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SHARPIN is a tumor‐associated gene involved in the growth and proliferation of many tumor types. A function of SHARPIN in cholangiocarcinoma (CCA) is so far unclear. Here, we studied the role and function of SHARPIN in CCA and revealed its relevant molecular mechanism. The expression of SHARPIN was analyzed in cholangiocarcinoma tissues from patients using immunohistochemistry, quantitative PCR, and western blot analysis. Expression of SHARPIN was suppressed/overexpressed by siRNA silencing or lentiviral overexpression vector, and the effect on cell proliferation was determined by the CCK‐8 assay and flow cytometry. Accumulation of reactive oxygen species was measured with MitoTracker, and JC‐1 staining showed mitochondrial fission/fusion and mitochondrial membrane potential changes as a result of the silencing or overexpression. The ferroptosis marker solute carrier family 7 member 11 (SLC7A11), glutathione peroxidase 4 (GPX4), and the antioxidant enzymes superoxide dismutase 1 (SOD‐1) and SOD‐2 were analyzed by western blot. The results showed that SHARPIN expression was increased in CCA tissue, and this was involved in cell proliferation. SHARPIN silencing resulted in accumulated reactive oxygen species, reduced mitochondrial fission, and a reduced mitochondrial membrane potential. Silencing of SHARPIN inhibited the ubiquitination and degradation of p53, and downregulated levels of SLC7A11, GPX4, SOD‐1, and SOD‐2, all of which contributed to excessive oxidative stress that leads to ferroptosis. Overexpression of SHARPIN would reverse the above process. The collected data suggest that in CCA, SHARPIN‐mediated cell ferroptosis via the p53/SLC7A11/GPX4 signaling pathway is inhibited. Targeting SHARPIN might be a promising approach for the treatment of CCA. SHARPIN‐mediated cell ferroptosis via the p53/SLC7A11/GPX4 signaling pathway is inhibited. Targeting SHARPIN might be a promising approach for the treatment of CCA.

How does the South China Sea issue affect China’s image in Southeast Asian countries? Has it diminished Southeast Asian countries’ perception of China? Based on the Global Database of Events, Language, and Tone (GDELT) from 2010 to 2024, this study empirically examines the impact of the South China Sea issue on Southeast Asian countries’ perception of China’s image using a panel multiple linear regression model. The empirical results show a significant positive correlation between the South China Sea issue and Southeast Asian countries’ perception of China’s image. Specifically, the positive impact of verbal events, material events, and the scale of events related to the South China Sea significantly enhances the positive evaluation and recognition of China among Southeast Asian countries. Additionally, GDP plays a moderating role in this process, weakening the positive impact of verbal events, factual events, and the scale of South China Sea events on China’s positive evaluation and recognition. In Southeast Asian countries with territorial disputes and sovereignty conflicts with China, the influence of factual events and the scale of South China Sea events on the perception of China’s image is more pronounced. In contrast, in Southeast Asian countries without such disputes, verbal events have a more significant impact on their perception of China’s image.

Background Psoriasis is a common chronic inflammatory skin disease characterized by epidermal keratinocyte hyperproliferation and persistent immune activation. Histone deacetylase 3 (HDAC3), a member of the class I HDAC family, plays critical roles in regulating immunity and inflammation. However, its precise expression profile and functional contribution to psoriasis pathogenesis remain poorly defined. Methods We first performed bioinformatics analysis of HDAC3 expression using the Gene Expression Omnibus (GEO) database. Subsequently, we employed a combination of cellular and molecular techniques, including hematoxylin and eosin (H&E) staining, immunohistochemistry, flow cytometry, quantitative real-time PCR (qRT-PCR), western blotting, and transmission electron microscopy (TEM), to analyze the role of HDAC3 in IMQ-induced psoriasis-like inflammation in mice and in vitro psoriasis models. Results HDAC3 expression was significantly upregulated in psoriasis lesions of patients and in both in vitro and in vivo models of psoriasis. Pharmacological inhibition of HDAC3 using the specific inhibitor RGFP966 alleviated IMQ-induced skin inflammation in mice and suppressed psoriasis-like phenotypes in vitro. Mechanistically, HDAC3 upregulation in an inflammatory microenvironment promoted oxidative stress, disrupted mitochondrial structural integrity, and triggered mitochondrial DNA leakage into the cytosol, thereby activating the cGAS-STING pathway in keratinocytes. Conclusion Our findings establish HDAC3 as a pivotal mediator of psoriasis pathogenesis through the cGAS-STING pathway via mitochondrial dysfunction. The role of HDAC3 in exacerbating epidermal hyperproliferation and inflammation highlights its potential as a therapeutic target. Targeting HDAC3 in keratinocytes may offer a novel strategy for preventing and treating psoriasis by modulating epigenetic regulation, mitochondrial homeostasis, and innate immune responses.

