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.

Methods: Fifty patients who underwent UBE-TLIF and 50 patients who underwent W-TLIF, each with >2 years of follow-up, were retrospectively analyzed. Outcomes included operative parameters, time to postoperative mobilization, paravertebral muscle atrophy and fat infiltration rates, clinical scores (Visual Analog Scale [VAS], Oswestry Disability Index [ODI], Japanese Orthopaedic Association [JOA]), modified Macnab criteria, fusion rates, and complications. Results: Compared with W-TLIF, the UBE-TLIF group had significantly less intraoperative blood loss, shorter operative times, and lower postoperative drainage volumes (p <0.05). The UBE-TLIF group showed faster postoperative recovery and shorter hospital stays. At 6 months, 1 year, and 2 years, W-TLIF patients had higher multifidus and erector spinae atrophy, and greater paravertebral muscle fat infiltration (p <0.05). The UBE-TLIF group also had lower VAS and ODI scores at 1 year and 2 years (p <0.05) and fewer surgical complications (6% vs. 10%). Fusion rates (94% vs. 92%) and modified Macnab outcomes (88% vs. 86%) were comparable (p >0.05). Conclusions UBE-TLIF is associated with reduced intraoperative trauma, quicker recovery, and fewer complications. In the long-term, it better preserves paravertebral muscle integrity and provides superior pain and functional outcomes.

ObjectiveType 2 diabetes mellitus (T2DM) often causes severe hepatic metabolic complications, dominated by metabolic associated fatty liver disease (MAFLD). Persistent hepatic steatosis and oxidative stress further trigger steatohepatitis and progressive liver damage, increasing the mortality risk of diabetic patients. Aerobic exercise effectively improves hepatic lipid metabolism and antioxidant capacity, but poor patient adherence restricts its long-term clinical application. Mitochondrial-derived mitochondrial open reading frame of the 12S rRNA type-c (MOTS-c) is a key peptide regulating insulin sensitivity and hepatic redox homeostasis. This study aimed to explore the protective mechanism of MOTS-c against T2DM-related liver injury and its combined beneficial effect with aerobic exercise via the NRF2/PPARγ signaling axis. This study aimed to investigate whether MOTS-c cooperates with aerobic exercise to alleviate T2DM-associated hepatic oxidative stress and metabolic dysfunction by activating the NRF2/PPARγ axis, and to clarify the molecular and transcriptomic characteristics of their combined intervention. MethodsStable MOTS-c overexpression and knockdown HepG2 cell lines were constructed using lentiviral transfection. An oleic acid-induced cellular lipid accumulation model and NRF2-knockout cell model were applied to verify the NRF2-dependent mechanism ofMOTS-c. Intracellular lipid deposition, triglyceride levels, antioxidant enzyme activities, and the expression of NRF2/PPARγ pathway-related genes and proteins were detected. In vivo, a T2DM rat model with obvious hepatic steatosis was established via a high-fat and high-sucrose diet combined with streptozotocin injection. Model rats received aerobic exercise, MOTS-c intraperitoneal injection, or combined intervention. We detected systemic glycolipid metabolic indicators, hepatic histopathological changes, and the expression of core proteins in the hepatic NRF2/PPARγ axis. Hepatic transcriptomic sequencing was performed to screen differentially expressed genes (DEGs) and enrich key pathways co-regulated by MOTS-c and aerobic exercise. ResultsCellular results showed that MOTS-c overexpression significantly reduced oleic acid-induced lipid deposition, enhanced antioxidant enzyme activity, and upregulated NRF2 and PPARγ expression. Conversely, MOTS-c knockdown aggravated hepatic lipid accumulation and oxidative damage and inhibited NRF2/PPARγ pathway activation. NRF2 knockout completely eliminated the protective effects of MOTS-c on lipid metabolism and redox balance, confirming its NRF2-dependent regulatory mechanism. In T2DM rats, both MOTS-c supplementation and aerobic exercise effectively improved insulin resistance, corrected glycolipid metabolic disorders, and alleviated hepatic steatosis, while consistently activating the hepatic NRF2/PPARγ axis. Compared with single intervention, the combined treatment showed a better improvement trend in hepatic metabolic and oxidative injury, without definitive synergistic effects. Transcriptomic analysis revealed that the co-regulated DEGs of MOTS-c and aerobic exercise were primarily enriched in lipid metabolism and PPAR signaling pathways, with multiple antioxidant and lipid-regulating genes significantly modulated by combined intervention. ConclusionMOTS-c exhibits obvious exercise-mimetic hepatoprotective effects in T2DM. It activates the hepatic NRF2/PPARγ axis to strengthen antioxidant defense, stabilize lipid metabolism, and relieve T2DM-associated hepatic steatosis and oxidative damage. Furthermore, MOTS-c produces additive beneficial effects with aerobic exercise, showing a superior intervention trend on diabetic liver dysfunction. This study identifies the NRF2/PPARγ axis as the core mechanism of MOTS-c-regulated hepatic protection, elucidates the transcriptomic basis of combined intervention, and provides a reliable theoretical basis and potential therapeutic target for clinical intervention in T2DM-complicated MAFLD.

