The Golgi apparatus (GA) is a key membranous organelle in eukaryotic cells, acting as a central component of the endomembrane system. It plays an irreplaceable role in the processing, sorting, trafficking, and modification of proteins and lipids. Under normal conditions, the GA cooperates with other organelles, including the endoplasmic reticulum (ER), lysosomes, mitochondria, and others, to achieve the precise processing and targeted transport of nearly one-third of intracellular proteins, thereby ensuring normal cellular physiological functions and adaptability to environmental changes. This function relies on Golgi protein quality control (PQC) mechanisms, which recognize and handle misfolded or aberrantly modified proteins by retrograde transport to the ER, proteasomal degradation, or lysosomal clearance, thus preventing the accumulation of toxic proteins. In addition, Golgi-specific autophagy (Golgiphagy), as a selective autophagy mechanism, is also crucial for removing damaged or excess Golgi components and maintaining its structural and functional homeostasis. Under pathological conditions such as oxidative stress and infection, the Golgi apparatus suffers damage and stress, and its homeostatic regulatory network may be disrupted, leading to the accumulation of misfolded proteins, membrane disorganization, and trafficking dysfunction. When the capacity and function of the Golgi fail to meet cellular demands, cells activate a series of adaptive signaling pathways to alleviate Golgi stress and enhance Golgi function. This process reflects the dynamic regulation of Golgi capacity to meet physiological needs. To date, 7 signaling pathways related to the Golgi stress response have been identified in mammalian cells. Although these pathways have different mechanisms, they all help restore Golgi homeostasis and function and are vital for maintaining overall cellular homeostasis. It is noteworthy that the regulation of Golgi homeostasis is closely related to multiple programmed cell death pathways, including apoptosis, ferroptosis, and pyroptosis. Once Golgi function is disrupted, these signaling pathways may induce cell death, ultimately participating in the occurrence and progression of diseases. Studies have shown that Golgi homeostatic imbalance plays an important pathological role in various major diseases. For example, in Alzheimer’s disease (AD) and Parkinson’s disease (PD), Golgi fragmentation and dysfunction aggravate the abnormal processing of amyloid β-protein (Aβ) and Tau protein, promoting neuronal loss and advancing neurodegenerative processes. In cancer, Golgi homeostatic imbalance is closely associated with increased genomic instability, enhanced tumor cell proliferation, migration, invasion, and increased resistance to cell death, which are important factors in tumor initiation and progression. In infectious diseases, pathogens such as viruses and bacteria hijack the Golgi trafficking system to promote their replication while inducing host defensive cell death responses. This process is also a key mechanism in host-pathogen interactions. This review focuses on the role of the Golgi apparatus in cell death and major diseases, systematically summarizing the Golgi stress response, regulatory mechanisms, and the role of Golgi-specific autophagy in maintaining homeostasis. It emphasizes the signaling regulatory role of the Golgi apparatus in apoptosis, ferroptosis, and pyroptosis. By integrating the latest research progress, it further clarifies the pathological significance of Golgi homeostatic disruption in neurodegenerative diseases, cancer, and infectious diseases, and reveals its potential mechanisms in cellular signal regulation.

