Search Results (5,874)

Accurate assessment of N staging in patients with non-small cell lung cancer (NSCLC) is critical for the development of effective treatment plans, the optimization of therapeutic strategies, and the enhancement of patient survival rates. This study proposes a hybrid model based on 3D convolutional neural networks (CNNs) and transformers for predicting the N-staging and survival rates of NSCLC patients within the NSCLC radiogenomics and Nsclc-radiomics datasets. The model achieved accuracies of 0.805, 0.828, and 0.819 for the training, validation, and testing sets, respectively. By leveraging the strengths of CNNs in local feature extraction and the superior performance of transformers in global information modeling, the model significantly enhances predictive accuracy and efficacy. A comparative analysis with traditional CNN and transformer architectures demonstrates that the CNN-transformer hybrid model outperforms N-staging predictions. Furthermore, this study extracts the one-year survival rate as a feature and employs the Lasso–Cox model for survival predictions at various time intervals (1, 3, 5, and 7 years), with all survival prediction p-values being less than 0.05, illustrating the time-dependent nature of survival analysis. The application of time-dependent ROC curves further validates the model’s accuracy and reliability for survival predictions. Overall, this research provides innovative methodologies and new insights for the early diagnosis and prognostic evaluation of NSCLC. Full article

Corrosive environments can adversely affect the fatigue performance of bridges and other building structures. In order to determine the influence of corrosion on the fatigue failure of concrete composite girders with a corrugated web on a steel bottom plate (hereinafter referred to as CGCWSB), a scaled model test was conducted on a CGCWSB with a span of 30 m, which served as the structural prototype. Through the model test, theoretical analysis, and numerical simulation, the influence of uniform corrosion and pitting corrosion on the fatigue failure of the CGCWSB was determined, and the propagation law of pitting fatigue crack was determined. The results show that (1) the uniform corrosion caused the stress of the CGCWSB to become larger and the performance of the CGCWSB was reduced, the stress growth of the test girder after corrosion was about 10%, the corrosion rate was 9%, the pitting unevenness coefficient was 1.25, and the relative corrosion life was 26.34 years; (2) the fatigue failure of the non-corroded girder belongs to the weld fatigue failure, and the fatigue failure of the corroded girder was the coexistence of weld fatigue failure and pitting fatigue failure; (3) uniform corrosion did not create a new fatigue source, but it did result in the test girder’s fatigue failure ahead of time. Pitting corrosion did, however, create a new fatigue source; (4) an exponential correlation was present between the propagation length of a pitting crack and the number of equal load cycles. The ultimate failure mode of a pitting fatigue crack was when the crack length reached the thickness of the plate and the component was torn and destroyed; (5) following corrosion, the fatigue life of the test girder was found to be reduced by 10.65%, which suggests that salt corrosion had a significant impact on the fatigue life of the composite girder. This research work can provide a reference for the design and promotion of the use of the CGCWSB. Full article

We aimed to investigate the fluid–solid–ice coupling mechanism as structures break through ice into water. Using LS–DYNA finite element software, a numerical simulation method is established, based on the ALE flow–solid coupling method, and the penalty function contact algorithm, which describes the structure–ice–water coupling interaction. The Eulerian algorithm is used to describe the air and water domains, while the Lagrange method is applied to the wedge and ice structure. The mechanical properties of ice are characterized using the elastic–plastic failure strain model. The feasibility of simulating the entry of structures into water via the ALE method is demonstrated by comparing the experimental and simulation results of wedges entering into water. The applicability of the ice material model in simulating collision–induced breakup is verified by comparing a simulation of a rigid plate hitting a spherical head of ice, with results from the ISO standard. The effects of water during icebreaking are assessed by simulating a wedge breaking through ice into water, as well as through ice without water. Additionally, the ice breakup and motion response of the wedge under different working conditions are compared by varying the wedge mass and icebreaking speed. Full article

