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Agricultural robots and unmanned farmland management require real-time and precise parsing of crop leaves at the edge to support variable application of pesticides, seedling condition monitoring, and phenotypic analysis. However, the field environment features drastic changes in light, leaf occlusion, and interference from background weeds, which can cause semantic fragmentation and boundary artifacts in lightweight models. This paper presents ES2-LeafSeg, a lightweight framework for leaf semantic segmentation tailored for edge deployment. The method employs EfficientNetV2 as the backbone encoder and introduces the State Space Semantic Enhancement Module (S2FEM) on skip connection features, modeling long-range dependencies and suppressing local texture noise through SSM pooling in row and column directions. Meanwhile, a cross-scale decoder (CSD) and a global context transformation (GCT) are designed to achieve multi-scale semantic fusion and boundary refinement. On the three-class segmentation task of the SoyCotton dataset, ES2-LeafSeg achieved mIoU of 0.817, mDice of 0.869, Fβw of 0.925, and MAE of 0.011, outperforming multiple classic and recent baselines while maintaining 23.67 M parameters and 49.62 FPS. Ablation experiments further verified the complementary contributions of S2FEM and GCT to regional consistency and boundary quality.

In this paper, we present a multi-parallel restricted additive Schwarz (MP-RAS) preconditioner construction method for cardiac electrophysiology simulation. This method is designed to address the need for solving large-scale linear systems in realistic cardiac electrophysiology simulations and can provide a more efficient computational tool for patient-specific electrical propagation modeling, arrhythmia studies, and the evaluation of ablation strategies. The proposed preconditioner is suitable for the finite element simulation of the anisotropic cardiac monodomain model. In particular, we construct the subdomains based on Morton code sorting, build submatrices by indices and decompose the formula for parallel computing. Given that the computing of each subdomain is relatively independent, the iteration can be extended to N-parallel. Numerical experiments indicate that for matrices of the same size and under the same number of partitions, Morton code sorting is at least 105 times faster than METIS, while the memory usages are reduced by 12∼32%. The iteration number is reduced by approximately two times compared with the Jacobi and block Jacobi preconditioned conjugate gradient (PCG) method. Comparative experiments with other solvers further demonstrate that the MP-RAS solver is highly efficient for solving this parabolic partial differential equation and have strong parallel scalability.

Hemorrhagic stroke (HS) is usually treated under microscopy, but recently, an increasing number of cases have been treated under neuroendoscopy. The objective of this study was to explore the feasibility and efficacy of a transcranial neuroendoscopic approach for HS. Based on etiology and clinical features, 203 HS patients were classified into two groups, with 100 patients in the primary HS (PHS) group and 103 patients in the secondary HS (SHS) group. All patients were treated either by full neuroendoscopy (FNE) or by neuroendoscopy combined with microsurgery (ECM). Outcomes were assessed according to the Glasgow Coma Scale (GCS) at discharge, and the rate of good plus excellent results was recorded as the GE rate to assess the treatment effect. All 203 patients underwent surgery successfully, with 165 patients who underwent FNE and 38 patients who underwent ECM. No patients died within 3 days after surgery, and the surgery-related mortality rate was 0%, but a total of 4 patients died by discharge, and the overall mortality rate was 1.97%. A total of 133 patients showed an excellent result and 16 showed a good result, for a total GE rate of 73%. Neuroendoscopy can provide excellent illumination, clear visualization, and multiangle views in HS. The transcranial neuroendoscopic approach is feasible and safe for both PHS and SHS and is very effective for hematoma evacuation. However, some aneurysms and most arteriovenous malformations and arteriovenous fistulas require ECM.

Plenty of immune cells infiltrate into the tumor microenvironment (TME) during tumor progression, in which myeloid-derived suppressor cells (MDSCs) represent a heterogeneous population of immature myeloid cells with immunosuppressive activity. Tumor cells and stromal cells facilitate the activation and expansion of MDSCs in TME via intercellular communication, and expanded MDSCs suppress anti-tumor immune responses through direct and indirect mechanisms. Currently, exosomes, which are a kind of extracellular vesicles (EVs) that can convey functional components, are demonstrated to participate in the local and distal intercellular communication between cells. Numerous studies have supposed that tumor-derived exosomes (TEXs), whose assembly and release can be modulated by TME, are capable of modulating the cell biology of MDSCs, including facilitating their activation, promoting the expansion, and enhancing the immunosuppressive function. Therefore, in this review, we mainly focus on the role of TEXs in the cell-cell communication between tumor cells and MDSCs, and discuss their clinical applications.

