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:Traditional methods of urinary tract reconstruction are limited by donor scarcity,high complication rates,and suboptimal functional recovery.Tissue engineering strategies offer new directions in this field.Since the urinary tract is mainly composed of muscle tissue,the key is to find suitable seed cells and efficiently induce them to differentiate into smooth muscle cells.Comparative studies on the efficacy of different smooth muscle cell induction regimens are still lacking. OBJECTIVE:To isolate,culture,and identify human urine-derived stem cells,and to compare the effects of two different induction protocols. METHODS:Human urine-derived stem cells were isolated from urine samples of 11 healthy adult volunteers by multiple centrifugations.Surface markers were identified by flow cytometry.The multi-directional differentiation potential of human urine-derived stem cells was verified through osteogenic and adipogenic differentiation.Differentiation was induced by transforming growth factor-β1 or transforming growth factor-β1 combined with platelet derived growth factor for 14 days.Immunofluorescence staining and western blot assay were employed to compare the expression differences of smooth muscle-specific proteins(α-SMA and SM22). RESULTS AND CONCLUSION:(1)Urine-derived stem cells were successfully isolated from the eight urine samples of healthy people.These cells exhibit a"rice grain"-like morphology and possess a robust proliferative capacity.(2)Urine-derived stem cells exhibited high expression of mesenchymal stem cell surface markers(CD73,CD90,and CD44)and extremely low expression of hematopoietic stem cell surface markers(CD34 and CD45).These cells did not express CD19,CD105,and HLA-DR.(3)After osteogenic and adipogenic differentiation,the formation of calcium nodules and lipid droplets was observed,with positive staining results from Alizarin Red S and Oil Red O staining.(4)After 14 days of smooth muscle induction culture,immunofluorescence staining revealed that the smooth muscle differentiation rate of urine-derived stem cells treated with a combination of transforming growth factor-β1 and platelet derived growth factor was significantly higher compared to those treated with transforming growth factor-β1 alone(P<0.005).(5)After 14 days of smooth muscle induction culture,western blot assay further demonstrated that the expression levels of α-SMA and SM22 in the transforming growth factor-β1/platelet derived growth factor group were significantly elevated compared to those in the transforming growth factor-β1 only group(P<0.005).These findings confirm that urine-derived stem cells can be non-invasively isolated using multiple rounds of centrifugation.Compared with transforming growth factor-β1 alone,the combination of transforming growth factor-β1 and platelet derived growth factor can improve the efficiency of inducing urine-derived stem cells to differentiate into smooth muscle cells.

ObjectiveTo evaluate the clinical efficacy of Huayu Tongluo Formula （化瘀通络方， HTF） in patients with mid-stage diabetic kidney disease of blood stasis syndrome and explore its potential mechanisms. MethodsA multi-center， randomized， double-blind， placebo-controlled clinical trial was conducted. Ninety patients of mid-stage diabetic kidney disease of blood stasis syndrome were divided into a control group of 46 cases and a treatment group of 44 cases. Both groups received conventional western medicine treatment， the treatment group additionally taking HTF， while the control group taking a placebo of the formula. The treatment was administered once daily for 24 weeks. The primary outcomes included 24-hour urine total protein （24 h-UTP）， serum albumin （Alb）， glycated hemoglobin （HbA1c）， and serum creatinine （Scr）.The secondary outcomes included changes in levels of endothelin-1 （ET-1）， nitric oxide （NO）， vascular endothelial growth factor （VEGF）， and traditional Chinese medicine （TCM） syndrome scores before and after treatment. Clinical efficacy was evaluated based on TCM syndrome scores and overall disease outcomes. Adverse reactions and endpoint events were recorded. ResultsIn the treatment group after treatment， 24 h-UTP， ET-1， and VEGF levels significantly decreased （P＜0.05）， Alb and NO levels significantly increased （P＜0.05）； while the TCM syndrome scores for edema， lumbar pain， numbness of limbs， dark purple lips， dark purple tongue or purpura， and thin， rough pulse all significantly decreased （P＜0.05）. In the control group， no significant changes were observed in any of the indicators after treatment （P＞0.05）.Compared with the control group， the treatment group showed significant reductions in 24 h-UTP， ET-1， and VEGF levels， and increases in Alb and NO levels （P＜0.05）. The TCM syndrome scores for edema， lumbar pain， dark purple tongue or purpura， and thin， rough pulse were all lower in the treatment group than in the control group （P＜0.05）. The total effective rate of TCM syndrome in the treatment group was 59.09% （26/44）， and the overall clinical effective rate was 45.45% （20/44）. In the control group， these rates were 15.22% （7/46） and 8.7% （4/46）， respectively， with the treatment group showing significantly better outcomes （P＜0.05）. A total of 7 adverse events occurred across both groups， with no significant difference （P＞0.05）. No endpoint events occurred during the study. ConclusionOn the basis of conventional treatment of Western medicine， HTF can further reduce urinary protein levels and improve clinical symptoms in patients with mid-stage diabetic kidney disease of blood stasis syndrome. The mechanism may be related to its effects on endothelial function.

