This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

Osteosarcoma (OS), chondrosarcoma (CS), and Ewing sarcoma (ES) represent primary malignant bone tumors and pose significant challenges in oncology research and clinical management. Conventional research methods, such as two-dimensional (2D) cultured tumor cells and animal models, have limitations in recapitulating the complex tumor microenvironment (TME) and often fail to translate into effective clinical treatments. The advancement of three-dimensional (3D) culture technology has revolutionized the field by enabling the development of in vitro constructed bone tumor models that closely mimic the in vivo TME. These models provide powerful tools for investigating tumor biology, assessing therapeutic responses, and advancing personalized medicine. This comprehensive review summarizes the recent advancements in research on 3D tumor models constructed in vitro for OS, CS, and ES. We discuss the various techniques employed in model construction, their applications, and the challenges and future directions in this field. The integration of advanced technologies and the incorporation of additional cell types hold promise for the development of more sophisticated and physiologically relevant models. As research in this field continues to evolve, we anticipate that these models will play an increasingly crucial role in unraveling the complexities of malignant bone tumors and accelerating the development of novel therapeutic strategies.
Bone Neoplasms/pathology* ; Humans ; Osteosarcoma/pathology* ; Tumor Microenvironment ; Sarcoma, Ewing/pathology* ; Chondrosarcoma/pathology* ; Animals ; Cell Culture Techniques/methods* ; Cell Culture Techniques, Three Dimensional/methods* ; Cell Line, Tumor

Protrusive facial deformities, characterized by the forward displacement of the teeth and/or jaws beyond the normal range, affect a considerable portion of the population. The manifestations and morphological mechanisms of protrusive facial deformities are complex and diverse, requiring orthodontists to possess a high level of theoretical knowledge and practical experience in the relevant orthodontic field. To further optimize the correction of protrusive facial deformities, this consensus proposes that the morphological mechanisms and diagnosis of protrusive facial deformities should be analyzed and judged from multiple dimensions and factors to accurately formulate treatment plans. It emphasizes the use of orthodontic strategies, including jaw growth modification, tooth extraction or non-extraction for anterior teeth retraction, and maxillofacial vertical control. These strategies aim to reduce anterior teeth and lip protrusion, increase chin prominence, harmonize nasolabial and chin-lip relationships, and improve the facial profile of patients with protrusive facial deformities. For severe skeletal protrusive facial deformities, orthodontic-orthognathic combined treatment may be suggested. This consensus summarizes the theoretical knowledge and clinical experience of numerous renowned oral experts nationwide, offering reference strategies for the correction of protrusive facial deformities.
Humans ; Orthodontics, Corrective/methods* ; Consensus ; Malocclusion/therapy* ; Patient Care Planning ; Cephalometry

The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans ; Malocclusion, Angle Class III/classification* ; Orthodontics, Corrective/methods* ; Consensus ; Child

Inflammatory bowel disease (IBD) is a chronic and recurrent intestinal disease, and has become a major global health issue. Individuals with IBD face an elevated risk of developing colorectal cancer (CRC), and recent studies have indicated that mitochondrial dysfunction plays a pivotal role in the pathogenesis of both IBD and CRC. This review covers the pathogenesis of IBD and CRC, focusing on mitochondrial dysfunction, and explores pharmacological targets and strategies for addressing both conditions by modulating mitochondrial function. Additionally, recent advancements in the pharmacological modulation of mitochondrial dysfunction for treating IBD and CRC, encompassing mitochondrial damage, release of mitochondrial DNA (mtDNA), and impairment of mitophagy, are thoroughly summarized. The review also provides a systematic overview of natural compounds (such as flavonoids, alkaloids, and diterpenoids), Chinese medicines, and intestinal microbiota, which can alleviate IBD and attenuate the progression of CRC by modulating mitochondrial function. In the future, it will be imperative to develop more practical methodologies for real-time monitoring and accurate detection of mitochondrial function, which will greatly aid scientists in identifying more effective agents for treating IBD and CRC through modulation of mitochondrial function.

