The Golgi body, a core organelle in eukaryotic cells, plays a critical role in protein modification, sorting, vesicular transport, and serves as a key site for lipid synthesis and glycosylation. Glucose and lipid metabolism are central processes for cellular energy maintenance and biosynthesis, and are closely linked to Golgi function. Recent studies have revealed the extensive involvement of the Golgi body in regulating glucose and lipid metabolism, where maintaining its structural and functional homeostasis is crucial for normal physiological activity. Under various stress conditions such as acidosis, hypoxia, and nutrient deficiency, the Golgi body undergoes structural and functional disruption, leading to Golgi stress. This in turn activates specific signaling pathways, such as those mediated by the cAMP-responsive element binding protein 3 (CREB3) and proteoglycans, to alleviate Golgi stress and enhance Golgi function. Golgi stress contributes to glucose and lipid metabolic disorders by affecting the activity of insulin receptors, glucose transporters, and lipid metabolism-related enzymes. For example, Golgi stress triggers the cleavage and release of the active fragment of CREB3, which enters the nucleus and upregulates the transcription of ADP-ribosylation factor 4 (ARF4) and key gluconeogenic enzymes, including phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase). ARF4 promotes vesicle retrograde transport between the Golgi and endoplasmic reticulum, maintains secretory capacity, and enhances hepatic glucose output. This pathway is particularly active under high-fat or lipotoxic stress, leading to fasting hyperglycemia. When damaged Golgi components accumulate beyond a tolerable threshold, the cell initiates an autophagic response, selectively encapsulating the damaged Golgi into autophagosomes, which then fuse with lysosomes to form autolysosomes, leading to Golgiphagy. This process results in the degradation and clearance of damaged Golgi, thereby regulating Golgi quantity, quality, and function. Golgiphagy also plays a significant role in regulating glucose and lipid metabolism. For instance, under high-glucose conditions, autophagic flux may be suppressed, impairing the timely clearance and renewal of damaged Golgi, compromising its normal function, and further exacerbating glucose metabolism disorders. Additionally, Golgiphagy may participate in lipid degradation and influence lipid synthesis and transport. Research indicates that Golgi stress and Golgiphagy play important roles in glucose and lipid metabolism-related diseases. For example, the leucine zipper protein (LZIP) under Golgi stress conditions can promote hepatic steatosis. In mouse primary cells and human tissues, LZIP induces the expression of apolipoprotein A-IV (APOA4), which increases peripheral free fatty acid uptake, resulting in lipid accumulation in the liver and contributing to the development of fatty liver disease. This review systematically outlines the structure and function of the Golgi apparatus, the molecular regulatory mechanisms of Golgi stress and Golgiphagy, and their synergistic roles. It further elaborates on how Golgi stress and Golgiphagy participate in the regulation of glucose and lipid metabolism, discusses their clinical significance in related diseases such as diabetes, fatty liver disease, and obesity, and highlights potential novel therapeutic strategies from the perspective of Golgi-targeted medicine. Finally, this article addresses the challenges and future directions in Golgi-targeted interventions, aiming to advance the clinical translation of such strategies and foster breakthroughs in the treatment of glucose and lipid metabolism-related disorders.