To enhance the autonomy and safety of civil aircraft during takeoff, deviation-correction, pitch tracking, and airspeed tracking control laws are designed based on the civil aircraft ground taxiing model, enabling automatic takeoff from ground taxiing to liftoff. Firstly, a combined correction control law using nose wheel steering and rudder deflection is designed based on this basis, and a power function-shaped influence factor is introduced for control allocation between the two. Secondly, a pitch angle tracking control law is designed for the transition phase from three-wheel to two-wheel ground taxiing. For the liftoff phase, an airspeed tracking control law is designed, with pitch angle as the inner loop and speed as the outer loop. A fade-out device is introduced to enable smooth transitions from the pitch tracking control command to the speed tracking control command. Finally, the effectiveness of the proposed combined correction, pitch tracking, and speed tracking control laws are verified through numerical simulations.

Metabolic reprogramming is a sign of malignant tumors, and targeting the metabolism of tumor cells has become a promising therapeutic approach. Here, we report that Silybin (a nontoxic flavonoid commonly used for liver protection) exhibits prominent anti‐tumor effects on human ovarian cancer cells. Treatment of an ovarian cancer cell line with Silybin interfered with glutamine metabolism and the tricarboxylic acid cycle. We applied the drug affinity responsive target stability approach to show that Silybin binds to isocitrate dehydrogenase 1 (IDH1). This combination leads to reduced phosphorylation of IDH1 and inhibits enzyme activity. IDH1 dysfunction significantly increases the ratio of NADP/NADPH in the cell, causing an increase in reactive oxygen species generation. Immunohistochemistry demonstrated that IDH1 was increased in ovarian cancer samples compared with normal para‐tumoral tissues. Xenograft murine experiments indicated that Silybin administered orally suppressed the growth of the tumor formed by ovarian cancer cells. In combination, our data strongly suggest that Silybin targets IDH1 in ovarian cancer cells and may be a novel treatment candidate. Here, we report that the Silybin exhibits prominent anti‐tumor effects on human ovarian cancer cells. Treatment of an ovarian cancer cell line with Silybin interfered with glutamine metabolism and the tricarboxylic acid cycle. In combination, our data strongly suggest Silybin targets IDH1 in ovarian cancer cells and it may provide a novel treatment candidate.

Accurate detection of cardiac arrhythmias from electrocardiogram (ECG) signals is essential for the early diagnosis of cardiovascular diseases but remains challenging due to the complex, non-linear nature of ECG waveforms. This study proposes HCTG-Net, a Hybrid CNN–Transformer Network with Gated Fusion, designed to jointly capture local morphological features and long-range temporal dependencies in ECG data. The model employs a dual-branch architecture, where a residual CNN extracts localized waveform patterns and a Transformer branch models global temporal context. A learnable gated fusion mechanism adaptively balances and integrates features from both branches at the per-dimension level. Experiments conducted on the MIT-BIH Arrhythmia Database demonstrate that HCTG-Net achieves superior performance compared with existing methods, reaching an overall accuracy of 0.9946 and F1-score of 0.9711. Visualization results show well-clustered feature distributions, confirming robust feature learning, while ablation studies verify the complementary roles of the CNN, Transformer, and fusion modules. Overall, HCTG-Net offers a powerful and adaptive framework for automatic ECG-based arrhythmia diagnosis and holds strong potential for real-time clinical and wearable healthcare applications.

One of the malignant transformation hallmarks is metabolism reprogramming, which plays a critical role in the biosynthetic needs of unchecked proliferation, abrogating cell death programs, and immunologic escape. However, the mechanism of the metabolic switch is not fully understood. Here, we found that the S-nitrosoproteomic profile of endogenous nitrogen oxide in ovarian cancer cells targeted multiple components in metabolism processes. Phosphofructokinase (PFKM), one of the most important regulatory enzymes of glycolysis, was S-nitrosylated by nitric oxide synthase NOS1 at Cys351. S-nitrosylation at Cys351 stabilized the tetramer of PFKM, leading to resist negative feedback of downstream metabolic intermediates. The PFKM-C351S mutation decreased the proliferation rate of cultured cancer cells, and reduced tumor growth and metastasis in the mouse xenograft model. These findings indicated that S-nitrosylation at Cys351 of PFKM by NOS1 contributes to the metabolic reprogramming of ovarian cancer cells, highlighting a critical role of endogenous nitrogen oxide on metabolism regulations in tumor progression.

