1.In Vitro and In Vivo Chemical Composition Analysis of Reference Sample of Jinshui Liujunjian Based on UPLC-Q-TOF-MS/MS
Xinyue YANG ; Huiyu LI ; Yaqi LOU ; Xingxing WANG ; Guifang YU ; Chenfeng ZHANG ; Zhenzhong WANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):166-173
ObjectiveTo elucidate the chemical composition of the reference sample of Jinshui Liujunjian and its distribution characteristics in blood and tissues of rats. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) was used to detect the reference sample solution, plasma, and tissue samples of Jinshui Liujunjian under positive and negative ion modes, respectively. Qualitative Analysis 10.0 software and a self-constructed database were employed for primary mass spectrum matching.Compound identification was further validated by comparing retention times, secondary mass spectral fragments, reference standards, and literature data to deduce fragmentation pathways. ResultsA total of 122 compounds were identified in the reference sample of Jinshui Liujunjian, including 47 flavonoids, 5 amino acids, 13 iridoids, 16 triterpenoid saponins, etc., of which 42 compounds were confirmed by comparison with reference substances. A total of 21 prototype components were identified in blood components; 50 prototype components were identified in different tissues, among which 13, 10, 7, 21, 11, 6, 14, and 40 prototype components were identified in the heart, liver, spleen, lung, kidney, brain, large intestine, and stomach, respectively. Among them, 7 compounds such as ferulic acid, glycyrrhizic acid, and nobiletin were exposed in the target organs of lung and kidney. ConclusionThis study elucidates the material basis of the reference samples of Jinshui Liujunjian, primarily composed of flavonoids and triterpenoid saponins, along with their in vivo distribution characteristics. These findings provide a scientific basis for establishing quality evaluation indicators and offer references for subsequent pharmacodynamic and pharmacokinetic investigations.
2.In Vitro and In Vivo Chemical Composition Analysis of Reference Sample of Jinshui Liujunjian Based on UPLC-Q-TOF-MS/MS
Xinyue YANG ; Huiyu LI ; Yaqi LOU ; Xingxing WANG ; Guifang YU ; Chenfeng ZHANG ; Zhenzhong WANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):166-173
ObjectiveTo elucidate the chemical composition of the reference sample of Jinshui Liujunjian and its distribution characteristics in blood and tissues of rats. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) was used to detect the reference sample solution, plasma, and tissue samples of Jinshui Liujunjian under positive and negative ion modes, respectively. Qualitative Analysis 10.0 software and a self-constructed database were employed for primary mass spectrum matching.Compound identification was further validated by comparing retention times, secondary mass spectral fragments, reference standards, and literature data to deduce fragmentation pathways. ResultsA total of 122 compounds were identified in the reference sample of Jinshui Liujunjian, including 47 flavonoids, 5 amino acids, 13 iridoids, 16 triterpenoid saponins, etc., of which 42 compounds were confirmed by comparison with reference substances. A total of 21 prototype components were identified in blood components; 50 prototype components were identified in different tissues, among which 13, 10, 7, 21, 11, 6, 14, and 40 prototype components were identified in the heart, liver, spleen, lung, kidney, brain, large intestine, and stomach, respectively. Among them, 7 compounds such as ferulic acid, glycyrrhizic acid, and nobiletin were exposed in the target organs of lung and kidney. ConclusionThis study elucidates the material basis of the reference samples of Jinshui Liujunjian, primarily composed of flavonoids and triterpenoid saponins, along with their in vivo distribution characteristics. These findings provide a scientific basis for establishing quality evaluation indicators and offer references for subsequent pharmacodynamic and pharmacokinetic investigations.
