ObjectiveTo establish an ultra-performance liquid fingerprint and multi-components determination method for Naomaili granules. To evaluate the quality of different batches by chemometrics， and the anti-neuroinflammatory effects of water extract and main components of Naomaili granules were tested in vitro. MethodsThe similarity and common peaks of 27 batches of Naomaili granules were evaluated by using Ultra performance liquid chromatography （UPLC） fingerprint detection. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） technology was used to determine the content of the index components in Naomaili granules and to evaluate the quality of different batches of Naomaili granules by chemometrics. LPS-induced BV-2 cell inflammation model was used to investigate the anti-neuroinflammatory effects of the water extract and main components of Naomaili granules. ResultsThe similarity of fingerprints of 27 batches of samples was > 0.90. A total of 32 common peaks were calibrated， and 23 of them were identified and assigned. In 27 batches of Naomaili granules， the mass fractions of 14 components that were stachydrine hydrochloride， leonurine hydrochloride， calycosin-7-O-glucoside， calycosin，tanshinoneⅠ， cryptotanshinone， tanshinoneⅡ_A， ginsenoside Rb₁， notoginsenoside R₁， ginsenoside Rg₁， paeoniflorin， albiflorin， lactiflorin， and salvianolic acid B were found to be 2.902-3.498， 0.233-0.343， 0.111-0.301， 0.07-0.152， 0.136-0.228， 0.195-0.390， 0.324-0.482， 1.056-1.435， 0.271-0.397， 1.318-1.649， 3.038-4.059， 2.263-3.455， 0.152-0.232， 2.931-3.991 mg∙g^-1， respectively. Multivariate statistical analysis showed that paeoniflorin， ginsenoside Rg₁， ginsenoside Rb₁ and staphylline hydrochloride were quality difference markers to control the stability of the preparation. The results of bioactive experiment showed that the water extract of Naomaili granules and the eight main components with high content in the prescription had a dose-dependent inhibitory effect on the release of NO in the cell supernatant. Among them， salvianolic acid B and ginsenoside Rb₁ had strong anti-inflammatory activity， with IC₅₀ values of （36.11±0.15） mg∙L^-1 and （27.24±0.54） mg∙L^-1， respectively. ConclusionThe quality evaluation method of Naomaili granules established in this study was accurate and reproducible. Four quality difference markers were screened out， and eight key pharmacodynamic substances of Naomaili granules against neuroinflammation were screened out by in vitro cell experiments.

ObjectiveTo conduct a theoretical study on the medical-rehabilitation integration. MethodsStarting from the background, objectives and content of the medical-rehabilitation integration, this study analyzed its innovative points from the dimensions of conceptual innovation, organizational innovation, model innovation and technological innovation. Results and ConclusionThe medical-rehabilitation integration is an innovation in medical services that takes conceptual innovation as the forerunner, organizational innovation as the foundation, model innovation as the carrier and technological innovation as the core.

Objective: To quantitatively assess the health risk of preservatives from beverages around primary schools in Anshun City, and to provide scientific basis for precise food safety supervision. Methods: From December 2023 to July 2024, 602 beverage samples were randomly collected from within 100 meters of 19 primary schools in Anshun City. The content of benzoic acid, sorbic acid, and dehydroacetic acid was detected according to GB 5009 series standards. Combined with children s physiological parameters (body weight 30 kg, daily intake 0.15 L), the Hazard Quotient (HQ) and Hazard Index (HI) models were used to evaluate health risks. Results: The total detection rate of preservatives from beverages around primary schools was 63.0%, and the total over limit rate was 9.0%. The detection rate of preservatives in flavored beverages was the highest (72.6%), and the highest over limit rate of preservatives in special purpose beverages was the highest (17.2%). The single preservative HQ (benzoic acid up to 0.47 ) and mixed HI (up to 0.55) of all samples were below 1(safety threshold). However, the HQ value of benzoic acid in flavored beverages (0.47) was 2.9 times that of sorbic acid (0.16), contributing significantly to health risk. Sensitivity analysis showed that if the daily consumption increased to 0.3 L, the HI value of flavored beverages would rise to 1.11, exceeding the safety threshold. Enterprise scale analysis showed that the exceedance rate of special purpose beverages in large enterprises reached 30.0%, while micro enterprises, accounting for a dominant market share (52.2%), constituted the main source of children s daily exposure to their products. Conclusions The overall health risk of perservatives in beverages sold near primary schools in Anshun City is controllable, but there is a noticeable risk of gradient. The risk of children’s exposure to preservatives through beverage consumption should not be ignored.

