ObjectiveThis paper aims to investigate the traditional Chinese medicine syndrome types in patients with chronic hepatitis B （CHB） complicated by metabolic dysfunction-associated fatty liver disease （MAFLD） and explore the correlations between these syndrome types and clinical indicators， as well as ocular manifestation characteristics， thereby providing a reference for syndrome differentiation and treatment strategies in traditional Chinese medicine. MethodsGeneral data， information from the four diagnostic methods of traditional Chinese medicine， clinical indicators， and ocular manifestation data were collected from 506 patients with CHB complicated by MAFLD enrolled at the Public Health Clinical Center of Chengdu between June 2024 and December 2024. Cluster analysis， principal component analysis， and complex network models were employed to identify the distribution patterns of traditional Chinese medicine syndromes. Correlations between different syndrome types and clinical indicators， as well as ocular manifestation characteristics， were further analyzed. ResultsThe predominant syndromes identified in patients with CHB complicated by MAFLD were dampness and heat accumulation （51.58%）， liver depression with spleen deficiency （31.62%）， blood stasis obstructing collaterals （8.89%）， and Qi-Yin deficiency （7.91%）. No statistically significant differences were found among the four syndrome types in routine blood tests and liver function indicators. However， patients with the dampness and heat accumulation type exhibited significantly higher levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， liver stiffness measurement （LSM）， controlled attenuation parameter （CAP）， and alpha-fetoprotein （AFP）， along with lower levels of high-density lipoprotein cholesterol （HDL-C）， compared with those with other syndrome types. Regarding ocular manifestations， the incidence of moon halo signs was significantly higher in patients with the blood stasis obstructing collaterals type than in those with other syndrome types. Additionally， the incidence in scleral zone 3 （corresponding to the large intestine） was higher in patients with the damp and heat accumulation type. ConclusionDampness and heat accumulation is the core syndrome type in patients with CHB complicated by MAFLD， commonly accompanied by spleen deficiency， liver depression， blood stasis， and Yin deficiency. A complex syndrome pattern characterized by a predominance of dampness and heat， along with a mixture of deficiency and excess， is formed. Different traditional Chinese medicine syndrome types are associated with distinct clinical indicators and ocular manifestation characteristics. Among them， patients with the dampness and heat accumulation type exhibit more pronounced metabolic disturbances and liver injury， whereas those with the blood stasis type show a higher incidence of moon halo signs. Abnormalities in scleral zone 3 are also more prevalent in patients with dampness and heat type.

ObjectiveThis paper aims to investigate the distribution patterns of traditional Chinese medicine syndromes in patients with chronic hepatitis B （CHB） comorbid with metabolically associated fatty liver disease （MAFLD） and analyze their correlation with clinical characteristics and the progression of liver fibrosis. MethodsA cross-sectional study method was employed， and 506 patients with CHB comorbid with MAFLD who attended the Hepatology Outpatient Department of Public Health Clinical Center of Chengdu from June 2024 to December 2024 were enrolled. General information， traditional Chinese medicine syndromes information， laboratory indicators， and imaging examination results were collected using case report forms （CRF）. Tongue images of patients were acquired using a tongue diagnosis instrument， and tongue feature parameters were extracted using computer image processing technology. Frequency analysis， factor analysis， and cluster analysis， and other methods were used to explore syndrome categories and distribution patterns. Non-parametric tests were used to compare the differences in clinical characteristics among different syndromes. Univariate and multivariate logistic regression analyses were performed to investigate the correlation between traditional Chinese medicine syndromes and the progression of liver fibrosis. ResultsThe main traditional Chinese medicine syndromes in patients with CHB comorbid with MAFLD were mainly dominated by damp-heat accumulation syndrome， liver stagnation and spleen deficiency syndrome， and phlegm-blood stasis syndrome， with damp-heat accumulation syndrome accounting for the highest proportion （41.89%）. Compared with those without damp-heat accumulation syndrome， patients with damp-heat accumulation syndrome had significantly lower tongue proper H value， tongue coating H value， and tongue coating a^* value （P<0.05）， significantly higher tongue coating b^* value （P<0.05）， significantly increased levels of white blood cell （WBC）， red blood cell （RBC）， hemoglobin （HGB）， and glucose （GLU）， increased CAP values （P<0.05）， a higher proportion of males （P<0.05）， and a younger age （P<0.05）. Univariate and multivariate logistic regression analyses show that age， hepatitis B surface antigen （HBsAg）， diabetes， and damp-heat accumulation syndrome are independent risk factors for liver fibrosis （P<0.05）， and that damp-heat accumulation syndrome is predominantly distributed in liver fibrosis stage F0-F1. ConclusionDamp-heat accumulation syndrome is a typical syndrome in patients with CHB comorbid with MAFLD， which is significantly associated with enhanced inflammatory response， metabolic disorders， and early liver fibrosis， and is a key link in disease progression. Clinical attention and early intervention are needed.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Artificial intelligence(AI)has emerged as a cutting-edge technology leading the future and is a key engine for China's development.In the innovation and research of medical devices,AI has provided critical support in the areas of intelligent diagnostic assistance,intelligent therapeutic assis-tance,intelligent monitoring,life support,et al.Ma-chine learning-enabled device software functions(ML-DSFs)have become an essential component of many medical devices.Recently,the United States Food and Drug Administration(FDA)released a draft guidance titled"Marketing Submission Rec-ommendations for a Predetermined Change Con-trol Plan for Artificial Intelligence/Machine Learn-ing(AI/ML)-Enabled Device Software Functions(Draft)."that aimed to provide a forward-looking approach to foster the development of ML medical devices.By supporting iterative updates through modifications,this approach ensures the continu-ous safety and effectiveness of the devices.This guidance represents the latest in regulatory direc-tion and is especially beneficial for enhancing the quality and efficiency of clinical trials for AI prod-ucts.Therefore,we plan to provide a detailed intro-duction and interpretation of the guidance,with the aim of learning from international advanced regulatory concepts and experiences to promote the development of ML-DSFs with more profound international influence.

