ObjectiveTo investigate the therapeutic mechanism of Xuefu Zhuyutang （XFZYT） for metabolic-associated fatty liver disease （MAFLD） through integrated network pharmacology and animal experiments. MethodsNetwork pharmacology was utilized to predict the core components， key therapeutic targets， and signaling pathways of XFZYT in the treatment of MAFLD. For animal experiments， a rat model of MAFLD was established by feeding a high-cholesterol diet for 4 weeks. Intervention was then administered with low-dose （2 g·kg^-1） and high-dose （4 g·kg^-1） XFZYT for 2 weeks. Biochemical assays were performed to measure the serum levels of aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. In addition， the activities of superoxide dismutase （SOD） and catalase （CAT） and levels of malondialdehyde （MDA） and glutathione （GSH） in the serum were measured. The same way was adopted to measure the levels of TC and TG in the liver tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to quantify the serum levels of interleukin （IL）-6， IL-1β， and tumor necrosis factor-alpha （TNF-α）. Histopathological evaluations included hematoxylin and eosin （HE） staining for liver tissue morphology， Oil Red O staining for lipid deposition， and dihydroethidium （DHE） probe staining for reactive oxygen species （ROS） levels. Western blot analysis was conducted to assess the protein levels of AMP-activated protein kinase （AMPK）， phosphorylated （p）-AMPK， nuclear factor erythroid 2-related factor 2 （Nrf2）， heme oxygenase-1 （HO-1）， nuclear factor-kappa B （NF-κB）， and p-NF-κB in the liver tissue. Untargeted metabolomics analysis of the serum was performed by liquid chromatography-tandem mass spectrometry （LC-MS/MS）. ResultsNetwork pharmacology analysis predicted 155 potential targets of XFZYT for MAFLD treatment， with core targets including signal transducer and activator of transcription 3 （STAT3）， protein kinase B1 （Akt1）， TNF， and IL-6. Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment primarily implicated the AMPK signaling pathway. Animal experiments demonstrated that compared with the normal group， the model group exhibited dyslipidemia， hepatic function impairment， pronounced hepatic lipid deposition， and inflammatory manifestations， with elevated serum levels of AST， ALT， TC， TG， LDL， and MDA （P<0.05）， reduced HDL and GSH levels plus decreased SOD and CAT activities （P<0.05）， downregulated protein levels of Nrf2， HO-1， and p-AMPK （P<0.05）， and upregulated protein level of p-NF-κB （P<0.05） in the liver tissue. Compared with the model group， XFZYT intervention groups showed significant amelioration of dyslipidemia and hepatic function impairment， markedly reduced hepatic lipid deposition and inflammatory cell infiltration， decreased serum levels of AST， ALT， TC， TG， LDL， and MDA （P<0.05）， increased HDL and GSH levels plus enhanced SOD and CAT activities （P<0.05）， upregulated protein levels of Nrf2， HO-1， and p-AMPK （P<0.05）， and downregulated protein level of p-NF-κB （P<0.05）. Serum metabolomics revealed 511 differentially expressed metabolites （231 upregulated and 280 downregulated） between normal and model groups， while XFZYT groups versus model group showed 94 differential metabolites （51 upregulated and 43 downregulated）. Among them， 11 metabolites displayed the most significant alterations， with enriched pathways including glycerolipid metabolism， cholesterol metabolism， and insulin resistance， multiple of which demonstrated AMPK association. ConclusionXFZYT alleviates MAFLD by regulating the AMPK signaling pathway and associated metabolic networks.