The Golgi body, a core organelle in eukaryotic cells, plays a critical role in protein modification, sorting, vesicular transport, and serves as a key site for lipid synthesis and glycosylation. Glucose and lipid metabolism are central processes for cellular energy maintenance and biosynthesis, and are closely linked to Golgi function. Recent studies have revealed the extensive involvement of the Golgi body in regulating glucose and lipid metabolism, where maintaining its structural and functional homeostasis is crucial for normal physiological activity. Under various stress conditions such as acidosis, hypoxia, and nutrient deficiency, the Golgi body undergoes structural and functional disruption, leading to Golgi stress. This in turn activates specific signaling pathways, such as those mediated by the cAMP-responsive element binding protein 3 (CREB3) and proteoglycans, to alleviate Golgi stress and enhance Golgi function. Golgi stress contributes to glucose and lipid metabolic disorders by affecting the activity of insulin receptors, glucose transporters, and lipid metabolism-related enzymes. For example, Golgi stress triggers the cleavage and release of the active fragment of CREB3, which enters the nucleus and upregulates the transcription of ADP-ribosylation factor 4 (ARF4) and key gluconeogenic enzymes, including phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase). ARF4 promotes vesicle retrograde transport between the Golgi and endoplasmic reticulum, maintains secretory capacity, and enhances hepatic glucose output. This pathway is particularly active under high-fat or lipotoxic stress, leading to fasting hyperglycemia. When damaged Golgi components accumulate beyond a tolerable threshold, the cell initiates an autophagic response, selectively encapsulating the damaged Golgi into autophagosomes, which then fuse with lysosomes to form autolysosomes, leading to Golgiphagy. This process results in the degradation and clearance of damaged Golgi, thereby regulating Golgi quantity, quality, and function. Golgiphagy also plays a significant role in regulating glucose and lipid metabolism. For instance, under high-glucose conditions, autophagic flux may be suppressed, impairing the timely clearance and renewal of damaged Golgi, compromising its normal function, and further exacerbating glucose metabolism disorders. Additionally, Golgiphagy may participate in lipid degradation and influence lipid synthesis and transport. Research indicates that Golgi stress and Golgiphagy play important roles in glucose and lipid metabolism-related diseases. For example, the leucine zipper protein (LZIP) under Golgi stress conditions can promote hepatic steatosis. In mouse primary cells and human tissues, LZIP induces the expression of apolipoprotein A-IV (APOA4), which increases peripheral free fatty acid uptake, resulting in lipid accumulation in the liver and contributing to the development of fatty liver disease. This review systematically outlines the structure and function of the Golgi apparatus, the molecular regulatory mechanisms of Golgi stress and Golgiphagy, and their synergistic roles. It further elaborates on how Golgi stress and Golgiphagy participate in the regulation of glucose and lipid metabolism, discusses their clinical significance in related diseases such as diabetes, fatty liver disease, and obesity, and highlights potential novel therapeutic strategies from the perspective of Golgi-targeted medicine. Finally, this article addresses the challenges and future directions in Golgi-targeted interventions, aiming to advance the clinical translation of such strategies and foster breakthroughs in the treatment of glucose and lipid metabolism-related disorders.

OBJECTIVE To explore the efficacy and safety of ruxolitinib in the treatment of myelofibrosis （MF）. METHODS A retrospective collection of data was conducted on 42 MF patients who were treated with ruxolitinib in a standardized manner for more than 6 months in the Third People’s Hospital of Bengbu from September 2018 to April 2024. The clinical symptom scores， spleen size reduction， and MF grading of the patients before and after treatment were analyzed. Additionally， the occurrence of adverse reactions with a causality assessment result of “definite”“probable” or “possible” was recorded. The patients’ survival status was followed up. RESULTS After 6 months of treatment， both clinical symptom scores and the total score were significantly decreased than before treatment （P＜0.05）. The length and thickness of the spleen were significantly shorter than before treatment （P＜0.05）. MF classification in 5 patients decreased by 1 level compared with baseline， 1 case was level 2 and dropped to level 0， 14 patients remained stable. The main adverse reactions were anemia （26 cases）， thrombocytopenia （14 cases）， infection （11 cases）， and gastrointestinal discomfort （9 cases）. Thirty-nine patients survived， with a survival rate of 92.86%. CONCLUSIONS Ruxolitinib can effectively improve the clinical symptoms of patients with MF， shrink the spleen， stabilize and even improve MF grading， and holds promise for bringing long-term survival benefits to MF patients. Adverse reactions are mainly anemia， thrombocytopenia， infection and gastrointestinal discomfort.