Background NOTCH signaling has been shown to play a role in the production of interleukin-22 (IL-22) by CD4 + T cells. Multiple T-helper (Th) cell populations secrete IL-22. Th22 (CD4 + IL22 + IFNγ − IL17A − ) cells are a subgroup of CD4 + effector T cells that primarily generate IL-22. The regulatory mechanisms of the NOTCH signaling pathway involved in differentiation of the Th22 cell subset have not been completely elucidated. This study aimed to further explore the involvement of NOTCH signaling in Th22 differentiation. Methods In vitro combination of IL-6, IL-23, and tumor necrosis factor-α (TNF-α) treatment with naïve CD4 + T cells established the Th22 cell induced model. NOTCH signaling was activated by jagged-1 and inhibited by (2S)-N-[(3,5-difluorophenyl) acetyl]-L-alanyl-2-phenyl]glycine 1,1-dimethylethyl ester (DAPT). HES-1 siRNA and HES-1 vector were employed to knock down and induce overexpression of HES-1 to investigate the effect of NOTCH signaling on the differentiation of CD4 + T cells into Th22 cells. Results We observed that the proportion of Th22 cells, along with Hes-1 , Ahr , and Il-22 mRNA and protein expression, was increased by both jagged-1 and overexpression of HES-1. On the other hand, after the combined cytokine treatment of cells, and exposure to jagged-1 and DAPT or HES-1 siRNA, there was a decrease in the Th22 cell proportion, mRNA and protein expression of HES-1, AHR, and IL-22. Conclusions Our study demonstrates that HES-1 enhancement in AHR and IL-22 up-regulation of NOTCH signaling can promote the skewing of naïve CD4 + T cells toward Th22 cells. Also, the results of our study show that HES-1 is a crucial factor in Th22 cell differentiation.

In this paper, a theoretical model of the propagation of a shear horizontal wave in a piezoelectric semiconductor semi-infinite medium is established using the optimized spectral method. First, the basic equations of the piezoelectric semiconductor semi-infinite medium are derived with the consideration of biased electric fields. Then, considering the propagation of a shear horizontal wave in the piezoelectric semiconductor semi-infinite medium, two equivalent mathematical models are established. In the first mathematical model, the Schottky junction is theoretically treated as an electrically imperfect interface, and an interface characteristic length is utilized to describe the interface effect of the Schottky junction. To legitimately confirm the interface characteristic length, a second mathematical model is established, in which the Schottky junction is theoretically treated as an electrical gradient layer. Finally, the dispersion and attenuation curves of shear horizontal waves are numerically calculated using these two mathematical models to discuss the influence of the Schottky junction on the dispersion and attenuation characteristics of shear horizontal waves. Utilizing the equivalence of these two mathematical models and the above numerical results, the numerical value of the interface characteristic length is reliably legitimately confirmed; this value is independent of the thickness of the upper metal layer, the doping concentration of the lower n-type piezoelectric semiconductor substrate, and biasing electric fields. Only the biasing electric field parallel to the Schottky junction can provide an evident influence on the attenuation characteristics of shear horizontal waves and enhance the interface effect of the Schottky junction. Since the second mathematical model is also a validation of our previous mathematical model established through the state transfer equation method, some numerical results calculated using these two mathematical models are compared with those obtained using the previous method to verify the correctness and superiority of the research work presented in this paper. Since these two mathematical models can better calculate the dispersion and attenuation curves of high-frequency waves in micro- and nano-scale piezoelectric semiconductor materials, the establishment of mathematical models and the revelation of physical mechanisms are fundamental to the analysis and optimization of micro-scale resonators, energy harvesters, and amplifications.

As global climate change intensifies and extreme weather events become more frequent, understanding the historical spatial distribution of vegetation is of critical importance. However, most vegetation studies are temporally limited to the post-1980 period due to satellite data constraints. To bridge this gap, we integrated tree-ring width chronologies from the International Tree-Ring Databank with Landsat-derived Enhanced Vegetation Index (EVI) data and evaluated three machine learning models—Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN)—to reconstruct annual, spatially explicit EVI for the period 1850–1985 in Diqing, Yunnan, China. RF regression was the best among the three with highest adjusted R2 (0.90) and lowest Root Mean Square Error (0.032). The RF-based reconstruction indicated a consistent increase in regional EVI from 1991 to 2005. Breakpoint analysis identified three distinct sub-periods, each with unique spatiotemporal variation patterns. In current times, the EVI value shows a significant positive correlation with average temperatures in June, July, August, and December. In the contemporary period, it also correlates significantly and positively with winter average temperatures, March average precipitation, and spring average precipitation. The spatial pattern for the past 100 years reflects the succession of the local vegetation ecosystem and provides an insight into the influences of natural disturbances (low-temperature damages and droughts) on vegetation growth. This study demonstrates the feasibility of reconstructing high-resolution, long-term vegetation spatial dynamics using tree-ring proxies and machine learning.