ObjectiveThe Golgi apparatus serves as a central hub in the eukaryotic secretory pathway, responsible for the processing, sorting, and trafficking of proteins and lipids. In mammalian cells, the Golgi typically forms a perinuclear ribbon-like structure composed of laterally connected cisternae stacks.The maintenance of Golgi ribbon structure depends on the balance of membrane flux across multiple intracellular trafficking pathways, yet the specific contributions of distinct trafficking branches to Golgi macroscopic morphology remain elusive. In mammalian cells, the Golgi ribbon is typically organized as a perinuclear, laterally connected structure composed of stacked cisternae, and its integrity is highly dynamic and sensitive to perturbations in membrane trafficking. This study aims to elucidate the role of coat protein complex I (COPI)-mediated retrograde transport in maintaining the Golgi ribbon and to dissect the functional relationship between the transmembrane cargo receptors LEPROT/LEPROTL1 (LEPROTs) and the COPI adaptor GOLPH3. MethodsUsing siRNA interference and gene-deficient cell lines, we selectively perturbed COPI- or adaptor protein complex 1 (AP-1)-mediated trafficking pathways in HeLa cells. To quantitatively evaluate Golgi morphology, we employed a “Golgi Angle”-based measurement to assess its circumferential distribution around the nucleus. The spatial distribution of the Golgi ribbon was quantitatively analyzed using confocal microscopy, while Golgi ultrastructure and vesicle density were examined via transmission electron microscopy. Additionally, the subcellular distribution of COPI components was assessed by immunofluorescence co-localization. ResultsSelective inhibition of COPI retrograde transport significantly induced the circumferential extension of the Golgi ribbon around the nucleus, whereas blocking AP-1-mediated anterograde transport resulted in Golgi compaction, indicating opposing roles. These results suggest that different trafficking branches downstream of ARF1 exert distinct and even antagonistic effects on Golgi morphology. LEPROTs-deficient cells exhibited a Golgi extension phenotype highly consistent with COPI impairment. Furthermore, knockdown of GOLPH3 in a LEPROTs double-knockout background produced a significant additive effect on Golgi extension, suggesting that LEPROTs and GOLPH3 play non-redundant roles in regulating COPI-related trafficking processes. Mechanistically, loss of either LEPROTs or GOLPH3 led to the aberrant accumulation of COPI components at endoplasmic reticulum exit sites, accompanied by a reduction in COPI-like vesicles around the Golgi. This redistribution indicates a defect in COPI recycling between the ER-Golgi interface and the Golgi apparatus. Ultrastructural analysis revealed that Golgi cisternae in defective cells became shorter and thicker while maintaining a stable number of stacks. In parallel, the density of Golgi-associated vesicles was markedly decreased, further supporting an impairment in COPI vesicle formation or budding processes. ConclusionThis study demonstrates that active COPI retrograde transport is a critical factor in restricting the over-connection of the Golgi ribbon and maintaining its compactness. Rather than causing fragmentation, partial disruption of COPI function leads to a distinct morphological outcome characterized by Golgi ribbon extension at the light microscopy level and cisternal remodeling at the ultrastructural level. LEPROTs and GOLPH3 cooperatively promote the recycling and vesiculation of COPI components, thereby imposing a structural constraint on the Golgi periphery. Our findings support a model in which multiple adaptor proteins act in parallel to sustain efficient COPI cycling, thereby maintaining Golgi structural homeostasis. These findings provide new cell biological evidence for the membrane trafficking basis of Golgi morphological homeostasis.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

ObjectiveIn order to provide a reference for the optimization of preparation process of stir-fried Glycyrrhizae Radix et Rhizoma（sf-GRR）， the quality changes during the processing was studied. MethodsGlycyrrhizae Radix et Rhizoma was processed by stir-frying for 17 min， and samples were collected every 1 min during the processing. The appearance color of the samples was determined by visual analysis technology， the moisture and extract of the process samples were detected by the drying method and the hot extraction method of alcohol-soluble extract in the general rules of the 2020 edition of Chinese Pharmacopoeia（part Ⅳ）， and the contents of liquiritin apioside， liquiritin， isoliquiritin apioside， isoliquiritin， licoricesaponin G₂ and glycyrrhizic acid in the process samples were determined by high performance liquid chromatography（HPLC）. Then principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and Spearman correlation analysis were used for clustering， discrimination and correlation analysis of the appearance color， moisture， extract and the contents of six internal components. Based on artificial neural network and random forest algorithm， the prediction model of processing degree of sf-GRR was established. On this basis， based on the five principles of quality marker（Q-Maker）， explore the monitoring Q-Maker of sf-GRR. ResultsThe color of Glycyrrhizae Radix et Rhizoma deepened after stir-frying， and the appearance color of the sample changed from light yellow to dark yellow during processing. During the stir-frying process， the moisture content showed a decreasing trend with the extension of processing time， while the extract content showed an increasing trend with the extension of processing time. After stir-frying， the contents of liquiritin apioside， liquiritin and licoricesaponin G₂ showed an overall decreasing trend， while the contents of isoliquiritin apioside and isoliquiritin increased， and the content of glycyrrhizic acid increased slightly. The correlation analysis showed that moisture was positively correlated with brightness（L^*） and red/green value（a^*）， and negatively correlated with yellow/blue value（b^*） and total color difference（E^*ab）. Isoliquiritin apioside and isoliquiritin had negative correlation with L^* and a^*， and positive correlation with b^* and E^*ab. The processing process of sf-GRR could be divided into two stages of the early stage（0-14 min） and the late stage（15-17 min）， and could be divided into three stages of the early stage（0-6 min）， the middle stage（7-14 min） and the late stage（15-17 min） by combining the moisture， extract， the contents of 6 components and color values. Based on artificial neural network analysis and random forest algorithm， isoliquiritin apioside， isoliquiritin， liquiritin and glycyrrhizic acid were selected as monitoring markers for sf-GRR. ConclusionBased on the analysis of the exterior-interior indicators of process samples of sf-GRR， this paper ultimately identifies four processing monitoring markers， which can provide a basis for optimizing the processing technology of sf-GRR.

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Objective:To explore the application value of multi-slice spiral CT (MSCT) perfusion imaging and magnetic resonance high-resolution vessel wall imaging (HR-VWI) in the evaluation of atherosclerotic ischemic stroke (IS).Methods:A total of 131 patients with atherosclerotic IS (study group) and 62 patients with non-atherosclerotic IS (control group) diagnosed and treated in Handan Central Hospital from May 2022 to May 2024 were retrospectively selected as the study objects. MSCT perfusion imaging and HR-VWI were completed before treatment. MSCT perfusion imaging indexes and HR-VWI indexes were compared between the two groups, and HR-VWI indexes and MSCT perfusion imaging indexes were compared among the study groups with different disease degrees. Receiver operating characteristics (ROC) curve was used to analyze the diagnostic value of HR-VWI indexes and MSCT perfusion imaging indexes in atherosclerotic IS.Results:The stenosis degree, out wall area at maximal lumen narrowing (OWA MLN), plaque loading rate and remodeling index in the study group were higher than those in the control group: (69.22 ± 12.57)% vs. (60.81 ± 10.38)%, (7.62 ± 1.03) mm 2 vs. (6.53 ± 1.18) mm 2, (42.51 ± 8.22)% vs. (36.53 ± 7.29)%, 1.32 ± 0.41 vs. 1.01 ± 0.29; while the lumen area at maximal lumen narrowing (LA MLN) in the study group was lower than that in the control group: (0.84 ± 0.28) mm 2 vs.(1.17 ± 0.41) mm 2, there were statistical differences ( P<0.05). The cerebral blood flow (CBF) and cerebral blood volume (CBV) in the study group were lower than those in the control group: 20.25 ± 2.83) ml/100 min vs. (23.66 ± 2.52) ml/100 min, (1.82 ± 0.53) ml/100g vs. (2.31 ± 0.63) ml/100 g; and the peak time (TTP) and mean transit time (MTT) in the study group were higher than those in the control group: (23.55 ± 4.86) s vs.(19.73 ± 3.73) s, (7.13 ± 1.22) s vs. (6.17 ± 1.06) s, there were statistical differences ( P<0.05). In the study group, with the aggravation of disease severity, the stenosis degree, OWA MLN, plaque load rate and remodeling index were gradually increased, while LA MLN was gradually decreased, there were statistical differences ( P<0.05). ROC curve analysis results showed that the area under the curve value of HR-VWI index combined evaluation and MSCT perfusion imaging index combined evaluation in the diagnosis of atherosclerotic IS was 0.921 and 0.828, respectively. Conclusions:HR-VWI and MSCT perfusion imaging can be used in the assessment of patient's condition of atherosclerotic IS. HR-VWI may be better in evaluating the condition of atherosclerotic IS.

