Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

OBJECTIVE To provide a reference for the pharmaceutical care of a patient with type 2 diabetes mellitus （T2DM） and limb-girdle muscular dystrophy （LGMD） who developed euglycemic diabetic ketoacidosis （euDKA） after taking empagliflozin. METHODS Clinical pharmacists provided pharmaceutical care for a patient with T2DM and LGMD who developed euDKA after taking empagliflozin. According to the patient’s recent use of medications and his conditions， clinical pharmacists assessed the correlation between euDKA and empagliflozin as “very likely”. As to euDKA， clinical pharmacists suggested discontinuing empagliflozin and metformin， and giving intravenous infusion of 10% Glucose injection instead of 5% Glucose injection for fluid resuscitation. Clinical pharmacists monitored the patient’s laboratory indicators such as arterial blood gas analysis， blood/urine ketones and electrolytes. They assisted physicians to decide when to stop intravenous supplements of liquid and insulin. Clinical pharmacists also assisted physicians to adjust the antidiabetic drugs and educated the patient to avoid empagliflozin or other sodium- glucose linked transporter 2 inhibitors （SGLT2i）. RESULTS Physicians adopted the suggestions of clinical pharmacists. After treatment， the patient’s condition improved， and he was allowed to be discharged with medication. CONCLUSIONS euDKA is a relatively rare and serious adverse reaction associated with SGLT2i， and the patients with LGMD are susceptible to euDKA. Clinical pharmacists assist physicians in developing personalized medication plans by evaluating the association between euDKA and empagliflozin， adjusting medication regimens，conducting pharmaceutical monitoring，and other pharmaceutical services. Meanwhile， they provide medication education to patients to ensure their medication safety.

OBJECTIVE To provide a reference for the pharmaceutical care of a patient with type 2 diabetes mellitus （T2DM） and limb-girdle muscular dystrophy （LGMD） who developed euglycemic diabetic ketoacidosis （euDKA） after taking empagliflozin. METHODS Clinical pharmacists provided pharmaceutical care for a patient with T2DM and LGMD who developed euDKA after taking empagliflozin. According to the patient’s recent use of medications and his conditions， clinical pharmacists assessed the correlation between euDKA and empagliflozin as “very likely”. As to euDKA， clinical pharmacists suggested discontinuing empagliflozin and metformin， and giving intravenous infusion of 10% Glucose injection instead of 5% Glucose injection for fluid resuscitation. Clinical pharmacists monitored the patient’s laboratory indicators such as arterial blood gas analysis， blood/urine ketones and electrolytes. They assisted physicians to decide when to stop intravenous supplements of liquid and insulin. Clinical pharmacists also assisted physicians to adjust the antidiabetic drugs and educated the patient to avoid empagliflozin or other sodium- glucose linked transporter 2 inhibitors （SGLT2i）. RESULTS Physicians adopted the suggestions of clinical pharmacists. After treatment， the patient’s condition improved， and he was allowed to be discharged with medication. CONCLUSIONS euDKA is a relatively rare and serious adverse reaction associated with SGLT2i， and the patients with LGMD are susceptible to euDKA. Clinical pharmacists assist physicians in developing personalized medication plans by evaluating the association between euDKA and empagliflozin， adjusting medication regimens，conducting pharmaceutical monitoring，and other pharmaceutical services. Meanwhile， they provide medication education to patients to ensure their medication safety.