Glycosylation constitutes a critical, highly intricate, and diverse co- and post-translational modification characterized by the covalent attachment of sugar moieties to proteins, lipids, or small RNAs. Complex glycans are ubiquitously present across nearly all living organisms. Despite their prevalence, our comprehension of glycan diversity remains limited, likely due to the inherent challenges associated with elucidating their structural complexity. Among post-translational modifications, protein glycosylation is notably prevalent, involving the enzymatic transfer of oligosaccharides to specific amino acid residues by glycosyltransferases. This modification plays a pivotal role in modulating protein function, including participation in various biological and biochemical recognition processes. G protein-coupled receptors (GPCRs), encoded by approximately one thousand genes, share a conserved architecture comprising seven transmembrane helices interconnected by three intracellular and three extracellular loops. Representing the largest family of human membrane proteins, GPCRs regulate a vast array of physiological and pathological processes, thereby constituting the most extensive class of therapeutic targets. In mammalian systems, the majority of GPCRs undergo glycosylation predominantly at their extracellular N-terminus or extracellular loops, primarily through N-linked and O-linked glycosylation. These covalent carbohydrate modifications exert profound effects on multiple facets of GPCR biology, including endoplasmic reticulum folding and quality control, membrane trafficking and surface expression, receptor internalization and recycling or degradation, ligand binding and signal transduction, biased signaling, and receptor dimerization. Notably, glycosylation can exert both positive and negative regulatory influences on these processes. Dysregulation of GPCR glycosylation has been implicated in a range of pathological conditions, such as cancer, diabetes, and neurological disorders, underscoring its physiological and pathological significance. Aberrant glycosylation patterns may lead to dysfunctional receptor signaling, thereby contributing to disease progression. Consequently, elucidating the precise roles of glycosylation in GPCR function not only enhances fundamental understanding of receptor biology but also facilitates the development of novel therapeutic strategies targeting glycosylation pathways or specific GPCR glycoforms. Although the functional consequences of glycosylation have been investigated for several decades, delineating their exact structural underpinnings has remained challenging due to the intrinsic flexibility and heterogeneity of carbohydrate structures. Recent advances in structural biology, particularly single-particle cryo-electron microscopy (cryo-EM) and X-ray crystallography, have catalyzed a paradigm shift in our understanding of GPCR glycosylation. The integration of these sophisticated structural techniques with biochemical approaches has redefined glycosylation as a complex structural element integral to receptor function. These developments provide a molecular framework for comprehending how glycans influence receptor pharmacology and open new avenues for the rational design of glyco-engineered biologics and allosteric modulators targeting specific extracellular motifs. This mini-review concentrates on glycosylation within the GPCR superfamily, summarizing the impact of glycosylation modifications on receptor function and regulatory mechanisms, recent progress in the structural biology of GPCR glycosylation, and prospective directions for future research in this field.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Radiation prevention and treatment drugs are a rapidly developing field.Radiation prevention and treatment drugs can be roughly divided into four categories:chemical synthetic drugs,biological products,natural plant extracts and traditional Chinese medicine compounds,which are widely used in medical,scientific research and other fields.This paper reviews the classification of radiation prevention and treatment drugs,which can be roughly divided into four categories:chemical synthetic drugs,biological products,natural plant extracts and traditional Chinese medicine compounds.At the same time,its mechanism of action and clinical application are elaborated in detail,and the risk assessment is carried out from the aspects of effectiveness,safety and drug interaction.Finally,the risk reduction strategies are summarized from the aspects of clinical medication specification and monitoring,continuous drug safety research,improvement of emergency reserve and support capacity and construction of full-cycle regulatory system,so as to provide reference for the rational application and further research of radiation prevention and treatment drugs.

