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.

AIM:To explore the potential of Huangqi sanqi mixture(AP)in improving renal fi-brosis by performing transcriptome sequencing of the kidneys of the unilateral ureteral ligation mouse group and the Huangqi sanqi mixture inter-vention group,and using bioinformatics to verify the signitficantly different lncRNAs mechanism.METHODS:Twenty-four C57 mice were divided in-to sham operation group,renal fibrosis group,Huangqi sanqi mixture intervention group(3.944 g/kg)and irbesartan positive control intervention group,with 6 mice in each group.A mouse model of renal fibrosis was established by unilateral ure-teral ligation(UUO).The animals were given intra-gastric administration after operation,and the ani-mals were sacrificed and the specimens were col-lected after seven consecutive days of administra-tion.The changes of Huangqi sanqi mixture on re-nal fibrosis pathological damage were analyzed by HE and Masson staining,and the protein levels of Fn and α-SMA in renal tissue of each group were detected by Western blot and immunohistochemis-try to evaluate the alleviating effect of Huangqi san-qi mixture on renal fibrosis.Subsequently,lncRNA expression information was obtained by transcrip-tome sequencing,and Quantitative Real-time PCR(qPCR)was performed after data quality,GO en-richment and differential lncRNA were analyzed.According to the differential lncRNA and target analysis results obtained by sequencing,lncRNA Gm51500/Adam12 was overexpressed in vitro,and its mechanism in the protection of renal fibrosis by Huangqi sanqi mixture was studied by immunohis-tochemistry,immunofluorescence staining and qP-CR verification.RESULTS:Compared with the mod-el group,the renal fibrosis of the mice in the Huangqi sanqi mixture intervention group was sig-nificantly reduced,and the protein levels of α-SMA and Fn and the expression of lncRNA in the renal tis-sue were significantly down-regulated(P＜0.000 1).Three lncRNAs were screened and verified to in-crease in the model group and significantly de-crease after AP intervention,namely lncRNA Gm29994,Gm51500 and Gm35391.Target analysis showed that lncRNA Gm51500 had the most signifi-cant relationship with Adam12.The results of ani-mal experiments showed that Adam12 was highly expressed in the kidney of UUO mice and was sig-nificantly inhibited after AP intervention.Subse-quent cell experiments confirmed that overexpres-sion of lncRNA Gm51500 could up-regulate TGF-β-induced renal tubular cell fibrosis and Adam12 ex-pression.Cell recovery experiments confirmed that Adam12 overexpression reversed the inhibitory ef-fect of AP on renal tubular cell injury and fibrosis.CONCLUSION:Huangqi sanqi mixture can improve renal fibrosis.Based on transcriptomic sequencing,lncRNA Gm51500/Adam12 axis may be a potential target for Huangqi sanqi mixture to improve renal fibrosis.

AIM:To explore the potential of Huangqi sanqi mixture(AP)in improving renal fi-brosis by performing transcriptome sequencing of the kidneys of the unilateral ureteral ligation mouse group and the Huangqi sanqi mixture inter-vention group,and using bioinformatics to verify the signitficantly different lncRNAs mechanism.METHODS:Twenty-four C57 mice were divided in-to sham operation group,renal fibrosis group,Huangqi sanqi mixture intervention group(3.944 g/kg)and irbesartan positive control intervention group,with 6 mice in each group.A mouse model of renal fibrosis was established by unilateral ure-teral ligation(UUO).The animals were given intra-gastric administration after operation,and the ani-mals were sacrificed and the specimens were col-lected after seven consecutive days of administra-tion.The changes of Huangqi sanqi mixture on re-nal fibrosis pathological damage were analyzed by HE and Masson staining,and the protein levels of Fn and α-SMA in renal tissue of each group were detected by Western blot and immunohistochemis-try to evaluate the alleviating effect of Huangqi san-qi mixture on renal fibrosis.Subsequently,lncRNA expression information was obtained by transcrip-tome sequencing,and Quantitative Real-time PCR(qPCR)was performed after data quality,GO en-richment and differential lncRNA were analyzed.According to the differential lncRNA and target analysis results obtained by sequencing,lncRNA Gm51500/Adam12 was overexpressed in vitro,and its mechanism in the protection of renal fibrosis by Huangqi sanqi mixture was studied by immunohis-tochemistry,immunofluorescence staining and qP-CR verification.RESULTS:Compared with the mod-el group,the renal fibrosis of the mice in the Huangqi sanqi mixture intervention group was sig-nificantly reduced,and the protein levels of α-SMA and Fn and the expression of lncRNA in the renal tis-sue were significantly down-regulated(P＜0.000 1).Three lncRNAs were screened and verified to in-crease in the model group and significantly de-crease after AP intervention,namely lncRNA Gm29994,Gm51500 and Gm35391.Target analysis showed that lncRNA Gm51500 had the most signifi-cant relationship with Adam12.The results of ani-mal experiments showed that Adam12 was highly expressed in the kidney of UUO mice and was sig-nificantly inhibited after AP intervention.Subse-quent cell experiments confirmed that overexpres-sion of lncRNA Gm51500 could up-regulate TGF-β-induced renal tubular cell fibrosis and Adam12 ex-pression.Cell recovery experiments confirmed that Adam12 overexpression reversed the inhibitory ef-fect of AP on renal tubular cell injury and fibrosis.CONCLUSION:Huangqi sanqi mixture can improve renal fibrosis.Based on transcriptomic sequencing,lncRNA Gm51500/Adam12 axis may be a potential target for Huangqi sanqi mixture to improve renal fibrosis.

