Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality, characterized by poor prognosis due to its high proliferative and invasive potential. Tumor metabolic reprogramming, particularly involving glucose metabolism, is essential for tumor survival. This study investigates the role of the Hippo pathway effector transcriptional co-activator with PDZ-binding motif (TAZ) in regulating gluconeogenesis and promoting tumorigenesis in HCC. Methods: TAZ expression in HCC was analyzed using The Cancer Genome Atlas data and validated in clinical samples and cell lines. TAZ was overexpressed or silenced in HCC cell lines to evaluate its effects on cell proliferation, apoptosis, migration, and invasion. The expression and prognostic relevance of the gluconeogenesis-related genes phosphoenolpyruvate carboxykinase 1 (PCK1) and glucose-6-phosphatase (G6PC) were examined, along with their correlation with TAZ expression. Tumor growth was assessed in nude mice. Interactions between TAZ and the glucocorticoid receptor (GR) were investigated using co-immunoprecipitation, immunofluorescence, and chromatin immunoprecipitation assays. Results: TAZ was significantly upregulated in HCC tissues and cell lines. TAZ overexpression enhanced proliferation, reduced apoptosis, and promoted migration and invasion. In contrast, PCK1 and G6PC were downregulated in HCC and showed a negative correlation with TAZ expression. Conclusion TAZ modulates gluconeogenesis and accelerates tumor growth, whereas its knockdown attenuates tumor progression. TAZ interacts with GR, suppressing its transcriptional activity on gluconeogenic gene promoters.

To analyze the clinical and genetic features of oculopharyngodistal myopathy (OPDM) patients and compare the phenotypic differences among various causative genes.

ObjectiveStroke poses a heavy burden due to its high mortality and morbidity rates. Accurate and real-time detection of lesions is pivotal for prompt clinical intervention and favorable prognosis. Electrical impedance tomography (EIT) and microwave tomography (MWT) have emerged as compelling alternatives for stroke screening, owing to their non-ionizing, non-invasive and portable nature. EIT provides information on tissue conductivity, and MWT offers high sensitivity to changes in dielectric properties. However, single-modality imaging is inherently limited, EIT suffers from low sensitivity to deep-seated tissues and severe ill-posedness of inverse problems, whereas MWT is challenged by strong nonlinearity in inverse scattering and susceptibility to modeling errors. Consequently, the clinical utility of standalone EIT or MWT for stroke diagnosis remains constrained by poor spatial resolution and imaging artifacts. To improve the accuracy and robustness of stroke imaging, a dual-modality fusion conditional denoising diffusion probabilistic model (DM-DDPM) was proposed for high-precision dual-modality image reconstruction. MethodsA dual-encoder network with a symmetric architecture and independently trained parameters was constructed to extract heterogeneous features separately from EIT boundary voltage measurements and MWT scattered field signals. Attentional feature fusion (AFF) is employed to integrate complementary information from the two modalities adaptively, generating robust fused priors that suppress redundant noise while preserving key physical characteristics. Subsequently, the fused priors are embedded into a Transformer-based diffusion model via a cross attention mechanism to guide the reverse denoising process. This approach effectively reduces artifacts and enhances the stability of conductivity distribution reconstruction. Time step embedding is introduced to enable the network to perceive the diffusion stage and further improve the accuracy of noise prediction. ResultsSimulated experiments demonstrated that DM-DDPM significantly outperforms single-modality and multi-modality networks under various noise levels. A head model simulation dataset was constructed based on COMSOL Multiphysics, and tests were carried out under 50 dB, 40 dB and 30 dB signal-to-noise ratio levels. At 30 dB, the average relative error (RE) was below 0.20, while the structural similarity index measure (SSIM) and correlation coefficient (CC) remained above 0.90 and 0.89, respectively. Compared with single-modality and multi-modality networks, artifacts were significantly reduced, lesion edges were clearer, and localization was more accurate. The model maintains high reconstruction quality and strong robustness for single, double, and triple lesions simultaneously. Furthermore, physical experiments were conducted using a 16-electrode EIT system and a 16-antenna MWT system with asynchronous data acquisition. These experiments confirmed the feasibility of the method in real-world scenarios and demonstrated that it can robustly reconstruct simulated lesions despite environmental interference and measurement noise, validating its reliability for practical clinical applications. ConclusionThe proposed method effectively combines complementary dual-modality information with a conditional diffusion model. Low accuracy and poor noise resistance in single-modality imaging were effectively addressed, while the noise amplification issue caused by direct multimodal data fusion was avoided. The proposed algorithm exhibits strong anti-noise interference ability and high imaging stability in both simulation and physical experiments. Precise localization of stroke lesions with different quantities was achieved, providing a high-precision, and practical technical support for clinical stroke detection.