3.Analyses of comorbidity patterns of chronic metabolic diseases among residents aged 35‒75 years in Nantong City, Jiangsu Province
Yuqi WANG ; Jie HUANG ; Bo CAI ; Yarong HAN ; Ling LIN ; Xingxing FANG
Shanghai Journal of Preventive Medicine 2026;38(3):187-192
ObjectiveTo analyze the comorbidity patterns of chronic metabolic diseases and their influencing factors among residents aged 35‒75 years old in Nantong City of Jiangsu Province, and to provide theoretical support for the prevention and control of comorbidities. MethodsThe permanent residents aged 35‒75 years from the Comprehensive Prevention and Control Project of Cardiovascular and Cerebrovascular Diseases in Nantong City from 2021 to 2024 were selected as the research subjects. Clustering analysis and association rule were used to investigate the comorbidity patterns of chronic metabolic diseases, and their influencing factors were identified through logistic regression analyses. ResultsThe prevalence of comorbidity of chronic metabolic diseases among residents aged 35‒75 years in Nantong City was 47.40%. Among comorbidity patterns based on disease counts, the prevalence of hypertension+dyslipidemia was highest in binary comorbidity patterns (6.25%), while that of hypertension+dyslipidemia+obesity was highest in ternary comorbidity patterns (4.01%). Association rules showed that in both binary and ternary comorbidity patterns, the confidence level was highest for obesity+hypertension (72.70%) and obesity+dyslipidemia+hypertension (74.54%). Renal insufficiency formed an independent cluster in cluster analyses. Logistic regression analyses revealed that, compared with the non-comorbidity group, males (OR=2.22, 95%CI: 1.69‒2.91), advanced age (45‒54 years, OR=1.38, 95%CI: 1.02‒1.88; 55‒64 years, OR=1.59, 95%CI: 1.14‒2.23; 65‒75 years, OR=2.34, 95%CI: 1.58‒3.47), and low physical activity (OR=1.26, 95%CI: 1.10‒1.65) were influencing factors for metabolic disease comorbidity. ConclusionIn the comorbidity patterns of chronic metabolic diseases among residents aged 35‒75 years in Nantong City, hypertension, diabetes mellitus, and dyslipidemia interact with each other. Individuals with obesity are more prone to diseases such as hypertension and dyslipidemia. Prevention and control of chronic metabolic diseases should be strengthened for males, individuals with low physical activity and advanced age.
4.Effects of different activators on platelet-rich plasma growth factors
Jianxiang LIU ; Xingxing FENG ; Shuxia WANG ; Rong ZHOU ; Mengxing LYU ; Kexuan QU
Chinese Journal of Tissue Engineering Research 2025;29(10):2067-2073
BACKGROUND:Growth factor is the key effect molecule that plays a role in platelet-rich plasma in clinical treatment.There are differences in the concentration of growth factor after different activators activate platelet-rich plasma,which is an important factor affecting clinical efficacy. OBJECTIVE:To analyze the influence of different activators on the mass concentration of growth factors in platelet-rich plasma. METHODS:Totally 12 healthy volunteers were recruited to collect EDTA-K2 anticoagulant venous blood.Secondary centrifugation was used to prepare platelet-rich plasma.The difference in mass concentrations of growth factors was compared between venous blood and platelet-rich plasma.The platelet-rich plasma was mixed with four activators(normal saline,thrombin,calcium gluconate,calcium gluconate+thrombin)according to the volume ratio of 10:1,and incubated in a constant temperature water bath at 37 °C for 30 minutes.After centrifugation,the supernatant was extracted and the mass concentration of growth factor was detected.The bacterial growth in supernatant was measured by blood agar plate.Pearson correlation was used to analyze the correlation between different activators and the mass concentration of growth factor in platelet-rich plasma,and the correlation between the value of thrombocytometer and the mass concentration of growth factors in platelet-rich plasma. RESULTS AND CONCLUSION:(1)The mass concentrations of platelet-derived growth factor-BB,platelet-derived growth factor-AB,vascular endothelial growth factor,and epidermal growth factor in platelet-rich plasma were 8.7,22.2,2.3,and 2.8 times of those in venous blood,respectively(P<0.05).(2)Compared with normal saline group,the mass concentrations of platelet-derived growth factor BB,platelet-derived growth factor AB,vascular endothelial growth factor,and epidermal growth factor were increased in the thrombin group,calcium gluconate group,and calcium gluconate+thrombin group(P<0.05).The mass concentration of platelet-derived growth factor BB in the thrombin group and calcium gluconate group was higher than that in the calcium gluconate+thrombin group(P<0.05),and the mass concentration of platelet-derived growth factor AB in the thrombin group was higher than that in the calcium gluconate group and calcium gluconate+thrombin group(P<0.05).Epidermal growth factor mass concentration in the thrombin group was lower than that in the calcium gluconate group and calcium gluconate+thrombin group(P<0.05).(3)The results of blood agar plate test showed no bacterial growth in the supernatant of the four groups.(4)Pearson correlation analysis showed that the mass concentration of platelet-derived growth factor BB in platelet-rich plasma was strongly positively correlated with thrombin(r=0.683,P<0.05),and the mass concentration of vascular endothelial growth factor was strongly positively correlated with thrombin,calcium gluconate,calcium gluconate+thrombin stimulant(r=0.730,0.789,0.686,P<0.05).There was no correlation between the value of thrombocytometer and the mass concentration of four kinds of growth factors(P>0.05).(5)The results suggest that different activators have an impact on the concentration of growth factors in platelet-rich plasma.It is suggested to choose different activators to improve clinical efficacy according to different growth factor mass concentrations and treatment needs.
