Objective:To evaluate the diagnostic performance of resting echocardiography in detecting severe coronary artery stenosis.Methods:A total of 136 patients with suspected coronary artery disease（CAD）who presented to Sichuan Provincial People's Hospital between January 2021 and December 2024 were prospectively enrolled. All patients underwent both coronary computed tomography angiography（CCTA）and transthoracic echocardiography within one week. Based on CCTA results，the patients were divided into non-severe stenosis group（ n=78）and severe stenosis group（ n=58）. Echocardiographic parameters including left atrial maximum volume（LAVmax），left ventricular global longitudinal strain（GLS），left ventricular longitudinal strain of endo-myocardium，mid-myocardium，epi-myocardium（LSendo，LSmid，LSepi），early diastolic mitral inflow velocity（E），early diastolic mitral annular velocity of the lateral and septal walls（e'），and E/e' were measured. Predictive factors for severe coronary stenosis were identified using LASSO regression，and a nomogram model was developed via multivariate Logistic regression. Model performance was evaluated using ROC curves，calibration curves，and decision curve analysis. Results:Multivariate Logistic regression analysis revealed LSendo，LAVmax，and E/e' as independent predictors of severe coronary artery stenosis. The nomogram constructed based on these predictors achieved an area under the curve of 0.798（95% CI=0.723-0.873），with sensitivity and specificity of 0.756 and 0.759，respectively. Conclusions:The resting echocardiography-based nomogram model demonstrates good diagnostic efficacy for severe coronary artery stenosis. It may serve as a noninvasive tool to assist in risk stratification and clinical decision-making in patients with suspected CAD.

To address the problem of data silos in dental specialties caused by equipment heterogeneity, this study developed an Intelligent Internet of Things (IoT)-enabled dental chair platform (hereinafter referred to as the intelligent platform) based on the concept of medical-engineering integration. The platform adopts a three-tier chair-domain interconnection architecture: the bottom tier integrates multi-source sensors and standardized interfaces for automated data acquisition and linkage with hospital information systems; the middle tier provides clinic-level management and remote teaching collaboration; and the top tier employs a blockchain-based secure cloud database for resource allocation and data management. Clinical validation at The Affiliated Stomatological Hospital of Nanjing Medical University demonstrated that, compared with a control group from the same period in 2023, the trial group achieved a 38.0% increase in average daily patient visits (80.6±6.8 vs. 58.4±5.2, t=15.16, P<0.001), a 24.6% reduction in average treatment time [(36.1±6.3) min vs. (47.9±8.5) min, t=7.72, P<0.001], a 39.2% reduction in waiting time [23.3 (16.5, 30.1) min vs. 38.3 (28.3, 48.3) min, U=32.00, P<0.001], a 30.4% reduction in equipment idle rate [8.7% (5.1%, 12.3%) vs. 12.5% (7.4%, 17.6%), U=251.00, P=0.003], and an increase in patient satisfaction from 88.2% (1 519/1 723) to 94.3% (2 186/2 318) ( t=7.26, P<0.001). User research confirmed that the functions most favored by clinicians and patients were "dental chair parameter updating and clinical data integration" [74.7% (80/107)] and "chairside display of diagnostic images" [76.8% (119/155)], respectively. Looking forward, the intelligent platform has the potential to integrate artificial intelligence-assisted diagnosis and 5G-enabled multicenter collaboration to further expand its clinical applications and accelerate the digital transformation of dental healthcare.

