This study investigated the functions and regulatory mechanism of Portulacae Herba and its chemical components on the Toll-like receptor 4(TLR4)/myeloid differentiation primary response 88(MyD88)/nuclear factor kappa B(NF-κB) inflammatory signaling pathway in the colon tissue of mice with dextran sodium sulfate(DSS)-induced ulcerative colitis(UC). A total of 35 mice were randomly divided into groups, including a blank group, a model group, a mesalazine group(0. 5 g·kg~(-1)), and low, medium,and high dose alkaloids from Portulacae Herba groups(9, 18, 36 mg·kg~(-1)), and a combination treatment group, with 5 mice in each group. The blank group was given purified water, while the other groups were continuously given a 3% DSS solution for 7 days to induce the UC model. From day 8 onwards, the treatment group received oral gavage according to the prescribed doses for 14 days. The overall condition, body weight, stool characteristics, and presence of blood in the stool were recorded daily. After the experiment, the disease activity index(DAI) was assessed for each group, and colon length was measured. Histopathological changes in colon tissue were examined using hematoxylin-eosin(HE) staining. The levels of pro-inflammatory cytokines, tumor necrosis factor-α(TNF-α),and interleukin-1β( IL-1β) in serum were measured by enzyme-linked immunosorbent assay( ELISA). The protein and m RNA expression of TLR4, MyD88, and NF-κB in colon tissue were measured using Western blot and quantitative real-time PCR(qPCR).Compared to the blank group, the model group showed a significant decrease in body weight, a notable increase in DAI scores, a significant shortening of colon length, and evident histopathological damage. The levels of inflammatory cytokines TNF-α and IL-1β in the serum were significantly elevated, and the protein and m RNA expression of TLR4, MyD88, and NF-κB in colon tissue were significantly up-regulated. In contrast, the alkaloids from Portulacae Herba treatment groups significantly improved symptoms and reduced body weight loss in mice, decreased DAI scores, alleviated colon shortening, lowered serum levels of TNF-α and IL-1β,significantly down-regulated the expression levels of TLR4, MyD88, and NF-κB proteins and genes in colon tissue, as well as reduced histopathological damage. Therefore, the study suggests that alkaloids from Portulacae Herba can alleviate intestinal inflammation damage in DSS-induced UC mice, with its mechanism involving the TLR4/MyD88/NF-κB signaling pathway.
Animals ; Colitis, Ulcerative/immunology* ; Toll-Like Receptor 4/immunology* ; Myeloid Differentiation Factor 88/metabolism* ; Mice ; NF-kappa B/metabolism* ; Signal Transduction/drug effects* ; Male ; Alkaloids/administration & dosage* ; Drugs, Chinese Herbal/administration & dosage* ; Humans ; Female ; Colon/metabolism* ; Disease Models, Animal

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

OBJECTIVE: The present study evaluated the effects of deep acupuncture at Weizhong acupoint (BL40) on bladder function and brain activity in a rat model of overactive bladder (OAB), and investigated the possible mechanisms around the acupuncture area that initiate the effects of acupuncture. METHODS: Adult female Sprague-Dawley rats were randomly divided into six groups, comprising a control group, model group, group treated with deep acupuncture at BL40, group treated with shallow acupuncture at BL40, group treated with acupuncture at non-acupoint next to BL40, and group treated with acupuncture at Xuanzhong (GB39). Urodynamic evaluation was used to observe the urination, and functional magnetic resonance imaging was used to observe the brain activation. The mechanism of acupuncture at BL40 in regulating bladder function was explored by toluidine blue staining and enzyme-linked immunosorbent assay, and the mechanism was verified by stabilizing mast cells (MCs) or blocking tibial nerve. RESULTS: Deep acupuncture at BL40 significantly increased the intercontraction interval in OAB rats and enhanced the mean amplitude of low frequency fluctuation of primary motor cortex (M1), periaquaductal gray matter (PAG), and pontine micturition center (PMC). It also increased the zero-lag functional connectivity between M1 and PAG and between PAG and PMC. Shallow acupuncture at BL40 and acupuncture at non-acupoint or GB39 had no effect on these indexes. Further studies suggested that deep acupuncture at BL40 increased the number and degranulation rate of MCs as well as the contents of 5-hydroxytryptamine, substance P, and histamine in the tissues around BL40. Blocking the tibial nerve by lidocaine injection or inhibiting MC degranulation by sodium cromoglycate injection obstructed the effects of acupuncture on restoring urinary function and modulating brain activation in OAB rats. CONCLUSION Deep acupuncture at BL40 may be more effective for inhibiting OAB by promoting degranulation of MCs around the acupoint and stimulating tibial nerve, thereby regulating the activation of the brain area that controls the lower urinary tract. Please cite this article as: Liu X, Zhang CY, Du XY, Li SS, Wang YQ, Zheng Y, Deng HZ, Fang XQ, Li JY, Wang ZQ, Xu SF, Mi YQ. Acupuncture at Weizhong (BL40) attenuates acetic acid-induced overactive bladder in rats by regulating brain neural activity through the modulation of mast cells and tibial nerves. J Integr Med. 2025; 23(1): 46-55.
Animals ; Urinary Bladder, Overactive/physiopathology* ; Mast Cells/physiology* ; Rats, Sprague-Dawley ; Female ; Acupuncture Therapy ; Acupuncture Points ; Rats ; Brain/physiopathology* ; Tibial Nerve/physiopathology* ; Acetic Acid ; Urinary Bladder/physiopathology*