This paper discusses the necessity of artificial intelligence(AI)technology empowering the field of traditional Chinese medicine(TCM)in the context of the intelligent era,the connotation and tasks of smart TCM,and the progress of related research and transformation.It closely follows the national orientation,rigid needs and problems,conducts top-level design,and proposes popular AI technologies that can be used in the field of TCM in the future and the research directions that smart TCM will focus on in the fu-ture,in order to further promote the integration of multidisciplinary cross-innovation and help realize the modernization,inheritance and innovation of TCM and lay the foundation.

Objective:To investigate the effect of osteoblast-derived extracellular vesicles(OB-EVs)on the proliferation and differentiation of osteoclasts,and to explore the possible molecular mechanism of extracellular vesicles involved in the communication between osteoblasts and osteoclasts.Methods:Primary osteoblasts were isolated from newborn mouse calvarial bone and induced by β-glycero phosphate,ascorbic acid and dexamethasone.Osteogenic feature was tested by alkaline phosphatase(ALP)and alizarin red S staining.Extracellular vesicles were isolated by ultracentrifugation from the cell culture supernatant.Vesicle morphology was observed by transmission electron microscopy,and the characteristic markers of tumor susceptibility gene 101(TSG101),ALG-2 interacting protein X(Alix)and cluster of differentiation 9(CD9)on the surface of extracellular vesicles were identified by Western blotting.Cell counting kit 8(CCK-8)assay was used to determine the proliferation effect of OB-EVs on mouse mononuclear macrophage RAW264.7 cells.Furthermore,the expression level of specific markers of osteoclast differentiation in RAW264.7 cells was detected by Western blotting after the combined effect of OB-EVs and receptor activator for nuclear factor κB ligand(RANKL).The number of osteoclasts was observed and compared with OB-EVs-treated mouse bone marrow-derived macrophages(BMMs)by tartrate-resistant acid phosphatase(TRAP)staining,and the effect of OB-EVs on osteoclast differentiation was determined.Results:The extracted OB-EVs showed a double-layer cup-like structure with a diameter of 30-150 nm,and TSG101,Alix and CD9 were expressed.RAW264.7 cells were stimulated with OB-EVs,and the results of CCK-8 assay showed that high concentration of OB-EVs(more than 20 μg/mL)inhibited cell proliferation(P<0.05).Western blotting analysis showed that the expression of osteoclast differentiation marker proteins such as c-Fos,activated T cell nuclear factor(NFATc1)and c-Jun N-terminal kinase(JNK)in RAW264.7 cells were significantly increased,and the promoting effect was enhanced with increasing of OB-EVs concentration(P<0.05).In addition,the combination of OB-EVs and RANKL on BMMs showed that the number of TRAP-positive cells was significantly higher than that of the RANKL induction group alone(P<0.05).Conclusion:OB-EVs can promote the differentiation of osteoclast precursor cells into osteoclasts,but high concentration of OB-EVs can inhibit proliferation of RAW264.7 cells.

Due to the long pathological process of Alzheimer disease(AD),this paper begins with the time-line of classical pathological events in AD and uses anomalous microglia activation as a starting point to elucidate the role of abnormal lipid metabolism in the pathological process of AD.This includes its influence on microglial pathology and its interactions with the two primary nodes of AD,namely,Amyloid-β and the microtubule-associated protein tau.Using this as a foundation,the paper briefly describes the effects of abnormal lipid metabolism caused by short-term and long-term high-fat diets on the pathological progression of AD and its potential mechanisms,aiming to provide a reference framework for the early intervention of AD.

Objective:To explore the effectiveness of a multimodal TeamSTEPPS course based on clinical cases in training surgical teams led by anesthesiologists, improve team cooperation in crisis management, and enhance clinical safety.Methods:The Department of Anesthesiology at Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, combined the TeamSTEPPS course with problem-based learning. Based on eight clinical cases, simulation-based training was conducted for interdisciplinary personnel, including anesthesiologists, surgeons, and operating room nurses. Pre- and post-training evaluations were conducted for 80 participants on theoretical knowledge and teamwork. Statistical analysis was performed using SPSS 27.0 software. The differences in scale scores before and after training were tested for normality. If normally distributed, results were expressed as mean ± standard deviation and analyzed using paired t-tests. Participant demographic data were represented using percentages. Results:The theoretical assessment scores after training were significantly higher than those before training [(76.45±8.34) vs. (60.21±5.90), t=13.55, P<0.001]. TeamSTEPPS Teamwork Perception Questionnaire and TeamSTEPPS Teamwork Attitudes Questionnaire scores were significantly higher after training than before training [(156.08±15.20) vs. (149.32±15.58) and (134.59±10.71) vs. (128.47±10.89)], with statistically significant differences ( P<0.001). Conclusions:The TeamSTEPPS management course in combination with problem-based learning can enhance the clinical theoretical knowledge of anesthesiologists and improve their team awareness and collaboration, thus improving their clinical competence in managing crisis events.

