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Aging is an inevitable time-dependent process associated with a gradual decline in many physiological functions. Importantly, some studies have supported that aging may be involved in the development of lung adenocarcinoma (LUAD). However, no studies have described an aging-related gene (ARG)-based prognosis signature for LUAD. Accordingly, in this study, we analyzed ARG expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). After LASSO and Cox regression analyses, a six ARG-based signature ( APOC3 , EPOR , H2AFX , MXD1 , PLCG2 , and YWHAZ ) was constructed using TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of overall survival (OS). Cox regression analysis indicated that the ARG signature was an independent prognostic factor in LUAD. A nomogram based on the ARG signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Moreover, to visualize the prediction results, we established a web-based calculator yurong.shinyapps.io/ARGs_LUAD/ . Calibration plots showed good consistency between the prediction of the nomogram and actual observations. Receiver operating characteristic curve and decision curve analyses indicated that the ARG nomogram had better OS prediction and clinical net benefit than the staging system. Taken together, these results established a genetic signature for LUAD based on ARGs, which may promote individualized treatment and provide promising novel molecular markers for immunotherapy.

Asia bears a disproportionate burden of head and neck cancer (HNC). This study aimed to analyze its spatial distribution and temporal trends in Asia from 1990 to 2021, projecting trends to 2030. We performed a secondary analysis of data from the Global Burden of Disease Study (GBD) 2021, examining disability-adjusted life years (DALYs) for HNC and its five major subtypes: nasopharyngeal cancer (NPC), thyroid cancer (TC), laryngeal cancer (LC), lip and oral cavity cancer (LOC), and other pharyngeal cancer (OPC), across five Asian subregions and 34 countries/territories from 1990 to 2021. Temporal trends were evaluated using Joinpoint regression, and projections to 2030 were generated through Bayesian Age-Period-Cohort model. From 1990 to 2021, DALYs for HNC increased in five subregions. In contrast, age-standardized DALY rates (ASDR) declined across all subregions except South Asia, with East Asia experiencing the most rapid decrease. In 2021, South Asia recorded the highest DALYs (6,412,639) and ASDR (405.82 per 100,000) for HNC. LOC was the main HNC type in most regions (32.41% - 46.23%), except East Asia, where NPC was most common (38.96%). South Asia also exhibited the highest ASDRs for LC (67.29), LOC (182.29), and OPC (93.00) per 100,000, while Southeast Asia demonstrated the highest ASDRs for NPC (50.77) and TC (18.22) per 100,000. Significant disparities in ASDR trends for HNC subtypes were observed across Asia. By 2030, South Asia is projected to maintain the highest ASDRs for HNC (394.59), LC (62.98), LOC (185.31), and OPC (95.50). East and Southeast Asia are expected to show comparable ASDRs for NPC (approximately 50.00), with Southeast Asia leading in TC ASDR (23.90). HNC remains a significant public health challenge in Asia, with substantial heterogeneity in its subtypes across the five subregions. Implementing targeted, region-specific strategies is crucial to mitigating the disease burden.

Traditional PID control faces challenges in addressing parameter uncertainty and nonlinearity in active suspension electrohydraulic servo actuators, leading to suboptimal performance. To address these challenges, a fractional-order PID (FOPID) controller optimization method based on the Multi-Strategy Improved Beluga Whale Optimization (MSIBWO) algorithm is proposed. Simulation results in MATLAB/Simulink demonstrate that the MSIBWO-FOPID controller significantly outperforms traditional PID and BWO-FOPID controllers in force tracking and robustness. For step input, the rise time and the root mean square error(RMSE) are reduced by 66.7 % and 70.3 % , respectively, compared to BWO-FOPID. For sine inputs, the system achieves better disturbance rejection and higher precision. Using a half-car model, the MSIBWO-FOPID controller improves ride comfort significantly. Under random road excitation, the RMSE values of the vehicle body’s vertical acceleration and pitch angle acceleration are reduced by 51.7 % and 13.1 % , respectively, compared to passive suspension, outperforming both PID and BWO-FOPID controllers.

