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 conversion of adenosine (A) to inosine (I) through deamination is the prevailing form of RNA editing, impacting numerous nuclear and cytoplasmic transcripts across various eukaryotic species. Millions of high-confidence RNA editing sites have been identified and integrated into various RNA databases, providing a convenient platform for the rapid identification of key drivers of cancer and potential therapeutic targets. However, the available database for integration of RNA editing in hematopoietic cells and hematopoietic malignancies is still lacking.Methods::We downloaded RNA sequencing (RNA-seq) data of 29 leukemia patients and 19 healthy donors from National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database, and RNA-seq data of 12 mouse hematopoietic cell populations obtained from our previous research were also used. We performed sequence alignment, identified RNA editing sites, and obtained characteristic editing sites related to normal hematopoietic development and abnormal editing sites associated with hematologic diseases.Results::We established a new database, "REDH", represents RNA editome in hematopoietic differentiation and malignancy. REDH is a curated database of associations between RNA editome and hematopoiesis. REDH integrates 30,796 editing sites from 12 murine adult hematopoietic cell populations and systematically characterizes more than 400,000 edited events in malignant hematopoietic samples from 48 cohorts (human). Through the Differentiation, Disease, Enrichment, and knowledge modules, each A-to-I editing site is systematically integrated, including its distribution throughout the genome, its clinical information (human sample), and functional editing sites under physiological and pathological conditions. Furthermore, REDH compares the similarities and differences of editing sites between different hematologic malignancies and healthy control.Conclusions::REDH is accessible at http://www.redhdatabase.com/. This user-friendly database would aid in understanding the mechanisms of RNA editing in hematopoietic differentiation and malignancies. It provides a set of data related to the maintenance of hematopoietic homeostasis and identifying potential therapeutic targets in malignancies.

Objective To establish a stable rat model of non-obese polycystic ovary syndrome(PCOS)with clinical characteristics.Methods Dehydroepiandrosterone(DHEA)was used to establish a PCOS rat model by subcutaneous injection.Three-week-old female SD rats were divided into a normal group,6 mg/kg DHEA model group,and 60 mg/kg DHEA model group.The model groups were subcutaneously injected with the corresponding dose of DHEA daily,while the normal group was subcutaneously injected with glycerol daily for 21 consecutive days.The model was evaluated with ovarian histopathology as the gold standard to determine the optimal dosage of DHEA to induce a PCOS rat model.On this basis,the optimal DHEA modeling dose was selected,and stop and continue modeling groups were set up to observe the model for 28 days and evaluate its maintenance.The stop modeling group was no longer given DHEA,and the continued modeling group was subcutaneously injected with 60 mg/kg DHEA every 48 h.The evaluation indicators included body mass,estrous cycle,fasting blood glucose,serum insulin,histopathologic morphology of the ovaries,and serum sex hormone levels.Results(1)Compared with the normal group,the 6 mg/kg and 60 mg/kg DHEA model groups showed no significant difference in body mass,and their estrous cycles were irregular.There were more cystically dilated large follicles in the ovaries;fewer mature follicles;reduced layers of granulosa cells,which were arranged in a sparse and disorganized manner;and fewer lutea in the 6 mg/kg and 60 mg/kg DHEA model groups than the normal group.Furthermore,serum T and E2 levels were significantly higher in the 60 mg/kg DHEA model group(P＜0.05)than the normal group.(2)The stop modeling group(A2 group)resumed regular estrous cycles after 2 weeks,various growth follicles and corpora lutea were observed in the ovarian tissues,the number of cystic follicles was reduced,the number of granulosa cell layers increased,mature follicles were visible,oocyte morphology was locally intact,and the levels of E2 and AMH were reduced compared with the normal group(A1 group)(P＜0.05).(3)The continue model group(B2 group)was in the late stage of estrous cycle for a long period,and there were more large follicles with cystic dilatation,fewer mature follicles,fewer layers of granulosa cells with a sparse and disordered arrangement,and significantly fewer corpus lutea in the ovaries compared with the normal group(B1 group).The levels of serum LH,LH/FSH,and T were elevated(P＜0.05).Conclusions Subcutaneous injection of 60 mg/kg DHEA for 21 consecutive days can be used to successfully construct a non-obese PCOS rat model that possesses clinical characteristics.Subcutaneous injection of 60 mg/kg DHEA every 48 hours maintains the stability of the model.