This paper discusses the necessity of artificial intelligence(AI)technology empowering the field of traditional Chinese medicine(TCM)in the context of the intelligent era,the connotation and tasks of smart TCM,and the progress of related research and transformation.It closely follows the national orientation,rigid needs and problems,conducts top-level design,and proposes popular AI technologies that can be used in the field of TCM in the future and the research directions that smart TCM will focus on in the fu-ture,in order to further promote the integration of multidisciplinary cross-innovation and help realize the modernization,inheritance and innovation of TCM and lay the foundation.

Objective:To explore the effectiveness of a multimodal TeamSTEPPS course based on clinical cases in training surgical teams led by anesthesiologists, improve team cooperation in crisis management, and enhance clinical safety.Methods:The Department of Anesthesiology at Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, combined the TeamSTEPPS course with problem-based learning. Based on eight clinical cases, simulation-based training was conducted for interdisciplinary personnel, including anesthesiologists, surgeons, and operating room nurses. Pre- and post-training evaluations were conducted for 80 participants on theoretical knowledge and teamwork. Statistical analysis was performed using SPSS 27.0 software. The differences in scale scores before and after training were tested for normality. If normally distributed, results were expressed as mean ± standard deviation and analyzed using paired t-tests. Participant demographic data were represented using percentages. Results:The theoretical assessment scores after training were significantly higher than those before training [(76.45±8.34) vs. (60.21±5.90), t=13.55, P<0.001]. TeamSTEPPS Teamwork Perception Questionnaire and TeamSTEPPS Teamwork Attitudes Questionnaire scores were significantly higher after training than before training [(156.08±15.20) vs. (149.32±15.58) and (134.59±10.71) vs. (128.47±10.89)], with statistically significant differences ( P<0.001). Conclusions:The TeamSTEPPS management course in combination with problem-based learning can enhance the clinical theoretical knowledge of anesthesiologists and improve their team awareness and collaboration, thus improving their clinical competence in managing crisis events.

Objective:To evaluate the bioequivalence and safety of domestic and original pyrazinamide tablets under fasting condition.Methods:A single center, randomized, open-label, two period self-crossover trial was conducted in healthy adult volunteers. The test preparation (T) of pyrazinamide tablets was produced by Taicang Pharmaceutical Factory and the reference preparation (R) was produced by A&Z Pharmaceutical Inc. (Pyrazinamide ?). The healthy subjects were randomly divided into 2 groups and took the drugs for 2 times with different order in each group, which were R-T group (subjects took R on day 1 and then T on day 8) and T-R group (subjects took T on day 1 and then R on day 8). Pharmacokinetic parameters were used as endpoints to assess the bioequivalence. Peripheral venous blood samples (3 ml) were collected from subjects within 1 hour before taking the drug and at 15, 30, 45, 60, 75, 90, 105, 120, 150, 180, and 210 minutes and 4, 5, 6, 8, 12, 24, 36, and 48 hours after taking the drug. Plasma was frozen after centrifugation of the blood samples. The plasma pyrazinamide concentrations were determined by a tandem liquid chromatography-mass spectrometry method and the main pharmacokinetic parameters such as peak concentration ( Cmax) and the area under the concentration-time curve (AUC), including AUC from time zero (pre-dose) to the time of the last quantifiable concentration (AUC 0-t) and AUC from time zero to infinity (AUC 0-∞), were calculated. The test and reference preparations were judged as bioequivalence when the 90% confidence intervals ( CI) of geometric mean ratios for AUC 0-t, AUC 0-∞, and Cmax all ranged from 0.80 to 1.25. Adverse events occurred in subjects during the trial were observed and recorded. Results:A total of 24 healthy volunteers were enrolled in the trial, including 16 males and 8 females aged 18-50 years, with 12 in the R-T and T-R groups, respectively. All subjects completed the trial. After taking medicine under fasting condition, the 90% CI of the geometric mean ratios of Cmax, AUC 0-t, and AUC 0-∞ for the test and reference preparations were 0.93-1.09, 0.98-1.03, and 0.98-1.03, respectively. During the trial, the incidence of adverse events was 25.0% (6/24) and 3 cases occurred after taking the test and reference preparations respectively, which were grade 1 in severity. Conclusion:The domestic and original pyrazinamide tablets were bioequivalence and with good safety when taken under fasting condition.