BACKGROUND:Radiotherapy for head and neck tumors is very likely to cause radiation-induced oral mucositis,which seriously affects the health of patients and the treatment plan of tumors.Mesenchymal stem cells have shown therapeutic potential in many diseases,and exosomes are one of the important factors for their function.At present,there is no application of adipose mesenchymal stem cell-derived exosomes in the study of radiation-induced oral mucositis. OBJECTIVE:To investigate the role of adipose mesenchymal stem cell-derived exosomes in radiation-induced oral mucositis. METHODS:Adipose mesenchymal stem cells and adipose mesenchymal stem cell-derived exosomes were extracted and identified.In vitro model of radiation-induced oral mucositis was induced by radiating oral mucosal epithelial cells with 3 Gy X-ray.Adipose mesenchymal stem cells or adipose mesenchymal stem cell-derived exosomes were pretreated for 48 hours before modeling.The proliferation capacity of oral mucosal epithelial cells was detected by EdU assay and clonal formation assay.A mouse model of radiation-induced oral mucositis was constructed through 3 Gy X-ray radiation.Adipose mesenchymal stem cells and adipose mesenchymal stem cell-derived exosomes were injected into the tail vein of radiation-induced oral mucositis mice.Hematoxylin-eosin staining and immunohistochemistry were used to evaluate the inflammatory changes of oral mucosal epithelial tissue. RESULTS AND CONCLUSION:(1)Compared with the control group,both adipose mesenchymal stem cells and adipose mesenchymal stem cell-derived exosomes promoted the formation of oral epithelial cell clones and increased the positive rate of EdU in oral epithelial cells.(2)Both adipose mesenchymal stem cells and adipose mesenchymal stem cell-derived exosomes alleviated the inflammation of oral mucosal epithelium of irradiated mice;CD45 positive cells decreased and PCNA positive cells increased in oral mucosal epithelium.It is concluded that adipose mesenchymal stem cell-derived exosomes promote the proliferation of oral mucosal epithelial cells and release oral mucosal inflammation in mice with radiation-induced oral mucositis.

BACKGROUND:In recent years,deep learning technologies have been increasingly applied in the field of oral medicine,enhancing the efficiency and accuracy of oral imaging analysis and promoting the rapid development of intelligent oral medicine. OBJECTIVE:To elaborate the current research status,advantages,and limitations of deep learning based on oral imaging in the diagnosis and treatment decision-making of oral diseases,as well as future prospects,exploring new directions for the transformation of oral medicine under the backdrop of deep learning technology. METHODS:PubMed was searched for literature related to deep learning in oral medical imaging published from January 2017 to January 2024 with the search terms"deep learning,artificial intelligence,stomatology,oral medical imaging."According to the inclusion criteria,80 papers were finally included for review. RESULTS AND CONCLUSION:(1)Classic deep learning models include artificial neural networks,convolutional neural networks,recurrent neural networks,and generative adversarial networks.Scholars have used these models in competitive or cooperative forms to achieve more efficient interpretation of oral medical images.(2)In the field of oral medicine,the diagnosis of diseases and the formulation of treatment plans largely depend on the interpretation of medical imaging data.Deep learning technology,with its strong image processing capabilities,aids in the diagnosis of diseases such as dental caries,periapical periodontitis,vertical root fractures,periodontal disease,and jaw cysts,as well as preoperative assessments for procedures such as third molar extraction and cervical lymph node dissection,helping clinicians improve the accuracy and efficiency of decision-making.(3)Although deep learning is promising as an important auxiliary tool for the diagnosis and treatment of oral diseases,it still has certain limitations in model technology,safety ethics,and legal regulation.Future research should focus on demonstrating the scalability,robustness,and clinical practicality of deep learning,and finding the best way to integrate automated deep learning decision support systems into routine clinical workflows.

Objective To investigate the role and related mechanisms of exosomes derived from mesenchymal stem cells (MSCs) in radiation-induced lung injury (RILI). Methods Human umbilical cord-derived MSCs were isolated and cultured for the extraction and identification of exosomes. Eighteen male SD rats were randomly divided into Control group, RILI group and RILI + exosomes group (EXO group), with 6 rats in each group. Except for Control group, the other groups received a single X-ray dose of 30 Gy to the right lung. Immediately after irradiation, the EXO group was administered 2 × 10⁹ exosomes/kg via tail vein injection. Control group and RILI group were given the same volume of normal saline. Eight weeks post-irradiation, the rats were sacrificed, lung tissue and peripheral venous blood were collected. HE and Masson staining were employed to observe the pathological and fibrotic changes of lung tissue. The levels of serum inflammatory factors IL-6, IFN-γ, TNF-α, and IL-10 were detected by ELISA. RT-qPCR was used to assess the mRNA levels of IL-1β, IL-6, Cdh1, and Col1a1 in lung tissue. The expression levels of Vimentin and TGF-β1 in lung tissue were measured by immunohistochemical staining. The expression levels of AMPK, p-AMPK, and TGF-β1 in lung tissue were detected by Western blot. Results MSC-derived exosomes were successfully extracted and identified. Compared with RILI group, EXO group showed significantly reduced pathological changes of lung inflammation and collagen deposition. The levels of serum inflammatory factors IL-6, INF-γ, and TNF-α were significantly decreased (P < 0.05), and the level of anti-inflammatory factor IL-10 was significantly increased (P < 0.05). The mRNA levels of IL-1β, IL-6, and Col1a1 in lung tissue were significantly decreased (P < 0.05 or P < 0.01), and the mRNA level of Cdh1 was significantly increased (P < 0.05 or P < 0.01). The levels of Vimentin and TGF-β1 in lung tissue were significantly reduced, while p-AMPK level was significantly up-regulated (P < 0.05). Conclusion Exosomes derived from MSCs may alleviate RILI by inhibiting inflammatory responses and regulating epithelial-mesenchymal transition mediated by AMPK/TGF-β1 signaling pathway.

