With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To investigate lymph node metastasis(LNM)in the prostatic anterior fat pad(PAFP)of PCa patients after robot-assisted radical prostatectomy(RARP),and analyze the clinicopathological features and prognosis of LNM in the PAFP.Methods:We retrospectively analyzed the clinicopathological data on 1 003 cases of PCa treated by RARP in the Department of Urolo-gy of PLA General Hospital from January 2017 to December 2022.All the patients underwent routine removal of the PAFP during RARP and pathological examination,with the results of all the specimens examined and reported by pathologists.Based on the pres-ence and locations of LNM,we grouped the patients for statistical analysis,compared the clinicopathological features between different groups using the Student's t,Mann-Whitney U and Chi-square tests,and conducted survival analyses using the Kaplan-Meier and Log-rank methods and survival curves generated by Rstudio.Results:Lymph nodes were detected in 77(7.7％)of the 1 003 PAFP samples,and LNM in 11(14.3％)of the 77 cases,with a positive rate of 1.1％(11/1 003).Of the 11 positive cases,9 were found in the upgraded pathological N stage,and the other 2 complicated by pelvic LNM.The patients with postoperative pathological stage≥T3 constituted a significantly higher proportion in the PAFP LNM than in the non-PAFP LNM group(81.8％[9/11]vs 36.2％[359/992],P=0.005),and so did the cases with Gleason score ≥8(87.5％[7/8]vs 35.5％[279/786],P=0.009).No statisti-cally significant differences were observed in the clinicopathological features and biochemical recurrence-free survival between the pa-tients with PAFP LNM only and those with pelvic LNM only.Conclusion:The PAFP is a potential route to LNM,and patients with LNM in the PAFP are characterized by poor pathological features.There is no statistically significant difference in biochemical recur-rence-free survival between the patients with PAFP LNM only and those with pelvic LNM only.Routine removal of the PAFP and inde-pendent pathological examination of the specimen during RARP is of great clinical significance.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

OBJECTIVES: This study aimed to evaluate the repeatability and reliability of a self-developed domestic wireless surface electromyography (sEMG) system (Oralmetry) in assessing the activity of the temporalis and masseter muscles to provide theoretical support for its clinical application. METHODS: Twenty-two volunteers were recruited. Through multiple repeated measurements, the sEMG signals of bilateral anterior temporalis and masseter muscles during maximum voluntary clenching were collected using the self-developed sEMG device, Oralmetry, and two commercial sEMG devices (Zebris and Teethan), filtered, screened, and standardized. Seven sEMG indicators for assessing masticatory muscle function were calculated. The intraclass correlation coefficient (ICC) was used to evaluate the repeatability of the measurements from the three sEMG devices, and statistical analysis was conducted to compare the consistency of the seven sEMG indicators obtained from the devices. RESULTS: Among the 22 participants, the ICC values of the repeated measurements from the three sEMG devices ranged from 0.88 to 0.99. The measurements of three sEMG indicators (antero-posterior coeffificient, percentage overlapping coeffificient_MM, and percentage overlapping coeffificient_TA) obtained by Zebris were significantly different from those obtained by Oralmetry and Teethan (P<0.05). No significant differences in the measurements of the seven sEMG indicators were found between Oralmetry and Teethan. CONCLUSIONS Oralmetry and the two commercial sEMG devices demonstrated good repeatability in capturing sEMG indicators for evaluating masticatory muscle function. In particular, Oralmetry showed the highest ICC values. All three devices also exhibited good consistency in measuring sEMG indicators, and a high agreement was observed between the two wireless sEMG devices (Oralmetry and Teethan). These findings provide theoretical support for the clinical application of Oralmetry.
Humans ; Electromyography/methods* ; Masseter Muscle/physiology* ; Masticatory Muscles/physiology* ; Wireless Technology ; Reproducibility of Results ; Temporal Muscle/physiology* ; Male ; Adult ; Female ; Young Adult

