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.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

Objective: To explore the effects of 8week highintensity interval training on body shape and adipokines of obese male college students, so as to provide practical reference for weight loss of obese college students. Methods: A total of 30 male college students [age (20.10±0.55)years] with body mass index (BMI) ≥28 kg/m2 were recruited in March 2022 at China University of Petroleum (East China). The 8week highintensity interval training (HIIT) intervention was conducted from 11 April to 10 June 2022, 3 times a week (Monday, Wednesday, Friday), each time for 16:30-17:30. Body composition and adipokine levels were assessed before and after the intervention. All indicators were compared by pairedsamples ttests and single factor repeated measurement analysis of variance before and after intervention, and Pearson correlation analyses were used to test for associations between variables. Results: After 8 weeks of intervention, BMI, waist circumference and body fat of obese male college students decreased from (31.36±4.41)kg/m2, (107.52±9.66)cm and (28.04±5.79)kg to (30.40±4.37)kg/m2, (100.67±8.29)cm and (22.56±5.22)kg, respectively (t=3.84, 8.02, 9.29). Fatfree body mass index increased from (70.19±5.54)kg/m2 to (75.34±5.25)kg/m2 (t=-8.65) (P<0.01). There were statistically significant differences in the levels of Leptin, Adiponectin, and Irisin before intervention, at week 4 and at week 8 (F=26.05, 35.62, 4.95, P<0.05). There was no statistically significant difference in the content of reticulin (F=3.62, P>0.05). Conclusions The 8week of HIIT can effectively improve body shape of obese male college students and affect the effects of adipokines in the body. HIIT can be added to sports exercise to improve the health status of obese college students.

Objective: To investigate the epidemiological characteristics of varicella outbreaks in primary and middle schools, and to establish a risk predictive model, so as to provide scientific guidance for the prevention of varicella outbreaks in schools. Methods: Based on a nested case-control study, primary and middle schools in 4 districts of Shanghai (Yangpu District and Jingan District) and Hangzhou (Xiaoshan District and Linping District) from January to December 2023 were selected to observe the status of varicella outbreaks. Associated factors of varicella outbreaks were investigated and used for establishing the predictive model, which was evaluated by the Hosmer-Lemeshow(H-L) goodness of fit test, receiver operating characteristic (ROC) curve, Calibration curve, decision curve analysis (DCA). Results: A total of 98 varicella outbreaks were included, with 195 schools without varicella outbreaks during the same period as controls. Eight factors, including the availability of warm water in restroom, availability of hand soap in restroom, average class size, duration of student attendance at school per day, presence of a fulltime school doctor, hesitancy of the school principal towards varicella vaccination, and rates of first and second doses of varicella vaccination, were identified as potential factors for school varicella outbreaks, with statistically significant differences (χ2/Z=10.01, 20.49, 17.43, 9.74, 32.17, 6.60, 2.20, 3.39, P<0.05). The 8 variables above were employed to construct a risk predictive model, and Hosmer-Lemeshow goodness of fit test yielded a χ2 value of 5.863 (P>0.05); the area under the ROC curve (AUC) was 0.846 (95%CI=0.799-0.893); Calibration curve analysis indicated good consistency between predicted and actual values of the model. DCA demonstrated favorable predictive performance of the model over a wide range. Conclusions The predictive model for school varicella outbreaks demonstrates satisfactory accuracy and efficacy. It suggested to make good use of this prediction model and take relevant measures to reduce the risk of varicella transmission in schools.

OBJECTIVE To construct a risk prediction model for non-compliance with inhaled medication in patients with chronic obstructive pulmonary disease （COPD）. METHODS A retrospective analysis was conducted on 365 COPD patients admitted to the cough and wheeze pharmaceutical care clinic of the First Hospital of Qinhuangdao from October 2021 to October 2023. The patients admitted from October 2021 to June 2023 were selected as the model group （n＝303）， and the patients admitted from July to October 2023 were selected as the validation group （n＝62）. The model group was divided into compliance subgroup （n＝126） and non-compliance subgroup （n＝177）. Univariate analysis combined with multivariate Logistic regression analysis were used to analyze the risk factors for non-compliance with inhaled formulations in patients； the risk prediction model was established through regression analysis， and the accuracy of the model prediction was evaluated based on the validation group of patients. RESULTS Multivariate Logistic regression analysis showed that simultaneous use of 2 inhaled formulations （OR＝3.730， 95%CI 1.996-6.971， P＜0.001）， the number of acute exacerbations within one year ≥2 （OR＝2.509， 95%CI 1.509-4.173， P＜0.001）， smoking （OR＝2.167， 95%CI 1.309-3.588， P＝0.003）， complicated with anxiety/depression （OR＝2.112， 95%CI 1.257-3.499， P＝0.004） and mMRC grading≥2 levels （OR＝1.701， 95%CI 1.014-2.853， P＝0.044） were risk factors for non-compliance with inhaled preparations. Based on this， a risk prediction model was established and the ROC curve was drawn. The areas under the curve of the model group and validation group were 0.836 and 0.928， and the overall accuracy of the model’s prediction was 88.71%. CONCLUSIONS The predictive model based on the simultaneous use of 2 inhaled formulations， the number of acute exacerbations within one year ≥2， smoking， complicated with anxiety/depression， mMRC grading ≥2 levels has certain predictive value for the risk of non-compliance with inhaled formulations for COPD patients.

