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Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related morbidity and mortality globally. While DDX52, an ATP-dependent RNA helicase, plays a role in several biological processes, its specific involvement in LUAD is yet to be elucidated. We utilized ROC curves to determine DDX52’s predictive potential for LUAD. Kaplan–Meier survival curves, along with univariate and multivariate Cox analyses, assessed the prognostic implications of DDX52 in LUAD. We constructed nomogram models to further delineate DDX52’s influence on prognosis, employed GSEA for functional analysis, and used qRT-PCR to examine DDX52 expression in LUAD tissues. DDX52 expression was notably higher in LUAD tissues, suggesting its potential as a negative prognostic marker. We observed a direct relationship between DDX52 expression and advanced T and N stages, as well as higher grading and staging in LUAD patients. Cox analyses further underscored DDX52’s role as an independent prognostic determinant for LUAD. GSEA insights indicated DDX52’s influence on LUAD progression via multiple signaling pathways. Our nomogram, founded on DDX52 expression, effectively projected LUAD patient survival, as validated by calibration curves. Elevated DDX52 expression in LUAD tissues signals its potential as a poor prognostic marker. Our findings emphasize DDX52’s role not only as an independent prognostic factor for LUAD but also as a significant influencer in its progression through diverse signaling pathways. The constructed nomogram also underscores the feasibility of predicting LUAD patient survival based on DDX52 expression.

As an efficient drug carrier, exosome has been widely used in the delivery of genetic drugs, chemotherapeutic drugs, and anti-inflammatory drugs. As a genetic drug carrier, exosomes are beneficial to improve transfection efficiency and weaken side effects at the same time. Here, we use genetic engineering to prepare engineered exosomes (miR-449a Exo) that can actively deliver miR-449a. It was verified that miR-449a Exo had good homology targeting capacity and was specifically taken up by A549 cells. Moreover, miR-449a Exo had high delivery efficiency of miR-449a in vitro and in vivo. We demonstrated that miR-449a Exo effectively inhibited the proliferation of A549 cells and promoted their apoptosis. In addition, miR-449a Exo was found to control the progression of mouse tumors and prolong their survival in vivo. Our research provides new ideas for exosomes to efficiently and actively load gene drugs, and finds promising methods for the treatment of non-small cell lung cancer.

Background In recent years, the Chinese government has been trying to improve informal-sector workers’ and farmers’ access to healthcare and reduce their financial burdens by introducing a plan of cost-sharing reduction, but the effect on outpatient care utilization remains unknown. Furthermore, scarce evidence has been provided to help understand the impact of cost-sharing reduction on healthcare use in low- and middle-income countries. The policy change of the coinsurance reduction for outpatient care from 75 to 55% for the enrollees of the Urban and Rural Residents Basic Medical Insurance in Taizhou, China in 2015 provides us a good quasi-experimental setting to explore such an impact. Methods We do a quasi-experimental study to explore the impact of coinsurance reduction on outpatient care use among the informal-sector workers and farmers aged 45 and above by estimating a fixed-effects negative binomial model with the difference-in-differences approach and the matching method. Heterogeneous effects in primary care clinics and for the older people aged 60 and above are also examined. Our data is from the China Health and Retirement Longitudinal Study 2013 and 2015. Results We find neither statistically significant impact of coinsurance reduction on outpatient care utilization in all health facilities for informal-sector workers and farmers aged 45 and above, nor heterogeneous effects in primary care clinics and for older people aged 60 and above. Conclusions We conclude that the coinsurance reduction cannot effectively improve the informal-sector workers’ and farmers’ utilization of healthcare if the cost-sharing undertaken by patients remains high even after the reduction. Besides, improving healthcare quality in primary care clinics may play a more important role than merely introducing a cost-sharing reduction plan in enhancing the role of primary care clinics as gatekeepers. We propose that only a substantial coinsurance reduction may help influence the utilization of healthcare for informal-sector workers and farmers, and enhancing the healthcare quality in primary care clinics should be given priority in low- and middle-income countries.