The integrated stress response, especially stress granules (SGs), contributes to host immunity. Typical G3BP1⁺ stress granules (tSGs) are usually formed after virus infection to restrain viral replication and stimulate innate immunity. Recently, several SG-like foci or atypical SGs (aSGs) with proviral function have been found during viral infection. We have shown that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N) protein induces atypical N⁺/G3BP1⁺ foci (N⁺foci), leading to the inhibition of host immunity and facilitation of viral infection. However, the precise mechanism has not been well clarified yet. In this study, we showed that the SARS-CoV-2 N (SARS2-N) protein inhibits dsRNA-induced growth arrest and DNA damage-inducible 34 (GADD34) expression. Mechanistically, the SARS2-N protein promotes the interaction between GADD34 mRNA and G3BP1, sequestering GADD34 mRNA into the N⁺foci. Importantly, we found that GADD34 participates in IRF3 nuclear translocation through its KVRF motif and promotes the transcription of downstream interferon genes. The suppression of GADD34 expression by the SARS2-N protein impairs the nuclear localization of IRF3 and compromises the host’s innate immune response, which facilitates viral replication. Taking these findings together, our study revealed a novel mechanism by which the SARS2-N protein antagonized the GADD34-mediated innate immune pathway via induction of N⁺foci. We think this is a critical strategy for viral pathogenesis and has potential therapeutic implications. Full article

Hysterothylacium aduncum is one of six pathogens responsible for human anisakiasis. Infection with H. aduncum can cause acute abdominal symptoms and allergic reactions and is prone to misdiagnosis in clinical practice. This study aims to enhance the efficiency and accuracy of detecting H. aduncum in food ingredients. We targeted the internal transcribed spacer 1 (ITS 1) regions of Anisakis to develop a visual screening method for detecting H. aduncum using recombinase polymerase amplification (RPA) combined with the CRISPR/Cas12a system. By comparing the ITS 1 region sequences of eight nematode species, we designed specific primers and CRISPR RNA (crRNA). The specificity of RPA primers was screened and evaluated, and the CRISPR system was optimized. We assessed its specificity and sensitivity and performed testing on commercial samples. The results indicated that the alternative primer ADU 1 was the most effective. The final optimized concentrations were 250 nM for Cas12a, 500 nM for crRNA, and 500 nM for ssDNA. The complete test procedure was achievable within 45 min at 37 °C, with a limit of detection (LOD) of 1.27 pg/μL. The amplified product could be directly observed using a fluorescence microscope or ultraviolet lamp. Detection results for 15 Anisakis samples were entirely consistent with those obtained via Sanger sequencing, demonstrating the higher efficacy of this method for detecting and identifying H. aduncum. This visual detection method, characterized by simple operation, visual results, high sensitivity, and specificity, meets the requirements for food safety testing and enhances monitoring efficiency. Full article

Soil salinization is currently one of the main abiotic stresses that restrict plant growth. Plant endophytic bacteria can alleviate abiotic stress. The aim of the current study was to isolate, characterize, and assess the plant growth-promoting and saline and alkaline stress-alleviating traits of Peribacillus simplex M1 (P. simplex M1) isolates from maize. One endophytic bacterial isolate, named P. simplex M1, was selected from the roots of maize grown in saline–alkali soil. The P. simplex M1 genome sequence analysis of the bacteria with a length of 5.8 Mbp includes about 700 genes that promote growth and 16 antioxidant activity genes that alleviate saline and alkaline stress. P. simplex M1 can grow below 400 mM NaHCO₃ on the LB culture medium; The isolate displayed multiple plant growth-stimulating features, such as nitrogen fixation, produced indole-3-acetic acid (IAA), and siderophore production. This isolate had a positive effect on the resistance to salt of maize in addition to the growth. P. simplex M1 significantly promoted seed germination by enhancing seed vigor in maize whether under normal growth or NaHCO₃ stress conditions. The seeds with NaHCO₃ treatment exhibited higher reactive oxygen species (ROS) levels than the maize in P. simplex M1 inoculant on maize. P. simplex M1 can colonize the roots of maize. The P. simplex M1 inoculant plant increased chlorophyll in leaves, stimulated root and leaf growth, increased the number of lateral roots and root dry weight, increased the length and width of the blades, and dry weight of the blades. The application of inoculants can significantly reduce the content of malondialdehyde (MDA) and increase the activity of plant antioxidant enzymes (Catalase (CAT), Superoxide Dismutase (SOD), and Peroxidase (POD)), which may thereby improve maize resistance to saline and alkaline stress. Conclusion: P. simplex M1 isolate belongs to plant growth-promoting bacteria by having high nitrogen concentration, indoleacetic acid (IAA), and siderophore, and reducing the content of ROS through the antioxidant system to alleviate salt alkali stress. This study presents the potential application of P. simplex M1 as a biological inoculant to promote plant growth and mitigate the saline and alkaline effects of maize and other crops. Full article