Background Platinum-resistant cases account for 25% of ovarian cancer patients. Our aim was to construct two novel prognostic models based on gene expression data respectively from ferroptosis and necroptosis, for predicting the prognosis of advanced ovarian cancer patients with platinum treatment. Methods According to the different overall survivals, we screened differentially expressed genes (DEGs) from 85 ferroptosis-related and 159 necroptosis-related gene expression data in the GSE32062 cohort, to establish two ovarian cancer prognostic models based on calculating risk factors of DEGs, and log-rank test was used for statistical significance test of survival data. Subsequently, we validated the two models in the GSE26712 cohort and the GSE17260 cohort. In addition, we took gene enrichment and microenvironment analyses respectively using limma package and GSVA software to compare the differences between high- and low-risk ovarian cancer patients. Results We constructed two ovarian cancer prognostic models: a ferroptosis-related model based on eight-gene expression signature and a necroptosis-related model based on ten-gene expression signature. The two models performed well in the GSE26712 cohort, but the performance of necroptosis-related model was not well in the GSE17260 cohort. Gene enrichment and microenvironment analyses indicated that the main differences between high- and low- risk ovarian cancer patients occurred in the immune-related indexes, including the specific immune cells abundance and overall immune indexes. Conclusion In this study, ovarian cancer prognostic models based on ferroptosis and necroptosis have been preliminarily validated in predicting prognosis of advanced patients treated with platinum drugs. And the risk score calculated by these two models reflected immune microenvironment. Future work is needed to find out other gene signatures and clinical characteristics to affect the accuracy and applicability of the two ovarian cancer prognostic models.

Currently, anti-PD-1/PD-L1 immunotherapy using immune checkpoint inhibitors is widely used in the treatment of multiple cancer types including lung cancer, which is a leading cause of cancer death in the world. However, only a limited proportion of lung cancer patients will benefit from anti-PD-1/PD-L1 therapy. Therefore, it is of importance to predict the response to immunotherapy for the precision treatment of patients. Although the expression of PD-L1 and tumor mutation burden (TMB) are commonly used to predict the clinical response of anti-PD-1/PD-L1 therapy, other factors such as tumor-specific genes, dMMR/MSI, and gut microbiome are also promising predictors for immunotherapy in lung cancer. Furthermore, invasive peripheral blood biomarkers including blood DNA-related biomarkers (e.g., ctDNA and bTMB), blood cell-related biomarkers (e.g., immune cells and TCR), and other blood-related biomarkers (e.g., soluble PD-L1 and cytokines) were utilized to predict the immunotherapeutic response. In this review, the current achievements of anti-PD-1/PD-L1 therapy and the potential biomarkers for the prediction of anti-PD-1/PD-L1 immunotherapy in lung cancer treatment were summarized and discussed.

With the growing demand for advanced biophysical signal monitoring systems, the development of stretchable, adaptable, and functional flexible materials has become essential. Flexible sensors capable of detecting facial expressions, voice signals, and environmental stimuli show great potential in personalized healthcare, human–machine interfaces, and wearable electronics. Despite advancements, current flexible sensors face limitations such as low sensitivity to micro‐strains, insufficient anisotropy, and poor environmental adaptability, restricting their broader application. This study introduces a high‐performance stretchable sensor composed of carbon nanotube (CNT) and silver (Ag)‐based conductive inks integrated with a monodomain liquid crystal elastomer (LCE) substrate (Ag/CNT/LCE). The LCE substrate offers sensitive mir‐costrains detection intrinsic anisotropy, and thermal‐response capability. The conductive ink combines the mechanical robustness of CNTs with the excellent conductivity of Ag, suppressing CNT aggregation and improving electrical stability under strain. The Ag/CNT/LCE sensor exhibits a gauge factor of 3.93, rapid response times (120 ms), and exceptional cyclic durability over 2500 cycles. Additionally, its thermoresponsive behavior enhances adaptability to environmental changes. Demonstrated applications include facial emotion recognition, voice monitoring, and deformation‐based environmental sensing. By integrating multifunctionality, structural durability, and dynamic adaptability, the Ag/CNT/LCE sensor serves as a promising platform for wearable electronics, and next‐generation healthcare technologies. Integrating Ag/CNT conductive inks with monodomain liquid crystal elastomers, this flexible sensor improves micro‐strain detection and stability. Utilizing thermal responsiveness and intrinsic anisotropy, the Ag/CNT/LCE platform accurately monitors facial micro‐expressions and thermal stimuli. This multifunctional design offers a reliable platform for sophisticated human‐machine interfaces and next‐generation wearable healthcare technologies.

Objectives Obesity has become a common health concern around the world. Maternal obesity could cause poor reproductive outcomes due to chronic ovarian inflammation and decreased oocyte quality. However, the strategies to improve the poor reproductive outcomes of obese females have not been fully studied. In this study, we aimed to explore the effects and underlying mechanisms of nicotinamide mononucleotide (NMN) on oocyte quality and reproductive performance of obese mice. Materials and Methods The obese mouse model was established by feeding high‐fat diet which was confirmed by body weight record, fasting blood glucose test and oral glucose tolerance test. The expression of ovary development related genes and inflammation related genes, including Lhx8, Bmp4, Adgre1, Ccl2, TNF‐α, Gal‐3, Clec10a and IL‐10 in ovaries and the expression of Bax and Sod1 in oocytes were detected using quantitative reverse transcription PCR (RT‐qPCR). The adipose size of abdominal fat tissue was determined with haematoxylin and eosin (H&E) staining. Immunofluorescence staining was performed to measure the ROS level, spindle/chromosome structure, mitochondrial function, actin dynamics and DNA damage of oocytes. Results The administration of NMN restored ovarian weight and reduced the adipose size of abdominal fat tissue and ovarian inflammation in high fat diet (HFD) mice. Furthermore, NMN treatment improved the oocytes quality partially by restoring the mitochondrial function and actin dynamics, reducing meiotic defects, DNA damage and ROS level and lipid droplet distribution of oocytes in HFD mice. On the long‐term effect, NMN restored offspring body weight of HFD mice. Conclusion NMN could improve the oocyte quality of HFD‐induced obese mice. Diagram illustrating the beneficial effects of NMN on the productivity of mice especially the ovary and oocyte quality in obese female mice. Intraperitoneal injection of NMN improved ovary quality of high fat diet mice. The administration of NMN restored the mitochondrial function and actin dynamics and reduced meiotic defects, DNA damage and ROS level of oocytes in obese mice. The administration of NMN also restored offspring body weight of obese mice. Therefore, the productivity of obese mice could be improved after NMN supplement.