For bone defect repair under co-morbidity conditions, the use of biomaterials that can be non-invasively regulated is highly desirable to avoid further complications and to promote osteogenesis. However, it remains a formidable challenge in clinical applications to achieve efficient osteogenesis with stimuli-responsive materials. Here, we develop polarized CoFe 2 O 4 @BaTiO 3 /poly(vinylidene fluoridetrifluoroethylene) [P(VDF-TrFE)] core-shell particle-incorporated composite membranes with high magnetoelectric conversion efficiency for activating bone regeneration. An external magnetic field force conduct on the CoFe 2 O 4 core can increase charge density on the BaTiO 3 shell and strengthens the β-phase transition in the P(VDF-TrFE) matrix. This energy conversion increases the membrane surface potential, which hence activates osteogenesis. Skull defect experiments on male rats showed that repeated magnetic field applications on the membranes enhanced bone defect repair, even when osteogenesis repression is elicited by dexamethasone or lipopolysaccharide-induced inflammation. This study provides a strategy of utilizing stimuli-responsive magnetoelectric membranes to efficiently activate osteogenesis in situ. Biomaterials that can be non-invasively activated to promote bone growth would be useful tools to repair bone defects in patients with comorbidities like inflammation or impaired osteogenesis. Here, the authors develop a composite membrane that can be stimulated by an external magnetic field and use it to correct skull defects in rats treated to reflect such comorbidities.

The current limited spaceborne hardware resources and the diversity of ship target scales in SAR images have led to the requirement of on-orbit real-time detection of ship targets in spaceborne synthetic aperture radar (SAR) images. In this paper, we propose a lightweight ship detection network based on the YOLOv4-LITE model. In order to facilitate the network migration to the satellite, the method uses MobileNetv2 as the backbone feature extraction network of the model. To solve the problem of ship target scale diversity in SAR images, an improved receptive field block (RFB) structure is introduced, enhancing the feature extraction ability of the network, and improving the accuracy of multi-scale ship target detection. A sliding window block method is designed to detect the whole SAR image, which can solve the problem of image input. Experiments on the SAR ship dataset SSDD show that the detection speed of the improved lightweight network could reach up to 47.16 FPS, with the mean average precision (mAP) of 95.03%, and the model size is only 49.34 M, which demonstrates that the proposed network can accurately and quickly detect ship targets. The proposed network model can provide a reference for constructing a spaceborne real-time lightweight ship detection network, which can balance the detection accuracy and speed of the network.

The scientific evaluation of passenger satisfaction for public transport is helpful to enhance the attraction of public transport. To improve the accuracy of passenger satisfaction evaluation for public transport and the scientificity and objectivity of the index weighting, combining the characteristics of analytic hierarchy process (AHP), entropy weight method (EWM) and fuzzy comprehensive evaluation(FCE) method, the passenger satisfaction evaluation system for Ningbo's urban public transportation was built. The paper analyzed 5046 questionnaires on conventional bus transit and 1682 questionnaires on rail transit in Ningbo city, Passenger satisfaction for Ningbo city's public transport was evaluated comprehensively, and the evaluation results showed that the overall passenger satisfaction of the public transport in Ningbo was 91.2 in 2019, The case study shows that the application of the AHP-EWM-FCE model on the multi-mode public transport system can objectively quantify passengers' feelings about urban public transport service, and thus provide a theoretical basis for the improvement of passenger satisfaction in Ningbo.

Synthetic aperture radar (SAR) imaging is used to identify ships, which is a vital task in the maritime industry for managing maritime fisheries, marine transit, and rescue operations. However, some problems, like complex background interferences, various size ship feature variations, and indistinct tiny ship characteristics, continue to be challenges that tend to defy accuracy improvements in SAR ship detection. This research study for multiscale SAR ships detection has developed an upgraded YOLOv5s technique to address these issues. Using the C3 and FPN + PAN structures and attention mechanism, the generic YOLOv5 model has been enhanced in the backbone and neck section to achieve high identification rates. The SAR ship detection datasets and AirSARship datasets, along with two SAR large scene images acquired from the Chinese GF-3 satellite, are utilized to determine the experimental results. This model’s applicability is assessed using a variety of validation metrics, including accuracy, different training and test sets, and TF values, as well as comparisons with other cutting-edge classification models (ARPN, DAPN, Quad-FPN, HR-SDNet, Grid R-CNN, Cascade R-CNN, Multi-Stage YOLOv4-LITE, EfficientDet, Free-Anchor, Lite-Yolov5). The performance values demonstrate that the suggested model performed superior to the benchmark model used in this study, with higher identification rates. Additionally, these excellent identification rates demonstrate the recommended model’s applicability for maritime surveillance.