Objective:To investigate the establishment, structural, and bonding interface characteristics of an artificial caries-affected dentin model with demineralization and discoloration as a basis of research on caries-affected dentin bonding repair.Methods:One hundred intact molars without caries were collected (acquired from Department of Oral and Maxillofacial Surgery, School & Hospital of Stomatology, Wuhan University from March to May 2023) and prepared as 5 mm thick dentin specimens. Then, they were screened and divided into 3 parts. One part of dentin specimens was subjected to bacterial biofilms to prepare artificial carious dentin (ACD). They were further ground by 600-grit SiC paper for 0, 12, 24, 36, and 48 s, respectively to obtain 5 groups with different layers of ACD: ACD-0, 12, 24, 36, and 48 s. Sound dentin was used as the control group. To determine the preparation parameter for artificial caries-affected dentin (ACAD), the first part of specimens was used for bacterial visualization observation ( n=3) and demineralization analysis experiments (micro-CT, Raman spectroscopy, and surface micro-hardness analyses, n=3). Another part of dentin specimens was allocated to 3 groups: control group (sound dentin), artificial caries-infected dentin group (ACD-0 s) and ACAD group (prepared according to the parameter determined by the experiments above). They were used for color tests ( n=10), Raman spectroscopy analysis ( n=6) and scanning electron microscope (SEM) observation ( n=1), thus comparing color, chemical composition and structure, and micro-morphology of 3 groups. The rest of dentin specimens were divided into 2 groups: sound dentin and ACAD ( n=6), which were bonded to composite resin with Single Bond Universal in a self-etch mode. Then, the bonding interface was measured using an electron probe micro-analyzer (EPMA). Results:The depth of bacterial invasion for ACD-0 s was (142.4±25.8) μm. And obvious bacteria were observed in the dentin tubules for the ACD-12 s group. For micro-CT, the demineralization depth was (283.9±25.6) μm for ACD-0 s and (139.2±27.9) μm for ACD-36 s. The grey values in some regions of the dentin surface for ACD-48 s resembled those of sound dentin. For Raman spectroscopy, the peak ratio of phosphate to amide Ⅰ was significantly lower for ACD-24 s [4.2 (3.2,6.7)] than ACD-36 s [6.7 (6.0,7.7)] ( P<0.05). Additionally, there was no significant difference in surface micro-hardness between ACD-24 s [8.3 (7.0,10.2) HV] and ACD-36 s [10.2 (9.1,11.4) HV] ( P>0.05). The preparation parameter of ACAD was determined to be grinding for 36 s based on the experimental results above. The brightness (L * value) and the yellow-blue chromaticity (b * value) of ACAD (76.69±2.54, 33.15±1.89) were significantly lower than those of the control group (85.23±1.68, 35.87±1.55) ( P<0.05). The red-green chromaticity (a * value) of ACAD (5.38±1.20) was significantly higher than that of the control group (0.71±0.86) ( P<0.05). Moreover, the collagen structure parameter in Raman spectroscopy (the peak ratio of amide Ⅲ to CH 2) of ACAD (1.089 7±0.038 5) was significantly higher than that of the control group (0.985 2±0.020 1) ( P<0.05). As shown in EPMA, the hybrid layer of ACAD [(4.72±1.03) μm] was significantly thicker than that of sound dentin [(3.02±0.66) μm] ( F=21.09, P<0.001) in a self-etch mode. Conclusions:ACAD is established through bacterial biofilm challenges followed by grinding for 36 s. It is partly demineralized and discolored with collagen structure changes, making it suitable for research on caries-affected dentin bonding.

