ARKF with an adaptive factor is utilized to estimate the image Jacobian matrix online, thereby eliminating the laborious camera calibration procedures and improving robustness against camera disturbances. Then, a data-driven MPC strategy is proposed, wherein the unknown nonlinear dynamic model is learned using the Koopman operator theory, resulting in a linear Koopman prediction model. Only input–output data are used to construct the prediction model, and hence, the proposed approach is robust against model uncertainties. Furthermore, with a symmetric quadratic cost function, the proposed approach solves the quadratic programming problem online, and visibility constraints as well as joint torque constraints are taken into account. As a result, the proposed KMPC scheme can be implemented in real time, and the UIBVS performance degradation which arises from the control torque constraints can be avoided. Simulations and comparisons for a 2-DOF robotic manipulator demonstrate the feasibility of the proposed approach. Simulation results further validate that the computation time of the proposed approach is comparable to the one of kinematic-based methods.

Abstract Background Humane treatment requires the provision of appropriate sedation and analgesia during medical diagnosis and treatment. However, limited information is available about the status of procedural analgesic interventions in Chinese hospitals. Therefore, a nationwide survey was established to identify challenges and propose potential improvement strategies. Methods Forty-three members of the Pain Group of Chinese Society of Anesthesiology established and reviewed the questionnaire, which included (1) general information on the hospitals, (2) the sedation/analgesia rate in gastrointestinal endoscopy, labor, flexible bronchoscopy, hysteroscopy in China, (3) staff assignments, (4) drug use for procedural analgesic interventions, and (5) difficulties in procedural analgesic interventions. The data were obtained using an online questionnaire sent to the chief anesthesiologists of Chinese hospitals above Grade II or members of the Pain Group of Chinese Society of Anesthesiology. Results Valid and complete questionnaires were received from 2198 (44.0%) hospitals, of which 64.5% were Grade III. The overall sedation/analgesia rates were as follows: gastroscopy (50.6%), colonoscopy (53.7%), ERCP (65.9%), induced abortion (67.5%), labor (42.3%), hysteroscopy (67.0%) and fiber bronchoscopy (52.6%). Compared with Grade II hospitals, Grade III hospitals had a higher proportion of procedural analgesic interventions services except for induced abortion. On average (median [IQR]), each anesthesiologist performed 5.7 [2.3—11.4] cases per day, with 7.3 [3.2—13.6] performed in Grade III hospitals and 3.4 [1.8—6.8] performed in Grade II hospitals (z = -7.065, p

Abstract Most current resistive memory has the problems of high and unstable threshold voltages and high device misread rates caused by low current switching ratios. To address these problems, an Al/poly(methyl methacrylate) (PMMA)/silkworm hemolymph:gold nanoparticles/PMMA/indium tin oxide memory device is fabricated by adding PMMA layers above and below the active layer. The device not only has stable bipolar switching characteristics with a high ON/OFF current ratio but also has a lower and more stable threshold voltage. Potentiation, depression, and spike‐time‐dependent plasticity at biological synapses are realized using this device. The device is successfully fabricated on a flexible substrate, and the device can still maintain a stable working state after 104 bending cycles. This research opens a new door for the future realization of artificial synapses in neural network hardware.

Abstract By collecting and sorting the energy demand data of developing and developed countries, this paper makes a comprehensive analysis of their energy demand, including the change of energy demand and the change trend of energy load in various sectors. The survey scope of the article includes the overall change trend of energy supply, natural gas, oil, electricity, coal, renewable energy (such as wind energy, solar energy, geothermal energy, tidal energy, etc.), and the data change of global carbon dioxide emission. Besides, this paper selects a variety of energy sources for comprehensive analysis to analyze the existing change trend in chronological order. The analysis methods include data statistics of primary energy production and consumption, energy intensity analysis of gross domestic product (GDP), production, and demand balance of oil, natural gas, and coal, and study the trade balance between different types of energy in different countries and regions. The regions examined in this review include the organization for economic cooperation and development (OECD); the group of seven (G7); Brazil, Russia, India, China and South Africa (BRICs); the European Union; Europe; North America; the Commonwealth of Independent States (CIS); Asia; Latin America; the Pacific Ocean; the Middle East and Africa. By studying these data, we can make a better summary of the current energy use, so as to conveniently grasp the context of energy development and have a general understanding of the current energy structure. Therefore, individuals and policymakers in the fields of energy trade can think more deeply about the future situation and draw conclusions.

