Objective:To construct a symptom network for type 2 diabetes mellitus (T2DM) patients, identify bridging symptoms and core symptoms, and explore influencing factors, providing references for precise and efficient symptom management.Methods:A convenience sampling method was used to select 340 T2DM patients hospitalized in the Endocrinology Department of Affiliated Hospital of North Sichuan Medical College from December 2023 to February 2024. A general information survey and the Chinese version of Diabetes Symptom Checklist-Revised were used to collect data. Multiple linear regression analysis was performed to explore the influencing factors of T2DM patients' lack of vitality. Network analysis was used to identify core symptoms and bridging symptoms among symptom clusters. A total of 340 questionnaires were distributed, and 336 valid questionnaires were returned, resulting in a valid response rate of 98.8% (336/340) .Results:The most common symptoms in T2DM patients included thirst and dry mouth, foamy urine, and overall fatigue. The most troublesome symptoms were overall fatigue, lack of vitality, and thirst and dry mouth. In the symptom network, lack of vitality had the highest intensity ( rs=7.980) and closeness centrality ( rc=0.014), followed by overall fatigue ( rs=7.940) and feeling down ( rs=7.200). Overall fatigue ( rbs=7.190, rbc=0.380) was identified as the strongest bridging symptom in the network. Univariate analysis showed that age, education level, diabetes duration, diabetes complications, and regular blood glucose monitoring were significant factors affecting lack of vitality in T2DM patients ( P<0.05). Multiple linear regression analysis indicated that education level, regular blood glucose monitoring, and diabetes complications were significant factors affecting lack of vitality ( P<0.05) . Conclusions:Lack of vitality is the core symptom in T2DM patients, and overall fatigue is the bridging symptom connecting different symptom clusters. The lack of vitality is influenced by factors such as education level, regular blood glucose monitoring, and diabetes complications. Healthcare providers should use symptom network analysis to timely identify core symptoms, bridging symptoms, and their influencing factors, and develop precise and efficient interventions to improve symptom management and reduce the symptom burden in T2DM patients.

Disruption of the intestinal mucosal barrier caused by gut dysbiosis and metabolic imbalance is the underlying pathology of inflammatory bowel disease (IBD). Traditional Chinese medicine Wuji Wan (WJW) is commonly used to treat digestive system disorders and showed therapeutic potential for IBD. In this interdisciplinary study, we aim to investigate the pharmacological effects of WJW against experimental colitis by combining functional metabolomics and gut-microbiota sequencing techniques. Treatment with WJW altered the profile of the intestinal microbiota and notably increased the abundance of Lactobacillus, thereby facilitating the conversion of tryptophan into indole-3-acetic acid (IAA) and indoleacrylic acid (IA). These indole derivatives activated the aryl hydrocarbon receptor (AhR) pathway, which reduced colonic inflammation and restored the expression of intestinal barrier proteins. Interestingly, the beneficial effects of WJW on gut barrier function improvement and tryptophan metabolism were disappeared in the absence of gut microbiota. Finally, pre-treatment with the AhR antagonist CH-223191 confirmed the essential role of IAA-mediated AhR activation in the therapeutic effects of WJW. Overall, WJW enhanced intestinal barrier function and reduced colonic inflammation in a murine colitis model by modulating Lactobacillus-IAA-AhR signaling pathway. This study provides novel insights into colitis pathogenesis and presents an effective therapeutic and preventive approach against IBD.

ObjectiveTo evaluate the overall dietary intake of adult residents in Sijing Town, Songjiang District, Shanghai, and to explore the association between dietary health literacy and diet quality. MethodsA total of 1 280 adult residents were selected as the research subjects using a multi-stage sampling method, and face-to-face questionnaire surveys were administered on site. Dietary intake data were collected using a Food Frequency Questionnaire (FFQ), and the overall diet quality of the participants was evaluated based on the Chinese Healthy Eating Index (CHEI). Participants were divided into low- and high-CHEI groups according to the median CHEI score. Logistic regression models were used to examine the association between dietary health literacy and diet quality. ResultsThe median CHEI score for adults in the area was 63.68 points. Multivariate logistic regression analysis revealed that adults with lower dietary health literacy had lower CHEI scores and poorer overall diet quality compared to those with higher dietary health literacy (OR=1.435, 95%CI:1.132‒1.819). ConclusionThe overall diet quality of adult residents in this region requires improvement. There is a significant positive correlation between the level of dietary health literacy and CHEI scores, suggesting that enhancing dietary health literacy may be an important strategy to improve resident’ dietary quality.