The device anomaly detection in an industrial control system (ICS) is essential for identifying devices with abnormal operating states or unauthorized access, aiming to protect the ICS from unauthorized access, malware, operational errors, and hardware failures. This paper addresses the issues of numerous manufacturers, complex models, and incomplete information by proposing a fingerprint extraction method based on ICS protocol communication models, applied to an anomaly detection model fine-tuned using the Llama3 model. By considering both hardware and software characteristics of ICS devices, the paper designs a fingerprint vector that can be extracted in both active and passive network communication environments. Experimental data include real ICS network traffic from an oilfield station and extensive ICS device traffic data obtained through network scanning tools. The results demonstrate that the proposed method outperforms existing methods in terms of accuracy and applicability, especially in differentiating devices from various manufacturers and models, significantly enhancing anomaly detection performance. The innovation lies in using large language models for feature extraction and the anomaly detection of device fingerprints, eliminating dependency on specific ICS scenarios and protocols while substantially improving detection accuracy and applicability. Full article

This study selected two sweet potato varieties as research subjects and conducted a field experiment using a two-factor design with two potassium (K) levels (K0 and K1) and five nitrogen (N) levels (N0–N4). The physiological changes in sweet potato leaves under different N and K treatments were measured, and nutrients such as the soluble sugar, protein, and starch content of sweet potato roots were analyzed. The results indicate that the activity of glutamine synthetase (GS) and the soluble protein content in sweet potato leaves increase first and then decrease with increasing N application, while K application can significantly increase the activity of GS and the soluble protein content. The N metabolic capacity of leaves is strongest when the fertilizer ratio is K1N2. The SPAD value of sweet potato leaves increases with increasing N application. The net photosynthetic rate, stomatal conductance, and intercellular CO₂ concentration first increase and then decrease with increasing N application. K fertilizer has a significant effect on these parameters. As the N application rate increases, the starch and protein content in the tubers increase, while the soluble sugar content decreases. However, the number of tubers per plant, fresh weight of the tubers, and dry weight of the tubers increase initially and then decrease, while the vine length continuously increases. The application of K fertilizer can significantly increase the number of tubers per plant and stem thickness of sweet potato. In conclusion, the appropriate N–K combined application can promote N metabolism, enhance the photosynthetic capacity of sweet potato, increase yield, and improve quality. Full article

Chemokines are integral components of the immune system and deeply involved in the pathogenesis and progression of inflammatory bowel disease (IBD) and colorectal cancer (CRC). Although a considerable amount of transcriptome data has been accumulated on these diseases, most of them are limited to a specific stage of the disease. The purpose of this study is to visually demonstrate the dynamic changes in chemokines across various stages of bowel diseases by integrating relevant datasets. Integrating the existing datasets for IBD and CRC, we compare the expression changes of chemokines across different pathological stages. This study collected 11 clinical databases from various medical centers around the world. Patients: Data of patient tissue types were classified into IBD, colorectal adenoma, primary carcinoma, metastasis, and healthy control according to the publisher’s annotation. The expression changes in chemokines in various pathological stages are statistically analyzed. The chemokines were clustered by different expression patterns. The chemokine family was clustered into four distinct expression patterns, which correspond to varying expression changes in different stages of colitis and tumor development. Certain chemokines and receptors associated with inflammation and tumorigenesis have been identified. Furthermore, it was confirmed that the 2,4,6-trinitrobenzenesulfonic acid (TNBS)-induced colitis model and the azoxymethane (AOM)/ dextran sulfate sodium (DSS)-induced colon cancer model shows stronger correlations with the clinical data in terms of chemokine expression levels. This study paints a panoramic picture of the expression profiles of chemokine families at multiple stages from IBD to advanced colon cancer, facilitating a comprehensive understanding of the regulation patterns of chemokines and guiding the direction of drug development. This study provides researchers with a clear atlas of chemokine expression in the pathological processes of inflammatory bowel disease and colon cancer. Full article