Objective To investigate the value of multi-slice spiral computed tomography (MSCT) features, along with the expression levels of epidermal growth factor receptor (EGFR) and insulin-like growth factor 1 receptor (IGF1R), in differential diagnosis of benign and malignant adrenal cortical tumors. Methods A total of 98 patients with adrenal cortical tumors admitted to Zibo Municipal Central Hospital from January 2020 to July 2024 were included in this study. All subjects underwent MSCT scans of the adrenal gland. The CT values of tumor parenchyma on plain scans and at arterial and venous phases were estimated. The surgical tumor specimens were collected for immunohistochemical staining and measurement of EGFR and IGF1R expression. The MSCT features and EGFR and IGF1R expression levels were compared among patients with different pathological types of adrenal cortical tumors. Results Of the 98 patients with adrenal cortical tumors, there were 18 cases with cortical carcinoma, 10 cases with metastatic tumors, 31 cases with pheochromocytoma, 25 cases with aldosterone-producing adenomas, and 14 cases with cortisol adenomas. The CT values of adrenal aldosterone-producing adenomas were significantly lower than other pathological types of adrenal cortical tumors on plain scans and at arterial and venous phases (P < 0.05). The CT values of metastatic tumors and cortical carcinoma were significantly lower than those of pheochromocytoma and cortisol adenomas at arterial and venous phases (P < 0.05). Specifically, at arterial and venous phases, the CT values of metastatic tumors were lower than those of cortical carcinoma, and the CT values of cortisol adenomas were lower than those of pheochromocytoma (P < 0.05). The positive expression levels of EGFR and IGF1R were higher in tumor specimens from patients with metastatic tumors and cortical carcinomas than from pheochromocytoma, aldosterone-producing adenomas, and cortisol adenomas (P < 0.05). There were no significant differences between patients with metastatic tumors and cortical carcinomas in terms of positive EGFR and IGF1R expression (P > 0.05). In addition, there were no significant differences in the proportions of positive EGFR and IGF1R expression among patients with malignant adrenal cortical tumors in terms of ages, genders, tumor sizes, and TNM stages (P > 0.05). Conclusion The CT values of MSCT scans at arterial and venous phases as well as EGFR and IGF1R expression levels correlate with the pathological types of adrenal cortical tumors.

Objective To explore the risk factors for postoperative respiratory failure (RF) in patients with esophageal cancer, construct a predictive model based on the least absolute shrinkage and selection operator (LASSO)-logistic regression, and visualize the constructed model. Methods A retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023. Patients were divided into a RF group and a non-RF (NRF) group according to whether RF occurred after surgery. Clinical data of the two groups were collected, and LASSO-logistic regression was used to optimize feature selection and construct the predictive model. The model was internally validated by repeated sampling 1000 times based on the Bootstrap method. Results A total of 217 patients were included, among which 24 were in the RF group, including 22 males and 2 females, with an average age of (63.33±9.10) years; 193 were in the NRF group, including 161 males and 32 females, with an average age of (62.14±8.44) years. LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) to predicted value (FEV1/FVC%pred) [OR=0.944, 95%CI (0.897, 0.993), P=0.026], postoperative anastomotic fistula [OR=4.106, 95%CI (1.457, 11.575), P=0.008], and postoperative lung infection [OR=3.776, 95%CI (1.373, 10.388), P=0.010] were risk factors for postoperative RF in patients with esophageal cancer. Based on the above risk factors, a predictive model was constructed, with an area under the receiver operating characteristic curve of 0.819 [95%CI (0.737, 0.901)]. The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit (P=0.527). The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5% and 50%. Conclusion FEV1/FVC%pred, postoperative anastomotic fistula, and postoperative lung infection are risk factors for postoperative RF in patients with esophageal cancer. The predictive model constructed based on LASSO-logistic regression analysis is expected to help medical staff screen high-risk patients for early individualized intervention.