ObjectiveTo investigate the effects of exogenous nitric oxide （NO） on the accumulation and quality formation mechanism of flavonoids in Scutellariae Radix. MethodsFresh roots of Scutellaria baicalensis were treated with sodium nitroprusside （SNP） solutions at concentrations of 0.0， 7.5， and 20 mmol·L^-1， respectively. Kits and supporting reaction systems were used to determine the following indicators of samples in each group， including （1） reactive oxygen species： changes in the content of nitric oxide （NO）， superoxide anion （O2-·）， and hydrogen peroxide （H₂O₂）， （2） lipid oxidation products： changes in the content of malondialdehyde （MDA）， （3） antioxidant enzymes： changes in the activity of superoxide dismutase （SOD）， catalase （CAT）， and peroxidase （POD）， and （4） metabolic key enzymes and metabolic intermediates： Changes in the activity of phenylalanine ammonia-lyase （PAL） and the content of 1，3-diphosphoglycerate （1，3-DPG）. High-performance liquid chromatography （HPLC） was used to determine the changes in the content of secondary metabolites in flavonoids such as baicalin， wogonoside， baicalein， and wogonin in each group. ResultsCompared with that on day 0， during the treatment with 20 mmol·L^-1 SNP solution， the content of NO， O2-·， H₂O₂， and MDA in fresh roots of Scutellaria baicalensis increased significantly （P<0.01）， by 138.7%， 75.7%， 292.9%， and 140.3% respectively. The activity of SOD， CAT， and POD increased by 100.7%， 41.4%， and 70.4% respectively （P<0.01）， and that of PAL increased by 111.1% （P<0.01）. The content of the secondary metabolites baicalin and wogonoside remained basically unchanged， while that of baicalein and wogonin increased by 401.3% and 457.9% respectively （P<0.01）. The content of 1，3-DPG increased by 165.0% （P<0.01）. In the 7.5 mmol·L^-1 SNP solution treatment group， the stress degree was relatively mild. Compared with that on day 0， the content of NO， O2-·， H₂O₂， and MDA increased by 76.2%， 57.7%， 221.4%， and 99.7% respectively （P<0.01）. The activity of antioxidant enzymes SOD， CAT， and POD increased by 79.5%， 55.6%， and 51.9% respectively （P<0.01）， and that of PAL increased by 69.0% （P<0.01）. The content of baicalein and wogonin increased by 204.7% and 272.2% respectively （P<0.01）， and that of 1，3-DPG increased by 128.0% （P<0.01）. The 20 mmol·L^-1 SNP group showed better performance than the 7.5 mmol·L^-1 SNP group. ConclusionSNP can simulate the physiological state of Scutellaria baicalensis under stress conditions， activate the antioxidant protection mechanism， promote the biosynthesis of flavonoids in Scutellariae Radix， and significantly improve the quality of medicinal materials in Scutellariae Radix.

Background Injury poses a serious threat to human health. As global warming continues to intensify, there is an urgent need to explore the impact of temperature changes on injury deaths. However limited research has focused on this issue. Objective To investigate the relationship between daily mean temperature change (Tm) and injury death, as well as to estimate the associated future death burden in Hunan Province. Methods We employed an individual-level, time-stratified case-crossing design to establish a conditional logistic regression model to analyze the exposure-response relationship between daily mean temperature change and injury death in Hunan Province from 2013 to 2018. Consequently, we conducted subgroup analysis of gender, age group, and injury type. Finally, we estimated the excess burden of injury death attributable to temperature changes under a sustainable development path [low emission scenario (SSP1-2.6)], regional competition path [high emission scenario (SSP3-7.0)], or fossil fuel development path [very high emission scenario (SSP5-8.5)]. Results The study collected 155577 injury deaths in Hunan Province. The results indicated that for each 1 ℃ increment in daily mean temperature, the cumulative excess risk (CER) of injury mortality among Hunan residents increased by 0.71% (95%CI: 0.53%, 0.90%). Notably, the CER for intentional injuries (1.06%, 95%CI: 0.51%, 1.61%) was higher than that for unintentional injuries (0.66%, 95%CI: 0.46%, 0.87%). Warmer temperatures were positively associated with CER of mortality due to drowning, falls, transport injuries, assaults, and suicides, while they were negatively associated with mortality due to poisoning. Compared with 2010–2019, for 2090–2099, the excess mortality rate (EMR) due to ambient temperature increase in Hunan Province under the SSP5-8.5 scenario (14.62/100000, 95%CI: 10.81/100000, 18.40/100000) would be higher than that of the SSP3-7.0 scenario (10.28/100000, 95%CI: 7.58/100000, 12.97/100000) and the SSP1-2.6 scenario (3.35/100000, 95%CI: 2.46/100000, 4.23/100000); the EMR would be around 2.5 times among men (20.64/100000, 95%CI: 14.44/100000, 26.8/100000) than that among women (8.33/100000, 95%CI: 3.98/100000, 12.6/100000). Among unintentional injuries, the leading contributors to EMR would be drowning (4.46/100000), falls (3.96/100000), and transport injuries (2.96/100000). And among intentional injuries, the EMR for suicide (2.08/100000) would be higher than that for assault (0.47/100000). Conclusion Climate warming will increase the total burden of injury-related deaths among residents in Hunan Province, especially in the absence of effective mitigation strategies and measures. It is necessary to strengthen the prevention and control of severe injuries closely related to temperature changes, such as drowning, falls, traffic, and suicides injuries, in order to reduce injury deaths associated with climate change.