Dissipative particle dynamics (DPD) simulations is used to study the effect of A_m/2B_mA_m/2 and H-shaped (A_m/4)₂B_m(A_m/4)₂ block copolymers on the interfacial properties of ternary blends. Our simulations show the following: (i) The capacity of block copolymers to diminish interfacial tension is closely linked to their compositions. With identical molecular weights and concentrations, H-shaped block copolymers outperform triblock copolymers in mitigating interfacial tension. (ii) The interfacial tension within the blends correlates positively with the escalation in H-shaped block copolymer molecular weight. This correlation suggests that H-shaped block copolymers featuring a low molecular weight demonstrate superior efficacy as compatibilizers when contrasted with those possessing a high molecular weight. (iii) Enhancing the concentration of H-shaped block copolymers fosters their accumulation at the interface, leading to a reduction in correlations between immiscible homopolymers and a consequent decrease in interfacial tension. (iv) As the length of the homopolymer chains increases, there is a concurrent elevation in interfacial tension, suggesting that H-shaped block copolymers perform more effectively as compatibilizers in blends characterized by shorter homopolymer chain lengths. These findings elucidate the associations between the efficacy of H-shaped block copolymer compatibilizers and their specific molecular characteristics. Full article

In the era of the fourth industrial revolution, competition among IT industries is becoming increasingly fierce. If a company is weak in its competitive advantage, it can have a huge negative impact on its organizational sustainability and ultimately lead to organizational failure. In such a research background, we highlighted that employees’ innovative performance via creativity acts as an alternative lubricant to increase the sustainable competitive advantage and promote overall organizational sustainability. In particular, employees’ innovative performance has a great relationship with organizational culture and types of leadership. Hence, we focused on exploring the ways in which visionary leadership increases employees’ innovative performance, presenting and verifying a moderated mediation research model related to the innovative performance. To verify our research model, this study conducted a survey of 303 employees from the information technology (IT) industry of SMEs in China. According to the results, visionary leadership was found to have a positive influence on both psychological empowerment and employees’ innovative performance. In addition, psychological empowerment partially mediated the impact of visionary leadership on the innovation performance. Finally, the organizational learning culture moderated the effects of psychological empowerment and the innovation performance. Overall, this study contributes to revealing the process that leads to employees’ innovative performance and contributes to expanding the research field by verifying the moderated mediation model for a sustainable competitive advantage and organizational sustainability in IT Industry 4.0 for SMEs. Full article

The Asian honey bee (Apis cerana) plays a crucial role in providing abundant bee products and in maintaining ecological balance. Despite the availability of the genomic sequence of the Asian honey bee, its transcriptomic information remains largely incomplete. To address this issue, here we constructed three pooled RNA samples from the queen, drone, and worker bees of A. cerana and performed full-length RNA sequencing using Nanopore single-molecule sequencing technology. Ultimately, we obtained 160,811 full-length transcript sequences from 19,859 genes, with 141,189 being novel transcripts, of which 130,367 were functionally annotated. We detected 520, 324, and 1823 specifically expressed transcripts in the queen, worker, and drone bees, respectively. Furthermore, we identified 38,799 alternative splicing (AS) events from 5710 genes, 44,243 alternative polyadenylation (APA) sites from 1649 gene loci, 88,187 simple sequence repeats (SSRs), and 17,387 long noncoding RNAs (lncRNAs). Leveraging these transcripts as references, we identified 6672, 7795, and 6804 differentially expressed transcripts (DETs) in comparisons of queen ovaries vs drone testes, worker ovaries vs drone testes, and worker ovaries vs queen ovaries, respectively. Our research results provide a comprehensive set of reference transcript datasets for Apis cerana, offering important sequence information for further exploration of its gene functions. Full article