Objectives:To explore the risk factors for death from ruptured acute aortic dissection during emergency treatment,construct and validate a risk prediction model for death from ruptured acute aortic dissection during emergency treatment. Methods:A total of 301 cases of acute aortic dissection patients who were admitted to Chinese Academy of Medical Sciences Fuwai Hospital from January 2018 to August 2021 were included in this study.Patients were divided into survival subgroup(n=239)and death subgroup(n=62)according to whether dissection rupture occurred in the acute stage of the disease.Univariate and multivariate analyses were performed.Logistic regression analysis was used to establish the risk prediction model.The Hosmer-Lemeshow test was conducted to assess the model's goodness of fit,and the receiver operating characteristic curve(ROC curve)was used to evaluate the model's predictive performance.A prospective validation was performed on 129 cases of acute aortic dissection patients admitted to our hospital's emergency department from September 2021 to September 2022. Results:Among the 301 cases of acute aortic dissection patients,there were 62 cases of rupture and death,with an incidence rate of 20.6%.The results of multivariate analysis showed that age(OR=1.066,95%CI:1.034-1.099),type A dissection(OR=0.045,95%CI:0.006-0.364),history of hypertension(OR=0.377,95%CI:0.167-0.850),and concomitant hypotension(OR=4.424,95%CI:1.467-13.340)were determinants of deaths.The model formula was Z=-5.624+0.064×age-0.976×history of hypertension(yes=1,no=0)-3.104×type(Type A=0,Type B=1)+1.487×concomitant hypotension(yes=1,no=0).The Hosmer-Lemeshow test result showed χ2=9.328,df=8,P=0.315,the area under the ROC curve was 0.874,sensitivity was 79.0%,specificity was 81.6%,and the maximum Youden index was 0.606.The model validation result showed that the area under the ROC curve was 0.722,sensitivity was 73.7%,specificity was 69.1%,and accuracy was 89.9%. Conclusions:Age,history of hypertension,dissection type,and combined hypotension are predictors of the risk prediction model for death from dissection rupture in patients with acute aortic dissection during emergency treatment.The model constructed in this study has good predictive performance,which can provide reference for medical staffto quickly identify high-risk patients for death from ruptured acute aortic dissection and timely predictive measures could be highlighted in indicated cases.

Objectives:To compare the diagnostic efficacy of non-ST-segment elevation myocardial infarction (NSTEMI) and the predictive value for major adverse cardiovascular events (MACE) of the 0/3-hour algorithm for high-sensitivity cardiac troponin (hs-cTn) recommended by the 2015 European Society of Cardiology (ESC) guidelines for the management of non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and the 2021 "Chinese Expert Consensus on Laboratory Testing and Clinical Application of Cardiac Troponin" in suspected acute coronary syndrome (ACS) patients in the Chinese population. Methods:This is a multicenter prospective observational study,including 1527 patients with suspected ACS from three clinical centers from January 2017 to September 2020.Plasma hs-cTnI levels were measured using the ARCHITECT assay at the time of presentation and 3 hours later in patients with suspected ACS (test determination).Clinical judgment (independent clinical judgment by cardiac experts,independent of the test results) was used as the gold standard to compare the sensitivity,specificity,and consistency of the two diagnostic algorithms,and to analyze their predictive value for MACE at 30 days and 180 days.MACE in this study was defined as a composite event of cardiovascular death,myocardial infarction,and unplanned coronary revascularization. Results:According to clinical judgment,there were 400 patients with NSTEMI and 1127 patients without NSTEMI.The 0/3-hour algorithm recommended by the 2021 Chinese Expert Consensus showed higher sensitivity in diagnosing NSTEMI than the 2015 ESC guidelines (91.50％[95％ CI:88.32％-94.04％]vs.87.75％[95％ CI:84.13％-90.80％]),but slightly lower specificity (93.88％[95％ CI:92.32％-95.21％]vs.95.56％[95％ CI:94.19％-96.69％]),with both differences being statistically significant (both P<0.001).In the follow-up at 30 days and 180 days,the incidence of MACE in patients diagnosed with NSTEMI by both algorithms was higher than in those without NSTEMI (P<0.001).The incidence of MACE at 30 days and 180 days for the group excluded from the diagnosis of NSTEMI by 2015 ESC guidelines was 0.19％ and 1.120％,respectively,and for the NSTEMI group was 2.89％ and 3.68％,respectively;for the group excluded from NSTEMI by the 2021 Chinese Expert Consensus,the incidence was 0.096％ and 0.770％,respectively,and for the NSTEMI group was 2.91％ and 4.36％,respectively.Cox analysis showed that the HR ratio for MACE at 180 days in the NSTEMI group diagnosed by both algorithms was 3.418 and 5.892,respectively,significantly higher than the group excluded from NSTEMI. Conclusions:The 0/3-hour algorithm recommended by the 2021 Chinese Expert Consensus has superior diagnostic sensitivity compared to the 2015 ESC NSTE-ACS guidelines,at the cost of slightly lower specificity.Both algorithms can effectively predict MACE within 180 days,but based on the data from this study,the algorithm recommended by the 2021 Chinese Expert Consensus is more sensitive in predicting the risk of MACE,and patients excluded from the diagnosis of NSTEMI by this method have a lower incidence of MACE,suggesting that its application in clinical practice may be more helpful in terms of long-term safe management of patients.

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.

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.

Objective This study aims to discuss the research hotspot and development trend in the field of polycystic ovary syndrome(PCOS)through bibliometric statistics and visual analysis of long noncoding RNA(lncRNA)related studies.Methods Utilizing the Web of Science core database as the literature data source,we searched for PCOS lncRNA-related literature from 2015 to 2023.CiteSpace software was used to conduct a visual analysis,including the annual distribution,citation trends,countries,institutions,funding sources and key words,as well as co-occurrence and cluster analysis of key words.Results The visual analysis of 108 PCOS lncRNA literature revealed that China was the country with the highest number of publications.The first contributing institution was the Shandong University.The national natural science fund of China gave the biggest funding.The keyword cluster analysis suggested that PCOS lncRNA signal pathway regulation,related receptor activators,and the expression of regulatory factors were the research hotspots in ovary syndrome lncRNA research.Conclusion LncRNA related regulatory factors,bioinformatics analysis,and gene transcription in PCOS are new targetsfor PCOS treatment,providing valuable insights for clinical therapy and new strategies for the development of PCOS-related pharmaceuticals.

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.