Objective To establish a scientific, comprehensive, and operable community resilience evaluation index system for emergent major infectious diseases. Methods Based on the social ecosystem theory, a preliminary evaluation index system was formed by using content analysis and boundary analysis. The index system was then supplemented and revised through panel discussions. The final index system and index weights were clarified by two rounds of Delphi method. Results The expert positive coefficient, expert authority coefficient, and expert coordination coefficient of the two rounds of expert consultations were examined. According to the screening principle of the ^“threshold method^”, the indicators were screened, and the weights of each indicator were determined in the second round of Delphi expert consultation. The analysis of the reliability of the indicator system showed Cronbach's α= 0.399 , indicating that the indicator system had a relatively high reliability. Factor analysis was carried out on 7 primary indicators, and the measure of sampling adequacy (MSA) values were all greater than 0.5, which passed the validity test. Conclusion A set of evaluation index system that can accurately reflect the resilience level of communities with emergent major infectious diseases has been constructed, including 7 primary indicators, 21 secondary indicators, 54 tertiary indicators, and 108 tertiary indicators, which has realized the quantitative evaluation of the hidden resilience level of communities.

Cardiovascular disease (CVD) remains one of the leading causes of mortality among adults globally, with continuously rising morbidity and mortality rates. Metabolic disorders are closely linked to various cardiovascular diseases and play a critical role in their pathogenesis and progression, involving multifaceted mechanisms such as altered substrate utilization, mitochondrial structural and functional dysfunction, and impaired ATP synthesis and transport. In recent years, the potential role of peroxisome proliferator-activated receptors (PPARs) in cardiovascular diseases has garnered significant attention, particularly peroxisome proliferator-activated receptor alpha (PPARα), which is recognized as a highly promising therapeutic target for CVD. PPARα regulates cardiovascular physiological and pathological processes through fatty acid metabolism. As a ligand-activated receptor within the nuclear hormone receptor family, PPARα is highly expressed in multiple organs, including skeletal muscle, liver, intestine, kidney, and heart, where it governs the metabolism of diverse substrates. Functioning as a key transcription factor in maintaining metabolic homeostasis and catalyzing or regulating biochemical reactions, PPARα exerts its cardioprotective effects through multiple pathways: modulating lipid metabolism, participating in cardiac energy metabolism, enhancing insulin sensitivity, suppressing inflammatory responses, improving vascular endothelial function, and inhibiting smooth muscle cell proliferation and migration. These mechanisms collectively reduce the risk of cardiovascular disease development. Thus, PPARα plays a pivotal role in various pathological processes via mechanisms such as lipid metabolism regulation, anti-inflammatory actions, and anti-apoptotic effects. PPARα is activated by binding to natural or synthetic lipophilic ligands, including endogenous fatty acids and their derivatives (e.g., linoleic acid, oleic acid, and arachidonic acid) as well as synthetic peroxisome proliferators. Upon ligand binding, PPARα activates the nuclear receptor retinoid X receptor (RXR), forming a PPARα-RXR heterodimer. This heterodimer, in conjunction with coactivators, undergoes further activation and subsequently binds to peroxisome proliferator response elements (PPREs), thereby regulating the transcription of target genes critical for lipid and glucose homeostasis. Key genes include fatty acid translocase (FAT/CD36), diacylglycerol acyltransferase (DGAT), carnitine palmitoyltransferase I (CPT1), and glucose transporter (GLUT), which are primarily involved in fatty acid uptake, storage, oxidation, and glucose utilization processes. Advancing research on PPARα as a therapeutic target for cardiovascular diseases has underscored its growing clinical significance. Currently, PPARα activators/agonists, such as fibrates (e.g., fenofibrate and bezafibrate) and thiazolidinediones, have been extensively studied in clinical trials for CVD prevention. Traditional PPARα agonists, including fenofibrate and bezafibrate, are widely used in clinical practice to treat hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) levels. These fibrates enhance fatty acid metabolism in the liver and skeletal muscle by activating PPARα, and their cardioprotective effects have been validated in numerous clinical studies. Recent research highlights that fibrates improve insulin resistance, regulate lipid metabolism, correct energy metabolism imbalances, and inhibit the proliferation and migration of vascular smooth muscle and endothelial cells, thereby ameliorating pathological remodeling of the cardiovascular system and reducing blood pressure. Given the substantial attention to PPARα-targeted interventions in both basic research and clinical applications, activating PPARα may serve as a key therapeutic strategy for managing cardiovascular conditions such as myocardial hypertrophy, atherosclerosis, ischemic cardiomyopathy, myocardial infarction, diabetic cardiomyopathy, and heart failure. This review comprehensively examines the regulatory roles of PPARα in cardiovascular diseases and evaluates its clinical application value, aiming to provide a theoretical foundation for further development and utilization of PPARα-related therapies in CVD treatment.