5.Independent component analysis for assessing functional abnormalities in frontoparietal attention network of patients with traumatic brain injury and analyzing neural mechanism of attention disorders
Gaiyun ZHANG ; Xingxing JIN ; Hongxia WANG ; Wangyi LIU ; Jinhui DUAN ; Ruifang YAN
Chinese Journal of Medical Imaging Technology 2025;41(7):1062-1067
Objective To assess functional abnormalities in frontoparietal attention network of patients with traumatic brain injury(TBI),and to analyze neural mechanism of its attention disorders based on independent component analysis(ICA).Methods Totally 84 TBI patients were prospectively enrolled and divided into mild(n=33),moderate(n=27)and severe TBI groups(n=24)according to symptoms,non-contrast enhanced MRI findings,Glasgow coma scale(GCS)and Mayo craniocerebral trauma grading criteria.ICA was used to extract and analyze the optimal independent components(IC)of the dorsal attention network(DAN)and ventral attention network(VAN).Multiple linear regression analyses were performed to explore the correlations of functional connectivity(FC)of brain regions being significantly different among groups within attention network and the scores of trail making test A/B(TMT-A/B).Results Compared with control group and mild TBI group,spatial distribution of DAN(especially bilateral frontal eye field[FEF])in moderate and severe TBI groups were significantly smaller,the clusters tended to be discrete,and the intensity were significantly weakened.The right temporal parietal junction(TPJ)and right ventral frontal cortex(VFC)of VAN in control group,mild and moderate TBI groups were significantly affected,and VFC connection strength was the highest in severe TBI group.FC intensity in right VFC of TBI patients was positively correlated with TMT-A score(r=0.654,P<0.001),which in left FEF was negatively correlated with TMT-B score(r=—0.383,P<0.001).Conclusion FC of frontoparietal attention network was abnormal in TBI patients,which might be neural mechanism for its attention behavior disorders.
6.Application of voice training in the treatment of speech disorders in patients with Parkinson′s disease
Xingxing AI ; Ziwen WANG ; Xiaoling LIN ; Yinglian LI ; Tianning LIU ; Xianghua YUAN ; Jiewei HUANG
Chinese Journal of Practical Nursing 2025;41(15):1196-1201
This article summarized the overview of voice training, common training forms, and the application effect of voice training in the treatment of speech disorders in Parkinson′s disease patients, analyzed the shortcomings of its application and put forward prospects for future research, aiming to provide valuable references for both patients and healthcare workers.
