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.

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) block downstream signaling pathways by inhibiting receptor tyrosine kinase activity, consequently suppressing proliferation, invasion and metastasis of tumor cells. EGFR-TKIs have been proven to be highly effective in patients with late non-small cell lung cancer (NSCLC) harboring EGFR sensitive mutations, significantly better than chemotherapy. Third-generation EGFR-TKIs, such as osimertinib, have emerged as the first-line treatment for advanced NSCLC patients with sensitive EGFR mutations. However, there are still some patients who exhibit primary resistance upon initial treatment with EGFR-TKIs. The exact mechanism of primary resistance remains unknown, and may be related to factors such as the structure of EGFR mutation subtypes, concurrent mutations, BIM deletion polymorphism, and high expression of programmed cell death-ligand 1. This review summarizes the molecular mechanisms of primary resistance to EGFR-TKIs and discusses potential therapeutic strategies, with the goal of optimizing precision targeted therapy for NSCLC patients.

Gastroesophageal varices （GOV） bleeding is a severe complication of portal hypertension with a high mortality rate. Animal models are indispensable tools for investigating its pathogenesis and developing novel therapeutic strategies. This article systematically reviews the methods for establishing various GOV models， with a particular focus on their efficacy in simulating the key pathological processes such as an increase in hepatic venous pressure gradient and the risk of bleeding， and it also proposes targeted strategies for model selection. Finally， this article discusses the application prospects of emerging techniques in the era of precision medicine， such as organoids and gene editing， in order to provide model selection and a theoretical reference for exploring the mechanism and clinical translation of GOV.

ObjectiveThis study aims to construct a reconstituted high-density lipoprotein (rHDL) delivery system loaded with kinsenoside (KD@rHDL), and to systematically evaluate its function in enhancing the phagocytosis of amyloid β-protein (Aβ) by microglia and improving the inflammatory state of microglia, as well as to preliminarily explore its potential application value in the treatment of Alzheimer’s disease (AD). MethodsKD@rHDL was prepared by the film hydration method combined with probe sonication and co-incubation. Its morphology was observed by transmission electron microscopy, and the particle size and Zeta potential were measured by dynamic light scattering. The encapsulation efficiency and drug loading were determined by high-performance liquid chromatography. The affinity between KD@rHDL and Aβ was analyzed by surface plasmon resonance (SPR) to assess its feasibility as a medium for Aβ clearance. At the cellular level, after treating mouse microglial cells (BV-2 cells) with KD@rHDL and adding fluorescently labeled Aβ, the phagocytic efficiency of microglia for Aβ was detected by confocal microscopy. Meanwhile, the CCK-8 method was used to evaluate the effect of KD@rHDL on cell viability to determine its safety. The trans-barrier transport ability of KD@rHDL was detected by Transwell assay. The expression levels of NLRP3 inflammasome and downstream inflammatory factor IL-1β in LPS-induced microglia were detected by Western blot to evaluate the regulatory effect of KD@rHDL on the inflammatory state of cells. ResultsCharacterization results showed that the successfully prepared KD@rHDL presented a typical discoid structure under transmission electron microscopy, with a uniform particle size distribution, an average particle size of approximately (14.4±0.24) nm, and a suitable negative Zeta potential, demonstrating good colloidal stability. The drug content determination results indicated that the encapsulation efficiency of KD@rHDL for kinsenoside was (42.24±1.30)%, and the drug loading was (6.03±0.19)%, indicating a good drug loading capacity. The CCK-8 assay results showed that in the set concentration range, the survival rates of BV2 and HT22 cells in the KD@rHDL treatment group were all above 90%, with no significant difference from the control group, indicating good cell safety of the formulation. The results of the Aβ phagocytosis experiment indicated that, compared with the Aβ oligomers (Aβo) group alone, the fluorescence signal intensity within microglia in the KD@rHDL treatment group was significantly enhanced, and a large amount of fluorescence-labeled Aβ was observed to accumulate intracellularly under a fluorescence microscope. The SPR assay results showed that rHDL had a strong affinity for Aβ, with an affinity constant reaching the nanomolar level. Transwell assay results indicated that KD@rHDL could effectively cross the bEnd.3 cell monolayer barrier and be taken up by BV2 and HT22 cells. Western blot assay results showed that high-dose KD@rHDL treatment could significantly reduce the expression level of NLRP3 protein in LPS-induced microglia and simultaneously down-regulate the maturation and secretion of IL-1β, indicating that KD@rHDL can effectively inhibit the activation of the NLRP3 inflammasome pathway and improve the neuroinflammatory state mediated by microglia. ConclusionThis study successfully constructed a reconstituted high-density lipoprotein delivery system loaded with kinsenoside (KD@rHDL). This nano-delivery system not only significantly enhances the phagocytic clearance ability of microglia towards Aβ, but also effectively inhibits the NLRP3/IL-1β-mediated inflammatory pathway, improving the inflammatory state of microglia. The above results indicate that KD@rHDL has a synergistic effect in promoting Aβ clearance and alleviating neuroinflammation, demonstrating potential therapeutic value for AD and providing new ideas and experimental basis for the development of subsequent AD treatment strategies.