Background: Recurrent pregnancy loss undermines the physical and mental health of women. Recent randomized controlled trials have reported some effects of traditional Chinese medicine (TCM); however, whether various TCM methods have different effectiveness remains unclear. Objective: To comprehensively evaluate the efficacy and adverse events of TCM for patients with RPL and to explore whether various TCM methods have different effectiveness. Methods: Ten databases were searched up to May 27, 2024. The risk of bias was assessed using the RoB2 tool. The certainty of the evidence was evaluated using the grading of Recommendations, Assessment, Development, and Evaluation tool. Pairwise and network analyses were conducted using Stata 18.0. Results: A total of 47 randomized controlled trials enrolling 6678 women with RPL were included. Pairwise analysis showed that use of TCM had a significantly lower miscarriage rate (RR 0.50 [95% CI 0.45, 0.55]), lower preterm birth rate (RR 0.81 [95% CI 0.67, 0.98), and lower adverse event rate (RR 0.46 [95% CI 0.37, 0.58]). Moreover, use of TCM was associated with a higher alive-fetus rate (RR 1.21 [95% CI 1.15, 1.26]), live-birth rate (RR 1.20 [95% CI 1.15, 1.25]), and full-term rate (RR 1.37 [95% CI 1.23, 1.53]) compared with nonuse of TCM. Network analysis demonstrated that Bushenshugan combined with conventional Western medicine was ranked the best for the reduction of miscarriage rate. Discussion: Use of TCM is more likely to improve pregnancy outcomes and reduce adverse events compared with nonuse of TCM in patients with RPL. Different TCM methods have differences in reducing the miscarriage rate. The Bushenshugan method might be a potential optimal TCM therapy, but more high-quality evidence is needed to further validate and evaluate the efficacy and safety.

ObjectiveTo explore the effects of vascular endothelial growth factor A （VEGFA） rs2010963 and rs3025039 polymorphisms on chemotherapy toxicities and clinical prognosis in children with brain tumors. MethodsA total of 104 pediatric patients with brain tumors receiving standardized chemotherapy were enrolled. Matrix-assisted laser desorption/ionization time of flight mass spectrometry was used for VEGFA rs2010963 and rs3025039 genotyping. The χ² test was applied to analyze the association between genotypes and chemotherapy‑related toxicities. Cox regression was used to evaluate the correlations of clinicopathological characteristics and genotypes with the progression‑free survival （PFS）. In addition， bioinformatic analyses were conducted to investigate the regulatory factors potentially affected by the two SNP loci. ResultsThe VEGFA expression in brain tumors （5.17±1.81） was significantly higher than that in normal tissues （4.33±1.56， P<0.001）. Patients with high VEGFA expression had significantly worse overall survival than patients with low VEGFA expression （P<0.001）. Among the 104 children with brain tumors included， the rs2010963 CC， CG， and GG genotypes accounted for 14.42%， 55.77%， and 29.81%， respectively. The frequencies of C and G alleles were 42.31% and 57.69%， respectively. The rs3025039 CC， CT， and TT genotypes accounted for 70.19%， 25.96%， and 3.85%， respectively. The frequencies of C and T alleles were 83.17% and 16.83%， respectively. The children with the rs3025039 CC genotype had significantly higher incidences of thrombocytopenia （46.58%） and gastrointestinal toxicity （56.16%） than CT genotype carriers （22.22% and 33.33%， respectively， P<0.05）， and significantly lower incidences of coagulation disorders （4.11%） than TT genotype carriers （50.00%， P<0.05）.The incidence of hyperlipidemia （2.74%） was significantly lower than that in the CT genotype carriers （14.82%， P<0.05）. The tumor type and the rs2010963 genotype were significantly associated with PFS （P<0.05） in univariable and multivariable Cox regression analysis. Bioinformatic analysis indicated that the rs2010963 and rs3025039 polymorphisms regulated VEGFA expression by affecting the binding of transcription factors and miRNAs to their target gene sequences， respectively. ConclusionThe VEGFA rs3025039 CC genotype is a risk factor for thrombocytopenia and gastrointestinal toxicity， and a protective factor for coagulation disorders and hyperlipidemia. The rs2010963 CG genotype is a protective factor for brain tumor progression.