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective To explore the prognostic factor and its predictive value of patients with Wilson disease-related acute-on-chronic liver failure(WD-ACLF).Methods The clinical data of 70 patients diagnosed as WD-ACLF admitted to the Department of Encephalopathy of the First Affiliated Hospital of Anhui University of Chinese Medicine from January 1,2017 to January 1,2022 were retrospectively collected.According to the 12-week prognosis,patients were divided into survival group(n=36)and death group(n=34).The data of the two groups were analyzed by univariate and multivariate logistic analysis to screen the prognostic risk factors and evaluate their predictive value.The model coefficient is omnibus tested,and the model-fitting degree is evaluated by the Hosmer-Lemeshow test.ROC curve was used to analyze the prognostic value for WD-ACLF between the new model and chronic liver failure-sequential organ failure assessment(CLIF-SOFA)score,model for end-stage liver disease(MELD)score and Child-Turcotte-Pugh(CTP)score.Results A total of 70 WD-ACLF patients were enrolled in present study,including 36 cases in survival group[22 males and 14 females with median age of 30.0(17.3,40.0)]and 34 cases in death group[25 males and 9 females with median age of 34.0(28.8,41.0)].Univariate analysis showed that the course of disease,prothrombin time(PT),activated partial thromboplastin time(APTT)were shorter in survival group than that in death group,the white blood cells(WBC),international normalized ratio(INR),aspartate transaminase(AST),total bilirubin(TBIL),blood urea nitrogen(BUN),creatinine(Cre)and ceruloplasmin(CER)levels and the proportion of infection,ascites,and upper gastrointestinal bleeding were lower in survival group than those in death group,however,the proportion of infection,ascites and upper digestive bleeding in the survival group were lower than those in the death group.Meanwhile,the red blood cells(RBC),hemoglobin(Hb),Na+ and total cholesterol(TC)level in the survival group were higher than those in the death group(P<0.05 or P<0.01).The results of multivariate logistic regression analysis showed that disease course(OR=1.176,95%CI 1.043-1.325),INR(OR=7.635,95%CI 1.767-32.980),TBIL(OR=1.012,95%CI 1.003-1.021),and upper gastrointestinal bleeding(OR=11.654,95%CI 1.029-131.980)were independent risk factors affecting the prognosis of WD-ACLF(P<0.05).Based on the results of logistic regression analysis,a joint model for predicting the prognosis of WD-ACLF was established.The AUC of the model for evaluating the prognosis of WD-ACLF was 0.941,which was greater than the CLIF-SOFA score(AUC=0.802),MELD score(AUC=0.897),and CTP score(AUC=0.722).Conclusions The course of disease,TBIL,INR,and upper gastrointestinal bleeding are risk factors that affect the prognosis of WD-ACLF.The prognosis model established based on this can more accurately predict the prognosis of WD-ACLF patients,and its predictive value is superior to CLIF-SOFA score,MELD score,and CTP score.

The growth of three plague phages from Qinghai Plateau in two Yersinia pestis strains(plague vaccine strains EV76 and 614F)and four non-Yersinia pestis strains(Yersinia pseudotuberculosis PTB3,PTB5,Escherichia coli V517,and Yersinia enterocolitica 52302-2)were detected through a micromethod based on the OmniLogTM microbial identification system and by the drop method,to provide a scientific basis for future ecological studies and classification based on the host range.For plague vaccine strains EV76 and 614F,successful phage infection and subsequent phage growth were observed in the host bacte-rium.Diminished bacterial growth and respiration and a concomitant decrease in color were observed with the OmniLogTM mi-crobial identification system at 33 ℃ for 48 h.Yersinia pseudotuberculosis PTB5 was sensitive to Yersinia pestis phage 476,but Yersinia pseudotuberculosis PST5 was insensitive to phage 087 and 072204.Three strains of non-Yersinia pestis(Yersinia pseudotuberculosis PTB3,Escherichia coli V517,and Yersinia enterocolitica 52302-2)were insensitive to Yersinia pestis pha-ges 087,072204,and 476 showed similar growth curves.The growth of phages 476 and 087,as determined with the drop method,in two Yersinia pestis strains(plague vaccine strains EV76 and 614F)and four non-Yersinia pestis strains(Yersinia pseudotuberculosis PTB3,Escherichia coli V517,and Yersin-ia enterocolitica 52302-2)showed the same results at 37 ℃,on the basis of comparisons with the OmniLogTM microbial i-dentification system;in contrast,phages 072204 did not show plaques on solid medium at 37 ℃ with plague vaccine strains EV76 and 614F.Determination based on the OmniLogTM detection system can be used as an alternative to the traditional determination of the host range,thus providing favorable application val-ue for determining the interaction between the phage and host bacteria.