OBJECTIVE To construct a risk prediction model for non-compliance with inhaled medication in patients with chronic obstructive pulmonary disease （COPD）. METHODS A retrospective analysis was conducted on 365 COPD patients admitted to the cough and wheeze pharmaceutical care clinic of the First Hospital of Qinhuangdao from October 2021 to October 2023. The patients admitted from October 2021 to June 2023 were selected as the model group （n＝303）， and the patients admitted from July to October 2023 were selected as the validation group （n＝62）. The model group was divided into compliance subgroup （n＝126） and non-compliance subgroup （n＝177）. Univariate analysis combined with multivariate Logistic regression analysis were used to analyze the risk factors for non-compliance with inhaled formulations in patients； the risk prediction model was established through regression analysis， and the accuracy of the model prediction was evaluated based on the validation group of patients. RESULTS Multivariate Logistic regression analysis showed that simultaneous use of 2 inhaled formulations （OR＝3.730， 95%CI 1.996-6.971， P＜0.001）， the number of acute exacerbations within one year ≥2 （OR＝2.509， 95%CI 1.509-4.173， P＜0.001）， smoking （OR＝2.167， 95%CI 1.309-3.588， P＝0.003）， complicated with anxiety/depression （OR＝2.112， 95%CI 1.257-3.499， P＝0.004） and mMRC grading≥2 levels （OR＝1.701， 95%CI 1.014-2.853， P＝0.044） were risk factors for non-compliance with inhaled preparations. Based on this， a risk prediction model was established and the ROC curve was drawn. The areas under the curve of the model group and validation group were 0.836 and 0.928， and the overall accuracy of the model’s prediction was 88.71%. CONCLUSIONS The predictive model based on the simultaneous use of 2 inhaled formulations， the number of acute exacerbations within one year ≥2， smoking， complicated with anxiety/depression， mMRC grading ≥2 levels has certain predictive value for the risk of non-compliance with inhaled formulations for COPD patients.

Introduction::Observational studies have revealed an association between waist circumference (WC) and atrial fibrillation (AF). However, it is difficult to infer a causal relationship from observational studies because the observed associations could be confounded by unknown risk factors. Therefore, the causal role of WC in AF is unclear. This study was designed to investigate the causal association between WC and AF using a two-sample Mendelian randomization (MR) analysis.Methods::In our two-sample MR analysis, the genetic variation used as an instrumental variable for MR was acquired from a genome-wide association study (GWAS) of WC (42 single nucleotide polymorphisms with a genetic significance of P <5 × 10 –8). The data of WC (from the Genetic Investigation of ANthropometric Traits consortium, containing 232,101 participants) and the data of AF (from the European Bioinformatics Institute database, containing 55,114 AF cases and 482,295 controls) were used to assess the causal role of WC on AF. Three different approaches (inverse variance weighted [IVW], MR–Egger, and weighted median regression) were used to ensure that our results more reliable. Results::All three MR analyses provided evidence of a positive causal association between high WC and AF. High WC was suggested to increase the risk of AF based on the IVW method (odds ratio [OR] = 1.43, 95% confidence interval [CI], 1.30–1.58, P = 2.51 × 10 -13). The results of MR–Egger and weighted median regression exhibited similar trends (MR–Egger OR = 1.40 [95% CI, 1.08–1.81], P = 1.61 × 10 -2; weighted median OR = 1.39 [95% CI, 1.21–1.61], P = 1.62 × 10 -6). MR–Egger intercepts and funnel plots showed no directional pleiotropic effects between high WC and AF. Conclusions::Our findings suggest that greater WC is associated with an increased risk of AF. Taking measures to reduce WC may help prevent the occurrence of AF.