Objective: To investigate the effects of fine particulate matter (PM2.5) exposure on acute myocardial infarction (AMI) mortality and years of life lost (YLL). Methods: Mortality data in Haizhu District, Guangzhou City from 2020 to 2024 were collected by the China Population Death Information Registration Management System and Guangdong Death Certificate Management System. Air pollution and meteorological data of the same period were obtained from the national environmental monitoring sites on the National Real-time Air Quality Release Platform and the Guangzhou Observatory, respectively. The single-pollutant model and multi-pollutant model were established by distributed lag non-linear model to analyze the effects of PM2.5 on AMI mortality and YLL. Results: From 2020 to 2024, there were 2 466 AMI death cases in Haizhu District, including 949 males and 1 517 females. Among them, 530 cases were aged <65 years, 494 cases were aged 65-74 years, and 1 442 cases were aged >74 years. The median daily average number of deaths was 1.3 (interquartile range, 2.0) cases, and the median daily average YLL was 16.4 (interquartile range, 24.8) person years. The median daily average mass concentration of PM2.5 was 24.3 (interquartile range, 18.0) μg/m3. In single-pollutant models, the maximum effects of PM2.5 on AMI mortality and YLL were observed at a cumulative lag of 7 days. For per 10 μg/m3 increment in the daily average concentration of PM2.5, the excess risk of AMI mortality increased by 8.793% (95%CI: 4.201% to 13.588%), and YLL increased by 2.059 (95%CI: 1.081 to 3.037) person-years. Gender-stratified analyses showed that PM2.5 significantly affected AMI mortality in males and YLL in males and females (all P<0.05). Age-stratified analyses revealed that PM2.5 significantly affected AMI mortality and YLL among residents aged <65 years and 65-74 years (all P<0.05). However, the difference between genders or the two age groups was not statistically significant (both P>0.05). In multi-pollutant models, when NO2, SO2, or O3 were introduced respectively at a cumulative lag of 7 days, the effects of PM2.5 on AMI mortality and YLL were enhanced compared to the single-pollutant model (all P<0.05). When PM10 was introduced alone or in combination with PM10, SO2, NO2, and O3, the effects of PM2.5 on AMI mortality and YLL were not statistically significant (all P>0.05). Conclusion Exposure to PM2.5 may increase the risk of AMI mortality and YLL, with varying effects across populations of different genders and ages.