Tumors are the second leading cause of death worldwide. Exosomes are a type of extracellular vesicle secreted from multivesicular bodies, with particle sizes ranging from 40 to 160 nm. They regulate the tumor microenvironment, proliferation, and progression by transporting proteins, nucleic acids, and other biomolecules. Compared with other drug delivery systems, exosomes derived from different cells possess unique cellular tropism, enabling them to selectively target specific tissues and organs. This homing ability allows them to cross biological barriers that are otherwise difficult for conventional drug delivery systems to penetrate. Due to their biocompatibility and unique biological properties, exosomes can serve as drug delivery systems capable of loading various anti-tumor drugs. They can traverse biological barriers, evade immune responses, and specifically target tumor tissues, making them ideal carriers for anti-tumor therapeutics. This article systematically summarizes the methods for exosome isolation, including ultracentrifugation, ultrafiltration, size-exclusion chromatography (SEC), immunoaffinity capture, and microfluidics. However, these methods have certain limitations. A combination of multiple isolation techniques can improve isolation efficiency. For instance, combining ultrafiltration with SEC can achieve both high purity and high yield while reducing processing time. Exosome drug loading methods can be classified into post-loading and pre-loading approaches. Pre-loading is further categorized into active and passive loading. Active loading methods, including electroporation, sonication, extrusion, and freeze-thaw cycles, involve physical or chemical disruption of the exosome membrane to facilitate drug encapsulation. Passive loading relies on drug concentration gradients or hydrophobic interactions between drugs and exosomes for encapsulation. Pre-loading strategies also include genetic engineering and co-incubation methods. Additionally, we review approaches to enhance the targeting, retention, and permeability of exosomes. Genetic engineering and chemical modifications can improve their tumor-targeting capabilities. Magnetic fields can also be employed to promote the accumulation of exosomes at tumor sites. Retention time can be prolonged by inhibiting monocyte-mediated clearance or by combining exosomes with hydrogels. Engineered exosomes can also reshape the tumor microenvironment to enhance permeability. This review further discusses the current applications of exosomes in delivering various anti-tumor drugs. Specifically, exosomes can encapsulate chemotherapeutic agents such as paclitaxel to reduce side effects and increase drug concentration within tumor tissues. For instance, exosomes loaded with doxorubicin can mitigate cardiotoxicity and minimize adverse effects on healthy tissues. Furthermore, exosomes can encapsulate proteins to enhance protein stability and bioavailability or carry immunogenic cell death inducers for tumor vaccines. In addition to these applications, exosomes can deliver nucleic acids such as siRNA and miRNA to regulate gene expression, inhibit tumor proliferation, and suppress invasion. Beyond their therapeutic applications, exosomes also serve as tumor biomarkers for early cancer diagnosis. The detection of exosomal miRNA can improve the sensitivity and specificity of diagnosing prostate and pancreatic cancers. Despite their promising potential as drug delivery systems, challenges remain in the standardization and large-scale production of exosomes. This article explores the future development of engineered exosomes for targeted tumor therapy. Plant-derived exosomes hold potential due to their superior biocompatibility, lower toxicity, and abundant availability. Furthermore, the integration of exosomes with artificial intelligence may offer novel applications in diagnostics, therapeutics, and personalized medicine.