Objective To construct an optimal prediction model of chickenpox in Urumqi, and to provide reference for formulating the prevention and control strategies of chickenpox. Methods The multivariate autoregressive moving average model (ARIMAX) and random forest model (RF) were established based on the monthly incidence of chickenpox in Urumqi from 2014 to 2018, and the monthly incidence of chickenpox in 2019 was used to test the models and evaluate their prediction effect. The prediction performance of the two models was compared, and the best model was selected to predict the incidence of chickenpox in Urumqi. Results The incidence of chickenpox in Urumqi showed a regular bimodal distribution with obvious seasonality, and it showed a slow upward trend from July 2014 to December 2019. The fitting model was ARIMA(0,1,0)(0,1,1)₁₂, the root mean square error (RMSE) and mean absolute error (MAE) of ARIMAX model training set were 1.29 and 0.95, respectively, and the RMSE and MAE of the test set were 1.88 and 1.44, respectively. The training set RMSE and MAE of RF model were 1.56 and 1.56, respectively, and the test set RMSE and MAE were 4.83 and 3.96, respectively. Conclusion The performance of ARIMAX model is better than that of RF model, which can better predict the incidence trend of chickenpox in Urumqi. It is necessary to optimize the prediction model according to the actual situation and provide scientific guidance for the prevention and control of chickenpox.

During orthodontic treatment, clinical monitoring of patients is a crucial factor in determining treatment success. It aids in timely problem detection and resolution, ensuring adherence to the intended treatment plan. In recent years, digital technology has increasingly permeated orthodontic clinical diagnosis and treatment, facilitating clinical decision-making, treatment planning, and follow-up monitoring. This review summarizes recent advancements in digital technology for monitoring orthodontic tooth movement, related complications, and appliance-wearing compliance. It aims to provide insights for researchers and clinicians to enhance the application of digital technology in orthodontics, improve treatment outcomes, and optimize patient experience. The digitization of diagnostic data and the visualization of dental models make chair-side follow-up monitoring more convenient, accurate, and efficient. At the same time, the emergence of remote monitoring technology allows orthodontists to promptly identify oral health issues in patients and take corresponding measures. Furthermore, the multimodal data fusion method offers valuable insights into the monitoring of the root-alveolar relationship. Artificial intelligence technology has made initial strides in automating the identification of orthodontic tooth movement, associated complications, and patient compliance evaluation. Sensors are effective tools for monitoring patient adherence and providing data-driven support for clinical decision-making. The application of digital technology in orthodontic monitoring holds great promise. However, challenges like technical bottlenecks, ethical considerations, and patient acceptance remain.

ObjectiveTo combine metabolomics， proteomics， and transcriptomics to analyze the biological characteristics of damp-heat toxin accumulation syndrome and damp-heat accumulation syndrome in acute gout. MethodsBlood samples were collected from 15 patients with damp-heat toxin accumulation syndrome and 15 patients with damp-heat accumulation syndrome in acute gout in clinical practice. Metabolomics technology was applied to detect serum metabolites， and an orthogonal partial sample least squares discriminant analysis model was constructed to screen for metabolites with significant intergroup changes， and enrichment pathway analysis and receiver operating characteristic （ROC） curve analysis were performed. Astral data independence acquisition （DIA） was used to detect serum proteins， perform principal component analysis and screen differential proteins， demonstrate differential ploidy by radargram， apply subcellular localisation to analyse protein sources， and finally apply weighted gene co-expression network analysis （WGCNA） to find key proteins. Transcriptome sequencing technology was also applied to detect whole blood mRNA， screen differential genes and perform WGCNA， and construct machine learning models to screen key genes. ResultsMetabolome differential analysis revealed 62 differential metabolites in positive ion mode and 26 in negative ion mode. These differential metabolites were mainly enriched in the mTOR signaling pathway and FoxO signaling pathway， with trans-3,5-dimethoxy-4-hydroxycinnamaldehyde， guanabenz， 4-aminophenyl-1-thio-beta-d-galactopyranoside showing the highest diagnostic efficacy. The proteome differential analysis found that 55 proteins up-regulated and 20 proteins down-regulated in the samples of damp-heat toxin accumulation syndrome. Notably， myelin basic protein （MBP）， transferrin （TF）， DKFZp686N02209， and apolipoprotein B （APOB） showed the most significant differences in expression. Differential proteins were mainly enriched in pathways related to fat digestion and absorption， lipid and atherosclerosis， and cholesterol metabolism. WGCNA showed the highest correlation between damp-heat toxin accumulation syndrome and the brown module， with proteins in this module primarily enriched in the hypoxia-inducible factor 1 （HIF-1） signaling pathway and lipid and atherosclerosis. Transcriptomic differential analysis identified 252 differentially expressed genes， with WGCNA indicating the highest correlation between damp-heat toxin accumulation syndrome and the midnight blue module. The random forest （RF） model was identified as the optimal machine learning model， predicting apolipoprotein B receptor （APOBR）， far upstream element-binding protein 2 （KHSRP）， POU domain class 2 transcription factor 2 （POU2F2）， EH domain-containing protein 1 （EHD1）， and family with sequence similarity 110A （FAM110A） as key genes. Integrated multi-omics analysis suggested that damp-heat toxin accumulation syndrome in the acute phase of gout is closely associated with lipid metabolism， particularly APOB. ConclusionCompared to damp-heat accumulation syndrome in the acute phase of gout， damp-heat toxin accumulation syndrome is more closely associated with lipid metabolism， particularly APOB， and lipid metabolism disorders contribute to the development of damp-heat toxin accumulation syndrome in patients with acute gout.