Objectives: As a novel member of the interleukin(IL)-1 family, IL-38 has shown therapeutic effects in various chronic inflammatory diseases. However, its role and underlying mechanisms in cardiovascular diseases, particularly atherosclerosis, remain unclear. This study aimed to explore the effects of IL-38 on atherosclerosis progression and its mechanisms in regulating macrophage function during the atherosclerotic process. Methods: To evaluate the therapeutic potential of IL-38 in atherosclerosis, we performed histopathological examinations and biochemical analyses in vivo. In vitro, we used primary bone marrow-derived macrophages (BMDMs) stimulated with oxidized low-density lipoprotein (ox-LDL) to assess the anti-inflammatory effects of IL-38 and quantified its impact on ox-LDL-induced macrophage polarization. To further elucidate the specific mechanisms by which IL-38 regulates macrophage function, we conducted mRNA sequencing and validated downstream regulatory signaling pathways. Results: IL-38 exhibited therapeutic potential in atherosclerosis by reducing atherosclerotic plaque formation, modulating plaque composition, suppressing the production of proinflammatory cytokines within plaques, and potentially regulating macrophage cholesterol metabolism. Moreover, IL-38 exerted significant anti-inflammatory effects on macrophages both in vivo and in vitro. Notably, it inhibited the polarization of macrophages toward the proinflammatory M1-like phenotype in both settings. Additionally, IL-38 impeded the phosphorylation and nuclear translocation of p65 in BMDMs and reduced ox-LDL-induced macrophage apoptosis. Conclusion: IL-38 holds therapeutic potential for atherosclerosis, as it alleviates disease progression, inhibits macrophage polarization toward the M1-like phenotype, suppresses nuclear factor-κB (NF-κB) signaling activation, and reduces macrophage apoptosis. This study provides new insights into the anti-inflammatory mechanisms by which IL-38 mitigates atherosclerosis.

Flame residence time (FRT) is an important indicator of flaming duration and is closely related to local heat release and associated ecological effects. However, the intrinsic mechanisms through which fuel bed structure affects FRT remains insufficiently understood. Clarifying how fuel bed structure affects FRT under flat, wind-free conditions is important for prescribed burning and ecological restoration. This study investigated surface fuels from typical forest types in southwestern China through controlled laboratory experiments conducted under flat, wind-free conditions, with moisture content, loading, thickness, and bulk density systematically varied. The driving mechanisms of fuel bed structural characteristics on FRT were systematically analyzed. Coniferous forests and moso bamboo had significantly lower FRT than broadleaved forests. Moisture content was the most influential factor, followed by thickness and bulk density, whereas loading had a relatively limited effect. Prediction models developed using machine learning methods significantly outperformed traditional regression approaches. Fuel bed structure is a critical factor controlling FRT. The high-accuracy prediction models established in this study enhance the mechanistic understanding of FRT. The findings provide a theoretical basis and practical support for prescribed burning and fire behavior modeling and may contribute to improved forest fire management.

Accurate apple origin identification and non-destructive internal quality evaluation are important for fruit traceability, quality grading, and post-harvest management. Unlike previous studies mainly focusing on origin classification, this study established a dual-task near-infrared spectroscopy framework integrating geographical origin classification and soluble solid content (SSC, °Brix) prediction for Fuji apples. Samples were collected from three representative production regions in China: Alar in Xinjiang, Yantai in Shandong, and Luochuan in Shaanxi. Near-infrared diffuse reflectance spectra were acquired from 375 apples, generating 3000 spectral samples for origin classification and 750 SSC-calibrated samples for sugar content prediction. For classification, six deep learning models were evaluated using standardized full-spectrum input without chemometric spectral preprocessing, and the Transformer achieved the best performance, with a test accuracy of 96.22%. For SSC regression, spectra were preprocessed using standard normal variate and Savitzky-Golay filtering. The DNN model achieved the best prediction performance, with MAE = 0.5958 °Brix, RMSE = 0.7333 °Brix, R = 0.8646, and Pearson r = 0.9338. These results indicate that near-infrared spectroscopy combined with deep learning can support both Fuji apple origin authentication and non-destructive local tissue SSC assessment.