Persistent left superior vena cava is a rare venous variant that is often combined with cardiovascular malformations. In thoracic surgery, especially mediastinal tumor resection, neglect of this variant may make the surgery difficult and risky, and careful preoperative imaging interpretation and adequate preoperative evaluation play an important role in the perioperative safety of the patient. In this paper, we reported a case of a 17-year-old female patient with a persistent left superior vena cava combined with mediastinal tumors. She was successfully discharged 5 days after thoracoscopic surgery, and after 3 years of postoperative follow-up, no tumor recurrence was observed.

Objective To specifically extract and analyze nascent proteins synthesized by bone marrow mesenchymal stem cells(BMSCs)after transplantation into ischemic hearts using a technique employing mutant methionyl-tRNA synthetase(MetRSL247G)for nascent protein labeling,in order to explore the potential mechanisms of action in BMSCs post-transplantation.Methods Point mutation at position 274 of the MetRS gene in BMSCs was induced via lentiviral infection to enable azidonorleucine(ANL)-mediated labeling of nascent proteins in BMSCs.The labeling efficiency was verified by means of fluorescent non-canonical amino-acid tagging(FUNCAT).Thirty healthy female C57BL/6J mice(8-10 weeks old)were divided into control and experimental groups,with 15 mice in each group.The acute myocardial infarction model was constructed by ligating the left anterior descending coronary artery in experimental group,while control mice underwent only thoracotomy without coronary ligation.After modeling,both groups received intramyocardial injections of MetRSL247G-modified BMSCs(MetRSL247G-BMSCs)at 3 different sites in the peri-infarct ischemic region.Mice were intraperitoneally injected with ANL every 6 hours for 4 times on postoperative days 0,2,and 6(n=5 for each time point)respectively,euthanized 24 h after the last injection,and cardiac tissues were isolated.The newly synthesized and labeled proteins produced by BMSCs after transplantation into the myocardium of experimental and control groups were collected,using an enrichment technique for ANL-tagged proteins and liquid chromatography-tandem mass spectrometry(LC-MS)analysis.Gene ontology(GO)analysis,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis,protein-protein interaction(PPI)analysis,and heatmap visualization analysis were performed to identify differentially expressed proteins at the 3 time points and screen key pathways and genes.Results Under fluorescence microscopy,the MetRSL247G lentivirus-infected BMSCs were observed to be labelled with mCherry signals,confirming the successful construction of the MetRSL247G-BMSCs cell line.Green fluorescent signals were detected only in nascent proteins in culture medium containing both MetRSL247G-BMSCs and ANL,validating the sensitivity and specificity of the labeling method.GO analysis revealed that differentially expressed proteins were primarily involved in basic cellular biological processes such as extracellular exosome formation,extracellular matrix organization,and focal adhesion.KEGG and PPI analyses indicated that the differential proteins were mainly involved in complement and coagulation cascade pathway,actin cytoskeleton regulation pathway,and apoptosis pathway.Heatmap analysis showed significantly upregulated expression of anti-apoptosis and cell adhesion-related factors in experimental group on day 1(P＜0.05),upregulated anti-apoptotic factors,pro-apoptotic factors,and cell adhesion-related factors on day 3(P＜0.05),and upregulated anti-apoptotic factors,cell differentiation-related factors,and cell adhesion-related factors on day 7(P＜0.05)compared with control group.Expression of apoptosis-inducing factor 1 was significantly downregulated on days 1 and 7(P＜0.05).On day 3,most differentially expressed proteins,including anti-apoptosis factors(Protein S100-A11,Clusterin,Gelsolin),pro-apoptosis factor(Cathepsin B),cell differentiation-related factor(Transgelin-2),and cell adhesion-related factors(Cofilin-1,Periostin,Fibronectin)were significantly upregulated(P＜0.05).Conclusions The MetRSL247G mutation enables BMSCs to incorporate ANL and synthesize labeled proteins,confirming the feasibility of this nascent protein labeling technique.Nascent proteins of BMSCs in ischemic myocardium primarily contribute to extracellular exosome secretion and extracellular matrix organization.BMSCs may adapt to and respond to ischemic and hypoxic environments by influencing complement and coagulation cascades,activating inflammatory factors,regulating actin cytoskeleton structure,and modulating apoptosis,thereby maintaining the survival of BMSCs.