OBJECTIVE To establish a content determination method for multiple components in Sophora flavescens from different origins and to evaluate its quality by combining with chemometrics. METHODS Thirteen batches （No. K1-K13） of S. flavescens from different origins were selected as test samples. A high-performance liquid chromatography-tandem triple quadrupole mass spectrometry （HPLC-MS/MS） method was established to determine the contents of 12 components， including matrine， oxymatrine， betaine， cytisine， N-methylcytisine， sophoridine， genistein， sophoricoside， sophorone， formononetin， sophorolone Ⅰ and norkurarinone in S. flavescens. Chromatographic separation was performed on a Shim-pack GIST-HP C18 column with a mobile phase consisting of methanol （A） and water containing 0.1% formic acid （B）， using gradient elution at a flow rate of 0.25 mL/min， column temperature of 35 ℃， and an injection volume of 3 μL. Mass spectrometry was conducted using an electrospray ionization source with positive and negative ion scanning. Data were collected in segments using the multiple reaction monitoring mode. Technique for order preference by similarity to ideal solution （TOPSIS） and grey relational analysis （GRA）methods were employed to compare and comprehensively evaluate the 13 batches of S. flavescens from different origins. RESULTS The methodological validation for the content determination met the relevant regulatory requirements. The contents of the 12 components were 490.66-1 231.00， 11 088.10- 18 021.50， 7.91-25.38， 903.97-1 713.64， 336.08-1 485.54，1 065.33-2 075.50， 27.52-71.80， 109.36-517.83， 6 034.55-10 632.73， 21.26-145.35， 814.84-1 911.32， 1 040.87-3 446.37 μg/g）， respectively. TOPSIS results showed that the top 7 samples in Euclidean distance ranking were K6， K12， K11， K3， K5， K10， K13. The GRA results showed that the top 7 samples in the relative correlation ranking were K12， K11， K10， K6， K13， K5， K3. CONCLUSIONS The established HPLC-MS/MS method is rapid， accurate， highly sensitive， stable and reliable. Combined with chemometrics methods， it can be used for the quality control and evaluation of S. flavescens. The comprehensive quality of samples K3， K5， K6（ from Hebei）， K10（ from Sichuan）， K11-K13（ from Shanxi）， etc. is relatively superior.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective To discuss the mechanism of the streaking artifact of Star-volumetric interpolated body examination(Star-VIBE)sequence and the influence of phase coding on it.Methods Twenty-six volunteers underwent many times Star-VIBE sequences scanning with different phase coding(320,640,960,1 280,1 600).The severity of streaking artifact of images in different phase cod-ing groups was evaluated qualitatively.The signal-to-noise ratio(SNR)of muscle,thyroid and contrast-enhanced artery,contrast-to-noise ratio(CNR)between soft tissues,and CNR between muscle and contrast-enhanced artery of the images in different phase coding groups were evaluated quantitatively.Results In qualitative evaluation,with the number of phase coding increased,the streaking artifact decreased(H=83.022,P＜0.005).In quantitative evaluation,SNRmuscle,SNRthyroid,SNRcontrast-enhanced artery and CNRcontrast-enhanced gradually increased with the increase of phase coding number(SNRmuscle:F=6.913,P＜0.005;SNRthyroid:F=3.930,P=0.005;SNRcontrast-enhanced artery:F=6.980,P＜0.005;CNRcontrast-enhanced:F=6.482,P＜0.005),while CNRsoft tissue showed no statistical difference(F=1.114,P=0.339).Conclusion There is streaking artifact on the image of the Star-VIBE sequence,which can be reduced by increas-ing the number of phase coding appropriately.The most suitable phase coding is 960.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

Pseudomonas aeruginosa(PA)is an opportunistic pathogen commonly involved in environmental-and difffcult-to-treat nosocomial infection.Currently,multidrug-resistant(MDR)and extensively drug-resistant(XDR)strains of PA are e-merging due to the inappropriate use of antibiotics,which has become a major threat related to healthcare.The antibiotics re-sistance mechanism of PA is very complicated.PA can acquire resistance through mutations in genes encoding for membrane-associated proteins,antibiotics inactivation enzymes and their regulatory proteins,antibiotics target proteins,and two-compo-nent systems.Additionally,resistance genes acquired by horizontal gene transfer(HGT)lead to resistance of PA,which are frequently localized within mobile genetic elements(MGEs),including genes encoding enzymes that inactivate and modify anti-biotics,proteins genes that protect and modify antibiotic targets.In this review,acquired resistance mechanisms of PA involved in gene mutations and HGT was summarized.This review would provide references for the prevention and treatment of PA in-fection,as well as the research and development of new antibiotics.