Objective:To investigate the endoscopic combined serological diagnosis strategy for G1 and G2 gastric neuroendocrine neoplasms (G-NENs), and to evaluate the safety, short-term, and long-term efficacy of two endoscopic treatment procedures: endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD).Methods:This study retrospectively analyzed the clinical data of 100 consecutive patients with G-NENs who were hospitalized at the Cancer Hospital of the Chinese Academy of Medical Sciences from January 2011 to October 2023. These patients underwent endoscopic treatment, and propensity score matching (PSM) was used to compare clinicopathological characteristics, as well as short-term and long-term efficacy of lesions in the EMR group and ESD group before and after treatment.Results:Among the 100 patients with G-NENs, the median age was 54 years old. Before surgery, 29 cases underwent endoscopic combined serological examination, and 24 of them (82.2%) had abnormally elevated plasma chromogranin A. The combined diagnostic strategy for autoimmune atrophic gastritis (AIG) achieved a diagnostic accuracy of 100%(22/22). A total of 235 G-NEN lesions were included, with 84 in the ESD group and 151 in the EMR group. The median size of the lesions in the ESD group (5.0 mm) was significantly larger than that in the EMR group (2.0 mm, P＜0.001). Additionally, the ESD group had significantly more lesions with pathological grade G2[23.8%(20/84) vs. 1.3%(2/151), P＜0.001], infiltration depth reaching the submucosal layer [78.6%(66/84) vs. 51.0%(77/151), P＜0.001], and more T2 stage compared to the EMR group[15.5%(13/84) vs. 0.7%(1/151), P＜0.001]. After PSM, 49 pairs of lesions were successfully matched between the two groups. Following PSM, there were no significant differences in the en bloc resection rate [100.0%(49/49) vs. 100.0%(49/49)], complete resection rate [93.9%(46/49) vs. 100.0%(49/49)], and complication rate [0(0/49) vs. 4.1%(2/49)] between the two groups. During the follow-up period, no recurrence or distant metastasis was observed in any of the lesions in both groups. Conclusions:The combination of endoscopy and serology diagnostic strategy has the potential to enhance the accuracy of diagnosing G1 and G2 stage G-NENs and their background mucosa. Endoscopic resection surgery (EMR, ESD) is a proven and safe treatment approach for G1 and G2 stage G-NENs.

Objectives:To develop and validate predictive models for esophageal squamous cell carcinoma (ESCC) using circulating cell-free DNA (cfDNA) terminal motif analysis. The goal was to improve the non-invasive detection of early-stage ESCC and its precancerous lesions.Methods:Between August 2021 and November 2022, we prospectively collected plasma samples from 448 individuals at the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences for cfDNA extraction, library construction, and sequencing. We analyzed 201 cases of ESCC, 46 high-grade intraepithelial neoplasia (HGIN), 46 low-grade intraepithelial neoplasia (LGIN), 176 benign esophageal lesions, and 29 healthy controls. Participants, including ESCC patients and control subjects, were randomly assigned to a training set ( n=284) and a validation set ( n=122). The training cohort underwent z-score normalization of cfDNA terminal motif matrices and a selection of distinctive features differentiated ESCC cases from controls. The random forest classifier, Motif-1 (M1), was then developed through principal component analysis, ten-fold cross-validation, and recursive feature elimination. M1's efficacy was then validated in the validation and precancerous lesion sets. Subsequently, individuals with precancerous lesions were included in the dataset and participants were randomly allocated to newly formed training ( n=243), validation ( n=105), and test ( n=150) cohorts. Using the same procedure as M1, we trained the Motif-2 (M2) random forest model with the training cohort. The M2 model's accuracy was then confirmed in the validation cohort to establish the optimal threshold and further tested by performing validation in the test cohort. Results:We developed two cfDNA terminal motif-based predictive models for ESCC and associated precancerous conditions. The first model, M1, achieved a sensitivity of 90.0%, a specificity of 77.4%, and an area under the curve (AUC) of 0.884 in the validation cohort. For LGIN, HGIN, and T1aN0 stage ESCC, M1's sensitivities were 76.1%, 80.4%, and 91.2% respectively. Notably, the sensitivity for jointly predicting HGIN and T1aN0 ESCC reached 85.0%. Both the predictive accuracy and sensitivity increased in line with the cancer's progression ( P＜0.001). The second model, M2, exhibited a sensitivity of 87.5%, a specificity of 77.4%, and an AUC of 0.857 in the test cohort. M2's sensitivities for detecting precancerous lesions and ESCC were 80.0% and 89.7%, respectively, and it showed a combined sensitivity of 89.4% for HGIN and T1aN0 stage ESCC. Conclusions:Two predictive models based on cfDNA terminal motif analysis for ESCC and its precancerous lesions are developed. They both show high sensitivity and specificity in identifying ESCC and its precancerous stages, indicating its potential for early ESCC detection.