AIM:To identify surrogate clinical bio-markers for profiling the eosinophilic status of an individual patient over induced sputum analysis.METHODS:We conducted a cross-sectional study on 100 asthmatic patients whose induced sputum was successfully collected.Subjects were further classified into either EA or NEA based on whether the percentage of sputum eosinophil count(SEC％)was≥3％.Demographic and clinical data were col-lected,including basic information,routine blood tests,lung function tests,bronchodilator reversibili-ty tests,fractional exhaled nitric oxide(FeNO),the Asthma Control Test(ACT)and the Asthma Control Questionnaire(ACQ).All variables significantly asso-ciated with EA were candidates for multivariate lo-gistic regression analysis.A scoring system present-ed as a nomogram for the prediction of EA was de-veloped.RESULTS:In the univariate analysis,com-pared with NEA subjects,those with EA were of older age and had worse asthma control and lung function in addition to higher values of blood eosin-ophils,serum IgE and FeNO.Multivariable logistic regression analysis revealed that age,FeNOx serum IgE and blood eosinophil count(BEC)were identi-fied as independent risk factors for eosinophilic asthma,which were all included in the nomogram.CONCLUSION:A combination assessment including age,FeNOx serum IgE and BEC could be applicable to clinicians in identifying eosinophilic asthma and is easier,faster,more inexpensive and more readily available than the induced sputum test.

Objective To explore the interaction mechanisms among different dimensions of online learning competence in undergraduates,providing scientific evidence for optimizing software design and online education strategies.Methods A cross-sectional study was conducted with 347 undergraduates from Kunming Medical University via an online questionnaire in October 2024.Reliability testing and exploratory factor analysis were performed using SPSS 26.0,while structural equation modeling was constructed with Amos 24.0.Results Driving force directly and positively influenced regulatory force(β=0.778,P<0.001)and reciprocal force(β=0.302,P=0.003),but had no significant direct effect on adaptive force(β=0.131,P=0.182).Regulatory force and reciprocal force both exerted direct positive effects on adaptive force(β=0.262,P=0.022;β=0.410,P<0.001).The indirect effect of driving force on adaptive force accounted for 78.1%of the total effect(P=0.007),with regulatory force showing a significant mediating role(β=0.178,P=0.023),while reciprocal force alone did not(β=0.108,P=0.060).A chain mediating effect(driving force→regulatory force→reciprocal force→adaptive force)was confirmed(β=0.124,P=0.004).Conclusion Driving force serves as the core of online learning competence,and adaptive capacity is enhanced through regulatory and reciprocal forces.To promote knowledge internalization and adaptability,it is required to optimize feedback mechanisms and deepen interactive designs in online learning platforms.