AIM To identify the chemical components of Longmu Qingxin Mixture by UPLC-Q-TOF-MS and study its material basis for the treatment of attention deficit hyperactivity disorder.METHODS The sample was detected by mass spectrometry in positive and negative ion mode on a Waters CORTECS? UPLC? T3 chromatographic column.The data were analyzed with Peakview 1.2 software and matched with the Natural Products HR-MS/MS Spectral Library 1.0 database,and the components were identified in combination with literature reports.The material basis of Longmu Qingxin Mixture for the treatment of attention deficit hyperactivity disorder was analysed according to the identified components.RESULTS Forty chemical components were identified,including 11 flavonoids,6 monoterpene glycosides,4 triterpene saponins,3 phenolic acids,6 alkaloids etc.,which mainly derived from Radix Astragali,Radix Paeoniae Alba,Radix Scutellariae,licorice root,Ramulus Uncariae cum,etc.,baicalein,formononetin,astragaloside Ⅳ and rhynchophylline may be the material basis for the therapeutic effect of Longmu Qingxin Mixture.CONCLUSION UPLC-Q-TOF-MS can quickly identify the chemical components of Longmu Qingxin Mixture.Flavonoids,triterpene saponins and alkaloids may be the material basis for Longmu Qingxin Mixture for the treatment of attention deficit hyperactivity disorder,which can provide the basis for its material basis research,quality standard establishment and pharmacological study of the dismantled formula.

ObjectiveThe absorption of substances into blood is mainly dependent on the mesenteric lymphatic pathway and the portal venous pathway. The substances transported via the portal venous pathway can be metabolized by the biotransformation in the liver. On the contrary, the substances in the mesenteric lymph fluid enter the blood circulation without biotransformation and can affect the body directly. Alcohol consumption is strongly linked to global health risk. Previous reports have analyzed the changes of metabolites in plasma, serum, urine, liver and feces after alcohol consumption. Whether alcohol consumption affects the metabolites in lymph fluid is still unknown. Therefore, it is particularly important to explore the changes of substances transported via the mesenteric lymphatic pathway and analyze their harmfulness after alcohol drinking. MethodsIn this study, male Wistar rats were divided into high, medium, and low-dosage alcohol groups (receiving Chinese Baijiu at 56%, 28% and 5.6% ABV, respectively) and water groups. The experiment was conducted by alcohol gavage lasting 10 d, 10 ml·kg^-1·d^-1. Then mesenteric lymph fluid was collected for non-targeted metabolomic analysis by using liquid chromatography-mass spectrometry (LC-MS) and bioinformatic analysis. Principal component analysis and hierarchical clustering were performed by using Biodeep. Meanwhile, KEGG enrichment analysis of the differential metabolites was also performed by Biodeep. MetaboAnalyst was used to analyze the relationship between the differential metabolites and diseases. ResultsThe metabolites in the mesenteric lymph fluid of the high-dosage alcohol group change the most. Based on the KEGG enrichment analysis, the pathways of differential metabolites between the high-dosage alcohol group and the control group are mainly enriched in the central carbon metabolism in cancer, bile secretion, linoleic acid metabolism, biosynthesis of unsaturated fatty acids, etc. Interestingly, in the biosynthesis of unsaturated fatty acids category, the content of arachidonic acid is increased by 7.25 times, whereas the contents of palmitic acid, oleic acid, stearic acid, arachidic acid and erucic acid all decrease, indicating lipid substances in lymph fluid are absorbed selectively after alcohol intake. It’s worth noting that arachidonic acid is closely related to inflammatory response. Furthermore, the differential metabolites are mainly related with schizophrenia, Alzheimer’s disease and lung cancer. The differential metabolites between the medium-dosage alcohol and the control group were mainly enriched in phenylalanine metabolism, valine, leucine and isoleucine biosynthesis, linoleic acid metabolism and cholesterol metabolism. The differential metabolites are mainly related to schizophrenia, Alzheimer’s disease, lung cancer and Parkinson’s disease. As the dose of alcohol increases, the contents of some metabolites in lymph fluid increase, including cholesterol, L-leucine, fumaric acid and mannitol, and the number of metabolites related to schizophrenia also tends to increase, indicatingthat some metabolites absorbed by the intestine-lymphatic pathway are dose-dependent on alcohol intake. ConclusionAfter alcohol intake, the metabolites transported via the intestinal-lymphatic pathway are significantly changed, especially in the high-dosage group. Some metabolites absorbed via the intestinal-lymphatic pathway are dose-dependent on alcohol intake. Most importantly, alcohol intake may cause inflammatory response and the occurrence of neurological diseases, psychiatric diseases and cancer diseases. High-dosage drinking may aggravate or accelerate the occurrence of related diseases. These results provide new insights into the pathogenesis of alcohol-related diseases based on the intestinal-lymphatic pathway.