OBJECTIVES: To investigate the clinicopathological characteristics and prognostic factors of pediatric Hodgkin lymphoma (HL). METHODS: A retrospective analysis was conducted on the clinical data of children with newly diagnosed HL from January 2011 to December 2023 at four hospitals: Fujian Medical University Union Hospital, Fujian Medical University Zhangzhou Hospital, First Affiliated Hospital of Xiamen University, and Fujian Children's Hospital. Patients were categorized into low-risk (R1), intermediate-risk (R2), and high-risk (R3) groups based on HL staging and pre-treatment risk factors. The patients received ABVD regimen or Chinese Pediatric HL-2013 regimen chemotherapy. Early treatment response and long-term efficacy were assessed, and prognostic factors were analyzed using the Cox proportional hazards regression model. RESULTS: The overall complete response (CR) rates after 2 and 4 cycles of chemotherapy were 42% and 68%, respectively. Compared with the ABVD regimen group, patients treated with the HL-2013 regimen in the R1 group showed significantly higher CR rates after both 2 and 4 cycles (P<0.05). However, no statistically significant differences in CR rates were observed between the two regimens in the R2 and R3 groups (P>0.05). The 5-year event-free survival (EFS) rate, overall survival rate, and freedom from treatment failure rate were 83%±4%, 97%±2%, and 88%±4%, respectively. Cox analysis indicated that the presence of a large tumor mass at diagnosis and failure to achieve CR after 4 cycles of chemotherapy were independent risk factors for lower EFS rates (P<0.05). CONCLUSIONS Pediatric HL generally has a favorable prognosis. The presence of a large tumor mass at diagnosis and failure to achieve CR after 4 cycles of chemotherapy indicate poor prognosis.
Humans ; Hodgkin Disease/pathology* ; Male ; Child ; Female ; Adolescent ; Retrospective Studies ; Child, Preschool ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Prognosis ; Proportional Hazards Models ; Survival Analysis ; Infant

OBJECTIVE: To screen factors affecting the prognosis of chronic myeloid leukemia (CML) patients, and construct a nomogram model for event-free survival (EFS). METHODS: To screen out meaningful variables by univariate and multivariate Cox regression analysis in CML patients, and construct a nomogram model using R software. The nomogram was validated using consistency index (C-index), receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), calibration curve, decision curve analysis (DCA), and risk stratification analysis. RESULTS: This study analyzed data from 116 CML patients. Univariate and multivariate Cox regression analysis demonstrated that age, peripheral blood basophil percentage, BCR-ABL1 ^IS at 3 months, and red blood cell distribution width (RDW) were independent prognostic factors of EFS. Subsequently, a nomogram was constructed based on the above predictors. The C-index of the nomogram was 0.733(95%CI : 0.676-0.790). The AUC values for predicting 1-, 3-, and 5-year EFS rate were 0.765, 0.855, and 0.827, respectively. The results of the calibration curve and DCA curve showed that the predictive model had good consistency, as well as strong clinical utility. The patients were stratified into high-risk group and low-risk group based on the total score of the model, there was a significant difference in EFS between the two groups (P < 0.001). CONCLUSION Age, peripheral blood basophil percentage, BCR-ABL1 ^IS at 3 months, and RDW were associated with the prognosis of CML patients. The nomogram model constructed in this study can accurately predict the prognostic status of CML patients, but its widespread application still requires external and prospective validation.
Nomograms ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/mortality* ; Proportional Hazards Models ; Erythrocyte Indices ; Risk Assessment/methods* ; Fusion Proteins, bcr-abl/genetics* ; Basophils ; Leukocyte Count ; Humans

