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 analyze the clinical outcomes of early invasive fungal disease(IFD)in patients after allogenetic hematopoietic stem cell transplantation(allo-HCST)with metagenomic next-generation sequencing(mNGS).Methods A retrospective analysis was conducted on patients undergoing allo-HCST in our Bone Marrow Transplantation Center between July 2021 and October 2022.These patients experienced one of the following conditions within 100 d after transplantation:① Patients with persistent fever and negative blood culture after empiric antimicrobial therapy for 72 h or longer;② Hyperpyrexia of unknown origin occurred again after effective anti-infection in the past;③ Symptoms in lower respiratory tract associated with lung lesions on CT scan,and empiric anti-infective therapy was ineffective.Peripheral blood or bronchoscopic alveolar lavage fluid were tested with mNGS,and overall survival(OS)and non-relapse mortality(NRM)were analyzed.Results There were 60 patients enrolled in this study.For the peripheral blood samples of 47 cases and bronchoalveolar lavage fluid samples of 13 cases,mNGS found that 19 cases were negative to pathogens,30 cases were non-fungal positive,and 11 case were fungal positive,including 3 cases of aspergillus,5 cases of mucor,2 cases of Candida tropicalis,and 1 case of Trichosporon asahii.Of the 11 patients with fungal positive,8 achieved complete remission after antifungal therapy according to the mNGS results.The 1-year OS and NRM of the 60 patients were 70.0％(95％CI:64.1％～75.9％)and 20.0％(95％CI:11.9％～32.5％),respectively,while those of the fungal infection patients were 54.5％(95％CI:49.5％～69.5％)and 36.4％(95％ CI:15.5％～70.3％),respectively.No significant differences were seen in 1-year OS(P=0.487)and 1-year NRM(P=0.358)among the negative,fungal infection and non-fungal infection patients,neither OS(P=0.238)and NRM(P=0.154)between the fungal infection and the non-fungal infection patients.Conclusion mNGS can rapidly diagnose the early IFD after allo-HSCT,which is helpful for timely and effective treatment and improves the prognosis of patients.

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.

The standardized workflow of computer-aided static guided implant surgery includes preoperative exami-nation,data acquisition,guide design,guide fabrication and surgery.Errors may occur at each step,leading to irrevers-ible cumulative effects and thus impacting the accuracy of implant placement.However,clinicians tend to focus on fac-tors causing errors in surgical operations,ignoring the possibility of irreversible errors in nonstandard guided surgery.Based on the clinical practice of domestic experts and research progress at home and abroad,this paper summarizes the sources of errors in guided implant surgery from the perspectives of preoperative inspection,data collection,guide de-signing and manufacturing and describes strategies to resolve errors so as to gain expert consensus.Consensus recom-mendation:1.Preoperative considerations:the appropriate implant guide type should be selected according to the pa-tient's oral condition before surgery,and a retaining screw-assisted support guide should be selected if necessary.2.Da-ta acquisition should be standardized as much as possible,including beam CT and extraoral scanning.CBCT performed with the patient's head fixed and with a small field of view is recommended.For patients with metal prostheses inside the mouth,a registration marker guide should be used,and the ambient temperature and light of the external oral scan-ner should be reasonably controlled.3.Optimization of computer-aided design:it is recommended to select a handle-guided planting system and a closed metal sleeve and to register images by overlapping markers.Properly designing the retaining screws,extending the support structure of the guide plate and increasing the length of the guide section are methods to feasibly reduce the incidence of surgical errors.4.Improving computer-aided production:it is also crucial to set the best printing parameters according to different printing technologies and to choose the most appropriate postpro-cessing procedures.