The incidence of intrahepatic cholangiocarcinoma (ICC) continues to rise, and there are no effective drugs to treat it. The immune microenvironment plays an important role in the development of ICC and is currently a research hotspot. Icaritin (ICA) is an innovative traditional Chinese medicine for the treatment of advanced hepatocellular carcinoma. It is considered to have potential immunoregulatory and anti-tumor effects, which is potentially consistent with the understanding of "Fuzheng" in the treatment of tumor in traditional Chinese medicine. However, whether ICA can be used to treat ICC has not been reported. Therefore, in this study, sgp19/kRas, an in situ ICC mouse model with intact immune system, was selected to evaluate the efficacy of ICA in the treatment of ICC in vivo for the first time, and the effects of ICA on the tumor immune microenvironment of ICC mice were analyzed by flow cytometry. This experiment was approved by the Experimental Animal Ethics Committee of Capital Medical University (approval number: AEEI-2023-138). In this study, sgp19/kRas ICC mouse model was treated with oral gavage of 100 mg·kg^-1 ICA. We found that ICA significantly inhibited tumor growth and tumor cell proliferation in the sgp19/kRas ICC mouse model after 3 weeks of treatment. Flow cytometry analysis indicated that ICA treatment markedly reduced the proportion of M2 macrophages and increased the number of CD3⁺CD4⁺ T cells. In vitro experiments demonstrated that ICA promoted macrophage polarization towards the M1 phenotype while inhibiting polarization towards the M2 phenotype. Furthermore, transcriptomic analysis suggested that ICA enhanced Toll-like receptor 9 (TLR9) expression, influencing macrophage nitric oxide metabolism synthesis pathways and receptor-related activities, thereby regulating macrophage polarization. In summary, this study demonstrates that ICA treatment significantly delays tumor progression in sgp19/kRas ICC mouse models. Mechanistically, ICA may achieve its anti-ICC effects by upregulating TLR9 receptor expression levels, promoting macrophage polarization towards the M1 phenotype, and altering the tumor immune microenvironment.

Objective To investigate the mechanism of the interaction between Wnt/β-catenin signaling and the epithelial mesenchymal transition(EMT)pathway in mediating sunitinib-resistance in renal cancer cells.Methods The sunitinib-resistant kidney cancer cell lines were constructed by stepwise increase in drug concentrations method with sunitinib,and were divided into resistance group,lv-NC group and lv-Twist group,and human kidney cancer cell lines were selected as normal group.The normal and drug-resistant groups were treated with conventional culture;the lv-NC group was treated with 40 μL of lv-NC lentivirus supernatant containing 2.25 × 108 TU·mL-1 for 72 h,and the lv-Twist group was treated with 50 μL of Twist lentivirus supernatant containing 1.64 × 108 TU·mL-1 for 72 h.The apoptosis ability was detected by flow cytometry;the cell migration ability was detected by cell scratch assay;the cell invasion ability was detected by Transwell assay;and the protein expression levels of Wnt1,β-catenin and Twist were detected by Western blotting assay.Results The apoptosis rates of control,resistant,lv-NC and lv-Twist groups were(17.60±0.59)％,(8.61±0.34)％,(8.60±0.40)％and(3.10±0.34)％;the migration rates were(14.10±0.12)％,(27.64±0.41)％,(14.24±0.45)％and(32.74±2.53)％;the number of invading cells was 27.33±1.15,53.33±1.53,46.00±2.65 and 99.33±2.52;the relative expression levels of Wnt1 protein were 0.10±0.01,0.96±0.06,0.39±0.03 and 3.09±0.31;the relative expression levels of β-catenin protein were 0.39±0.01,1.48±0.16,0.81±0.05 and 1.24±0.14;the relative expression levels of Twist protein were 0.10±0.02,0.91±0.04,0.39±0.03 and 3.09±0.31,respectively.The differences of above indexes were statistically significant between the resistant group and the normal group,and between the lv-Twist group and the lv-NC group(all P＜0.05).Conclusion Twist(EMT related protein)mediates sunitinib resistance in renal cell carcinoma by interacting with Wnt/β-catenin signaling pathway.