Objective:To identify the risk factors for ascending aortic dilatation and develop a prediction model using LASSO-Logistic regression in patients with normally functioning bicuspid aortic valves（BAV）.Methods:Eight-four adult patients with BAV diagnosed as having normal valve function by transthoracic echocardiography who attended to the General Hospital of Ningxia Medical University between June 2024 and April 2025 were prospectively selected，there were 42 patients with ascending aortic dilatation and 42 patients without dilatation.The patients were divided into a training set（60 cases）and a test set（24 cases）using stratified random sampling at a ratio of 7 to 3 via the R caret package. All subjects underwent transthoracic echocardiography，lipid and plasma matrix metalloproteinases（MMP）and tissue inhibitors（TIMP）levels detection. The inverse probability of treatment weighting（IPTW）method was employed to control for potential confounding factors. LASSO and multifactorial binary Logistic regression was applied to screen the independent risk factors for ascending aortic dilatation of BAV and development a nomogram prediction model. The accuracy，consistency and clinical applicability of the prediction model were evaluated by applying the ROC curve，calibration curve，and decision curve analysis（DCA），respectively.Results:①After adjustment for IPTW，LASSO-Logistic regression analysis identified left ventricular global longitudinal strain（LVGLS）and plasma MMP-2 levels as independent risk factors for ascending aortic dilatation in BAV patients with normal valve function.②The nomogram prediction model constructed based on the above screening features，and the area under the curve（AUC）of ROC for the training set and test set were 0.917 and 0.903，with specificities of 0.867 and 0.917，and sensitivities of 0.933 and 0.916，respectively. ③Calibration curves demonstrated satisfactory alignment，with C-indices of 0.908（95% CI=0.879～0.937）for the training set and 0.903（95% CI=0.874 - 0.932）for the test set. Hosmer-Lemeshow goodness-of-fit tests indicated strong consistency between predicted and observed outcomes，with P-values of 0.138 and 0.750 for the training and test sets，respectively.The DCA curve demonstrated that within a threshold probability range of 0.04 - 0.90 in the test set，the clinical decision-making model provided a higher net benefit rate for patients with BAV. Conclusions:LVGLS absolute value reduction and elevated plasma MMP-2 levels are independent risk factors for predicting ascending aortic dilatation in BAV patients with normal valve function. The prediction model based on LASSO-Logistic regression has good predictive value，providing a scientific basis for clinical decision-making in patients with BAV and aortic diseases.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Sjögren's syndrome (SS) is an autoimmune disease characterized primarily by oral and periocular dryness. Astragalus-Salvia (AS) and Ophiopogon-Dendrobium (OD) represent two frequently utilized herb pairs in SS treatment. While the combination of AS-OD herb pairs demonstrates clinical efficacy in alleviating SS symptoms, its underlying mechanism remains unclear. This investigation sought to assess the therapeutic effects and elucidate the potential mechanisms of AS-OD in non-obese diabetic (NOD)/Ltj mice with SS. The study utilized NOD/Ltj mice as SS models, administering AS-OD treatment for 10 weeks at doses of 113.1, 226.2, and 339.3 mg·d^-1·20 g^-1. Results demonstrated that AS-OD improved SS symptoms, evidenced by enhanced salivary flow rate, decreased anti-SSA/Ro and anti-SSB/La antibody levels, increased swimming duration, and reduced lactate (LA) and blood urea nitrogen (BUN) levels in NOD/Ltj mice. AS-OD reduced lymphocyte infiltration, enhanced Aquaporin-5 (AQP5) expression in the submandibular gland, decreased inflammatory cytokine levels in the submandibular gland, and reduced the T helper type 17/regulatory T lymphocyte (Th17/Treg) cell ratio in the spleen. Transcriptomic and proteomic analyses indicated AS-OD's involvement in regulating phosphatidylinositol-3-kinase/protein kinase B (PI3K/AKT) and Janus kinase 3/signal transducer and activator of transcription 3 (JAK1/STAT3) pathways, with inhibitory effects validated in both NOD/Ltj mice submandibular gland and A-253 cells. Furthermore, AS-OD enhanced cell viability and reduced A-253 cell apoptosis through the PI3K/AKT pathway. In A-253 cells, AS-OD reduced inflammatory cytokine levels, CXC chemokine ligand 9/10 (CXCL9/10), and T-cell chemotaxis by inhibiting the JAK1/STAT3 pathway. AS-OD mitigates SS by suppressing inflammation and immune responses through the PI3K/AKT and JAK1/STAT3 pathways.
Animals ; STAT3 Transcription Factor/genetics* ; Sjogren's Syndrome/immunology* ; Mice, Inbred NOD ; Proto-Oncogene Proteins c-akt/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Signal Transduction/drug effects* ; Janus Kinase 1/genetics* ; Humans ; Female ; Astragalus Plant/chemistry* ; Male