7.Effect of an obstetric artificial intelligence assistant combined with a family-centered health education model on mothers and their spouses: a prospective randomized controlled trial
Suyu ZHANG ; Xueling ZHANG ; Qianqian QI ; Keting ZENG ; Xingxing DENG ; Lin YU ; Lili DU ; Fang HE ; Yong WANG ; Shuang ZHANG ; Dunjin CHEN
Chinese Journal of Perinatal Medicine 2025;28(10):835-841
Objective:To evaluate the effect of an obstetric artificial intelligence (AI) assistant combined with a family-centered health education model on maternal self-care ability, comfort status, and spousal caregiving ability.Methods:This prospective, single-center, parallel randomized controlled trial used 1∶1 randomization and was conducted as a superiority trial. Postpartum mothers and their spouses admitted to family-style single rooms at the Third Affiliated Hospital of Guangzhou Medical University between October 2024 and April 2025 were enrolled and randomly assigned to control or intervention groups using a random number table. The control group received conventional health education, while the intervention group received conventional health education plus the AI-assisted family-centered model. Interventions were administered at 2 hours, 6 hours, and 24 hours postpartum, and before discharge. Outcomes included maternal self-care ability, comfort status, and spousal caregiving ability, which were assessed at 2 hours postpartum and before discharge. Data were analyzed using independent and paired t-tests and Chi square tests. Results:Of the 88 mother-spouse dyads initially recruited, four were excluded due to mother-infant separation (e.g., neonatal jaundice), leaving 84 dyads (42 per group). After the intervention, the intervention group showed significantly higher maternal self-care ability scores [(192.81±13.80) vs. (181.00±21.41) scores, t=3.00], higher maternal comfort scores [(104.43±7.52) vs. (96.00±14.29) scores, t=3.38], and better spousal caregiving ability [(6.07±3.13) vs. (9.50±5.02) scores, t=-3.76] compared to the control group (all P<0.05). Conclusion:The obstetric AI assistant combined with a family-centered health education model significantly improved maternal self-care ability and comfort status, as well as spousal caregiving ability.
8.Risk factors for new-onset atrial fibrillation after off-pump coronary artery bypass grafting: A systematic review and meta-analysis
Xingxing CHEN ; Li YANG ; Yunqing GU ; Yinghong LI ; Yaqin CHENG ; Hui WANG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2025;32(10):1478-1486
Objective To systematically evaluate the risk factors for new-onset atrial fibrillation (NOAF) after off-pump coronary bypass grafting (OPCABG). Methods PubMed, EMbase, Web of Science, The Cochrane Library, Wanfang data, CBM, VIP, and CNKI databases were systematically searched by computer to collect studies related to the risk factors for NOAF after OPCABG from the establishment of the database to July 2023. Literature screening and quality evaluation were conducted independently by two researchers. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literature. RevMan 5.3 and Stata15.0 were used for meta-analysis. Results Finally, 19 case-control studies related to the risk factors for NOAF after OPCABG were included, all of which were high-quality literature with NOS score≥6 points, with a total of 7019 subjects. The results of meta-analysis showed that the following factors were associated with NOAF after OPCABG: (1) the patient’s own factors: age (MD=3.51, 95%CI 2.39 to 4.63, P<0.01); (2) preoperative factors: history of hypertension (OR=1.17, 95%CI 1.04 to 1.32, P=0.01), history of myocardial infarction (OR=1.21, 95%CI 1.06 to 1.38, P<0.01), history of percutaneous coronary intervention (OR=2.22, 95%CI 1.03 to 4.77, P=0.04), EuroSCOREⅡ score (MD=0.59, 95%CI 0.25 to 0.94, P<0.01), low-density lipoprotein (MD=0.11, 95%CI 0.02 to 0.20, P=0.02), left atrial diameter (MD=1.64, 95%CI 0.24 to 3.04, P=0.02); (3) postoperative and treatment factors: left ventricular end-diastolic diameter (MD=1.16, 95%CI 0.33 to 1.99, P<0.01), left ventricular ejection fraction (MD=0.90, 95%CI 0.07 to 1.73, P=0.03), mechanical ventilation time (MD=2.78, 95%CI 1.65 to 3.90, P<0.01), B-type natriuretic peptide (MD=219.67, 95%CI 27.46 to 411.88, P=0.03), ICU retention time (MD=7.07, 95%CI 5.64 to 8.50, P<0.01). Conclusion The existing evidence shows that age, history of hypertension, history of myocardial infarction, history of percutaneous coronary intervention, preoperative EuroSCOREⅡscore, preoperative low-density lipoprotein, preoperative left atrial diameter, postoperative left ventricular end-diastolic diameter, postoperative left ventricular ejection fraction, postoperative mechanical ventilation time, postoperative B-type natriuretic peptide, and postoperative ICU retention time are risk factors for NOAF after OPCABG. Clinical attention should be paid to the above factors to achieve early identification, thereby reducing the incidence of NOAF after OPCABG and improving the clinical prognosis of patients.
9.Brain computer interface nursing bed control system based on deep learning and dual visual feedback.