AIM:To explore the effects of Jianpi Huatan formula on regulating T cells and helper T cells 17(Th17)cells in patients with polycystic ova-ry syndrome(PCOS)due to spleen deficiency and phlegm dampness syndrome,and conduct a model evaluation.METHODS:Ninety-two patients with spleen deficiency phlegm dampness syndrome(PCOS)admitted to our hospital from January 2023 to October 2024 were selected as the research sub-jects.Propensity score matching(PSM)method was used to match them in a 1:1 ratio,with 46 pa-tients in each group.The control group received conventional treatment,while the observation group received treatment with Jianpi Huatan for-mula on the basis of the control group.Compared and analyze the differences in clinical data and lab-oratory indicators between two groups;Compared the changes of sex hormone,glucose metabolism and TCM syndrome score before and after treat-ment in the two groups,and focused on the chang-es of regulatory T cells(Treg)and Th17 cells in the two groups before and after treatment;And used the Generalized Estimation Equation(GEE)model to analyze its improvement.Multiple linear regres-sion analysis was used to examine its correlation with the score of traditional Chinese medicine syn-drome.A time effect model of Jianpi Huatan formu-la for treating PCOS with spleen deficiency and phlegm dampness syndrome was established using a nonlinear mixed effects model.The fitting effect of the final model was evaluated through the good-ness of fit.Bootstrap was used to test and evaluate the stability of model parameters.Visual prediction testing was used to evaluate the predictive perfor-mance of the model.Typical time effect curves of traditional Chinese medicine symptom scores was simulated based on the final model for each base-line.RESULTS:After treatment,the total effective rate of the observation group was significantly high-er than that of the control group(χ2=4.842,P=0.028);Compared with before treatment,after 1months and 3 months of treatment,TC,TG,LDL-C,T,LH,FSH,AMH,FPG,FINS,HOMA-IR,the score of traditional Chinese medicine syndrome were sig-nificantly reduced,while E2 and HDL-C were signifi-cantly increased,and the improvement in the ob-servation group was significantly greater than that in the control group(P<0.05);The results of repeat-ed measures ANOVA showed significant difference-sin the time effects,inter group effects,and interac-tion effects of Treg,Th17,and Treg/Th17 between the two groups of patients(P<0.05).The GEE anal-ysis results showed that the improvement of Treg,Th17,and Treg/Th17 in the observation group were better than that in the control group(P<0.05);The results of multiple linear regression analysis showed that the levels of TC,TG,LDL-C,T,LH,FSH,AMH,FPG,FINS,HOMA-IR,Th17 were significantly positively correlated with TCM syndrome score,while the levels of E2,HDL-C,Treg,and Treg/Th17 were significantly negatively correlated with TCM syndrome score(P<0.05);The decrease in tradition-al Chinese medicine symptom score compared to baseline gradually increases over time,eventually reaching the pharmacological platform,which was consistent with the classic Emax model.After gradu-ally screening covariates,it was found that the baseline value of traditional Chinese medicine symptom score had a significant impact on the effi-cacy parameter Emax.The final model was Emax,i=15.42+1.21×(Baselinei-24.41).The goodness of fit results showed that the final model had a good fit-ting effect on the measured data.The model pa-rameters obtained from Bootstrap testing were very consistent with the original model,indicated that the model parameter estimation was robust.The visual prediction test results showed that the model had good predictive performance.The typi-cal efficacy time curve showed that the higher the baseline value of TCM symptom score,the greater the decrease in score.At 3 months of treatment,the TCM symptom score at each baseline basically decreased to below 10 points.CONCLUSION:The formula for strengthening the spleen and resolving phlegm can effectively improve the levels of Treg and Th17 in PCOS patients with spleen deficiency and phlegm dampness syndrome,and has good therapeutic effects,which is worthy of clinical appli-cation.