Objective: To analyze the change trends in the body shape indicators and proportions of students in Harbin from 2010 to 2024, and to investigate ergonomic compatibility of functional dimensions of school desks and chairs with current student shape indicators, so as to provide a reference for revising furniture standards of desks and chairs. Methods: Between September and November of both 2010 and 2024, a combination of convenience sampling and stratified cluster random sampling was conducted across three districts in Harbin, yielding samples of 6 590 and 6 252 students, respectively. Anthropometric shape indicators cluding height, sitting height, crus length, and thigh length-and their proportional changes were compared over the 15-year period. The 2024 data were compared with current standard functional dimensions of school furniture. The statistical analysis incorporated t-test and Mann-Whitney U- test. Results: From 2010 to 2024, average height increased by 1.8 cm for boys and 1.5 cm for girls; sitting height increased by 1.5 cm for both genders; crus length increased by 0.3 cm for boys and 0.4 cm for girls; and thigh length increased by 0.5 cm for both genders. The ratios of sitting height to height, and sitting height to leg length increased by less than 0.1 . The difference between desk chair height and 1/3 sitting height ranged from 0.4-0.8 cm. Among students matched with size 0 desks and chairs, 22.0% had a desk to chair height difference less than 0, indicating that the desk to chair height difference might be insufficient for taller students. The differences between seat height and fibular height ranged from -1.4 to 1.1 cm; and the differences between seat depth and buttock popliteal length ranged from -9.8 to 3.4 cm. Among obese students, the differences between seat width and 1/2 hip circumference ranged from -20.5 to -8.7 cm, while it ranged from -12.2 to -3.8 cm among non obese students. Conclusion Current furniture standards basically satisfy hygienic requirements; however, in the case of exceptionally tall and obese students, ergonomic accommodations such as adaptive seating allocation or personalized adjustments are recommended to meet hygienic requirements.

Objective: To evaluate the accuracy of body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR) in screening true obesity among children, so as to provide a scientific basis for precise screening and early prevention and control of childhood obesity. Methods: A total of 1 322 children aged 10-15 years old were surveyed by the Huantai Children Cardiovascular Health Cohort in 2021. Fat mass percentage (FMP) and fat mass index (FMI) were measured by bioelectrical impedance analysis, with FMP or FMI values at or above the age and sex-specific 70th percentiles as the criteria for defining true obesity. BMI, WC and WHtR were used to define general obesity and central obesity. The accuracy of these measures in screening for true obesity was evaluated by calculating the missed diagnosis rate, misdiagnosis rate, area under the curve(AUC) for receiver operating characteristic and Kappa coefficient. Results: Boys had higher BMI [(21.79±4.56) kg/m 2], WC [(76.41±12.53) cm] and WHtR (0.47±0.07) than girls [(20.83±4.13) kg/m 2, (70.69±10.06) cm, (0.45±0.06)] ( t =4.02, 9.19, 6.63), while boys had lower FMP [(18.29±8.35)%] and FMI [(4.35±2.79) kg/m 2] than girls [(24.87±6.51)%, (5.44±2.53) kg/m 2] ( t =-16.10,-7.42) ( P <0.01). Using FMP as a reference standard, the diagnosis error rates of screening for true obesity based on BMI, WC and WHtR were 12.24%, 2.11% and 2.11%, respectively; the diagnosis error rates were 10.88%, 27.28% and 24.33%; the AUC values were 0.88, 0.85 and 0.87; the Kappa coefficients were 0.67, 0.48 and 0.52. Using FMI as a reference standard, rates of BMI, WC and WHtR screening for true obesity were 14.20%, 1.23% and 2.78%; the diagnosis error rates were 4.81%, 20.84% and 18.14 %; the AUC values were 0.90, 0.89 and 0.90; the Kappa coefficients were 0.81, 0.64 and 0.67. Conclusions BMI has a higher diagnosis error rate in screening for true obesity in children, while WC and WHtR have higher diagnosis error rates. It is recommended to promote body fat assessment in clinical practice, so as to achieve more accurate prevention and control of chronic diseases.