This paper summarizes Professor SHI Zaixiang's clinical experience in treating high fever caused by sepsis using Chaihu Guizhi Ganjiang Decoction （柴胡桂枝干姜汤）. He holds that the key pathogenesis of sepsis involves constrained heat in the shaoyang and internal accumulation of water and fluids. The clinical manifestations such as high fever， chills， and alternating sensations of cold and heat are attributed to pathogenic heat constrained in the shaoyang. Meanwhile， soft tissue edema and serous cavity effusions are due to shaoyang dysfunction and internal water retention. In clinical practice， treating sepsis-related high fever requires addressing both the shaoyang-constrained heat and the associated edema and effusions. The therapeutic approach focuses on harmonizing the shaoyang and resolving internal fluids， using Chaihu Guizhi Ganjiang Decoction as the base formula with flexible modifications. Professor SHI emphasizes that this formula shows a rapid antipyretic effect， particularly in cases where multiple anti-infective treatments have failed.

Objective: To investigate the status of drug resistance before anti-retroviral therapy among newly dignosed HIV/AIDS patients aged ≥50 years in Yangzhou City, Jiangsu Province, so as to provide the evidence for improving the anti-retroviral therapy effect of AIDS. Methods: HIV/AIDS patients aged ≥50 years who were newly dignosed in Yangzhou City from 2021 to 2024 and did not receive anti-retroviral therapy were selected. Basic information were collected through the Chinese Disease Prevention and Control Information System. Blood samples were collected to determine CD4+T lymphocyte (CD4 cell) counts and HIV-1 viral load. Following nucleic acid extraction, the pol gene region was amplified using reverse transcription and nested PCR, and subsequently subjected to Sanger sequencing. The resulting sequences were uploaded to the Stanford University HIV Drug Resistance Database to analyze drug resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs), and nucleoside reverse transcriptase inhibitors (NRTIs). Results: Totally 404 blood samples from HIV/AIDS patients were collected, with successful sequencing of the pol gene region in 341 cases. Among them, 253 (74.19%) were males and 88 (25.81%) were females, with a mean age of (62.48±7.60) years. A total of 152 cases (44.57%) had CD4 cell counts below 200 cells/μL, and 296 cases (86.80%) had HIV-1 viral loads exceeding 5 000 copies/mL. A total of 87 cases exhibited drug resistance-associated mutations, corresponding to a mutation rate of 25.51%. The predominant mutation site was V179, with a mutation rate of 17.01%. A total of 29 cases exhibited resistance to at least one drug, resulting in a resistance rate of 8.50%. The resistance rates to NNRTIs, PIs, and NRTIs were 5.57%, 2.93%, and 1.17%, respectively. The HIV/AIDS patients exhibited varying degrees of resistance to 13 anti-retroviral drugs, with low- or intermediate-level drug resistance being predominant. High-level drug resistance cases were observed against NNRTIs such as nevirapine and efavirenz. Conclusions The drug resistance rate before anti-retroviral therapy among newly dignosed HIV/AIDS patients aged ≥50 years in Yangzhou City was at a moderate level. The predominant resistance mutation was observed at V179 site, with NNRTIs resistance being most prevalent, primarily demonstrating low- or intermediate-level drug resistance.