The nonlinear dynamic response of an aquaculture cage array caused by wave-frequency and low-frequency excitations coupled with the nonlinearity of the mooring and the netting system is a complicated problem. So far, this problem still has not been completely understood. To address this issue, we consider the nonlinear interaction of an extreme wave with an aquaculture cage array containing 16 net cages in a 2 × 8 configuration. This paper aims to provide insight into understanding the nonlinear dynamics of an aquaculture cage array via time–frequency analysis. Time-domain analysis shows that the cage array exhibits weak nonlinearity in the surge and heave motions. On the contrary, there is strong nonlinearity in the sway motion under 45° and 90° wave attacks. Aside from this, the frequency-domain analysis indicates that nonlinearities exist in all three of these different responses (surge/sway/heave). Particularly, the low-frequency component has a predominant effect on the nonlinearity of the sway motion under 45° and 90° wave attacks. With this understanding, future aquaculture fish farms that contain multiple cages (i.e., cage array) can be potentially designed to withstand severe conditions in the open ocean.

Many graph construction methods for clustering cannot consider both local and global data structures in the construction of initial graph. Meanwhile, redundant features or even outliers and data with important characteristics are addressed equally in the graph optimization process. These lead to the learned representation graph may not capture the optimal structure when clustering. This paper proposes a novel model for clustering, named adaptive graph construction and low-rank representation of weighted noise (ACLWN), to overcome these problems. ACLWN is composed of an adaptive representation graph construction model named ARG, and an adaptive weighted sparse representation graph learning model named AWSG. In ARG, manifold learning and sparse representation are employed to capture the local structure of data. In AWSG, an adaptive weighted matrix is proposed to strengthen the important features and improve the robustness of the low-dimensional representation graph. Moreover, constraints such as non-negative low-rank, sparsity and distance regularization terms are imposed to capture the local and global structures of data. Comprehensive experimental results show that our method outperforms the compared state-of-the-art methods. The low-dimensional representation graph constructed by ACLWN is more suitable for clustering.

Abstract Deep learning techniques and deep networks have recently been extensively studied and widely applied to single image super‐resolution (SR). Among them, channel attention has garnered the most focus owing to its significant boost in the presentational power of a convolutional neural network. However, the original channel attention neglects the critical importance of the positional information, thus imposing performance limitations. Here, a novel perspective, namely, a coordinate attention mechanism, is explored to alleviate the aforementioned problem, and accordingly result in an enhanced SR performance. Specifically, a deep residual coordinate attention SR network (COSR) is proposed, which mainly incorporates the presented coordinate attention blocks into a deep nested residual structure. The coordinate attention captures the positional information by computing the average value vector from the two spatial directions, thus aggregating the features in different coordinates. The nested residual blocks pass low‐frequency information from the top to the end through the skip connection lines, allowing convolution filters to concentrate more on high‐frequency textures and edges, thereby reducing the difficulty of reconstruction. Extensive experiments demonstrate that our proposed COSR achieves a better performance and exceeds many state‐of‐the‐art SR methods in terms of both quantitative metrics and visual quality.

KRAS is one of the most frequently activated oncogenes in human cancers. Although the role of KRAS mutation in tumorigenesis and tumor maintenance has been extensively studied, the relationship between KRAS and the tumor immune microenvironment is not fully understood. Here, we identified a role of KRAS in driving tumor evasion from innate immune surveillance. In samples of lung adenocarcinoma from patients and Kras-driven genetic mouse models of lung cancer, mutant KRAS activated the expression of cluster of differentiation 47 (CD47), an antiphagocytic signal in cancer cells, leading to decreased phagocytosis of cancer cells by macrophages. Mechanistically, mutant KRAS activated PI3K/STAT3 signaling, which restrained miR-34a expression and relieved the posttranscriptional repression of miR-34a on CD47. In 3 independent cohorts of patients with lung cancer, the KRAS mutation status positively correlated with CD47 expression. Therapeutically, disruption of the KRAS/CD47 signaling axis with KRAS siRNA, the KRASG12C inhibitor AMG 510, or a miR-34a mimic suppressed CD47 expression, enhanced the phagocytic capacity of macrophages, and restored innate immune surveillance. Our results reveal a direct mechanistic link between active KRAS and innate immune evasion and identify CD47 as a major effector underlying the KRAS-mediated immunosuppressive tumor microenvironment.