Pai WANG ; Xingxing JI ; Jiali WANG ; Xiaojun YU
Journal of Biomedical Engineering 2025;42(5):1021-1028
In order to meet the need of autonomous control of patients with severe limb disorders, this paper designs a nursing bed control system based on motor imagery-brain computer interface (MI-BCI). In view of the low decoding performance of cross-subjects and the dynamic fluctuation of cognitive state in the existing MI-BCI technology, the neural network structure optimization and user interaction feedback enhancement are improved. Firstly, the optimized dual-branch graph convolution multi-scale neural network integrates dynamic graph convolution and multi-scale convolution. The average classification accuracy is higher than that of multi-scale attention temporal convolution network, Gram angle field combined with convolution long short term memory hybrid network, Transformer-based graph convolution network and other existing methods. Secondly, a dual visual feedback mechanism is constructed, in which electroencephalogram (EEG) topographic map feedback can improve the discrimination of spatial patterns, and attention state feedback can enhance the temporal stability of signals. Compared with the single EEG topographic map feedback and non-feedback system, the average classification accuracy of the proposed method is also greatly improved. Finally, in the four classification control task of nursing bed, the average control accuracy of the system is 90.84%, and the information transmission rate is 84.78 bits/min. In summary, this paper provides a reliable technical solution for improving the autonomous interaction ability of patients with severe limb disorders, which has important theoretical significance and application value.
Humans
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Brain-Computer Interfaces
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Deep Learning
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Electroencephalography
;
Feedback, Sensory
;
Neural Networks, Computer
;
Beds
10.Bisdemethoxycurcumin suppresses liver fibrosis-associated hepatocellular carcinoma via inhibiting CXCL12-induced macrophage polarization.
Wei YUAN ; Xinxin ZENG ; Bin CHEN ; Sihan YIN ; Jing PENG ; Xiong WANG ; Xingxing YUAN ; Kewei SUN
Chinese Journal of Natural Medicines (English Ed.) 2025;23(10):1232-1247
Chronic, unresolved inflammation correlates with persistent hepatic injury and fibrosis, ultimately progressing to hepatocellular carcinoma (HCC). Bisdemethoxycurcumin (BDMC) demonstrates therapeutic potential against HCC, yet its mechanism in preventing hepatic "inflammation-carcinoma transformation" remains incompletely understood. In the current research, clinical HCC specimens underwent analysis using hematoxylin-eosin (H&E) staining and immunohistochemistry (IHC) to evaluate the expression of fibrosis markers, M2 macrophage markers, and CXCL12. In vitro, transforming growth factor-β1 (TGF-β1)-induced LX-2 cells and a co-culture system of LX-2, THP-1, and HCC cells were established. Cell functions underwent assessment through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), flow cytometry, and Transwell assays. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blotting and immunofluorescence evaluated the differential expression of molecules. The interaction between β-catenin/TCF4 and CXCL12 was examined using co-immunoprecipitation (Co-IP), dual luciferase, and chromatin immunoprecipitation (ChIP) assays. A DEN-induced rat model was developed to investigate BDMC's role in liver fibrosis-associated HCC (LFAHCC) development in vivo. Our results showed that clinical HCC tissues exhibited elevated fibrosis and enriched M2 macrophages. BDMC delayed liver fibrosis progression to HCC in vivo. BDMC inhibited the inflammatory microenvironment induced by activated hepatic stellate cells (HSCs). Furthermore, BDMC suppressed M2 macrophage-induced fibrosis and HCC cell proliferation and metastasis. Mechanistically, BDMC repressed TCF4/β-catenin complex formation, thereby reducing CXCL12 transcription in LX-2 cells. Moreover, CXCL12 overexpression reversed BDMC's inhibitory effect on macrophage M2 polarization and its mediation of fibrosis, as well as HCC proliferation and metastasis. BDMC significantly suppressed LFAHCC development through CXCL12 in rats. In conclusion, BDMC inhibited LFAHCC progression by reducing M2 macrophage polarization through suppressing β-catenin/TCF4-mediated CXCL12 transcription.
Animals
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Liver Neoplasms/etiology*
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Humans
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Carcinoma, Hepatocellular/immunology*
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Liver Cirrhosis/complications*
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Macrophages/drug effects*
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Male
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Rats
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Chemokine CXCL12/genetics*
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Diarylheptanoids/pharmacology*
;
Rats, Sprague-Dawley
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beta Catenin/genetics*

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