Objective To measure the three-dimensional(3D)motion of the knee joint in healthy people and patients after total knee arthroplasty(TKA).Methods The coordinate system for the tibia and femur of the knee joint was established,and the marking points were pasted at the bone landmarks.Then the 3D motion of human knee joint was measured by biplane high-speed photogrammetry,and the data were processed according to the coordinate transformation.Results The peak values of adduction and abduction,internal and external rotation,internal and external translation,and proximal and distal movement of the artificial knee joint were larger than those of the healthy knee joint(P<0.05),but there was no statitistic difference in posterior displacement between the artificial and healthy knee joints(P=0.05).Conclusions By measuring the knee joint motion,not only the difference in knee joint motion between the healthy volunteers and TKA patients was revealed,but also the effectiveness of biplane high-speed photography in knee joint kinematic measurement was demonstrated.

Objective:To analyze the association of peripheral blood systemic immune-inflammation index(SII),neutrophil-to-lymphocyte ratio(NLR),platelet-to-lymphocyte ratio(PLR)with disease severity and progno-sis in elderly patients with chronic pulmonary heart disease(CPHD).Methods:A total of 180 elderly CPHD pa-tients admitted in Xuancheng Central Hospital between September 2021 and January 2023 were enrolled as case group.Healthy volunteers who simultaneously underwent physical examinations in our hospital were selected as con-trol group(n=50).According to the 28d prognosis,the case group was divided into death group(n=45)and sur-vival group(n=135).Levels of peripheral blood SII,NLR and PLR were compared among above-mentioned groups;Spearman correlation analysis was used to analyze the association of above indexes with cardiac function class and prognosis in these patients.Multivariate Logistic regression analysis was used to analyze risk factors for death in these patients.The predictive value of SII,NLR,and PLR for death in elderly CPHD patients was ana-lyzed using receiver operating characteristic(ROC)curve.Results:Compared with those in control group,those in the case group had significant higher levels of peripheral blood SII,NLR and PLR(P＜0.001 all).Compared with NYHA class Ⅱ group and class Ⅲ group,those in class Ⅳ group had significant higher levels of peripheral blood SII[(1759.87±179.43)vs.(1148.33±121.57)vs.(1392.44±146.36)],NLR[(8.65±0.89)vs.(7.14±0.75)vs.(7.76±0.81)],PLR[(152.45±16.79)vs.(125.29±13.46)vs.(138.77±13.58)];and levels of peripheral blood SII,NLR,PLR in class Ⅲ group were significantly higher than those of class Ⅱ group(P＜0.001 all).Com-pared with patients in survival group,those in death group had significant higher levels of peripheral blood SII[(1723.86±189.65)vs.(1296.81±142.33)],NLR[(8.24±0.89)vs.(7.63±0.78)],PLR[(148.75±15.26)vs.(134.41±14.58)](P＜0.001 all).Spearman correlation analysis indicated that the levels of peripheral blood SII,NLR and PLR were significant positively correlated with the severity and poor prognosis(r=0.336～0.432,P＜0.05 or＜0.01;r=0.319～0.504,P＜0.05 or＜0.01)in elderly CPHD patients.Multivariate Logistic regression analy-sis indicated that peripheral blood SII,NLR,PLR and smoking were independent risk factors for death(OR=1.024～9.514,P＜0.05 or＜0.01)in elderly CPHD patients.ROC curve indicated that area under curve(AUC)of combination of SII,NLR and PLR predicting death in elderly CPHD patients was 0.979(95％CI 0.946～0.995),significantly higher than those of each single detection[SII:0.847(95％CI 0.786～0.896),NLR:0.832(95％CI 0.769～0.883),PLR:0.881(95％CI 0.825～0.925),Z=3.988,4.386,4.217,P＜0.01 all].The nomogram calibration curve and decision curve showed good consistency and net benefit of the model.Conclusion:Peripheral blood SII,NLR and PLR are associat-ed with the severity and prognosis of elderly CPHD patients,and have certain predictive value for patient's prognosis.