Chlorophyll-a (Chl-a) concentration monitoring is very important for managing water resources and ensuring the stability of marine ecosystems. Due to their high operating efficiency and high prediction accuracy, backpropagation (BP) neural networks are widely used in Chl-a concentration inversion. However, BP neural networks tend to become stuck in local optima, and their prediction accuracy fluctuates significantly, thus posing restrictions to their accuracy and stability in the inversion process. Studies have found that metaheuristic optimization algorithms can significantly improve these shortcomings by optimizing the initial parameters (weights and biases) of BP neural networks. In this paper, the adaptive nonlinear weight coefficient, the path search strategy “Levy flight” and the dynamic crossover mechanism are introduced to optimize the three main steps of the Artificial Ecosystem Optimization (AEO) algorithm to overcome the algorithm’s limitation in solving complex problems, improve its global search capability, and thereby improve its performance in optimizing BP neural networks. Relying on Google Earth Engine and Google Colaboratory (Colab), a model for the inversion of Chl-a concentration in the coastal waters of Hong Kong was built to verify the performance of the improved AEO algorithm in optimizing BP neural networks, and the improved AEO algorithm proposed herein was compared with 17 different metaheuristic optimization algorithms. The results show that the Chl-a concentration inversion model based on a BP neural network optimized using the improved AEO algorithm is significantly superior to other models in terms of prediction accuracy and stability, and the results obtained via the model through inversion with respect to Chl-a concentration in the coastal waters of Hong Kong during heavy precipitation events and red tides are highly consistent with the measured values of Chl-a concentration in both time and space domains. These conclusions can provide a new method for Chl-a concentration monitoring and water quality management for coastal waters.

Objective This study aims to assess the prognostic and diagnostic value of inflammatory indexes related to gestational diabetes mellitus (GDM) from the second trimester to the third trimester of pregnancy. Materials and methods In this study, we randomly selected 65 pregnant women diagnosed with GDM at our hospital from December 2022 to June 2023 to form the GDM group ( n  = 65). Additionally, 65 pregnant women at the same gestational weeks without GDM were selected as the Normal group ( n  = 65). We collected gestational information and serum samples at 24 and 36 weeks of gestation from the participants. The levels of NLRP3, IL-1Ra, and TBP-2 were determined using enzyme-linked immunosorbent assay (ELISA) to explore their changes during pregnancy. Further, this study analyzed the changes in the levels of NLRP3, IL-1Ra, and TBP-2 at 24 and 36 weeks of gestation in GDM patients and their correlation with gestational diabetes mellitus. Results The study showed that pre-pregnancy body mass index (BMI), neonatal weight, gestational hypertension, and macrosomia are significantly associated with the occurrence of GDM ( P  < 0.05). Statistical analysis comparing the normal and GDM groups found no significant changes in the levels of NLRP3, IL-1Ra, and TBP-2 with the progression of gestation in the normal group. In contrast, in the GDM group, the levels of IL-1Ra in serum samples at 24 and 36 weeks were significantly increased ( P  < 0.05) while the levels of NLRP3 and TBP-2 were significantly reduced ( P  < 0.05). At 36 weeks, there was a positive correlation between the levels of NLRP3, IL-1Ra, and TBP-2. Compared to the normal group, the overall levels of NLRP3, IL-1Ra, and TBP-2 in the GDM group were lower ( P  < 0.05) and the weight of the newborns was significantly correlated with these three indicators ( P  < 0.05), specifically newborn weight increased with the levels of NLRP3 and TBP-2 but decreased with the increase of IL-1Ra ( P  < 0.05). Multifactorial logistic regression analysis further revealed that NLRP3 is an independent factor influencing GDM ( P  < 0.05). ROC curve analysis of the NLRP3 level at 24 weeks of gestation found that NLRP3 has a good value in predicting GDM (AUC = 0.720, 95%CI 0.630–0.809, P  < 0.001) and the combined prediction of NLRP3, IL-1Ra, and TBP-2 also showed a good predictive value for GDM. Conclusion The changes in NLRP3, IL-1Ra, and TBP-2 persisted throughout the 24 to 36 weeks of gestation, playing an important role in predicting the occurrence of GDM and the weight of the newborn.

Various nanoparticles have been applied as chemical demulsifiers to separate the crude-oil-in-water emulsion in the petroleum industry, including graphene oxide (GO). In this study, the Janus amphiphilic graphene oxide (JGO) was prepared by asymmetrical chemical modification on one side of the GO surface with n-octylamine. The JGO structure was verified by Fourier-transform infrared spectra (FTIR), transmission electron microscopy (TEM), and contact angle measurements. Compared with GO, JGO showed a superior ability to break the heavy oil-in-water emulsion with a demulsification efficiency reaching up to 98.25% at the optimal concentration (40 mg/L). The effects of pH and temperature on the JGO’s demulsification efficiency were also investigated. Based on the results of interfacial dilatational rheology measurement and molecular dynamic simulation, it was speculated that the intensive interaction between JGO and asphaltenes should be responsible for the excellent demulsification performance of JGO. This work not only provided a potential high-performance demulsifier for the separation of crude-oil-in-water emulsion, but also proposed novel insights to the mechanism of GO-based demulsifiers.