Objective To explore the predictive value of dose surface histogram(DSH)in image guided radiotherapy(IGRT)for radiotherapy-induced acute radiation proctitis(ARP)in cervical cancer(CCA).Methods Totally 380 patients with CCA IGRT admitted to some hospital from May 2019 to May 2023 were selected prospectively and randomly divided into a control group(n=1 80)and an experimental group(n=200).The patients in the 2 groups were followed up and the incidence rates of ARP were counted,and rectal dose distribution was evaluated using dose volume histogram(DVH)in the control group and DSH in the experimental group.The predictive values of DVH and DSH for ARP were evaluated and compared using ROC curves.Statistical analysis was performed using SPSS 21.0 software.Results The two groups did not have statistically significant difference in the incidence rate of ARP(P＞0.05),while there were significant differences in the evaluation indicators of the rectal dose distribution(P＜0.05).V40,V50,S40 and S50 proved to have low predictive values for grade Ⅰ-Ⅳ ARP with AUC 0.700(P＜0.05);V60 and S60 had moderate predictive values for grade Ⅰ-Ⅳ ARP with AUC greater than 0.700 and less than or equal to 0.900(P＜0.05);V70,V78,S70 and S7s showed high predictive values for grade Ⅰ-Ⅳ ARP with AUC higher than 0.900(P＜0.05).Delong's test results indicated that DVH and DSH had no significant differences in AUC when used to predict gradeⅠ-Ⅳ ARP(allP＞0.05).Conclusion DSH is essentially the same as DVH when used for the prediction of grade Ⅰ-Ⅳ ARP due to CCA IGRT,and thus can be used for the supplementation and optimization of radiotherapy planning systems.[Chinese Medical Equipment Journal,2025,46(3):48-53]

The xylitol dehydrogenase(XDH)is a crucial enzyme involved in the xylose utilization in pentose-catabolizing yeasts and fungi.In addition to producing xylulose,XDH can also be employed to develop a biosensor for monitoring xylitol concentration.In this study,the gene encoding the thermophilic fungus Talaromyces emersonii XDH(TeXDH)was heterologously expressed in Escherichia coli BL21(DE3)at 16 ℃ in the soluble form.Recombinant TeXDH with high purity was purified by using a Ni-NTA affinity column.Size-exclusion chromatography and SDS-PAGE analysis demonstrated that the puri-fied recombinant TeXDH exists as a native trimer with a molecular mass of approximately 116 kD,and is composed of three identical subunits,each with a molecular weight of around 39 kD.The TeXDH strictly preferred NAD+as a coenzyme to NADP+.The optimal temperature and pH of the TeXDH were 40 ℃and 10.0,respectively.After EDTA treatment,the enzyme activity of TeXDH decreased to 43.26％of the initial enzyme activity,while the divalent metal ions Mg2+or Ca2+could recover the enzyme activity of TeXDH,reaching 103.32％and 110.69％of the initial enzyme activity,respectively,making them the optimal divalent metal ion cofactors for TeXDH enzyme.However,the divalent metal ions of Mn2+,Ni2+,Cu2+,Zn2+,Co2+,and Cd2+significantly inhibited the activity of TeXDH.ICP-MS and molecular doc-king studies revealed that 1 mol/L of TeXDH bound 2 mol/L Zn2+ions and 1 mol/L Mg2+ion.Further-more,TeXDH exhibited a high specificity for xylitol,laying the foundation for the development of future xylitol biosensors.