The wave-driven floating photobioreactors (PBRs) with advantages of easy in scaling-up, low energy inputs and low fabricating cost, hold great potential for massive and cost-energy effective microalgae production. However, their applications may be seriously challenged by intermittent waves that could produce very poor mixing under poor wave conditions, leading to a significant reduction of biomass productivity or even collapse of the cultures. To improve the utilization efficiency of waves for efficient and stable microalgae production in the floating PBRs, this work aims at numerically studying the fluid-dynamics of the floating PBRs, as well as the effects from wave conditions, culture depth and three different PBRs’ structures of square, rectangular and circular types. The results showed that the liquid inside the floating PBRs follow a periodic sinusoidal and reciprocating flow, and the square PBR had aggressive mixing characteristics at high wave excitation frequency, while the rectangular PBR produced more intense mixing at low wave excitation frequency. Regarding the culture depth, the dependence of liquid mixing on the culture depth showed a decreasing trend. Moreover, the results indicated that the PBRs with a high culture depth had several dead zones, although there was apparent upward flow at the high excitation frequency. This work provides valuable insight into increasing the utilization efficiency of wave energy for mixing enhancement in the floating PBRs and their design.

Aiming at the low efficiency of vector control system caused by unreasonable current allocation, an improved energy saving control strategy based on weighted average current method is proposed in this paper, and the research is carried out on the background of interior permanent magnet synchronous motor vector control system. This method does not add new parameters, but achieves the goal of reducing motor loss and improving current utilization rate. Firstly, according to the mathematical model of permanent magnet synchronous motor considering iron loss resistance, the relationship between motor torque and d-q axis current is deduced. Then, by introducing the weighted average current factor, the minimum copper loss current and the minimum iron loss current are calculated analytically. Finally, the simulation analysis shows that the energy saving strategy proposed in this paper can further reduce the electrical loss of permanent magnet motor compared with the traditional energy saving control method, which proves the feasibility of this method in improving the energy efficiency of the vector control system of permanent magnet motor.

BackgroundBilateral multiple ground glass opacities (GGOs) are observed in quite a part of patients with early-stage lung adenocarcinoma. For this so-called synchronous multiple primary lung cancer (sMPLC), targeting immune checkpoint is a favorable option in addition to surgical resection. The purpose of this study is to reveal the safety and efficacy of performing immune checkpoint inhibitors (ICIs) on patients with sMPLC and to explore the biomarkers of the efficacy.MethodsA total of 21 patients with sMPLC were enrolled and all included cases were pathologically confirmed adenocarcinoma after conducting surgical treatment for unilateral GGOs. ICIs of Sintilimab were then used to target programmed death 1 (200mg i.v., Q3W) for up to 10 cycles. Seven patients of them received the other surgery for contralateral GGOs, and multiomics assessments, including neoantigens, somatic mutations, and methylated loci, were further performed to investigate potential biomarkers.ResultsGrade 1 or 2 treatment-related adverse events (AEs) occurred in most of the patients (12/21, 57.1%), and one subject withdrawn for grade 3 AEs. For the seven patients underwent twice surgeries, twelve and thirteen GGOs were achieved before and after the use of ICIs separately, and a favorable efficacy was observed among six lesions after immunotherapy (> 50% pathologic tumor regression). Tumor infiltration T-cell and B-cell were further shown to be associated with the biological activity of ICIs. According to mechanism-based multiomics analyses, MUC19- and PCDHB5- mutations were indicated to correlate with a favorable prognosis of sMPLC underwent immunotherapy, and our results suggested that immunogenetic mutation and associated promoter methylation could provide a quantitative explanation for the pathologic response of GGOs.ConclusionOur study provides evidence that the use of ICIs contributed favorable efficacy and safety to patients with sMPLC. Immune infiltration and immunogenic biomarkers are revealed to be implications of performing ICIs on sMPLC. These preliminary findings exhibit the prospects in performing neoadjuvant or adjuvant immunotherapies on patients with sMPLC.Clinical Trial Registrationhttps://www.chictr.org.cn/showproj.aspx?proj=36878, identifier ChiCTR1900022159.