Objective:To explore the curative efficacy and safety of microwave ablation(MWA)combined with percutaneous ethanol injection(PEI)in treating thyroid cystic solid nodule.Methods:A total of 62 patients with thyroid cystic solid nodule,who admitted to The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University from January 2021 to December 2022,were selected,and they were divided into microwave group(n=28,only single MWA)and combination group(n=34,MWA combined with PEI)according to different treatment plans.The reduction rate of the volume of thyroid nodules,indicators of thyroid function,clinical symptom and the score of physical signs,as well as the incidence of perioperative complications,were compared between two groups after treatment.Results:After treatment,the reduction rate of the volume of thyroid nodule was(88.97±6.36)%in the combination group,which was higher than that(88.15±5.69)%in the microwave group,and the differences in those indicators between the two groups were statistically significant(t=2.465,P＜0.05).The differences of the indicators of thyroid function before and after treatment between two groups were not significant(P＞0.05).The clinical symptoms and the scores of physical signs of both groups after treatment were lower than that before treatment(P＞0.05).The incidence of perioperative complications in the combination group was 17.65%,which was lower than 42.68%in the microwave group(P＜0.05),and the difference of that between the two groups was significant(x2=4.736,P＜0.05).Conclusion:The curative efficacy of the combination of MWA and PEI is better than MWA alone,which has better safety.

Objective:To explore the application value of radiomics, deep learning, and their combined models in predicting the efficacy of radioiodine adjuvant therapy in patients with papillary thyroid cancer (PTC).Methods:A retrospective analysis was conducted on the clinical and imaging data of 131 PTC patients (38 males, 93 females; age 41(33, 48) years) who received first 131I treatment at the Affiliated Hospital of Guilin Medical University from January 2018 to March 2023. Patients were randomly divided into a training set ( n=105) and a test set ( n=26) at the ratio of 8∶2. Multivariate logistic regression analysis was used to screen clinical features to determine independent predictors affecting the efficacy of 131I therapy. Radiomics and deep learning features were extracted from the enhanced CT scans and were combined by using the extremely randomized trees (ExtraTrees) algorithm to construct radiomics, deep learning, and combined models. The predictive abilities of the models were evaluated by AUC, and the Delong test was applied to compare the difference between AUCs. Results:Higher pre-ablation stimulated thyroglobulin (ps-Tg) levels (odds ratio( OR)=1.060, 95% CI: 1.025-1.095, P=0.004) and bilateral lesions ( OR=5.085, 95% CI: 1.452-17.814, P=0.033) were independent predictors of the efficacy of 131I therapy in intermediate to high-risk PTC patients. In the training set, the radiomics model (AUC=0.853) and combined model (AUC=0.880) significantly outperformed the deep learning model (AUC=0.711; Z values: 2.48, 3.09, P values: 0.013, 0.002), while there was no statistically significant difference between the radiomics and combined models ( Z=0.51, P=0.610). In the test set, AUCs of the radiomics, deep learning, and combined models were 0.746, 0.624, and 0.876, respectively, and the AUC of the combined model was higher than that of the radiomics model or deep learning model ( Z values: 2.05, 1.99, P values: 0.040, 0.047). Conclusion:The combined model demonstrates superior performance over the standalone radiomics model and deep learning model in predicting the efficacy of 131I treatment in PTC patients.

Objective To develop a machine learning-based risk prediction model for postoperative acute kidney injury(AKI)and a model for mortality in obese patients admitted to intensive care unit(ICU)in order to improve early warning and prognostic evaluation to support clinical decision-making.Methods Data of obese postoperative ICU patients were retrospectively retrieved from the MIMIC-Ⅳ and eICU databases for statistical analysis.Ultimately,2 520 patients(670 from MIMIC-Ⅳ and 1 850 from eICU databases)were included to build the risk prediction models for AKI and mortality.The data included demographic information,vital signs,laboratory findings,surgical types,comorbidities,and medication use.After data cleaning and preprocessing,Boruta feature selection was applied,followed by the construction of prediction models using 7 machine learning algorithms,that is,Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),k-Nearest Neighbors(KNN),Na?ve Bayes(NB),Neural Network(NNET),Support Vector Machine(SVM),and XGBoost.Model performance was evaluated through cross-validation and external validation.Results In the risk prediction models of AKI,the SVM model achieved the highest AUC value of 0.80 in the testing set and 0.71 in the external validation test.For the risk prediction models of mortality,the GBM model outperformed others in the prediction,attaining an AUC value of 0.91 in the testing set.Conclusion Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed,and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients.