Objective To establish a liquid chromatography-tandem mass spectrometry(LC-MS/MS)method for the determination of ginsenoside Rh2(GRh2)in plasma of mice,so as to provide preclinical data support for the pharmacokinetic study and application of GRh2.Methods C57BL16 mice were given 7.5 mg/kg GRh2 by gavage.After administration,0.03 mL of whole blood was collected at 5 min,10 min,15 min,30 min,1 h,2 h,4 h,and 8 h.Then,the whole blood was centrifuged and the serum was treated with 0.1％formic acid acetonitrile,dried by nitrogen(40℃),and redissolved with 50.0 pL 50％methanol solution containing 100 ng/mL diclofenac sodium.After vortex mixing for 5 min at room temperature,it was put into the automatic sampler for sampling analysis.The chromatographic column was Waters BEHC18(2.1 mm × 50.0 mm,1.7 pm),the mobile phase was aqueous solution containing 0.1％formic acid and acetonitrile solution containing 0.1％formic acid at a flow rate of 0.60 mL/min,the column temperature was 40℃,and the injection volume was 1.00 pL.The electric spray ion source,positive ion mode and multiple reaction monitoring mode were performed.A standard curve was established to calculate blood drug concentration.The blood drug concentration-time curve was established according to the blood drug concentration,and the main pharmacokinetic parameters were calculated.Results The linear range of the standard curve of drug containing plasma was 100-40 000 ng/mL,and the correlation coefficient(r)was 0.996 0.After internal standard normalization,the matrix effect factors of GRh2 were 1.09,1.06,and 1.00(between 0.8 and 1.2),indicating no significant matrix effect.The precision and accuracy results showed that the average measured concentration of GRh2 samples at each concentration level was 103,333,23 800 and 35 000 ng/mL,the inter batch standard deviation was 6.47-1 120 ng/mL,the inter batch relative standard deviation was 1.5％-8.3％,and the inter batch accuracy deviation was 93.3％-111.1％.The long-term stability,short-term stability,repeated freeze-thaw property,and extraction recovery rate of GRh2 were all good.The pharmacokinetic parameters Tmax and Cmax of GRh2 in mice were(1.42±1.01)h and(1 251±495)ng/mL,respectively,indicating that the absorption and utilization rate of GRh2 in vivo was high and GRh2 had good drug performance.Conclusion The established LC-MS/MS method is accurate and reliable,and can be used to determine the concentration of GRh2 in mouse plasma and study its pharmacokinetic.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Objective To study the regulatory effect of Qufeng Xiaodian Formula on serum differential metabolites of allergic purpura,and provide scientific basis for the diagnosis and treatment of allergic purpura in traditional Chinese medicine.Methods Sixty rats were randomly divided into a blank control group(referred to as the blank group),a model group,a compound glycyrrhizin group,a low-dose Qu Feng Xiao Dian Fang group,a medium dose Qu Feng Xiao Dian Fang group,and a high-dose Qu Feng Xiao Dian Fang group according to a random number table method,with 10 rats in each group.The model group was constructed by combining dried ginger,pepper,and long pepper with ovalbumin to create an allergic purpura rat model.After successful modeling,each treatment group was intervened with corresponding drugs for 4 weeks.After 4 weeks,serum was collected and non targeted metabolomics screening of serum differential metabolites was performed using ultra-high performance liquid chromatography quadrupole time-of-flight tandem mass spectrometer(UPLC-QTOF/MS).Subsequently,data extraction and multivariate statistical analysis will be conducted to identify potential metabolic pathways.Results Compared with the control group,there were 91 possible differential metabolites in the serum of the model group rats,corresponding to 20 metabolic pathways;Compared with the model group,there were a total of 43 possible differential metabolites in the serum of rats in the wind dispelling and disease eliminating group,corresponding to 15 metabolic pathways.Among them,there are a total of 12 metabolic pathways.Inflammatory metabolites such as arachidonic acid and ceramide can damage vascular endothelium.Ten biomarkers,including arachidonic acid and ceramide,were significantly abnormal in the serum of the model group rats compared to the normal group.The Qufeng Xiaodian formula can significantly reverse these metabolites and significantly enrich them in arachidonic acid metabolism and sphingolipid metabolism pathways.Conclusion Qufeng Xiaodian Formula has a certain regulatory effect on metabolites such as arachidonic acid and ceramide that affect vascular endothelial injury.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To study the regulatory effect of Qufeng Xiaodian Formula on serum differential metabolites of allergic purpura,and provide scientific basis for the diagnosis and treatment of allergic purpura in traditional Chinese medicine.Methods Sixty rats were randomly divided into a blank control group(referred to as the blank group),a model group,a compound glycyrrhizin group,a low-dose Qu Feng Xiao Dian Fang group,a medium dose Qu Feng Xiao Dian Fang group,and a high-dose Qu Feng Xiao Dian Fang group according to a random number table method,with 10 rats in each group.The model group was constructed by combining dried ginger,pepper,and long pepper with ovalbumin to create an allergic purpura rat model.After successful modeling,each treatment group was intervened with corresponding drugs for 4 weeks.After 4 weeks,serum was collected and non targeted metabolomics screening of serum differential metabolites was performed using ultra-high performance liquid chromatography quadrupole time-of-flight tandem mass spectrometer(UPLC-QTOF/MS).Subsequently,data extraction and multivariate statistical analysis will be conducted to identify potential metabolic pathways.Results Compared with the control group,there were 91 possible differential metabolites in the serum of the model group rats,corresponding to 20 metabolic pathways;Compared with the model group,there were a total of 43 possible differential metabolites in the serum of rats in the wind dispelling and disease eliminating group,corresponding to 15 metabolic pathways.Among them,there are a total of 12 metabolic pathways.Inflammatory metabolites such as arachidonic acid and ceramide can damage vascular endothelium.Ten biomarkers,including arachidonic acid and ceramide,were significantly abnormal in the serum of the model group rats compared to the normal group.The Qufeng Xiaodian formula can significantly reverse these metabolites and significantly enrich them in arachidonic acid metabolism and sphingolipid metabolism pathways.Conclusion Qufeng Xiaodian Formula has a certain regulatory effect on metabolites such as arachidonic acid and ceramide that affect vascular endothelial injury.

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.