Cyber mimic defense is designed to ensure endogenous security, effectively countering unknown vulnerabilities and backdoors, thereby addressing a significant challenge in cyberspace. However, the immense scale of real-world networks and their intricate topology pose challenges for measuring the efficacy of cyber mimic defense. To capture and quantify defense performance within specific segments of these expansive networks, we embrace a partitioning approach that subdivides large networks into smaller regions. Metrics are then established within an objective space constructed on these smaller regions. This approach enables the establishment of several fine-grained metrics that offer a more nuanced measurement of cyber mimic defense deployed in complex networks. For example, the common-mode index is introduced to highlight shared vulnerabilities among diverse nodes, the transfer probability computes the likelihood of risk propagation among nodes, and the failure risk assesses the likelihood of cyber mimic defense technology failure within individual nodes or entire communities. Furthermore, we provide proof of the convergence of the transfer probability. A multitude of simulations are conducted to validate the reliability and applicability of the proposed metrics.

General synthetic aperture radar (SAR) image automatic target recognition (ATR) methods perform well under standard operation conditions (SOCs). However, they are not effective in extended operation conditions (EOCs). To improve the robustness of the ATR system under various EOCs, an ATR method for SAR images based on the scattering parameter Gaussian mixture model (GMM) is proposed in this paper. First, an improved active contour model (ACM) is used for target–background segmentation, which is more robust against noise than the constant false alarm rate (CFAR) method. Then, as the extracted attributed scattering center (ASC) is sensitive to noise and resolution, the GMM is constructed using the extracted ASC set. Next, the weighted Gaussian quadratic form distance (WGQFD) is adopted to measure the similarity of GMMs for the recognition task, thereby avoiding false alarms and missed alarms caused by the varying number of scattering centers. Moreover, adaptive aspect–frame division is employed to reduce the number of templates and improve recognition efficiency. Finally, based on the public measured MSTAR dataset, different EOCs are constructed under noise, resolution change, model change, depression angle change, and occlusion of different proportions. The experimental results under different EOCs demonstrate that the proposed method exhibits excellent robustness while maintaining low computation time.

Abstract Background Emerging evidence suggests that long noncoding RNAs (lncRNAs) play crucial roles in various cancers. In the present study, we aim to investigate the function and molecular mechanism of an up‐regulated and survival‐associated lncRNA, LINC00525, in lung adenocarcinoma (LUAD). Methods The expression level of LINC00525 in tissues was determined by quantitative reverse transcription polymerase chain reaction (RT‐qPCR) and in situ hybridization (ISH). The functional role of LINC00525 in LUAD was investigated using gain‐and loss‐of‐function approaches, both in vivo and in vitro. RNA pull‐down, RNA immunoprecipitation (RIP), chromatin immunoprecipitation (ChIP), triplex‐capture assay, dual‐luciferase assay, gene expression microarray, and bioinformatics analysis were used to investigate the potential underlying mechanisms involved. Results LINC00525 is highly expressed in LUAD cells and tissues. Survival analysis indicated that upregulation of LINC00525 was associated with poor prognosis in patients with LUAD patients. Knockdown of LINC00525 inhibited cell proliferation and cell cycle progression in vitro. In xenograft models, LINC00525 knockdown suppressed tumor growth and tumorigenesis of tumor‐bearing mice. Mechanistically, LINC00525 epigenetically suppressed p21 transcription by guiding Enhancer Of Zeste 2 Polycomb Repressive Complex 2 Subunit (EZH2) to the p21 promoter through an formation of RNA‐DNA triplex with the p21 promoter, leading to increased trimethylation of lysine 27 on histone 3 (H3K27me3) of the p21 promoter. In addition, LINC00525 repressed p21 expression post‐transcriptionally by enhancing p21 mRNA decay. LINC00525 promoted p21 mRNA decay by competitively binding to RNA Binding Motif Single Stranded Interacting Protein 2 (RBMS2). Conclusion Our findings demonstrate that LINC00525 promotes the progression of LUAD by reducing the transcription and stability of p21 mRNA in concert with EZH2 and RBMS2, thus suggesting that LINC00525 may be a potential therapeutic target for clinical intervention in LUAD.