Objectives To identify key clinical factors influencing recurrence in osteosarcoma patients,to construct and validate a Nomogram-based recurrence risk prediction model,thereby providing a quantitative tool for clinical decision-making and recurrence prevention/control.Methods Clinical data of 469 osteosarcoma patients admitted to Yunnan Cancer Hospital between 2013～2022 were retrospectively collected.Statistical analysis was performed using R software(version 4.3.2).Potential influencing factors were initially screened via univariate analysis and LASSO regression analysis.Independent predictors of osteosarcoma recurrence were then identified using multivariate logistic regression analysis.Based on the identified independent factors,a Nomogram prediction model for recurrence risk was constructed.The area under the receiver operating characteristic curve(AUC)was used to evaluate the model's discriminative ability.Results Among the entire cohort,68 patients experienced recurrence,yielding a recurrence rate of 14.50%.Multivariate analysis identified the following as independent predictors of recurrence:Primary Tumor Location:Tibial lesions(P=0.009)were associated with a significantly lower recurrence risk compared to femoral lesions(OR=0.297),while lesions in"Other Bones"(P=0.008)carried a significantly higher risk(OR=3.294).Biopsy Method:Needle biopsy(P=0.033)was associated with a significantly lower recurrence risk compared to open biopsy(OR=0.461).Lung Metastasis Status:Patients with lung metastasis(P<0.001)had a significantly higher recurrence risk than those without(OR=11.873).Lymphocyte Count:A higher lymphocyte count(P=0.001)was a protective factor,associated with a lower recurrence risk(OR=0.450).The constructed Nomogram prediction model demonstrated excellent performance:Validation results showed an AUC=0.842(95%CI:0.806～0.875),indicating outstanding discriminative ability.Conclusions This study successfully constructed and validated a Nomogram prediction model for osteosarcoma recurrence risk integrating key clinical factors.The model demonstrates superior discriminative ability and can accurately and quantitatively assess the recurrence risk for individual patients.This tool thus provides critical reference for guiding clinical treatment decisions.

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

Hormesis effect has been observed in the secondary metabolite synthesis of microorganisms induced by rare earth elements. However, the underlying molecular mechanism remains unclear. To analyze the molecular mechanism of the regulatory effect of Rhodotorula mucilaginosa in the presence of lanthanum chloride, different concentrations of lanthanum chloride were added to the fermentation medium of Rhodotorula mucilaginosa, and the carotenoid content was subsequently measured. It was found that the concentrations of La³⁺ exerting the promotional and inhibitory effects were 0-100 mg/L and 100-400 mg/L, respectively. Furthermore, the expression of 33 genes and the synthesis of 55 metabolites were observed to be up-regulated, while the expression of 85 genes and the synthesis of 123 metabolites were found to be down-regulated at the concentration range of the promotional effect. Notably, the expression of carotenoid synthesis-related genes except AL1 was up-regulated. Additionally, the content of β-carotene, lycopene, and astaxanthin demonstrated increases of 10.74%, 5.02%, and 3.22%, respectively. The expression of 5 genes and the synthesis of 91 metabolites were up-regulated, while the expression of 35 genes and the synthesis of 138 metabolites were down-regulated at the concentration range of the inhibitory effect. Meanwhile, the content of β-carotene, lycopene, and astaxanthin decreased by 21.73%, 34.81%, and 35.51%, respectively. In summary, appropriate concentrations of rare earth ions can regulate the synthesis of secondary metabolites by modulating the activities of various enzymes involved in metabolic pathways, thereby exerting the hormesis effect. The findings of this study not only contribute to our comprehension for the mechanism of rare earth elements in organisms but also offer a promising avenue for the utilization of rare earth elements in diverse fields, including agriculture, pharmaceuticals, and healthcare.
Lanthanum/pharmacology* ; Rhodotorula/genetics* ; Carotenoids/metabolism* ; Hormesis/drug effects* ; Fermentation ; Multiomics

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.