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Allergic diseases such as allergic rhinitis (AR), allergic asthma (AAS), atopic dermatitis (AD), food allergy (FA), and eczema are systemic diseases caused by an impaired immune system. Accompanied by high recurrence rates, the steadily rising incidence rates of these diseases are attracting increasing attention. The pathogenesis of allergic diseases is complex and involves many factors, including maternal-fetal environment, living environment, genetics, epigenetics, and the body’s immune status. The pathogenesis of allergic diseases exhibits a marked heterogeneity, with phenotype and endotype defining visible features and associated molecular mechanisms, respectively. With the rapid development of immunology, molecular biology, and biotechnology, many new biological drugs have been designed for the treatment of allergic diseases, including anti-immunoglobulin E (IgE), anti-interleukin (IL)-5, and anti-thymic stromal lymphopoietin (TSLP)/IL-4, to control symptoms. For doctors and scientists, it is becoming more and more important to understand the influencing factors, pathogenesis, and treatment progress of allergic diseases. This review aimed to assess the epidemiology, pathogenesis, and therapeutic interventions of allergic diseases, including AR, AAS, AD, and FA. We hope to help doctors and scientists understand allergic diseases systematically.

Combine harvesters, as essential equipment in agricultural engineering, frequently experience structural faults due to their complex structure and harsh working conditions, which severely affect their reliability and operational efficiency, leading to significant downtime and reduced agricultural productivity during critical harvesting periods. Therefore, developing accurate and timely Fault Detection and Diagnosis (FDD) techniques is crucial for ensuring food security. This paper provides a systematic and critical review and analysis of the latest advancements in research on data-driven FDD methods for structural faults in combine harvesters. First, it outlines the typical structural sections of combine harvesters and their common structural fault types. Subsequently, it details the core steps of data-driven methods, including the acquisition of operational data from various sensors (e.g., vibration, acoustic, strain), signal preprocessing methods, signal processing and feature extraction techniques covering time-domain, frequency-domain, time–frequency domain combination, and modal analysis among others, and the use of machine learning and artificial intelligence models for fault pattern learning and diagnosis. Furthermore, it explores the required system and technical support for implementing such data-driven FDD methods, such as the applications of on-board diagnostic units, remote monitoring platforms, and simulation modeling. It provides an in-depth analysis of the key challenges currently encountered in this field, including difficulties in data acquisition, signal complexity, and insufficient model robustness, and consequently proposes future research directions, aiming to provide insights for the development of intelligent maintenance and efficient and reliable operation of combine harvesters and other complex agricultural machinery.

Combination chemotherapy is still of great importance as part of the standard clinical care for patients with HER2 positive breast cancer. As an attractive component, gold nanoparticles (AuNPs) have been extensively studied as biosafety nanomaterials, but they are rarely explored as drug nanocarriers for targeted co-delivery of multiple chemotherapeutics. Herein, a novel affibody-DNA hybrid strands modified AuNPs were fabricated for co-loading nucleoside analogue (5-fluorodeoxyuridine, FUdR) and anthracycline (doxorubicin, Dox). FUdRs were integrated into DNA hybrid strands decorated on AuNPs by DNA solid phase synthesis, and Dox molecules were intercalated into their duplex regions. Affibody molecules coupled to the DNA hybrid strands were distributed the surface of AuNPs, giving them targeting for HER2. The new dual-drug-containing affibody-DNA-AuNPs (Dox@affi-F/AuNPs) owned compact and stable spherical nanostructures, and precise drug loading. Cytotoxicity tests demonstrated that these nanoparticles caused a higher inhibition in HER2 overexpressing breast cancer cells, and showed better synergistic antitumor activity than simple mixture of the two drugs. The related mechanistic studies proved that Dox@affi-F/AuNPs achieved a remarkable combined antitumor activity of Dox and FUdR by promoting more cells to enter apoptosis pathway. Our work provided a nanomedicine platform for targeted co-delivery of nucleoside analog therapeutics and anthracycline anticancer drugs to achieve synergistic treatment of HER2 + cancer.