Objective:To identify the relationship between the CT arterial radiomics score and the treatment response to neoadjuvant therapy for pancreatic cancer.Methods:The clinical data of 243 pancreatic cancer patients who received surgical resection after neo-adjuvant therapy in the First Affiliated Hospital of Naval Medical University from March 2017 to March 2023 were retrospectively analyzed. Based on the tumor regression grade (TRG), the patients were divided into good response group (TRG 0-1, n=30) and non-good response group (TRG 2-3, n=213). The clinical, radiological and pathological features were compared between two groups. Fully-automated segmentation tool was used for segmenting the arterial CT scan of pancreatic tumor before and after treatment. Python package was applied to extract the radiomics features of tumors after segmentation and the extracted features were reduced and chosen using the least absolute shrinkage and selection operator (Lasso) logistic regression algorithm. Lasso logistic regression formula was applied to calculate the arterial radiomics score. Univariate and multivariate logistic regression models were used to analyze the association between arterial radiomics score and treatment response to neoadjucant therapy. Receiver operating-characteristics (ROC) curve was drawn and area under curve (AUC), specificity, sensitivity and accuracy for evaluating the treatment response were calculated. The clinical usefulness of arterial radiomics score for diagnosing the response of neoadjuvant treatment for pancreatic cancer were determined by decision curve analysis (DCA) . Results:A total of 330 arterial radiomics CT features were obtained, and 9-selected arterial phase features associated with treatment response were determined after being reduced by the Lasso logistic regression algorithm. Univariate analysis showed that the arterial radiomics score, three-dimensional diameter after neoadjuvant therapy, pancreatic contour, T stage, N stage, Peri-pancreatic nerve invasion, lymph-vascular space invasion (LVSI) and invasion of duodenum were all associated with treatment response (all P value <0.05). Multivariate logistic regression analyses confirmed that arterial radiomics score was obviously associated with the neoadjuvant treatment response ( P<0.001). At the cut-off value of 1.93, AUC of the arterial radiomics score for diagnosing neoadjuvant treatment response was 0.92, and the specificity, sensitivity and accuracy was 86.7%, 84.5% and 84.8%. DCA demonstrated that when the percentage for predicting the treatment response by using the arterial radiomics score was >0.2, the patients could benefit from the application of arterial radiomics score for evaluating neoadjuvant therapy response. Conclusions:The arterial radiomics score was strongly correlated with the neoadjuvant treatment response of pancreatic cancer, and can accurately predict neoadjuant treatment efficacy.

Background::Early detection of esophageal squamous cell carcinoma (ESCC) can considerably improve the prognosis of patients. Aberrant cell-free DNA (cfDNA) methylation signatures are a promising tool for detecting ESCC. However, available markers based on cell-free DNA methylation are still inadequate. This study aimed to identify ESCC-specific cfDNA methylation markers and evaluate the diagnostic performance in the early detection of ESCC.Methods::We performed whole-genome bisulfite sequencing (WGBS) for 24 ESCC tissues and their normal adjacent tissues. Based on the WGBS data, we identified 21,469,837 eligible CpG sites (CpGs). By integrating several methylation datasets, we identified several promising ESCC-specific cell-free DNA methylation markers. Finally, we developed a dual-marker panel based on methylated KCNA3 and OTOP2, and then, we evaluated its performance in our training and validation cohorts. Results::The ESCC diagnostic model constructed based on KCNA3 and OTOP2 had an AUC of 0.91 [95% CI: 0.85–0.95], and an optimal sensitivity and specificity of 84.91% and 94.32%, respectively, in the training cohort. In the independent validation cohort, the AUC was 0.88 [95% CI: 0.83–0.92], along with an optimal sensitivity of 81.5% and specificity of 92.9%. The model sensitivity for stage I–II ESCC was 78.4%, which was slightly lower than the sensitivity of the model (85.7%) for stage III–IV ESCC. Conclusion::The dual-target panel based on cfDNA showed excellent performance for detecting ESCC and might be an alternative strategy for screening ESCC.