ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

Hepatocellular carcinoma (HCC) is a lethal cancer with high morbidity rates worldwide. It is a major threat to public health in China, due to the combination of known and new risk factors, such as endemic hepatitis B virus (HBV), dietary aflatoxin exposure, and the occurrence of metabolic dysfunction-associated steatotic liver disease (MASLD). Although many methods for surveillance and multimodal therapies, such as surgery, local ablation, transarterial therapy, and new systemic agents, have been available, the survival rates of HCC remains poor. They have very limited durable responses, long post-treatment recurrence rates, and high resistance to treatment. This reflects an imperfect picture of the biological cause of the disease and a need for new mechanistic or targeted techniques. A significant characteristic of HCC, in common with other aggressive cancers, is the presence of reprogrammed, hyperactive cell metabolism. Tumor cells hijack metabolic pathways to promote their uncontrolled growth, stress survival, invasion and metastasis. While classical mechanisms such as the Warburg effect, lipid metabolism and glutamine utilization have been understood, the lysosome, which was once viewed as a static “waste disposal unit” to remove old organelles and proteins, is instead a dynamic signaling and metabolic core. The lysosomes incorporate nutrients, energy and stress signals by master regulators such as mTORC1 (activated on its surface) that balance anabolic growth and catabolic recycling to the cellular demands. In HCC, lysosomes are not passive, but are highly active and dysregulated. HCC cells upregulate lysosomes, which scavenge intracellular components via enhanced autophagy and engulf extracellular proteins via macropinocytosis, crucial for survival in the nutrient-poor, hypoxic tumor microenvironment. In addition to metabolism, lysosomes exhibit pro-invasive functions by secreting hydrolases to remodel the extracellular matrix, promote angiogenesis, and suppress stromal immune cells to foster a pro-tumor microenvironment. In a clinical context, lysosomes play an important role in therapeutic resistance: they sequester and inactivate chemotherapeutics via lysosomal sequestration, and enhanced autophagic flux protects the cell from therapy-induced damage, contributing to relapse, as lysosomal dysfunction is a key cause of treatment failure. This makes lysosomes promising yet challenging therapeutic targets in HCC. Recent preclinical and early clinical studies investigate multiple strategies to exploit the susceptibility of lysosomes: lysosome-specific agents, alkalinizing the lysosome lumen or inducing membrane permeabilization and lysosome-dependent cell death; pharmacological inhibition of key lysosomal enzymes or autophagy to impair nutrient recycling and stress adaptation; smart nanotherapeutic agents or antibody-drug conjugates, specifically activated in the acidic lysosomal environment or utilizing lysosomal pathways for efficient intracellular drug release; and combination strategies of lysosome-targeting agents with tyrosine kinase inhibitors or immunotherapy to overcome resistance and achieve synergistic antitumor effects. In summary, our review systematically presents the role of lysosomes in HCC, from metabolic reprogramming and microenvironmental adaptation to therapeutic resistance. By synthesizing the latest mechanistic insights and preclinical advances, this review highlights the indispensable role of lysosomes in the complex HCC biological network, emphasizing that an in-depth understanding of this dynamic organelle holds great promise for developing innovative, targeted therapies, offering new hope for improving the poor prognosis of global HCC patients.

Hepatitis D virus （HDV）， as a defective virus， relies on the envelope protein of hepatitis B virus （HBV） to complete replication and transmission. Chronic hepatitis B （CHB） patients comorbid with HDV infection may experience significant acceleration of liver disease progression and a significantly higher risk of serious complications such as liver cirrhosis and hepatocellular carcinoma （HCC） compared with the patients with CHB alone， which poses a serious threat to the life and health of patients. At present， the coverage rate of HDV screening needs to be improved， and some patients with HBV/HDV co-infection have not been found in time. Therefore， strengthening the understanding of HDV among clinicians， expanding the scope of HDV screening， identifying patients with infection in a timely manner， and performing standardized antiviral therapy and long-term follow-up management are of great significance for improving the prognosis of patients， reducing disease burden， improving the quality of life of patients， and achieving the global goal of “eliminating viral hepatitis as a public health threat by 2030”.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