Objective:To investigate the endoscopic combined serological diagnosis strategy for G1 and G2 gastric neuroendocrine neoplasms (G-NENs), and to evaluate the safety, short-term, and long-term efficacy of two endoscopic treatment procedures: endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD).Methods:This study retrospectively analyzed the clinical data of 100 consecutive patients with G-NENs who were hospitalized at the Cancer Hospital of the Chinese Academy of Medical Sciences from January 2011 to October 2023. These patients underwent endoscopic treatment, and propensity score matching (PSM) was used to compare clinicopathological characteristics, as well as short-term and long-term efficacy of lesions in the EMR group and ESD group before and after treatment.Results:Among the 100 patients with G-NENs, the median age was 54 years old. Before surgery, 29 cases underwent endoscopic combined serological examination, and 24 of them (82.2%) had abnormally elevated plasma chromogranin A. The combined diagnostic strategy for autoimmune atrophic gastritis (AIG) achieved a diagnostic accuracy of 100%(22/22). A total of 235 G-NEN lesions were included, with 84 in the ESD group and 151 in the EMR group. The median size of the lesions in the ESD group (5.0 mm) was significantly larger than that in the EMR group (2.0 mm, P＜0.001). Additionally, the ESD group had significantly more lesions with pathological grade G2[23.8%(20/84) vs. 1.3%(2/151), P＜0.001], infiltration depth reaching the submucosal layer [78.6%(66/84) vs. 51.0%(77/151), P＜0.001], and more T2 stage compared to the EMR group[15.5%(13/84) vs. 0.7%(1/151), P＜0.001]. After PSM, 49 pairs of lesions were successfully matched between the two groups. Following PSM, there were no significant differences in the en bloc resection rate [100.0%(49/49) vs. 100.0%(49/49)], complete resection rate [93.9%(46/49) vs. 100.0%(49/49)], and complication rate [0(0/49) vs. 4.1%(2/49)] between the two groups. During the follow-up period, no recurrence or distant metastasis was observed in any of the lesions in both groups. Conclusions:The combination of endoscopy and serology diagnostic strategy has the potential to enhance the accuracy of diagnosing G1 and G2 stage G-NENs and their background mucosa. Endoscopic resection surgery (EMR, ESD) is a proven and safe treatment approach for G1 and G2 stage G-NENs.

Objectives:To develop and validate predictive models for esophageal squamous cell carcinoma (ESCC) using circulating cell-free DNA (cfDNA) terminal motif analysis. The goal was to improve the non-invasive detection of early-stage ESCC and its precancerous lesions.Methods:Between August 2021 and November 2022, we prospectively collected plasma samples from 448 individuals at the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences for cfDNA extraction, library construction, and sequencing. We analyzed 201 cases of ESCC, 46 high-grade intraepithelial neoplasia (HGIN), 46 low-grade intraepithelial neoplasia (LGIN), 176 benign esophageal lesions, and 29 healthy controls. Participants, including ESCC patients and control subjects, were randomly assigned to a training set ( n=284) and a validation set ( n=122). The training cohort underwent z-score normalization of cfDNA terminal motif matrices and a selection of distinctive features differentiated ESCC cases from controls. The random forest classifier, Motif-1 (M1), was then developed through principal component analysis, ten-fold cross-validation, and recursive feature elimination. M1's efficacy was then validated in the validation and precancerous lesion sets. Subsequently, individuals with precancerous lesions were included in the dataset and participants were randomly allocated to newly formed training ( n=243), validation ( n=105), and test ( n=150) cohorts. Using the same procedure as M1, we trained the Motif-2 (M2) random forest model with the training cohort. The M2 model's accuracy was then confirmed in the validation cohort to establish the optimal threshold and further tested by performing validation in the test cohort. Results:We developed two cfDNA terminal motif-based predictive models for ESCC and associated precancerous conditions. The first model, M1, achieved a sensitivity of 90.0%, a specificity of 77.4%, and an area under the curve (AUC) of 0.884 in the validation cohort. For LGIN, HGIN, and T1aN0 stage ESCC, M1's sensitivities were 76.1%, 80.4%, and 91.2% respectively. Notably, the sensitivity for jointly predicting HGIN and T1aN0 ESCC reached 85.0%. Both the predictive accuracy and sensitivity increased in line with the cancer's progression ( P＜0.001). The second model, M2, exhibited a sensitivity of 87.5%, a specificity of 77.4%, and an AUC of 0.857 in the test cohort. M2's sensitivities for detecting precancerous lesions and ESCC were 80.0% and 89.7%, respectively, and it showed a combined sensitivity of 89.4% for HGIN and T1aN0 stage ESCC. Conclusions:Two predictive models based on cfDNA terminal motif analysis for ESCC and its precancerous lesions are developed. They both show high sensitivity and specificity in identifying ESCC and its precancerous stages, indicating its potential for early ESCC detection.