Objective To detect the expression level of 4-aminobutyrate aminotransferase(ABAT)in bone marrow of patients with myelodysplastic syndrome(MDS),and analyze its influence on clinicopathological features and prognosis of patients.Methods From January 2016 to March 2020,92 patients with MDS and 30 patients with acute myeloid leukemia(AML)from the First Affiliated Hospital of Xingtai Medical College were retrospectively collected.Meanwhile,30 patients with immunothrombocytopenia who did not develop MDS or other clonal diseases of the blood system during a 3-year follow-up were collected as control group.Real-time quantitative fluorescent PCR(qRT-PCR)was used to detect the relative expression level and methylation level of ABAT mRNA of all patients,and the relative expression level and methylation level of ABAT mRNA among different clinical characteristics of MDS patients were compared.Multivariate logistic regression analysis was used to analyze the risk factors affecting the adverse prognosis of MDS.The clinical value of detecting ABAT methylation level in predicting poor prognosis of MDS patients was analyzed by receiver operating characteristic(ROC)curve.Kaplan-Meier method was used to calculate the 3-year survival rate between groups with different ABAT mRNA relative expression levels and methylation levels,and log-rank test was used for their comparison.Results The expression level of ABAT mRNA in MDS group(0.42±0.08)was lower than that in control group(0.56±0.15)and AML group(0.52±0.10),while the methylation level of ABAT(32.51±5.32)was higher than that of AML group(26.21±4.58)and control group(10.25±4.31),and the differences were significant(t=4.251,4.562;10.415,8.326,all P<0.001).The methylation level of ABAT in high-risk patients(42.65±5.32)was higher than that in low-risk patients(25.63±4.16),intermediate-risk-1 patients(30.59±2.51)and intermediate-risk-2 patients(33.25±3.69)by IPSS risk grade,and the differences were significant(t=8.329,7.077,15.874,all P<0.001).Poor Karyotype analysis result[OR(95%CI):4.973(1.524～8.581),P=0.004],high IPSS risk grade[OR(95%CI):8.542(2.365～14.521),P<0.001]and ABAT hypermethylation level[OR(95%CI):6.178(1.589～13.021),P<0.001]were the risk factors affecting the poor prognosis of MDS.The cut-offvalue of ABAT methylation level to predict the poor prognosis of MDS were 30.54,and the area under the curve(AUC),the sensitivity and specificity were 0.92,0.874 and 0.851,respectively.The 3-year survival rate of the high ABAT methylation group(>30.54)was 66.67%,which was lower than that of the low ABAT methylation group(≤30.54)was 93.18%,with significant difference(Log-rank x2=9.814,P=0.002).Conclusion The ABAT methylation levels in MDS bone marrow increase,which is a risk factor affecting the poor prognosis of patients.ABAT basal level>30.54 is expected to become a factors predicting the poor prognosis of patients.

Objective:To evaluate the efficacy and prognostic factors of allogeneic hematopoietic stem cell transplantation (allo-HSCT) in patients with secondary acute myeloid leukemia (sAML) .Methods:In this multicenter, retrospective clinical study, adult patients aged ≥18 years who underwent allo-HSCT for sAML at four centers of the Zhejiang Hematopoietic Stem Cell Transplantation Collaborative Group from January 2014 to November 2022 were included, and the efficacy and prognostic factors of allo-HSCT were analyzed.Results:A total of 95 patients were enrolled; 66 (69.5%) had myelodysplastic syndrome-acute myeloid leukemia (MDS-AML) , 4 (4.2%) had MDS/MPN-AML, and 25 (26.3%) had therapy-related AML (tAML) . The 3-year CIR, LFS, and overall survival (OS) rates were 18.6% (95% CI 10.2%-27.0%) , 70.6% (95% CI 60.8%-80.4%) , and 73.3% (95% CI 63.9%-82.7%) , respectively. The 3-year CIRs of the M-AML group (including MDS-AML and MDS/MPN-AML) and the tAML group were 20.0% and 16.4%, respectively ( P=0.430) . The 3-year LFSs were 68.3% and 75.4%, respectively ( P=0.176) . The 3-year OS rates were 69.7% and 75.4%, respectively ( P=0.233) . The 3-year CIRs of the groups with and without TP53 mutations were 60.0% and 13.7%, respectively ( P=0.003) ; the 3-year LFSs were 20.0% and 76.5%, respectively ( P=0.002) ; and the 3-year OS rates were 40.0% and 77.6%, respectively ( P=0.002) . According to European LeukmiaNet 2022 (ELN2022) risk stratification, the 3-year CIRs of patients in the low-, intermediate-, and high-risk groups were 8.3%, 17.8%, and 22.6%, respectively ( P=0.639) . The three-year LFSs were 91.7%, 69.5%, and 65.6%, respectively ( P=0.268) . The 3-year OS rates were 91.7%, 71.4%, and 70.1%, respectively ( P=0.314) . Multivariate analysis revealed that advanced disease at allo-HSCT and TP53 mutations were independent risk factors for CIR, LFS, and OS. Conclusion:There was no significant difference in the prognosis of patients who underwent allo-HSCT among the MDS-AML, MDS/MPN-AML, and tAML groups. Advanced disease at transplantation and TP53 mutations were poor prognostic factors. ELN2022 risk stratification had limited value for predicting the prognosis of patients with sAML following allo-HSCT.

Obesity and related metabolic syndromes have been recognized as important disease risks,in which the role of adipokines cannot be ignored.Adiponectin(ADP)is one of the key adipokines with various beneficial effects,including improving glucose and lipid metabolism,enhancing insulin sensitivity,reducing oxidative stress and inflammation,promoting ceramides degradation,and stimulating adipose tissue vascularity.Based on those,it can serve as a positive regulator in many metabolic syndromes,such as type 2 diabetes(T2D),cardiovascular diseases,non-alcoholic fatty liver disease(NAFLD),sarcopenia,neurodegenerative diseases,and certain cancers.Therefore,a promising therapeutic approach for treating various metabolic diseases may involve elevating ADP levels or activating ADP receptors.The modulation of ADP genes,multimerization,and secretion covers the main processes of ADP generation,providing a comprehensive orientation for the development of more appropriate therapeutic strategies.In order to have a deeper understanding of ADP,this paper will provide an all-encompassing review of ADP.