Objective: To explore the effect of YTH domain family protein 1(YTHDF1) on the activation, proliferation and migration of hepatic stellate cells(HSCs) by regulating mitochondrial fission mediated by mitochondrial fission protein 1(Fis1). Methods: The mouse hepatic stellate cell line JS-1 was treated with 5 ng/ml TGF-β1 for 24 h to induce its activation and proliferation, andYTHDF1-siRNA was used to construct aYTHDF1silencing model.The experiment was divided into Control group, TGF-β1 group, TGF-β1+si-NC group and TGF-β1+si-YTHDF1 group.Expression changes ofYTHDF1,Fis1and key indicators of fibrosis, type Ⅰ collagen(CollagenⅠ) and α-smooth muscle actin(α-SMA) were detected through reverse transcription quantitative polymerase chain reaction(RT-qPCR) and Western blot; CCK-8 was used to detect cell proliferation ability; Transwell migration assay and cell scratch assay were used to detect cell migration ability; immunofluorescence staining experiment was used to detect the effect ofYTHDF1onFis1-mediated mitochondrial fission; finally, JC-1 staining was used to experimentally detect the effect ofYTHDF1on mitochondrial membrane potential. Results: Compared with the Control group, RT-qPCR and Western blot experimental results showed that the expression ofYTHDF1andFis1increased in the TGF-β1 group(P<0.05,P<0.01;P<0.000 1), as well as the fibrosis markersCollagenⅠand the expression level of α-SMA increased(P<0.01;P<0.001,P<0.000 1); while adding CCK-8, the experimental results showed that the proliferation ability of HSCs in the TGF-β1 group was enhanced(P<0.000 1); Transwell experimental results showed that the migration ability of HSCs in the TGF-β1 group was enhanced(P<0.01); the cell scratch experiment results showed that the migration ability of HSCs in the TGF-β1 group was enhanced(P<0.000 1); the immunofluorescence experiment results showed that the TGF-β1 group Mito-Tracker Red staining andFis1co-localization signal increased(P<0.05); JC-1 staining experiment results showed that the mitochondrial membrane potential increased in the TGF-β1 group(P<0.01). Compared with the TGF-β1+si-NC group, RT-qPCR and Western blot experimental results showed that the expression ofYTHDF1andFis1in the TGF-β1+si-YTHDF1 group was reduced(P<0.01;P<0.001), and fibrosis markers the levels ofCollagenⅠandα-SMAwere reduced(P<0.01;P<0.001,P<0.01).CCK-8 experimental results showed that the proliferation ability of HSCs in the TGF-β1+si-YTHDF1 group was weakened(P<0.000 1); Transwell experiment results showed that the migration ability of HSCs in the TGF-β1+si-YTHDF1 group was weakened(P<0.001); cell scratch experiment results showed that the migration ability of HSCs in the TGF-β1+si-YTHDF1 group was weakened(P<0.000 1); immunofluorescence experiment results showed that the Mito-Tracker Red staining andFis1co-localization signal decreased in the TGF-β1+si-YTHDF1 group(P<0.01); JC-1 staining experiment results showed that mitochondrial membrane potential decreased in the TGF-β1+si-YTHDF1 group(P<0.05). Conclusion YTHDF1promotes the activation, proliferation and migration capabilities of HSCs by positively regulatingFis1-mediated mitochondrial fission. This suggests thatYTHDF1may be a key gene involved in regulating the activation, proliferation and migration of HSCs.

BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.