Objective To design a night vision simulation training system to provide pilots with practical training on ground night vision goggles.Methods The system had its hardware composed of a control stick,a throttle lever,rudder pedals,a head-up display(HUD),a control box,a computer,a projector and a screen.The HUD and control box were designed using night vision-compatible lighting technology to simulate the ambient light conditions pilots experienced when flying with night vision goggles.The software of the system consisted of five ones developed with C++programming languge for visual scene simulation,instrument simulation,flight performance simulation,integrated management control and cockpit manage-ment.Night vision images and computer-rendered images of typical scenes with varying brightness levels were collected.Objective image evaluation metrics such as contrast and brightness were used as inputs,while subjective evaluation data served as outputs to construct and train a support vector machine(SVM)model.Totally 30 typical night vision training scenarios were selected based on model validation and optimization to evaluate the system's optical fidelity.Results The average fidelity score for the 30 typical night vision training scenarios was 8.05,indicating that the system could realistically simulate terrain and landscapes under various lighting and weather conditions during night flights and static and dynamic targets in the air,on the ground and at sea.Conclusion The system meets the desired requirements and effectively facilitates night vision training for pilots.[Chinese Medical Equipment Journal,2025,46(3):21-26]

Objective:The clinical symptoms of children with global developmental delay (GDD) were analyzed to provide the scientific basis for the intervention of children with GDD.Methods:The results of the neuro-psychobehavioral scale were collected from 32 511 children with GDD from June 2020 to November 2023. Inclusion criteria: Children diagnosed with GDD according to the Diagnostic and Statistical Manual of Mental Disorders-V, ages 0.0 to 4.9 years. Exclusion criteria: children with common hearing impairment and visual impairment. The Chi-square tests were used for statistical analysis.Results:There were more boys than girls with GDD in outpatient clinics (68.2% vs. 31.8%). Among the children, the proportion of developmental delay in 5, 4, 3, and 2 domains was 31.1%, 23.4%, 22.9% and 22.6% respectively. The rate of delay in 2-3 domains was lower in boys (41.9%) than in girls (53.1%). The rate of delay in 4-5 domains was higher in boys (58.1%) than in girls (46.9%) ( χ2=352.11, P<0.001). Overall, outpatient GDD decreased with age. From 1.0-1.9 to 4.0-4.9 years of age, the proportion of children with developmental delay in 5 domains increased with age (18.2%, 36.4%, 43.9%, 52.4%). Among children aged 0.0-0.9 years, the proportion of 2 domains of developmental delay was higher (33.4%).Among children aged 1.0-1.9 years, the proportion of 2-3 domains of developmental delay was higher (30.7%). Among children aged 2.0-, 3.0-, 4.0-4.9 years, the proportion of developmental delay in 5 domains was higher (36.4%, 43.9%, 52.4%). In children with GDD, the fine motor delay occurred most frequently (85.1%), followed by social self-care (83.9%), language (79.0%), adaptation (62.3%), and gross motor (52.8%). The frequency of developmental delays in fine motor, adaptability, language, and social self-care in boys was higher than that in girls ( χ2=161.37, χ2=41.10, χ2=320.90, χ2=238.54, all P<0.001). The age groups with the highest delay incidence of gross motor, fine motor, adaptability, language, and social self-care were: 4.0-4.9 years (70.6%), 3.0-3.9 years (97.4%), 4.0-4.9 years (81.2%), 2.0-2.9 years (90.9%),2.0-2.9 years (95.4%). The proportions of fine motor delay in GDD children aged 0.0-0.9, 3.0-3.9 and 4.0-4.9 years were (74.5%, 97.4%, 96.8%) and the proportions of social self-care delay in GDD children aged 1.0- and 2.0-2.9 years were (92.1%, 95.4%). Peripheral and mild developmental delays were predominant in children with GDD. The proportion of severe language delay (6.4%) was higher than that in other fields. Conclusions:The proportion of GDD children with developmental delay in 4-5 domains was 54.5%. The most frequent domain of delay was fine motor. The frequencies of developmental delays in fine motor skills, adaptability, language, and social self-care in boys were higher than in girls. Most of the developmental delays in GDD children were marginal and mild. The rate of severe developmental delay in language was higher than in other domains.

The 97th Annual Meeting of the Japanese Gastric Cancer Association was held from March 12 to March 14,2025,in Nagoya,Japan.The conference was chaired by Professor Kazuhiro Uyama from Fujita Medical University and attracted nearly 2 000 scholars from around the world,including Japan,China,the republic of Korea,the United States,and Europe.With the theme of"Digital Innovation in Gastric Tumors,"the conference focused on the application of artificial intelligence,robotic surgery,and other innovations in the treatment of gastric cancer.It explored how high-precision and highly reproducible robotic surgical techniques are transforming traditional approaches to gastric cancer surgery,along with topics such as digital innovation,future medical policies,and strategies that herald a new era in healthcare.The meeting featured one main venue and 60 sub-venues with different themes,ultimately accepting 1 003 submissions.A total of 158 oral presentations covering 80 topics and 203 poster presentations were delivered.Among them,approximately 145 lectures were related to robotic surgery for gastric cancer,and when including poster presentations,nearly 255 topics were associated with gastric cancer robotic surgery.Additionally,the 7th edition of the Japanese Gastric Cancer Treatment Guidelines was released during the meeting.Our team had the honor of participating in this prestigious event.Drawing from our experience at both this conference and the 17th Annual Meeting of the Japanese Society for Robotic Surgery held in Utsunomiya,Japan,from March 7 to March 8,2025,we provide a detailed report on the latest advancements in robotic surgery for gastric cancer,hoping to offer valuable insights and references for fellow surgeons both in China and abroad.