Objective To investigate the cIinicopathological features and immunohistochemical expression of gastric hyperplastic polyps(GHPs)with dysplasia/adenocarcinoma.Methods A retrospective analysis of 24 cases(44 polyps)that were diagnosed as GHPs with dysplasia/adenocarcinoma in our hospital from January 2020 to December 2024 was reviewed,and clinical,histomorphological,immunophenotypic and follow-up data were analyzed.Results There were 20 female and 4 male cases,with a mean age of(65.5±7.9)(range 56～76)years.Among 44 polyps,3 occurred in the antrum of the stomach,1 in the gastric horn,and 40 in the fundus/body.Among the polyps,32 cases were diagnosed as high-grade dysplasia,4 cases as low-grade dysplasia,4 cases as coexistence of low-grade+high-grade dysplasia,2 cases as mucinous adenocarcinoma,1 cases as poorly differentiated adenocarcinoma,and 1 cases as signet-ring cell carcinoma.The histological manifestations of 23 cases of background mucosa were autoimmune metaplastic atrophic gastritis(AMAG).the P53 of 8 polyps showed a mutant expression pattern.Through MUC5/MUC6/MUC2/CD10 joint examination,33 cases showed gastric type(25 cases of which were foveal epithelium type),4 cases were intestinal type,5 cases were mixed gastrointestinal type,and 2 cases were non-gastrointestinal type.Conclusion The neoplastic transformation of GHPs is closely related to AMAG.It is necessary for clinicians and pathologists to strengthen their evaluation of background mucosa,to achieve early detection,early diagnosis and early treatment.

Objective:To preliminarily investigate the role of methylation in the epigenetic regulation of the pathogenesis of non-syndromic orofacial clefts (NSOC), and to address the gaps in previous explorations of susceptibility genes associated with NSOC.Methods:We conducted an association analysis of single nucleotide polymorphisms (SNPs) and genes related to methylation using data from a large-scale genome-wide association study involving Han Chinese patients with non-syndromic orofacial clefts and healthy controls.Results:A significant association was found between NSOC and the DNA methylation gene TET1, as well as the histone methylation gene NSD1. Specifically, the minor allele G of rs3733875 significantly increased the risk of non-syndromic cleft lip with or without palate (NSCLP) ( P=1.18×10 -4, OR=1.292), while the minor allele C of rs10998379 elevated the risk of non-syndromic cleft palate only (NSCPO) ( P=7.29×10 -5, OR=1.268); conversely, the minor allele T of rs4558056 was identified as a protective factor for NSCL/P ( P=1.17×10 -4, OR=0.792). Conclusions:This study revealed that the DNA methylation gene TET1 and the histone methylation gene NSD1 are associated with NSOC. The pathogenesis of NSOC involves interactions among multiple factors, including genetic, environmental, and epigenetic determinants, among which methylation modifications represent a crucial component.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

Objective To propose an improved Y OLOv8-based visible small target detection method to solve the problems of the UAV visible light system in accuracy and timeliness when applied to measuring small targets.Methods A YOLOv8 network consisting of Backbone,Neck and Head was used as the base framework to construct an AGC-YOLO model.Firstly,a convolutional block attention module(CBAM)was incorporated into Backbone to improve the feature expression of the model;secondly,some traditional convolution modules were replaced with the changeable kernel convolution module AKconv to reduce the network parameters;finally,a Gold-YOLO module was involved in Neck to enhance the detection ability for targets with different sizes.VisDrone2019 dataset was used to carry out ablation and comparison experiments,and the efficacy of the AGC-YOLO model for detecting small targets was evaluated in terms of mean average precision(mAP),frames per second(FPS),giga floating-point operations per second(GFLOPs)and parameters.Results The AGC-YOLO model had the FPS,GFLOPs and parameters being 31.90,9.20 and 11.30 M respectively,meeting the real-time detection speed requirements of drones(FPS not lower than 30),in which the mAP50(the mAP with the intersection over union being 0.5)was increased by 15％,6％and 5％when compared with those of the lightweight YOLOv8n,Ghost-YOLO and YOLO-BiFPN models.Conclusion The method proposed behaves well in speed,decreased parameters and precision,and is worthy promoting for UAV visible small target detection.[Chinese Medical Equipment Journal,2025,46(1):1-6]