To address the problem of data silos in dental specialties caused by equipment heterogeneity, this study developed an Intelligent Internet of Things (IoT)-enabled dental chair platform (hereinafter referred to as the intelligent platform) based on the concept of medical-engineering integration. The platform adopts a three-tier chair-domain interconnection architecture: the bottom tier integrates multi-source sensors and standardized interfaces for automated data acquisition and linkage with hospital information systems; the middle tier provides clinic-level management and remote teaching collaboration; and the top tier employs a blockchain-based secure cloud database for resource allocation and data management. Clinical validation at The Affiliated Stomatological Hospital of Nanjing Medical University demonstrated that, compared with a control group from the same period in 2023, the trial group achieved a 38.0% increase in average daily patient visits (80.6±6.8 vs. 58.4±5.2, t=15.16, P<0.001), a 24.6% reduction in average treatment time [(36.1±6.3) min vs. (47.9±8.5) min, t=7.72, P<0.001], a 39.2% reduction in waiting time [23.3 (16.5, 30.1) min vs. 38.3 (28.3, 48.3) min, U=32.00, P<0.001], a 30.4% reduction in equipment idle rate [8.7% (5.1%, 12.3%) vs. 12.5% (7.4%, 17.6%), U=251.00, P=0.003], and an increase in patient satisfaction from 88.2% (1 519/1 723) to 94.3% (2 186/2 318) ( t=7.26, P<0.001). User research confirmed that the functions most favored by clinicians and patients were "dental chair parameter updating and clinical data integration" [74.7% (80/107)] and "chairside display of diagnostic images" [76.8% (119/155)], respectively. Looking forward, the intelligent platform has the potential to integrate artificial intelligence-assisted diagnosis and 5G-enabled multicenter collaboration to further expand its clinical applications and accelerate the digital transformation of dental healthcare.

Objective:To evaluate the diagnostic performance of resting echocardiography in detecting severe coronary artery stenosis.Methods:A total of 136 patients with suspected coronary artery disease（CAD）who presented to Sichuan Provincial People's Hospital between January 2021 and December 2024 were prospectively enrolled. All patients underwent both coronary computed tomography angiography（CCTA）and transthoracic echocardiography within one week. Based on CCTA results，the patients were divided into non-severe stenosis group（ n=78）and severe stenosis group（ n=58）. Echocardiographic parameters including left atrial maximum volume（LAVmax），left ventricular global longitudinal strain（GLS），left ventricular longitudinal strain of endo-myocardium，mid-myocardium，epi-myocardium（LSendo，LSmid，LSepi），early diastolic mitral inflow velocity（E），early diastolic mitral annular velocity of the lateral and septal walls（e'），and E/e' were measured. Predictive factors for severe coronary stenosis were identified using LASSO regression，and a nomogram model was developed via multivariate Logistic regression. Model performance was evaluated using ROC curves，calibration curves，and decision curve analysis. Results:Multivariate Logistic regression analysis revealed LSendo，LAVmax，and E/e' as independent predictors of severe coronary artery stenosis. The nomogram constructed based on these predictors achieved an area under the curve of 0.798（95% CI=0.723-0.873），with sensitivity and specificity of 0.756 and 0.759，respectively. Conclusions:The resting echocardiography-based nomogram model demonstrates good diagnostic efficacy for severe coronary artery stenosis. It may serve as a noninvasive tool to assist in risk stratification and clinical decision-making in patients with suspected CAD.

Acute myelogenous leukemia (AML) is a heterogeneous disease characterized by malignant proliferation of hematopoietic stem cells, and its morbidity and mortality are increasing, which seriously threatens human health. In recent years, many studies have shown that PI3K-AKT-mTOR signaling pathway is involved in the management of various biological processes in cells, and its abnormal activation is closely related to the occurrence and development of tumors. Therefore, this article reviews the recent research progress of PI3K-AKT-mTOR signaling pathway in the pathogenesis, progression and treatment of AML.