Oocyte senescence alters the shape and function, thereby weakening the fertilization potential. Nicotinamide mononucleotide (NMN) reverses age-related dysfunctions in various organs. Studies had shown long-term administration of NMN reduced the physiological decline associated in aged mice and reversed the aging of the ovaries. However, the protective effect of NMN on aged porcine oocytes is still unclear. In this study, we investigated the effects of NMN on aging porcine oocytes and subsequent embryonic development. We established a model of senescence of porcine oocytes after ovulation by extending the culture time in vitro. NMN supplementation significantly reduced reactive oxygen species (ROS) levels in senescence oocytes and increased the mRNA levels of antioxidant genes SOD1 and Cat . The mitochondrial membrane potential of aged oocytes treated with NMN was increased compared with that of untreated oocytes. In addition, the mRNA level of apoptosis-related gene Bax was significantly decreased in senescence oocytes treated with NMN, while the mRNA level of anti-apoptosis-related gene BCL-2 was significantly increased. Furthermore, NMN supplementation enhanced the subsequent development ability of senescent oocytes during in vitro aging. Compared with untreated senescent oocytes, the blastocyst formation rate and pluripotent genes of senescent oocytes treated with NMN were significantly increased. Taken together, these results suggest that NMN is beneficial for delaying the aging process in porcine oocytes.

The South China Sea is rich in cone snail resources, known for producing conotoxins with diverse biological activities such as analgesic, anticancer, and insecticidal effects. In this study, five vermivorous cone snail samples were collected from the South China Sea and their crude venom was extracted to investigate the variations in venom components and activities, aiming to identify highly active samples for further research. Cluster analysis using reverse-phase high-performance liquid chromatography (RP-HPLC) fingerprints and mitochondrial cytochrome c oxidase I (COI) gene sequences revealed that the diversity of venom components across different conotoxin species is genetically correlated. Activity assays demonstrated that all five cone snail venoms exhibited lethal effects on insects and zebrafish. Notably, the crude venom of Conus quercinus showed the highest insecticidal activity with an LD50 of 0.6 μg/mg, while C. tessellatus venom exhibited the most potent zebrafish lethality with an LD50 of 0.2 μg/mg. Furthermore, the crude venom from four cone snail species demonstrated toxicity against ovarian cancer cells, and only C. caracteristicu venom displayed significant analgesic activity. This study systematically identifies cone snail samples with promising insecticidal, anticancer, and analgesic properties, paving the way for the development and utilization of cone snail resources from the South China Sea and offering a novel approach for advancing marine peptide drug research.

Imaging technology enhances radar environment awareness. Imaging radar can provide richer target information for traffic management systems than conventional traffic detection radar. However, there is still a lack of research on millimeter-wave radar imaging technology for urban traffic surveillance. To solve the above problem, we propose an improved three-dimensional FFT imaging algorithm architecture for radar roadside imaging in urban traffic scenarios, enabling the concurrence of dynamic and static targets imaging. Firstly, by analyzing the target characteristics and background noise in urban traffic scenes, the Monte-Carlo-based constant false alarm detection algorithm (MC-CFAR) and the improved MC-CFAR algorithm are proposed, respectively, for moving vehicles and static environmental targets detection. Then, for the velocity ambiguity solution problem with multiple targets and large velocity ambiguity cycles, an improved Hypothetical Phase Compensation algorithm (HPC-SNR) is proposed and complimented. Further, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is used to remove outliers to obtain a clean radar point cloud image. Finally, traffic targets within the 50 m range are presented as two-dimensional (2D) point cloud imaging. In addition, we also try to estimate the vehicle type by target point cloud size, and its accuracy reaches more than 80% in the vehicle sparse condition. The proposed method is verified by actual traffic scenario data collected by a millimeter-wave radar system installed on the roadside. The work can support further intelligent transportation management and extend radar imaging applications.