Abstract To promote the mental health of college students and build campus based psychological support system, the study explains that current applications of digital health interventions (DHIs) include independent forms based on a single technology or platform, as well as integrated forms that combine multiple digital technologies with traditional mental health services. These interventions have positive effects on alleviating negative emotions among college students, enhancing psychological resilience, improving quality of life, and ameliorating academic performance. However, differences still exist in the stability of intervention effects. Future development requires continuous improvement in institutional construction, ethical governance and capacity building.

Lung cancer ranks first in morbidity and mortality among malignant tumors in China. Low-dose computed tomography (LDCT), as the primary screening method, faces increasingly prominent challenges of false positives and overdiagnosis associated with its high sensitivity. In recent years, the integration of artificial intelligence (AI) and three-dimensional reconstruction technology has provided a novel approach to addressing these challenges. This review highlights how AI and three-dimensional reconstruction contribute to improving image quality, enabling precise identification of pulmonary nodules and intelligent risk stratification, optimizing dynamic follow-up strategies, and assisting in preoperative planning, thereby driving the transformation of the LDCT screening paradigm. Meanwhile, current technical limitations and future directions are also discussed.

Objective To construct an index system for assessment of schistosomiasis transmission risk following natural disasters such as rainstorms, floods, earthquakes, mudslides, and landslides, so as to provide insights into rapid identification of schistosomiasis transmission risk post-disasters and formulation of targeted schistosomiasis control strategies. Methods An initial framework for the index system for assessment of schistosomiasis transmission risk following natural disasters was drafted through literature review, brainstorming, and focus group discussions. Two rounds of expert correspondence consultations were conducted using the Delphi method to refine and finalize the system, and the degrees of expert activeness, authority and endorse ment, and consensus were evaluated. In addition, the weights of each index were calculated using the analytic hierarchy process. Results A total of 18 experts participated in the consultation. The expert positive coefficients were 100.00% and 94.44% for two rounds of consultations, with authority coefficients of 0.92 and 0.94, respectively. The coefficients of coordination on the index importance, rationality and operability were 0.209, 0.185, 0.222 and 0.407, 0.214, 0.257 for two rounds of consultations, respectively, and all consistency tests were statistically significant (χ² = 246.771 to 505.278, all P values < 0.001). Following two rounds of expert consultations, an index system consisting of 6 first-level indicators, 15 second-level indicators, and 49 third-level indicators was ultimately constructed. In terms of first-level indicators, “disaster situation”, “previous epidemics”, “healthcare guarantee”, “response capacity” and “emergency recovery” had the highest weights, each at 18.18%. Regarding second-level indicators, “Schistosoma japonicum infections in animals”, “S. japonicum infections in snails” and “medical treatment” had the highest weights, each at 7.35%. In terms of third-level indicators, ten items had the highest weights, including “identification of schistosomiasis cases”, “detection of S. japonicum infections in wild feces”, “detection of S. japonicum infections in snails”, “reserves of schistosomiasis diagnostic/testing reagents and consumables”, “reserves of chemotherapy agents for human and animal schistosomiasis”, “reserves of cercariacides”, “periodical surveillance on schistosomiasis”, “identification of schistosomiasis transmission risk and timely response”, “normal provision of diagnosis and treatment services” and “post-disaster schistosomiasis surveillance”, each at 2.40%. Conclusion A scientific, systematic, and practical index system has been constructed for assessment of schistosomiasis transmission risk following natural disasters, which may provide insights into rapid post-disaster identification of schistosomiasis transmission risk, formulation of targeted schistosomiasis control strategies and optimization of resource allocation.