ObjectiveTo understand the measles, rubella, and mumps antibody seroprevalence among the children aged 18 years and younger in Karamay City, and to evaluate the effectiveness of vaccination. MethodsA stratified whole cluster random sampling method was used to investigate the antibody seroprevalence of measles, rubella, and mumps among the healthy children aged 18 years and younger in Karamay City, and to further analyze the positive antibody rates and the geometric mean concentration (GMC) of antibodies. ResultsA total of 620 people were investigated, and the positive rates of IgG to measles, rubella, and mumps were 72.74%,62.26%, and 86.45%, respectively, with a GMC of308.94 mIU·mL^-1, 21.81 mIU·mL^-1, and 249.10 U·mL^-1. There were statistically significant differences in the positive rates of antibodies to measles, rubella, and mumps among different age groups (χ²_measles=76.707, P<0.001; χ²_rubella=60.804, P<0.001; χ²_mumps=35.407, P<0.001). The differences in positive rates were statistically significant among individuals with different intervals from the time of their last dose vaccination (χ²_measles=60.533, P<0.001; χ²_rubella=46.331, P<0.001; χ²_mumps=22.825, P<0.001). ConclusionThe antibody levels of measles, rubella and mumps among the people aged 18 years and younger in Karamay City are found to be low. Two doses of measles-mumps-rubella (MMR) vaccine should be given to children born before 2020, and if necessary, supplementary immunization with MMR vaccine should be carried out before they are enrolled in nursery and kindergarten. Additionally, regular population-based antibody surveillance should be conducted to promptly identify the people with weak immunity, which is conducive to effectively reducing and controlling the epidemic situation of measles, rubella and mumps in schools.

Oxidative stress due to aberrant metabolism is considered as a crucial contributor to diabetes and its complications. Hyperglycemia and hyperlipemia boost excessive reactive oxygen species generation by elevated mitochondrial respiration, increased nicotinamide adenine dinucleotide phosphate oxidase activity, and enhanced pro-oxidative processes, including protein kinase C pathways, hexosamine, polyol, and advanced glycation endproducts, which exacerbate oxidative stress. Oxidative stress plays a significant role in the onset of diabetes and its associated complications by impairing insulin production, increasing insulin resistance, maintaining hyperglycemic memory, and inducing systemic inflammation. A more profound comprehension of the molecular processes that link oxidative stress to diabetes is crucial to new preventive and therapeutic strategies. Therefore, this review discusses the mechanisms underlying how oxidative stress contributes to diabetes mellitus and its complications. We also summarize the current approaches for prevention and treatment by targeting the oxidative stress pathways in diabetes.
Oxidative Stress/physiology* ; Humans ; Diabetes Mellitus/physiopathology* ; Diabetes Complications/metabolism* ; Reactive Oxygen Species/metabolism* ; Glycation End Products, Advanced/metabolism* ; Animals

(+)-Strebloside, a significant bioactive compound isolated from the roots of Streblus asper Lour., demonstrates inhibitory effects against multiple malignancies. However, its specific function and underlying mechanistic pathways in Non-Hodgkin lymphoma (NHL) remain unexplored. This investigation sought to elucidate the role and potential mechanisms of (+)-strebloside-induced NHL cell death. The results demonstrated that (+)-strebloside significantly induced apoptosis and ferroptosis in NHL cells, including those from Raji cell-derived xenograft models. Mechanistic analyses revealed that (+)-strebloside enhanced six-transmembrane epithelial antigen of prostate 3 (STEAP3)-induced ferroptosis in NHL, and STEAP3 inhibition reduced the proliferation-inhibitory effects of (+)-strebloside. Furthermore, (+)-strebloside suppressed NHL proliferation through the mitogen-activated protein kinase (MAPK) pathway, and extracellular signal-regulated kinase (ERK) inhibition diminished the proliferation-inhibitory activity induced by (+)-strebloside. These findings indicate that (+)-strebloside presents promising therapeutic potential for NHL treatment.
Humans ; Ferroptosis/drug effects* ; Lymphoma, Non-Hodgkin/physiopathology* ; Cell Line, Tumor ; MAP Kinase Signaling System/drug effects* ; Animals ; Cell Proliferation/drug effects* ; Mice ; Apoptosis/drug effects* ; Membrane Proteins/genetics* ; Xenograft Model Antitumor Assays ; Male ; Mice, Nude