BACKGROUND:U937 cells can be used as a cell model for studying the biological characteristics,signaling pathways,and therapeutic targets of acute myeloid leukemia.Although it has been reported that long non-coding RNA KIAA0125 is highly expressed in acute myeloid leukemia,its biological function in U937 cells remains unclear,and its mechanism of action in the occurrence and development of acute myeloid leukemia needs to be further clarified. OBJECTIVE:To investigate the expression level of long non-coding RNA KIAA0125 in peripheral blood of patients with acute myeloid leukemia and its effect on the proliferation and apoptosis of U937 cells. METHODS:RNA-sequencing was used to analyze the bone marrow monocyte samples from acute myeloid leukemia patients,and the differentially expressed gene long non-coding RNA KIAA0125 was screened.The expression of long non-coding RNA KIAA0125 in peripheral blood of patients with acute myeloid leukemia was detected by qRT-PCR.The relationship between long non-coding RNA KIAA0125 mRNA expression and prognosis in bone marrow cells of 173 acute myeloid leukemia patients and 70 healthy people was statistically analyzed by GEPIA database.Subsequently,recombinant lentivirus technology and CRISPR/Cas9-SAM technology were used to construct U937 cell lines with knockdown/overexpression of long non-coding RNA KIAA0125.qRT-PCR was used to detect the knockdown/overexpression efficiency of long non-coding RNA KIAA0125.Next,CCK-8 assay,flow cytometry,and western blot assay were used to detect the effects of knockdown/overexpression of long non-coding RNA KIAA0125 on the proliferation and apoptosis of U937 cells.Finally,western blot assay was used to detect the effect of knockdown/overexpressed long non-coding RNA KIAA0125 on Wnt/β-catenin signaling pathway-related proteins. RESULTS AND CONCLUSION:(1)The results of qRT-PCR showed that long non-coding RNA KIAA0125 was highly expressed in peripheral blood of acute myeloid leukemia patients.The results of GEPIA database showed that long non-coding RNA KIAA0125 was highly expressed in bone marrow cells of acute myeloid leukemia patients,and the high expression group had worse overall survival.(2)The knockdown efficiency of long non-coding RNA KIAA0125 in knockdown group was 70%,and the U937 cells that stably down-regulated long non-coding RNA KIAA0125 expression were successfully constructed.The expression of long non-coding RNA KIAA0125 in overexpression group was four times that of vector group,and stable U937 cells were successfully constructed.(3)Knockdown of long non-coding RNA KIAA0125 inhibited the proliferation of U937 cells and promoted their apoptosis.Overexpression of long non-coding RNA KIAA0125 promoted the proliferation of U937 cells but had no significant effect on the apoptosis of U937 cells.(4)Knockdown of long non-coding RNA KIAA0125 inhibited the activity of Wnt/β-catenin signaling pathway,while overexpression of long non-coding RNA KIAA0125 activated Wnt/β-catenin signaling pathway.These results confirm that long non-coding RNA KIAA0125 is highly expressed in acute myeloid leukemia peripheral blood.Long non-coding RNA KIAA0125 may affect the proliferation and apoptosis of U937 cells by regulating the Wnt/β-catenin signaling pathway,and may be a potential prognostic marker for acute myeloid leukemia.

ObjectiveThis study aims to investigate the dynamic changes in general body parameters, blood glucose, and blood lipid profiles in obese cynomolgus monkeys, exploring the correlations among these parameters and providing a reference for research on the obese cynomolgus monkey model. Methods30 normal male cynomolgus monkeys aged 5 - 17 years old (with body mass index < 35 kg/m² and glycated hemoglobin content < 4.50%) and 99 spontaneously obese male cynomolgus monkeys (with body mass index ≥35 kg/m² and glycated hemoglobin content < 4.50%) were selected. Over a period of three years, their abdominal circumference, skinfold thickness, body weight, body mass index, fasting blood glucose, glycated hemoglobin, and four blood lipid indicators were monitored. The correlations between each indicator were analyzed using repeated measurement ANOVA, simple linear regression, and multiple linear regression correlation analysis method. Results Compared to the control group, the obese group exhibited significantly higher levels of abdominal circumference, skinfold thickness, body weight, body mass index, and triglyceride (P＜0.05). In the control group, skinfold thickness increased annually, while other indicators remained stable. Compared with the first year, the obese group showed significantly increased abdominal circumference, skinfold thickness, body weight, body mass index, triglyceride, and fasting blood glucose in the second year(P＜0.05), with this increasing trend persisting in the third year (P＜0.05). In the control group, the obesity incidence rates in the second and third years were 16.67% and 23.33%, respectively, while the prevalence of diabetes remained at 16.67%. In the obese group, the diabetes incidence rates were 29.29% and 44.44% in years 2 and 3, respectively. Among the 11-13 year age group, the incidence rates were 36.36% and 44.68%, while for the group older than 13 years, the rates were 28.13% and 51.35%. Correlation analysis revealed significant associations (P＜0.05) between fasting blood glucose and age, abdominal circumference, skinfold thickness, body weight, and triglyceride in the diabetic monkeys. Conclusion Long-term obesity can lead to the increases in general physical indicators and fasting blood glucose levels in cynomolgus monkeys, and an increase in the incidence of diabetes. In diabetic cynomolgus monkeys caused by obesity, there is a high correlation between their fasting blood glucose and age, weight, abdominal circumference, skinfold thickness, and triglyceride levels, which is of some significance for predicting the occurrence of spontaneous diabetes.