ObjectiveTo analyze the characteristics of 150 patients with spinal cord injury complicated with spasticity. MethodsA cross-sectional survey was conducted on 150 patients with spinal cord injury accompanied by spasticity from September, 2019 to December, 2024. Their age, gender, cause of injury, injury site, severity of injury, spasticity severity and other indicators were recorded. The relationships between different characteristics were analyzed, and a correlation analysis of disease duration, spasticity grade, injury level, injury severity and age were conducted. ResultsThere was no significant difference in age distribution between patients with tetraplegia and paraplegia (Z = 0.806, P = 0.420). The proportions of trauma (χ² = 3.982, P = 0.046) and tetraplegia (χ² = 10.559, P = 0.010) were higher in males than in females. Trauma was the main cause of injury in both tetraplegia and paraplegia patients; the proportion of tetraplegia was higher than paraplegia in trauma patients, while paraplegia was higher than tetraplegia in non-trauma patients (χ² = 11.885, P < 0.001). Patients with tetraplegia was dominated by incomplete injury, whereas patients with paraplegia was dominated by complete injury (χ² = 10.885, P = 0.012). Grade A injury was predominant in trauma patients (P = 0.003). Spasticity grade showed a very weak positive correlation with disease duration (r = 0.175, P = 0.032) and age (r = 0.168, P = 0.040). Injury severity showed a very weak positive correlation with age (r = 0.183, P = 0.025). ConclusionCharacteristics of patients with spinal cord injury complicated with spasticity is different with gender, cause of injury, injury level, injury severity.

ObjectiveProtein-protein interactions (PPIs) are fundamental to the execution of biological functions within living cells. However, traditional biochemical methods, such as co-immunoprecipitation (Co-IP), often fail to capture transient, weak, or membrane-associated interactions due to the stringent detergent requirements for cell lysis. Proximity labeling (PL) has emerged in recent years as a transformative technology for mapping the proteomes of specific subcellular compartments and identifying dynamic interactomes in situ. Golgi protein 73 (GP73, also known as GOLPH2), a resident type II Golgi transmembrane protein, is a well-recognized clinical biomarker for liver diseases, including hepatocellular carcinoma (HCC). Despite its clinical significance, the comprehensive physiological and pathological functions of GP73 remain partially understood. This study aims to establish an APEX2-mediated proximity labeling system specifically targeting GP73 to map its interactome in a living cellular environment, thereby providing new insights into its molecular roles and regulatory mechanisms. MethodsTo achieve spatial specificity, we first constructed a stable cell line expressing a fusion protein consisting of GP73 and the engineered soybean peroxidase APEX2. The localization of the GP73-APEX2 fusion protein was validated to ensure it correctly targeted the Golgi apparatus. The proximity labeling reaction was initiated by incubating the cells with biotin-phenol (BP) for 30 min, followed by a brief (1 min) treatment with1 mmol/L hydrogen peroxide (H₂O₂). This catalytic reaction converts BP into highly reactive, short-lived biotin-phenoxyl radicals that covalently attach to endogenous proteins within a small labeling radius of the GP73-APEX2 enzyme. Subsequently, the cells were quenched, and biotinylated proteins were enriched using high-affinity streptavidin-coated magnetic beads. The captured “neighbor” proteins were subjected to on-bead digestion and analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS) for high-throughput identification. Rigorous bioinformatics analysis, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction network mapping, was performed to interpret the biological significance of the identified candidates. ResultsOur results demonstrate the successful establishment of a robust and sensitive APEX2-based proximity labeling system for GP73. We identified a total of 95 high-confidence interacting proteins that were significantly enriched in the GP73 proximity proteome compared to control groups. Bioinformatics analysis revealed that these interactors were predominantly associated with biological processes such as vesicular transport, protein localization, and, most notably, molecular functions related to “ribosome binding” and “translation regulation”. This suggested an unexpected role for the Golgi-resident GP73 in the cellular translation machinery. To validate these findings, we performed targeted biochemical assays which confirmed a direct interaction between GP73 and the subunits of the eukaryotic translation initiation factor 3 (eIF3) complex, specifically EIF3G and EIF3I. Furthermore, functional validation using the surface sensing of translation (SUnSET) assay—a non-radioactive method to monitor protein synthesis—revealed that the overexpression of GP73 significantly promoted global protein translation levels in the cell, whereas its depletion or inhibition resulted in reduced translation efficiency. ConclusionThis study successfully utilized APEX2-mediated proximity labeling to provide the first systematic map of GP73 interactome in living cells. Our findings uncover a novel, unconventional function of GP73 as a regulator of cellular protein translation, likely mediated through its interaction with the eIF3 complex. This discovery significantly broadens our understanding of the biological roles of GP73 beyond its traditional function in the Golgi apparatus and suggests that it may act as a bridge between Golgi-related trafficking and the protein synthesis machinery. Furthermore, the technical framework established in this study provides a valuable template for investigating other complex organelle-associated protein networks and resolving transient macromolecular interactions in various physiological and pathological contexts.