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures

OBJECTIVE: Meta-analysis of the clinical efficacy of plate and external fixator fixation in the treatment of AO-C type distal radius fractures. METHODS: PubMed, Embase, Cochrane Medical Library, Web of Science, CNKI, Wanfang, VIP and SinoMed databases were searched for all literature on randomized controlled clinical trials of AO-C distal radius fractures. The search time limits were from each database. The database will be established until June 30, 2023. The included studies were extracted according to the Cochrane Handbook (Version 6.3, 2022) for information extraction and literature quality evaluation. RevMan 5.4 was used to evaluate the risk of Publication bias, test heterogeneity and Perform Meta-analysis. The outcome indicators were:imaging anatomy indicators (volar inclination angle, ulnar deviation angle, radial height), wrist joint mobility (flexion, extension, rotation, ulnar deviation), complication rate, and comparison of surgical treatments (operative blood loss, operation time, hospitalization time, fracture healing time) and wrist joint function scores and related scales. RESULTS: (1) A total of 28 studies were included, with a total of 2 192 patients, including 1 096 cases in the plate internal fixation group and 1 096 cases in the external fixation group.(2) Meta analysis results showed:the surgical treatment situation of the external fixation group:surgical blood loss MD=-37.93, 95%CI(-48.54, -27.31), P<0.000 01;operation time MD=-31.58, 95%CI(-48.96, -14.20), P<0.000 4;hospitalization time MD=-4.58, 95%CI(-5.44, -3.71), P<0.000 01;the fracture healing time MD=-0.88, 95%CI(-1.35, -0.41), P<0.000 2, which were significantly better than that of the plate internal fixation group(P<0.05).(3) The two groups:palmar inclination angle MD=-0.17, 95%CI(-0.95, 0.61), P=0.68;ulnar declination MD=0.22, 95%CI(-0.73, 1.17), P=0.65, radial height MD=-0.24, 95%CI(-1.15, 0.67), P=0.60;flexion and extension MD=-5.63, 95%CI(-11.85, 0.58), P=0.08;rotation MD=-5.80, 95%CI(-12.77, 1.17), P=0.10, radioulnar deviation MD=-2.86, 95%CI(-10.87, 5.15), P=0.48;complication rate RR=0.96, 95%CI(0.63, 1.46), P=0.83;Gartland-Werley clinical wrist score MD=0.13, 95%CI(-0.80, 1.06), P=0.78;excellent and good rate of Gartland-Werley wrist clinical score RR=0.93, 95%CI(0.87, 1.01), P=0.08;excellent and good rate of Cooney wrist score RR=0.99, 95%CI(0.62, 1.59), P=0.98;wrist DASH score MD=-4.67, 95%CI(-14.96, 5.62), P=0.37;the differences were not significant (P>0.05). CONCLUSION Compared with internal fixation with plate, external fixation can significantly reduce the amount of surgical bleeding, shorten the operation time, hospitalization time and fracture healing time, and its imaging anatomical indicators, wrist mobility, and complications can be significantly reduced in treating AO-C distal radius fractures. Rates and wrist function scores were equivalent.
Humans ; External Fixators ; Bone Plates ; Radius Fractures/surgery* ; Fracture Fixation/methods* ; Fracture Fixation, Internal ; Wrist Fractures

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective:To explore the effects of workload factors and social psychological factors on work-related musculoskeletal disorders (WMSDs) , construct a preventive decision-assisted ensemble learning model, and propose screening methods with clinical significance.Methods:In October 2022, 1071 workers from optoelectronic enterprises were selected as the research subjects by cluster sampling method. The general situation of workers, workload factors, social psychological factors and the occurrence of WMSDs were collected by using questionnaires. logistic regression, Extreme Gradient Boosting (XGBoost) , ensemble learning and classification chain model were adopted to explore the key factors influencing WMSDs, and the area under curve (AUC) was used to evaluate the model performance.Results:The incidence of WMSDs among workers in optoelectronic enterprises in the past year was 47.7% (511/1071) , among which the incidence of multi-site WMSDs was 54.4% (278/511) . logistic regression analysis showed that prolonged sitting, personnel shortage and forward neck tilt were risk factors for the occurrence of WMSDs in workers ( P<0.05) . XGBoost identified the key social psychological factors influencing WMSDs as low mood, mental tension, perceived happiness level, psychological calmness and tranquility. The integrated classification chain model based on the ordered label order had certain efficacy (AUC>0.7) when analyzing WMSDs at the neck, waist, shoulder, back, elbow and hip positions. Conclusion:Workload factors are the main risk factors for the occurrence of WMSDs among workers in optoelectronic enterprises, and social psychological factors also have potential influences. The construction of a classification chain model can accurately identify the occurrence of WMSDs in multiple parts. The alternating prevention strategy of workload factors and social psychological factors has important public health significance.

Objective: To explore the current status and influencing factors of eating behaviors in adolescents, so as to provide a theoretical foundation for health promotion education among adolescents. Methods: Based on the database from Survey of Chinese Family Health Index (2021), by a random number table method, 1 065 teenagers were selected from the provincial capitals of 22 provinces and 5 autonomous regions in China, as well as 4 municipalities directly under the central government. A general characteristic questionnaire, Patient Health Questionnaire-9 (PHQ-9), Short Form of the Family Health Scale (FHS-SF), 10-item Short Version of the Big Five Personality(BFP-10), Content-based Media Exposure Scale (CM-E) and Sakata Eating Behavior Scale Short Form(EBS-SF) were used to collect information. Multivariate stepwise linear regression analysis was employed to identify and analyze related factors of eating behaviors among adolescents. Receiver operating characteristic was used to validate the predictive ability of the EBS-SF score for overweight and obesity among adolescents. Results: The average scores of BFI-10,C-ME, FHS-SF, PHQ-9 and EBS-SF were (33.08±4.64)(19.20±4.55)(38.48±6.65)(6.09±5.63)(16.75±4.36), respectively. Multivariate linear regression showed that family type (other types), agreeableness, conscientiousness, family health and depression were the main related factors of EBS-SF scores among adolescents( B =2.61,-0.42,0.20,-0.11,0.23, P <0.05).The analysis of receiver operating characteristic curve showed that the EBS-SF scores had a good ability in predicting obesity among male adolescents ( AUC= 0.73, P <0.01). Conclusions Family type, big five personality, family health,depression are the related factors of eating behaviors among adolescents. EBS-SF scores are predictive of obesity in adolescents, which would provide a new perspective for promoting healthy eating habits among adolescents.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