Objective:To investigate the distribution and epidemic characteristics of respiratory pathogens in children before and after COVID-19 epidemic in Lanzhou.Methods:Two hundred and eighty-six children hospitalized with acute upper respiratory tract infection in Central Hospital of Gansu Province and Gansu Maternal and Child Health Hospital from October to November of 2020 and October to November of 2021 were selected respectively as the research objects, and a retrospective analysis was made.IgM antibodies of nine pathogens, including influenza virus A(IVA), influenza virus B(IVB), parainfluenza virus(PIV), adenovirus(ADV), mycoplasma pneumoniae(MP), chlamydia pneumoniae(CP), respiratory syncytial virus(RSV), echovirus(ECHO)and coxsackie virus B(CVB), were detected, and the basic information and epidemic characteristics were statistically analyzed.Results:The total positive rates of IgM antibodies of nine pathogens before and after the epidemic in COVID-19 were 31.8%(91/286)and 5.9%(17/286)respectively, after the epidemic, the detection rates dropped significantly, and there was significant difference among them( χ2= 62.505, P<0.05); After the epidemic, the detection rates of ADV, MP and CVB were all lower than those before the epidemic, and there were significant differences among these groups( χ2= 39.281, 12.167, 10.155, all P<0.05). The positive detection rates in the age group of 1 month ~1 year, ~3 years, ~6 years and>6 years before the outbreak were 37.4%(37/99), 38.3%(36/94), 16.7%(12/72)and 28.6%(6/21)respectively, and there were significant differences among these groups( χ2=34.055, P<0.05); Among them, the detection rates of MP in the age group 1 month ~1 year, ~3 years, ~6 years and>6 years were 16.2%(6/37), 25.0%(9/36), 16.7%(2/12)and 100%(6/6)respectively, and there were significant differences among these groups( χ2=10.289, P<0.05); CVB was not detected in>6 years group, the positive detection rates of CVB were 16.2%(6/37), 22.2%(8/36)and 25.0%(3/12)in the age group of 1 month ~1 year, ~3 years, ~6 years respectively, and there were significant differences among these groups( χ2= 27.742, P< 0.05). After the epidemic, the positive detection rates of the patients in the age group of 1 month ~1 year, ~3 years, ~6 years and>6 years were 5.9%(4/68), 4.0%(3/75), 5.7%(6/106)and 10.8%(4/37), with no statistical significance( χ2=2.235, P>0.05); Among them, the positive rates of IVB were 25.0%(1/4), 33.3%(1/3)and 66.7%(4/6)in the age group of 1 month ~1 year, ~3 years, ~6 years respectively, and in the age group>6 years was not detected, and there were significant differences among these groups( χ2= 96.022, P< 0.05). The detection rates of mixed infection of pathogens before and after the epidemic were 5.6%(16/286)and 0.3%(1/286)respectively, with no statistical significance( χ2= 2.314, P>0.05). Conclusion:The distribution of common pathogens of acute upper respiratory tract infection among children in Lanzhou was different before and after COVID-19 epidemic.

A new teaching mode with the combination of online teaching and flipped class was designed and implemented in the Stomatological College of Nanjing Medical University based on the National Online Open Courses, the Virtual Interactive Network Teaching Platform and the E-learning Network Teaching Platform. The new online course system of orthodontic education was constructed with several components including the process and outcome assessments, the professional literature and knowledge summary reports and the virtual interactive online training. With the informative and convenient online teaching resources and modes, students′ comprehensive abilities of independent learning were improved.

OBJECTIVETo study the association between single nucleotide polymorphisms of thioredoxin reductase-2 (TrxR2) gene and the susceptibility to Kashin-Beck disease (KBD).

METHODSPolymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to analyze the genotype frequencies of rs5748469 in TrxR2 gene in 84 KBD patients and 109 healthy control subjects.

RESULTSThe genotype frequencies of A/A, A/C, and C/C in the KBD patients were 83.33%, 15.48% and 1.19%, as compared with the frequencies of 74.31%, 25.69%, and 0.00% in the healthy control, respectively, showing no significant difference in the single nucleotide polymorphisms of TrxR2 gene between the two groups (P=0.13).

CONCLUSIONNo obvious correlation can be found between rs5748469 polymorphisms in TrxR2 gene and the susceptibility to KBD.

Adult ; Alleles ; Female ; Genetic Predisposition to Disease ; Genotype ; Humans ; Kashin-Beck Disease ; genetics ; Male ; Middle Aged ; Polymorphism, Restriction Fragment Length ; Polymorphism, Single Nucleotide ; Thioredoxin Reductase 2 ; genetics