In this study, the effects of variations in the height ($h$) and bottom radius ($r$) of black silicon microstructures on their absorptance and photoelectric response efficiency were analyzed. By using the relation $\cot {\displaystyle \frac{\theta }{2}}={\displaystyle \frac{h}{r}}$ to combine the parameters, it was found that changes in morphology affected the absorptance of black silicon microstructures, with $h$ being directly proportional to the absorptance, while $r$ was inversely proportional. A positive correlation was observed between $\cot {\displaystyle \frac{\theta }{2}}$ and absorptance. However, the correlation between $\cot {\displaystyle \frac{\theta }{2}}$ and photoelectric response efficiency was not significant. Through Raman spectroscopy analysis of the samples, it was concluded that as the laser ablation energy density increased, more lattice defects were introduced, weakening the charge carrier transport efficiency. This study further elucidated the mechanism by which microstructural changes impacted the absorptance and energy density of black silicon, providing valuable insights for optimizing its energy density. Full article

Jointly building the Economic Corridor of the Eurasia Continent (ECEC), which is one of the most important parts of the Silk Road Economic Belt, is a pivotal initiative for fostering regional development. Forests, which serve as a green foundation of economic resilience, underpin this effort. However, there is an imbalance in ecological status due to differences in natural resources and the social economy along the economic corridor. This imbalance has led to alterations in landscapes, yet the specific changes and their underlying relationships are still much less understood. Here, we quantitatively detected changes in the forest landscape and its ecological efforts over the ECEC via widespread, satellite-based and long-term land cover maps released by the European Space Agency (ESA) Climate Change Initiative (CCI). Specifically, the coupling between changes in forest coverage and landscape patterns, e.g., diversity, was further examined. The results revealed that forest coverage fluctuated and declined over the ECEC from 1992 to 2018, with an overall reduction of approximately 9784.8 km² (i.e., 0.25%). Conversions between forests and other land cover types were widely observed. The main displacements occurred between forests and grasslands/croplands (approximately 48%/21%). Moreover, the landscape diversity in the study area increased, as measured by the effective diversity index (EDI), during the study period, despite obvious spatial heterogeneity. Notably, this pattern of landscape diversity was strongly associated with forest displacement and local urban development through coupling analysis, consequently indicating increasing fragmentation rather than biological diversity. This study highlights the coupled relationship between quantitative and qualitative changes in landscapes, facilitating our understanding of environmental protection and policy management. Full article

Robust water management is in intense demand in many water scarcity areas, such as arid and semi-arid regions in the world. As part of the regional water management strategy, rain enhancement is vital to replenish groundwater reservoirs, and the key challenge is how to assess its effectiveness. Some recent weather modification experiments attained cloud seeding effect through advanced in situ measurement coupled with accurate numerical simulation. However, there is still a lack of an objective and scientific approach to quantitatively evaluate the rain enhancement effect, especially for many non-randomized operational cloud seeding activities in China. In this study, we proposed a composite evaluation approach by analyzing two operational aircraft cloud seeding cases in stratus clouds in Shaanxi, China. By calculating the aircraft cloud seeding agent plumes, the target areas (as well as the control areas) of cloud seeding were dynamically and roughly determined. Physical properties, such as radar reflectivity and precipitation, were individually quantified in these areas. The cloud seeding effect was then evaluated by calculating the difference in parameter variation between target and control areas. This approach can be applied to qualitative analysis in a single aircraft cloud seeding operation and can also provide quantitative statistical results from multiple cloud seeding cases. We found that the average precipitation enhancement percentage of 18 operational aircraft cloud seeding cases is ~4.84%. Note that the homogeneity hypothesis of the seeding cloud, the error in the calculation of the target area, and the selection of control areas are the major uncertainties likely in the evaluation of the cloud seeding effect by this approach. Full article