Pocket molds are widely applied, whose pockets usually contain many transition corners. The machining efficiency of pocket mold can be improved significantly through deep milling. However, tools are subject to quick wear and damage during corner deep milling. Corner rounding along tool path by different approaches has great influence on the tool wear in deep milling of hardened steel pocket mold. Therefore, conducting related researches on tool wear is of practical significance. Firstly, continuous cutting pocket molds were designed for typical corners of different corner rounding approaches as per the basic theory of tool engagement angle in milling, and then hardened steel was subject to deep milling and the tool was inspected and analyzed; afterwards, tool wear process and mechanism, etc. were studied. The results showed that during the deep milling of hardened steel, adhesion, oxidation, and diffusion wear appeared gradually since the stabilization of tool wear and further aggravated along with the cutting process, which led to wear and peeling of coating as well as highly possible tool damage like tipping and chipping of tool nose in later period. It was easy to generate high tool-chip interface temperature and great tool load in the high-speed deep milling of hardened steel with small corner rounding radius. In this case, the cutting edge was under considerable thermal fatigue and mechanical shock and thus subject to extensive abrasion wear, adhesion wear, and diffusion wear. The tool wear could be reduced notably by increasing the corner rounding radius.

BackgroundEnhancing immunogenicity and antigen-presentation efficiency is critical for tumor vaccine development. While yeast-surface glycoprotein side chains can improve antigen presentation, their ability to deliver tumor antigens remains limited.MethodsThe composite carbon nanopolymers (Asparagine-N-acetylglucosamine-Mannose derived carbon nanopolymers, ANM-NPs) mimicking yeast-surface glycans side chains were prepared using asparagine, N-acetylglucosamine and mannose as precursors via microwave-assisted synthesis method. Combined with whole-cell tumor antigen (T-Ag), the vaccine ANM-NPs@T-Ag was prepared. The expression levels of major histocompatibility complex-II, CD80, and CD86 were analyzed by flow cytometry to evaluate the enhancement of antigen presentation. The antitumor efficacy of ANM-NPs@T-Ag was assessed by H22-LUC and B16-F10-LUC tumor-bearing models.ResultsANM-NPs have an average particle size of approximately 21.69 nm and exhibit good stability. Compared with traditional aluminum adjuvants, ANM-NPs demonstrate superior efficacy in promoting antigen presentation and immune activation. ANM-NPs effectively stimulated innate immunity, facilitated immune cell infiltration, and enhanced adaptive immune responses. The vaccine ANM-NPs@T-Ag targeted dendritic cells via mannose receptors, activating the lectin pathway, improving complement opsonization, and enhancing antigen presentation. ANM-NPs@T-Ag stimulated cellular/humoral immunity, increased tumor-specific IgG, and inhibited tumor growth. ANM-NPs@T-Ag also enhanced the antitumor effect of α-PD-1 (programmed cell death protein-1).ConclusionThese findings demonstrate that ANM-NPs can serve as a potential vaccine adjuvant, and ANM-NPs@T-Ag represents a promising tumor vaccine candidate.Cite Now

MicroRNAs (miRNAs) are a class of short, single-stranded, noncoding RNAs, with a length of about 18–22 nucleotides. Extracellular vesicles (EVs) are derived from cells and play a vital role in the development of diseases and can be used as biomarkers for liquid biopsy, as they are the carriers of miRNA. Existing studies have found that most of the functions of miRNA are mainly realized through intercellular transmission of EVs, which can protect and sort miRNAs. Meanwhile, detection sensitivity and specificity of EV-derived miRNA are higher than those of conventional serum biomarkers. In recent years, EVs have been expected to become a new marker for liquid biopsy. This review summarizes recent progress in several aspects of EVs, including sorting mechanisms, diagnostic value, and technology for isolation of EVs and detection of EV-derived miRNAs. In addition, the study reviews challenges and future research avenues in the field of EVs, providing a basis for the application of EV-derived miRNAs as a disease marker to be used in clinical diagnosis and even for the development of point-of-care testing (POCT) platforms.