Alternative splicing (AS) is a promising clinical target for cancer treatment at the post-transcriptional level. We previously identified a unique AS profile in triple-negative breast cancer (TNBC), which is regulated by the splicing regulator TAR DNA-binding protein-43 (TDP43), thus indicating the crucial role of TDP43 in heterogeneous TNBC. Cluster of differentiation 44 (CD44), a widely recognized marker for breast cancer stem cells (BCSCs), is extensively spliced into CD44 variant AS isoforms (CD44v) during the development of breast cancer. At present, however, the regulatory mechanism of CD44v is not fully understood. In the current study, we found that loss of TDP43 inhibits BCSC stemness by reducing the abundance of CD44v. In addition, serine-arginine-rich splicing factor 3 (SRSF3), another splicing factor and partner of TDP43, acts as an upstream regulator of TDP43 to maintain CD44v isoforms and thereafter BCSC stemness. Mechanistically, SRSF3 stabilizes the mRNA of TDP43 by inhibiting nonsense-mediated decay (NMD). These findings illustrate the important role of complicated regulatory networks formed by splicing factors in TNBC progression, thus providing potential therapeutic targets from an AS perspective.

Peas ( Pisum sativum L. ) are a cornerstone of sustainable agriculture, yet their potential is limited by fragmented agronomic practices. This review provides an integrated synthesis of advancements across cultivation, mechanized harvesting, and post-harvest storage. Key findings reveal that optimal growth conditions and nanotechnology interventions can significantly enhance abiotic stress tolerance. Mechanized harvesting innovations reduce yield losses by up to 40%, but smallholder adoption and terrain compatibility remain critical challenges. Effective post-harvest strategies, including low-temperature storage and hermetic bags, are crucial for preserving quality. Despite progress, systemic barriers persist. Future research must prioritize interdisciplinary solutions—combining genomics, precision engineering, and farmer training—to unlock the full potential of peas as a keystone crop for sustainable food systems.

This study analyzes hydrometeor evolution during rapid intensification (RI) and tropical cyclone (TC) intensity dependence using satellite data. Previous studies have suggested ice cloud water or non‐convective precipitation as a predictor of RI from different perspectives. However, few studies have focused on the impact of TC intensity or comprehensive comparisons to identify better indicators. During RI, hydrometeor contents in weak TCs increase over the entire region, whereas they increase mainly in the inner‐core region and decrease in advance in the outer‐core region for strong TCs. Hydrometeor contents in the inner‐core are higher in RI than in slow intensification, and their maxima location is related to TC intensity and intensification rate. Cloud water path (CWP) in the inner‐core region is most correlated with the intensification rate, especially in weak TCs. Therefore, the CWP can serve as a predictor of RI and can be applied to all TC intensities. Plain Language Summary Stronger tropical cyclones (TCs) often undergo rapid intensification (RI) and cause significant damage. However, accurately predicting its intensity is difficult. A close relationship exists between TC intensity changes and cloud content. Previous studies have shown a connection between the ice water content, precipitation, and RI of TCs. However, few studies have comprehensively compared the hydrometeors and precipitation associated with RI and the impact of TC intensity. During the RI, various cloud contents increase in the entire area of a weak TC, while they increase mainly in the inner‐core area and decrease in advance in the outer‐core area of a strong TC. The cloud contents in the inner‐core are higher in RI than in slow intensification, and their maximum locations are related to the TC intensity and intensification rate. Among the cloud content and precipitation types, the water cloud content in the TC inner‐core area is the best indicator of the intensification rate, applicable to all TC intensities, especially for weak TCs. Understanding the relationship between clouds and TC intensification facilitates prediction of TC intensity and reduces the impact of disasters. Key Points Hydrometeor contents increase in the entire area of a weak TC but mainly in the inner‐core of a strong TC during rapid intensification (RI) RI has higher inner‐core hydrometeor contents than slow cases, and the maxima location is linked to TC intensity and intensification rate The cloud water content in the inner‐core area has the largest correlation with the TC intensification rate, especially in a weak TC

Acute postoperative pain represents a significant clinical challenge, yet its underlying mechanisms remain incompletely understood. A previous study found that PD-1/PD-L1can relieve chronic pain. Mechanical withdrawal thresholds (MWT) and thermal withdrawal latency (TWL) were quantified in rats at baseline (pre-incision) and at postoperative timepoints of 2, 8, and 24 h. Concurrently, PD-1/PD-L1 expression levels and neuroinflammatory markers were assessed at the 24-hour terminal timepoint. PD-1 inhibitors and agonists were administered via intrathecal injection immediately after surgical incision and at 12 h postoperatively, respectively. It was found that incision surgery resulted in significant postoperative pain accompanied by upregulation of PD-1/PD-L1 and neuroinflammation. Inhibition of PD-1 expression could further exacerbate acute postoperative pain by upregulating neuroinflammation, whereas upregulation of PD-1 expression could alleviate acute postoperative pain by inhibiting neuroinflammation. Activation of the PD-1/PD-L1 pathway relieves acute postoperative pain induced by plantar incision. This may be a therapeutic target for acute postoperative pain.