Digital intraoral scanning is a hot topic in the field of oral digital technology.In recent years,digital intra-oral scanning has gradually become the mainstream technology in orthodontics,prosthodontics,and implant dentistry.The precision of digital intraoral scanning and the accuracy and stitching of data collection are the keys to the success of the impression.However,the operators are less familiar with the intraoral scanning characteristics,imaging process-ing,operator scanning method,oral tissue specificity of the scanned object,and restoration design.Thus far,no unified standard and consensus on digital intraoral scanning technology has been achieved at home or abroad.To deal with the problems encountered in oral scanning and improve the quality of digital scanning,we collected common expert opin-ions and sought to expound the causes of scanning errors and countermeasures by summarizing the existing evidence.We also describe the scanning strategies under different oral impression requirements.The expert consensus is that due to various factors affecting the accuracy of digital intraoral scanning and the reproducibility of scanned images,adopting the correct scanning trajectory can shorten clinical operation time and improve scanning accuracy.The scanning trajec-tories mainly include the E-shaped,segmented,and S-shaped methods.When performing fixed denture restoration,it is recommended to first scan the abutment and adjacent teeth.When performing fixed denture restoration,it is recommend-ed to scan the abutment and adjacent teeth first.Then the cavity in the abutment area is excavated.Lastly,the cavity gap was scanned after completing the abutment preparation.This method not only meets clinical needs but also achieves the most reliable accuracy.When performing full denture restoration in edentulous jaws,setting markers on the mucosal tissue at the bottom of the alveolar ridge,simultaneously capturing images of the vestibular area,using different types of scanning paths such as Z-shaped,S-shaped,buccal-palatal and palatal-buccal pathways,segmented scanning of dental arches,and other strategies can reduce scanning errors and improve image stitching and overlap.For implant restora-tion,when a single crown restoration is supported by implants and a small span upper structure restoration,it is recom-mended to first pre-scan the required dental arch.Then the cavity in the abutment area is excavated.Lastly,scanning the cavity gap after installing the implant scanning rod.When repairing a bone level implant crown,an improved indi-rect scanning method can be used.The scanning process includes three steps:First,the temporary restoration,adjacent teeth,and gingival tissue in the mouth are scanned;second,the entire dental arch is scanned after installing a standard scanning rod on the implant;and third,the temporary restoration outside the mouth is scanned to obtain the three-di-mensional shape of the gingival contour of the implant neck,thereby increasing the stability of soft tissue scanning around the implant and improving scanning restoration.For dental implant fixed bridge repair with missing teeth,the mobility of the mucosa increases the difficulty of scanning,making it difficult for scanners to distinguish scanning rods of the same shape and size,which can easily cause image stacking errors.Higher accuracy of digital implant impres-sions can be achieved by changing the geometric shape of the scanning rods to change the optical curvature radius.The consensus confirms that as the range of scanned dental arches and the number of data concatenations increases,the scanning accuracy decreases accordingly,especially when performing full mouth implant restoration impressions.The difficulty of image stitching processing can easily be increased by the presence of unstable and uneven mucosal mor-phology inside the mouth and the lack of relatively obvious and fixed reference objects,which results in insufficient ac-curacy.When designing restorations of this type,it is advisable to carefully choose digital intraoral scanning methods to obtain model data.It is not recommended to use digital impressions when there are more than five missing teeth.