Objectives:This study aims to evaluate the causal relationship between plasma proteins and myocardial infarction(MI)using two-sample bidirectional Mendelian randomization(MR)analysis,identify key biomarkers,and validate their expression.Methods:The study utilized publicly available genome-wide association study(GWAS)data of 4 907 plasma proteins as the exposure factor,with single nucleotide polymorphisms(SNPs)as instrumental variables,and four MI datasets as outcomes.Two-sample MR analysis was performed using the inverse variance weighted(IVW)method,complemented by simple model,weighted model,weighted median estimator(WME),and MR-Egger regression methods to assess the causal relationship between exposure factors and outcomes.Venn diagrams and word clouds were used to screen proteins associated with MI as candidate biomarkers.Reverse MR analysis was conducted to evaluate reverse causality.Sensitivity analysis was performed to assess the robustness of the results.Immunohistochemistry(IHC)was used to validate the expression of proteasome activator subunit 1(PSME1)and vacuolar protein sorting 29(VPS29)in the aorta of mice,and enzyme-linked immunosorbent assay(ELISA)was used to verify the expression of PSME1 and VPS29 in plasma from patients with acute myocardial infarction(AMI).Results:The two-sample MR analysis indicated that PSME1 was significantly negatively associated with myocardial infarction in all four datasets,with OR(95%CI)of 0.684(0.557-0.839),0.990(0.987-0.993),0.579(0.448-0.748),and 0.993(0.990-0.996),respectively,with all P<0.001.Similarly,VPS29 also showed a significant negative association with MI in all four datasets,with OR(95%CI)of 0.902(0.862-0.945),0.998(0.997-0.999),0.866(0.808-0.929),and 0.998(0.997-0.999),respectively,with all P<0.001.Reverse MR analysis did not detect reverse causality,and sensitivity analysis confirmed the robustness of the results.IHC results showed significantly reduced expression of PSME1 and VPS29 in the aortas of AMI mice with an atherosclerotic background compared to control mice(both P<0.05).ELISA results indicated significantly lower plasma levels of PSME1 and VPS29 in AMI patients compared to healthy controls(both P<0.05).Conclusions:Higher levels of PSME1 and VPS29 are negatively associated with the risk of MI,suggesting that PSME1 and VPS29 may serve as protective biomarkers for cardiovascular diseases.

Objective To analyze the influencing factors of diabetes insipidus after pituitary tumor surgery,thereby providing evidence for enhancing perioperative management of pituitary tumor surgery and preventing diabetes insipidus after pituitary tumor surgery.Methods The clinical data of patients who underwent pituitary tumor surgery in our hospital from January 2014 to December 2024 were retrospectively analyzed.The relationship between each variable and postoperative diabetes insipidus was explored through univariate analysis,and multi-variate regression analysis was used to identify the independent risk factors for the occurrence of postoperative diabetes insipidus.Results Univariate analysis showed that the occurrence of diabetes insipidus after pituitary tumor surgery was related to tumor invasiveness,tumor growth direction,surgical resection degree,surgical time and surgical method(P<0.05).Logistic regression analysis showed that the surgical time>4 hours(P=0.001)and tumor growth breaking through diaphragma sellae(P=0.004)were independent risk factors for the occurrence of postoperative diabetes insipidus.Conclusion The surgical time and tumor growth direction are closely related to diabetes insipidus after pituitary tumor surgery;therefore,in order to reduce the incidence of diabetes insipidus after pituitary tumor surgery,a thorough evaluation should be conducted preoperatively to clarify the direction of tumor growth;minimally invasive surgery should be adopted as much as possible during the operation and the skills of surgeons should be improved to shorten the surgical time;and close observation should performed after surgery.