Abstract Background Considering the increase in the proportion of lung adenocarcinoma (LUAD) cases among all lung cancers and its considerable contribution to cancer‐related deaths worldwide, we sought to identify novel oncogenes to provide potential targets and facilitate a better understanding of the malignant progression of LUAD. Methods The results from the screening of transcriptome and survival analyses according to the integrated Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) data were combined, and a promising risk biomarker called meiotic nuclear divisions 1 (MND1) was selectively acquired. Cell viability assays and subcutaneous xenograft models were used to validate the oncogenic role of MND1 in LUAD cell proliferation and tumor growth. A series of assays, including mass spectrometry, co‐immunoprecipitation (Co‐IP), and chromatin immunoprecipitation (ChIP), were performed to explore the underlying mechanism. Results MND1 up‐regulation was identified to be an independent risk factor for overall survival in LUAD patients evaluated by both tissue microarray staining and third party data analysis. In vivo and in vitro assays showed that MND1 promoted LUAD cell proliferation by regulating cell cycle. The results of the Co‐IP, ChIP and dual‐luciferase reporter assays validated that MND1 competitively bound to tumor suppressor Kruppel‐like factor 6 (KLF6), and thereby protecting E2F transcription factor 1 (E2F1) from KLF6‐induced transcriptional repression. Luciferase reporter and ChIP assays found that E2F1 activated MND1 transcription by binding to its promoter in a feedback manner. Conclusions MND1, KLF6, and E2F1 form a positive feedback loop to regulate cell cycle and confer DDP resistance in LUAD. MND1 is crucial for malignant progression and may be a potential therapeutic target in LUAD patients.

Abstract Background Primitive neuroectodermal tumor (PNET) is a relatively rare malignant small round cell tumor, and the occurrence of cervical PNET during pregnancy is extremely rare. Case presentation A case of pregnancy complicated by PNET at our hospital was reported. A 19-year-old pregnant woman presented to the hospital due to multiple instances of vaginal bleeding during the first and second trimesters. She was initially considered for threatened abortion but was ultimately diagnosed with cervical PNET. No standard treatment plan has been developed for pregnant women with this tumor. After completing the necessary examinations, doctors cooperated with the patient and her family to develop a surgical treatment plan. The patient recovered well after surgery, but she refused radiotherapy and chemotherapy. After nearly 3 years of follow-up visits, the patient is alive with no signs of recurrence. Conclusions PNET during pregnancy is a rare but complex condition. It is necessary to devise an individualized treatment plan according to gestational age. Timely surgical treatment can significantly prolong the survival time of patients but may also lead to fetal loss and the inability to carry a pregnancy.

In the present study, a fluid-filled RF MEMS (Radio Frequency Micro-Electro-Mechanical Systems) switch is proposed and designed. In the analysis of the operating principle of the proposed switch, air, water, glycerol and silicone oil were adopted as filling dielectric to simulate and research the influence of the insulating liquid on the drive voltage, impact velocity, response time, and switching capacity of the RF MEMS switch. The results show that by filling the switch with insulating liquid, the driving voltage can be effectively reduced, while the impact velocity of the upper plate to the lower plate is also reduced. The high dielectric constant of the filling medium leads to a lower switching capacitance ratio, which affects the performance of the switch to some extent. By comparing the threshold voltage, impact velocity, capacitance ratio, and insertion loss of the switch filled with different media with the filling media of air, water, glycerol, and silicone oil, silicone oil was finally selected as the liquid filling medium for the switch. The results show that the threshold voltage is 26.55 V after filling with silicone oil, which is 43% lower under the same air-encapsulated switching conditions. When the trigger voltage is 30.02 V, the response time is 10.12 μs and the impact speed is only 0.35 m/s. The frequency 0–20 GHz switch works well, and the insertion loss is 0.84 dB. To a certain extent, it provides a reference value for the fabrication of RF MEMS switches.

As a representative new energy source, solar energy has the advantages of easy access to resources and low pollution. However, due to the uncertainty of the external environment, photovoltaic (PV) modules that collect solar energy are often covered by foreign objects in the environment such as leaves and bird droppings, resulting in a decrease in photoelectric conversion efficiency, power losses, and even the “hot spot” phenomenon, resulting in damage to the modules. Existing methods mostly inspect foreign objects manually, which not only incurs high labor costs but also hinders real-time monitoring. To address these problems, this paper proposes an IDETR deep learning target detection model based on Deformable DETR combined with transfer learning and a convolutional block attention module, which can identify foreign object shading on the surfaces of PV modules in actual operating environments. This study contributes to the optimal operation and maintenance of PV systems. In addition, this paper collects data in the field and constructs a dataset of foreign objects of PV modules. The results show that the advanced model can significantly improve the target detection AP values.