Objective:To construct a symptom network for type 2 diabetes mellitus (T2DM) patients, identify bridging symptoms and core symptoms, and explore influencing factors, providing references for precise and efficient symptom management.Methods:A convenience sampling method was used to select 340 T2DM patients hospitalized in the Endocrinology Department of Affiliated Hospital of North Sichuan Medical College from December 2023 to February 2024. A general information survey and the Chinese version of Diabetes Symptom Checklist-Revised were used to collect data. Multiple linear regression analysis was performed to explore the influencing factors of T2DM patients' lack of vitality. Network analysis was used to identify core symptoms and bridging symptoms among symptom clusters. A total of 340 questionnaires were distributed, and 336 valid questionnaires were returned, resulting in a valid response rate of 98.8% (336/340) .Results:The most common symptoms in T2DM patients included thirst and dry mouth, foamy urine, and overall fatigue. The most troublesome symptoms were overall fatigue, lack of vitality, and thirst and dry mouth. In the symptom network, lack of vitality had the highest intensity ( rs=7.980) and closeness centrality ( rc=0.014), followed by overall fatigue ( rs=7.940) and feeling down ( rs=7.200). Overall fatigue ( rbs=7.190, rbc=0.380) was identified as the strongest bridging symptom in the network. Univariate analysis showed that age, education level, diabetes duration, diabetes complications, and regular blood glucose monitoring were significant factors affecting lack of vitality in T2DM patients ( P<0.05). Multiple linear regression analysis indicated that education level, regular blood glucose monitoring, and diabetes complications were significant factors affecting lack of vitality ( P<0.05) . Conclusions:Lack of vitality is the core symptom in T2DM patients, and overall fatigue is the bridging symptom connecting different symptom clusters. The lack of vitality is influenced by factors such as education level, regular blood glucose monitoring, and diabetes complications. Healthcare providers should use symptom network analysis to timely identify core symptoms, bridging symptoms, and their influencing factors, and develop precise and efficient interventions to improve symptom management and reduce the symptom burden in T2DM patients.

Objective:To identify the risk factors for ascending aortic dilatation and develop a prediction model using LASSO-Logistic regression in patients with normally functioning bicuspid aortic valves（BAV）.Methods:Eight-four adult patients with BAV diagnosed as having normal valve function by transthoracic echocardiography who attended to the General Hospital of Ningxia Medical University between June 2024 and April 2025 were prospectively selected，there were 42 patients with ascending aortic dilatation and 42 patients without dilatation.The patients were divided into a training set（60 cases）and a test set（24 cases）using stratified random sampling at a ratio of 7 to 3 via the R caret package. All subjects underwent transthoracic echocardiography，lipid and plasma matrix metalloproteinases（MMP）and tissue inhibitors（TIMP）levels detection. The inverse probability of treatment weighting（IPTW）method was employed to control for potential confounding factors. LASSO and multifactorial binary Logistic regression was applied to screen the independent risk factors for ascending aortic dilatation of BAV and development a nomogram prediction model. The accuracy，consistency and clinical applicability of the prediction model were evaluated by applying the ROC curve，calibration curve，and decision curve analysis（DCA），respectively.Results:①After adjustment for IPTW，LASSO-Logistic regression analysis identified left ventricular global longitudinal strain（LVGLS）and plasma MMP-2 levels as independent risk factors for ascending aortic dilatation in BAV patients with normal valve function.②The nomogram prediction model constructed based on the above screening features，and the area under the curve（AUC）of ROC for the training set and test set were 0.917 and 0.903，with specificities of 0.867 and 0.917，and sensitivities of 0.933 and 0.916，respectively. ③Calibration curves demonstrated satisfactory alignment，with C-indices of 0.908（95% CI=0.879～0.937）for the training set and 0.903（95% CI=0.874 - 0.932）for the test set. Hosmer-Lemeshow goodness-of-fit tests indicated strong consistency between predicted and observed outcomes，with P-values of 0.138 and 0.750 for the training and test sets，respectively.The DCA curve demonstrated that within a threshold probability range of 0.04 - 0.90 in the test set，the clinical decision-making model provided a higher net benefit rate for patients with BAV. Conclusions:LVGLS absolute value reduction and elevated plasma MMP-2 levels are independent risk factors for predicting ascending aortic dilatation in BAV patients with normal valve function. The prediction model based on LASSO-Logistic regression has good predictive value，providing a scientific basis for clinical decision-making in patients with BAV and aortic diseases.

Extended reality (XR) includes a variety of visualisation technologies such as virtual reality, augmented reality, and mixed reality. It refers to a combination of the real and the virtual entities through computers to create a virtual environment where human and computer can interact, characterized by immersion, interactivity, conceptualization, and combination of reality and fiction. Recently, great progress has been made in the application of XR in the fields of medical education, precision medicine, telemedicine, surgical assistance and navigation so that XR has drawn increasing attention. This paper briefly describes the concept of XR and its technological development, expounds its clinical application in orthopedics, surgery in particular, analyzes the existing problems and difficulties, and predicts its future development trend. This review may help readers gain a more comprehensive and in-depth understanding of the history, current status and future development of intelligent orthopaedics based on XR technology.