OBJECTIVE: To explore the effect of bear bile powder (BBP) on acute lung injury (ALI) and the underlying mechanism. METHODS: The chemical constituents of BBP were analyzed by ultra-high-pressure liquid chromatography-mass spectrometry (UPLC-MS). After 7 days of adaptive feeding, 50 mice were randomly divided into 5 groups by a random number table (n=10): normal control (NC), lipopolysaccharide (LPS), dexamethasone (Dex), low-, and high-dose BBP groups. The dosing cycle was 9 days. On the 12th and 14th days, 20 µL of Staphylococcus aureus solution (bacterial concentration of 1 × 10^-7 CFU/mL) was given by nasal drip after 1 h of intragastric administration, and the mice in the NC group was given the same dose of phosphated buffered saline (PBS) solution. On the 16th day, after 1 h intragastric administration, 100 µL of LPS solution (1 mg/mL) was given by tracheal intubation, and the same dose of PBS solution was given to the NC group. Lung tissue was obtained to measure the myeloperoxidase (MPO) activity, the lung wet/dry weight ratio and expressions of CD14 and other related proteins. The lower lobe of the right lung was obtained for pathological examination. The concentrations of inflammatory cytokines including interleukin (IL)-6, tumour necrosis factor α (TNF-α ) and IL-1β in the bronchoalveolar lavage fluid (BALF) were detected by enzyme linked immunosorbent assay, and the number of neutrophils was counted. The colonic contents of the mice were analyzed by 16 sRNA technique and the contents of short-chain fatty acids (SCFAs) were measured by gas chromatograph-mass spectrometer (GC-MS). RESULTS: UPLC-MS revealed that the chemical components of BBP samples were mainly tauroursodeoxycholic acid and taurochenodeoxycholic acid sodium salt. BBP reduced the activity of MPO, concentrations of inflammatory cytokines, and inhibited the expression of CD14 protein, thus suppressing the activation of NF-κB pathway (P<0.05). The lung histopathological results indicated that BBP significantly reduced the degree of neutrophil infiltration, cell shedding, necrosis, and alveolar cavity depression. Moreover, BBP effectively regulated the composition of the intestinal microflora and increased the production of SCFAs, which contributed to its treatment effect (P<0.05). CONCLUSIONS BBP alleviates lung injury in ALI mouse through inhibiting activation of NF-κB pathway and decreasing expression of CD14 protein. BBP may promote recovery of ALI by improving the structure of intestinal flora and enhancing metabolic function of intestinal flora.
Animals ; Acute Lung Injury/pathology* ; Lipopolysaccharides ; Ursidae ; Gastrointestinal Microbiome/drug effects* ; Bile/chemistry* ; Lipopolysaccharide Receptors/metabolism* ; Powders ; Male ; Lung/drug effects* ; Mice ; Peroxidase/metabolism* ; Signal Transduction/drug effects* ; Cytokines/metabolism*

Objective To investigate the impact of risk prevention and control on the quality efficiency of medical equipment procurement.Methods The medical equipment procurement projects with enhanced risk prevention measures during 2023(119 items)were assigned to an observation group,while those without strengthened risk control during 2022(118 items)were enrolled into a control group.The two groups were compared in terms of bid failure/rejection rates,procurement completion cycles(including procurement execution cycle and total procurement cycle)and procurement satisfaction.Statistical analysis was performed using SPSS 20.0 software.Results The observation group demonstrated significantly lower bid failure/rejection rates when compared with the control group(≥2 occurrences:5.88％vs.15.25％,P＜0.05).The procurement execution cycle was notably shorter in the observation group((69.16±78.65)d vs.(97.67±49.84)d,P＜0.05),though no significant difference was observed in total procurement cycle(P＞0.05).The observation group behaved better significantly than the control group in procurement efficiency,equipment performance,procedural compliance and post-purchase service satisfaction(all P＜0.05).Conclusion Risk prevention and control measures in medical equipment procurement effectively reduce bid failure/rejection risks while enhancing procurement quality efficiency.[Chinese Medical Equipment Journal,2025,46(3):81-85]

P53 is a key tumor suppressor gene,which is regulated in many ways.Zinc finger 148(ZNF148)and SP5,as zinc finger transcription factors(TFs),play important roles in tumor suppression and carcinogenesis.The regulatory relationship between these two TFs and p53 has not been reported.In this paper,Ishikawa and A549 cell lines with different p53 expression levels were used as research mod-els to explore the transcriptional regulation of the P53 gene by ZNF148 and SP5.The data showed that there were differences in the expression of ZNF148 and SP5 in the two cell lines.The mRNA expression of ZNF148 in Ishikawa was 1.9 times higher than that of A549,and the mRNA expression of SP5 in A549 was 802.4 times that of ZNF148.Data showed that in Ishikawa cells,the expression of P53 de-creased(81.8％)after ZNF148 knockdown,and increased(2.6 times)after SP5 overexpression.Transfection of si-SP5 and ZNF148 expression plasmids into A549 cells increased the mRNA expression of P53 by 6.6 times and 14.6 times,respectively.These results indicate that ZNF148 could activate,whereas SP5 could inhibit,P53 expression.The conserved cis-element of ZNF148 and SP5 TFs was found in the region of the P53 promoter by bioinformatics methods.The data from dual luciferase reporter gene assay showed that the luciferase activity of ZNF148 in Ishikawa and A549 cells was increased by 2.1-fold and 4.2-fold compared with the control group(P＜0.05).Compared with the control group,the normalized relative luciferase activity of transfected SP5 decreased by 77.1％and 35.7％(P＜0.05).However,when the cis-element of ZNF148 and SP5 was mutated,the effect disappeared.Further trans-fection of ZNF148 and SP5 with different ratios revealed that SP5 could reverse the transcriptional activa-tion of P53 by ZNF148.Studies have shown that ZNF148 shares a common site with SP5,and the ratio of the two TFs may influence the transcriptional activity of P53.The expression of the Wnt pathway and the cell proliferation rate after knockdown of ZNF148 and SP5 were further studied to explore the role of the two TFs.Our data show that ZNF148 and SP5 could regulate the transcriptional activity of P53,and their expression levels and interaction may be the key factors regulating P53 expression.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.