OBJECTIVE: The role of cold spells of different intensities in the economic burden of death is crucial for health adaptation to climate change, especially in a multi-site setting. The objective of the study was to explore the economic burden of mortality attributable to cold spells. METHODS: We performed a two-stage time-series analysis using the Value of Statistical Life (VSL) approach to evaluate the economic impact of mortality related to cold spells of varying lengths and intensities. This analysis employed a case-crossover design, with a distributed lag nonlinear model (DLNM) used for analysis. Analysis was stratified according to age, sex, and region of origin. The results of the assessment show that cold spells have an enormous impact on the economic losses of mortality due to climate change and aging. RESULTS: Totally, 8.3% (95% CI: 0.0%, 16.0%) to 13.8% (95% CI: 1.0%, 24.8%) of VSL were ascribed to cold spells, accounting for economic losses of 4.71 (95% CI: 0.34, 8.47) to 11.45 (95% CI: 0.00, 21.00) billion CNY, in the cold season. The population aged over 65 y and females are particularly vulnerable. Economic impacts in warmer regions, such as the southern and subtropical zones, are more extensive than those in the northern and temperate zones. CONCLUSION Customizing cold spell prevention measures for vulnerable populations or regions is vital to alleviating the socioeconomic burden.
China/epidemiology* ; Humans ; Female ; Male ; Cold Temperature/adverse effects* ; Aged ; Middle Aged ; Adult ; Mortality ; Infant ; Child ; Adolescent ; Child, Preschool ; Young Adult ; Climate Change ; Aged, 80 and over ; Cost of Illness ; Infant, Newborn

AIM To study the chemical constituents from the water fraction of rhizoma of Smilax trinervula Miq.and their biological activities.METHODS Polyamide,silica gel,Sephadex LH-20,ODS and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT mothod,and the inhibitory activities on α-glucosidase were determined by PNPG method.RESULTS Eleven compounds were isolated and identified as tyrosine(1),uridine(2),2-(2',3',4'-trihydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(3),2-(1',2',3',4'-tetrahydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(4),2-(1',2',3',4'-tetrahydroxybutyl)-5-(2",3",4"-trihydroxybutyl)-pyrazine(5),uracil(6),2-(1',2',3',4'-tetrahydroxybutyl)-5-(1",2",3",4"-tetrahydroxybutyl)-pyrazine(7),dioscin(8),shikimic acid(9),pyrazine(10),3,4-dihydroxyphenyethyl alcohol 8-O-β-D-glycopyranoside(11).The IC50 values of compounds 8 to human breast cancer cell MCF-7 was(2.36±0.26)μg/mL,and the IC50 values of compounds 3-5 and 7 to α-glucosidase were(1.54±0.15)-(10.53±0.38)μg/mL.CONCLUSION Compounds 1-7,10 are isolated from Smilax genus for the first time,and compound 9,11 are first isolated from this plant.Compound 8 has anti-tumor activity,and compounds 3-5,7 have α-glucosidase inhibitory activities.

Objective:To explore the effects of workload factors and social psychological factors on work-related musculoskeletal disorders (WMSDs) , construct a preventive decision-assisted ensemble learning model, and propose screening methods with clinical significance.Methods:In October 2022, 1071 workers from optoelectronic enterprises were selected as the research subjects by cluster sampling method. The general situation of workers, workload factors, social psychological factors and the occurrence of WMSDs were collected by using questionnaires. logistic regression, Extreme Gradient Boosting (XGBoost) , ensemble learning and classification chain model were adopted to explore the key factors influencing WMSDs, and the area under curve (AUC) was used to evaluate the model performance.Results:The incidence of WMSDs among workers in optoelectronic enterprises in the past year was 47.7% (511/1071) , among which the incidence of multi-site WMSDs was 54.4% (278/511) . logistic regression analysis showed that prolonged sitting, personnel shortage and forward neck tilt were risk factors for the occurrence of WMSDs in workers ( P<0.05) . XGBoost identified the key social psychological factors influencing WMSDs as low mood, mental tension, perceived happiness level, psychological calmness and tranquility. The integrated classification chain model based on the ordered label order had certain efficacy (AUC>0.7) when analyzing WMSDs at the neck, waist, shoulder, back, elbow and hip positions. Conclusion:Workload factors are the main risk factors for the occurrence of WMSDs among workers in optoelectronic enterprises, and social psychological factors also have potential influences. The construction of a classification chain model can accurately identify the occurrence of WMSDs in multiple parts. The alternating prevention strategy of workload factors and social psychological factors has important public health significance.