This study investigates the tribological behavior and wear mechanisms of Q235 steel components subjected to abrasive interaction with rice, a critical challenge in agricultural machinery performance and longevity. We employed a comprehensive multi-scale framework, integrating bench-top tribological testing, advanced Discrete Element Method (DEM) coupled with a wear model (DEM-Wear), and detailed surface characterization. Bench tests revealed a composite wear mechanism for the rice–steel tribo-pair, transitioning from mechanical polishing under mild conditions to significant soft abrasive micro-cutting driven by the silica particles inherent in rice during high-load, high-velocity interactions. This elucidated fundamental friction and wear phenomena at the micro-level. A novel, calibrated DEM-Wear model was developed and validated, accurately predicting macroscopic wear “hot spots” on full-scale combine harvester header platforms with excellent geometric similarity to real-world wear profiles. This provides a robust predictive tool for component lifespan and performance optimization. Furthermore, fractal analysis was successfully applied to quantitatively characterize worn surfaces, establishing fractal dimension (Ds) as a sensitive metric for wear severity, increasing from ~2.17 on unworn surfaces to ~2.3156 in severely worn regions, directly correlating with the dominant wear mechanisms. This study offers a valuable computational approach for understanding and mitigating wear in tribosystems involving complex particulate matter, contributing to improved machinery reliability and reduced operational costs.

Porcine deltacoronavirus (PDCoV) is a novel swine enteropathogenic coronavirus with worldwide distribution. PDCoV belongs to the Deltacoronavirus (DCoV) genus, which mainly includes avian coronaviruses (CoVs). PDCoV has the potential to infect human and chicken cells in vitro, and also has limited infectivity in calves. However, the origin of PDCoV in pigs, the host range, and cross-species infection of PDCoV still remain unclear. To determine whether PDCoV really has the ability to infect chickens in vivo, the three lines of chicken embryos and specific pathogen free (SPF) chickens were inoculated with PDCoV HNZK-02 strain to investigate PDCoV infection in the current study. Our results indicated that PDCoV can infect chicken embryos and could be continuously passaged on them. Furthermore, we observed that PDCoV-inoculated chickens showed mild diarrhea symptoms and low fecal viral RNA shedding. PDCoV RNA could also be detected in multiple organs (lung, kidney, jejunum, cecum, and rectum) and intestinal contents of PDCoV-inoculated chickens until 17 day post-inoculation by real-time quantitative PCR (qRT-PCR). A histology analysis indicated that PDCoV caused mild lesions in the lung, kidney, and intestinal tissues. These results prove the susceptibility of chickens to PDCoV infection, which might provide more insight about the cross-species transmission of PDCoV.

HighlightsA simple two-step multi-element co-doping strategy is proposed to fabricate core-shell structured LiCoO2 based on the different diffusivities of dopant ions.The high diffusivity Al3+/Mg2+ ions occupy the core of single-crystal grain while the low diffusivity Ti4+ ions enrich the shell layer. In-situ XRD demonstrates the mitigated structural distortion under a high cut-off voltage of 4.6 V, resulting in a significantly improved cycling stability.Inactive elemental doping is commonly used to improve the structural stability of high-voltage layered transition-metal oxide cathodes. However, the one-step co-doping strategy usually results in small grain size since the low diffusivity ions such as Ti4+ will be concentrated on grain boundaries, which hinders the grain growth. In order to synthesize large single-crystal layered oxide cathodes, considering the different diffusivities of different dopant ions, we propose a simple two-step multi-element co-doping strategy to fabricate core–shell structured LiCoO2 (CS-LCO). In the current work, the high-diffusivity Al3+/Mg2+ ions occupy the core of single-crystal grain while the low diffusivity Ti4+ ions enrich the shell layer. The Ti4+-enriched shell layer (~ 12 nm) with Co/Ti substitution and stronger Ti–O bond gives rise to less oxygen ligand holes. In-situ XRD demonstrates the constrained contraction of c-axis lattice parameter and mitigated structural distortion. Under a high upper cut-off voltage of 4.6 V, the single-crystal CS-LCO maintains a reversible capacity of 159.8 mAh g−1 with a good retention of ~ 89% after 300 cycles, and reaches a high specific capacity of 163.8 mAh g−1 at 5C. The proposed strategy can be extended to other pairs of low- (Zr4+, Ta5+, and W6+, etc.) and high-diffusivity cations (Zn2+, Ni2+, and Fe3+, etc.) for rational design of advanced layered oxide core–shell structured cathodes for lithium-ion batteries.