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 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 explore the genetic etiology and clinical phenotype of a child with Triadin knockout syndrome (TKOS), and to review the relevant literature of TKOS patients due to variants of TRDN gene. Methods:A child who was admitted to the Children′s Hospital of Xi′an Jiaotong University on March 19, 2023 due to sudden cardiac arrest 3 days earlier was selected as the study subject. Peripheral blood samples (2 to 3 mL) were collected from the child and her parents for the extraction of genomic DNA and whole exome sequencing (WES). Pathogenic variants were searched from databases such as the Genome Aggregation Database (gnomAD) and Online Mendelian Inheritance in Man (OMIM), and were assessed based on the guidelines from the American College of Medical Genetics and Genomics (ACMG). Sanger sequencing was carried out for family validation of the pathogenic variants. Using keywords such as " arrhythmias" " TRDN" and " Triadin" both in Chinese and English, relevant literature on TKOS patients due to variants of the TRDN gene was retrieved from the CNKI, Wanfang Data Knowledge Service Platform, and PubMed databases, and the time of literature retrieval was set from January 1, 2012 to December 1, 2023. This study has been approved by the Ethics Committee of the Affiliated Children′s Hospital of Xi′an Jiaotong University (No. 20230097), and informed consent was obtained from the parents of the child. Results:The child had experienced syncope and cardiac arrest after exercise. Electrocardiographic examination revealed QTc interval prolongation, T-wave inversion in precordial leads V1-V3, polymorphic ventricular premature beat (VPB), and ventricular tachycardia (VT) along with increased heart rate. WES and Sanger sequencing revealed that the child has harbored a homozygous c.463del(p.E155Kfs*20) variant of the TRDN gene, for which both of the parents were heterozygous. Based on the guidelines from the ACMG, the variant was classified as pathogenic (PVS1+ PM2+ PM3). The child was ultimately diagnosed with TKOS. In total 12 publications on TOKS cases caused by TRDN gene variants were retrieved, which involved 30 patients and 28 carriers of single heterozygous variant of the TRDN gene. Among the 30 TKOS patients, 20 had carried homozygous variants of the TRDN gene, and 10 had carried compound heterozygous variants, and all had exhibited significant clinical phenotype of arrhythmia, with most cases had experienced malignant arrhythmia induced by exercise and/or excitement during infancy or early childhood, leading to recurrent syncope and cardiac arrest. Of note, none of the 28 carriers of single heterozygous variant had abnormal clinical phenotype. Conclusion:The homozygous c.463del(p.E155Kfs20) variant of the TRDN gene probably underlay the pathogenesis of cardiac arrest in this child. Above discovery has enriched the mutational spectrum of the TRDN gene.This mutation may represent a genetic cause for cardiac arrest in children with TKOS.

Objective To design a multisensory supported device and evaluate its effectiveness on preterm infants(born before 34 weeks)during NICU hospitalization.Methods The multisensory supported device is composed of a basement,several soft cushions and an adjustable eye mask.The inner layer of the device comprises of the head and tail boundaries,serves as uterine wall-like circular boundaries.The outer skeleton is equipped with multisensory stimulation modules to provide visual,hearing,and tactile sensory stimulations for premature infants.The study was conducted in a NICU of a tertiary A children specialist hospital in Shanghai,China.The convenience sampling method was used and based on the ratio of 1∶2 between the experimental and the control group in this study.The control group was treated by standard nursing care,while the experiment group was treated with the multisensory supported device in addition to NICU conventional care.All infants were assessed during the week of admission and again at corrected gestational age of 36 weeks.The actigraphy watch which was used for 72 hours continuous record of the activities of study infants,allows the researcher to compare the activity scores,wakefulness and sleep indicators of 2 groups of infants.Results 71 preterm infants were enrolled in the study,and 60 preterm infants completed data collection for study data analysis,including 20 in the experimental group and 40 in the control group.There were no statistical differences in demographic characteristics and clinical status regarding wakefulness,sleep and physical development between the 2 groups in baseline(P＞0.05).At 36 weeks of corrected gestational age,the activity score of the experimental group was(46.61±12.14)points,and that of the control group was(57.33±18.36)points,with statistically significant differences in 2 groups(P=0.024).The total waking time of the experimental group was(384.85±169.42)min,and that of the control group was(492.08±220.45)min,with statistically significant differences in 2 groups(P=0.049).There was no statistical difference in other indicators between 2 groups(P＞0.05).Conclusion The multisensory supported device can reduce high-frequency unpleasant activity as well as frequent wakefulness status,which could promote the sleeping quality of preterm infants.Further studies are needed to verify further effects of the device on premature infants'physical development.