Objective:To evaluate the accuracy of a self-developed extraoral scanning system based on photogrammetry technology, and to provide evidence for advancing the development and clinical application evaluation of domestically produced scanning devices.Methods:This research group developed a photogrammetry-based implant extraoral scanning system with customized scan bodies. Two distinct edentulous implant resin models were designed and three-dimensional (3D)-printed by Center of Digital Dentistry, Peking University School and Hospital of Stomatology, containing 6 (Model 1) and 8 (Model 2) abutment analogs respectively. Reference data acquisition was performed using a high-precision denture 3D scanner with scan caps mounted on the analogs. Specialized scan bodies were then mounted on the analogs for 3D positional data acquisition using both the self-developed system (experimental group) and the clinically established system (control group). Each system conducted 10 repeated scans per model. Trueness was assessed through root mean square error (RMSE), linear deviation (LD), and angular deviation (AD) relative to reference data, while precision was determined through intra-group RMSE analysis. Systematic comparisons included inter-group performance on identical models and intra-group variability across different models.Results:For Model 1, the experimental group showed statistically significant advantages over controls in intra-group RMSE [(3.10±0.71) μm vs (4.61±1.51) μm, P<0.001], reference-data RMSE [(21.48±0.60) μm vs (32.50±0.63) μm, P<0.001], linear deviation [23.64 (32.35) μm vs 44.86 (55.73) μm, P<0.001], and angular deviation [0.29° (0.29°) vs 0.23° (0.33°), P<0.001]. In Model 2, significant improvements were observed in intra-group RMSE [(4.47±1.58) μm vs (6.21±2.07) μm, P<0.001], reference-data RMSE [(38.84±0.86) μm vs (43.69±1.34) μm, P<0.001], and linear deviation [37.95 (50.68) μm vs 49.71 (58.89) μm, P<0.001]. Both groups exhibited model-dependent variability, with RMSE of precision and trueness of both groups, linear deviation of experimental group, angular deviation of control group showing statistically significant increases (all P<0.001) corresponding to abutment analog quantity. Conclusions:The self-developed scanning system demonstrates superior accuracy in 3D positional acquisition of abutment analogs compared to the contral group system, with implant number identified as a critical determinant of extraoral scanning accuracy.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To evaluate the accuracy of a self-developed extraoral scanning system based on photogrammetry technology, and to provide evidence for advancing the development and clinical application evaluation of domestically produced scanning devices.Methods:This research group developed a photogrammetry-based implant extraoral scanning system with customized scan bodies. Two distinct edentulous implant resin models were designed and three-dimensional (3D)-printed by Center of Digital Dentistry, Peking University School and Hospital of Stomatology, containing 6 (Model 1) and 8 (Model 2) abutment analogs respectively. Reference data acquisition was performed using a high-precision denture 3D scanner with scan caps mounted on the analogs. Specialized scan bodies were then mounted on the analogs for 3D positional data acquisition using both the self-developed system (experimental group) and the clinically established system (control group). Each system conducted 10 repeated scans per model. Trueness was assessed through root mean square error (RMSE), linear deviation (LD), and angular deviation (AD) relative to reference data, while precision was determined through intra-group RMSE analysis. Systematic comparisons included inter-group performance on identical models and intra-group variability across different models.Results:For Model 1, the experimental group showed statistically significant advantages over controls in intra-group RMSE [(3.10±0.71) μm vs (4.61±1.51) μm, P<0.001], reference-data RMSE [(21.48±0.60) μm vs (32.50±0.63) μm, P<0.001], linear deviation [23.64 (32.35) μm vs 44.86 (55.73) μm, P<0.001], and angular deviation [0.29° (0.29°) vs 0.23° (0.33°), P<0.001]. In Model 2, significant improvements were observed in intra-group RMSE [(4.47±1.58) μm vs (6.21±2.07) μm, P<0.001], reference-data RMSE [(38.84±0.86) μm vs (43.69±1.34) μm, P<0.001], and linear deviation [37.95 (50.68) μm vs 49.71 (58.89) μm, P<0.001]. Both groups exhibited model-dependent variability, with RMSE of precision and trueness of both groups, linear deviation of experimental group, angular deviation of control group showing statistically significant increases (all P<0.001) corresponding to abutment analog quantity. Conclusions:The self-developed scanning system demonstrates superior accuracy in 3D positional acquisition of abutment analogs compared to the contral group system, with implant number identified as a critical determinant of extraoral scanning accuracy.

Objective:To develop an original-mirror alignment associated deep learning algorithm for intelligent registration of three-dimensional maxillofacial point cloud data,by utilizing a dynamic graph-based registration network model(maxillofacial dynamic graph registration network,MDGR-Net),and to provide a valuable reference for digital design and analysis in clinical dental applications.Methods:Four hundred clinical patients without significant deformities were recruited from Peking University School of Stomatology from October 2018 to October 2022.Through data augmentation,a total of 2 000 three-dimensional maxillofacial datasets were generated for training and testing the MDGR-Net algorithm.These were divided into a training set(1 400 cases),a validation set(200 cases),and an internal test set(200 cases).The MDGR-Net model constructed feature vectors for key points in both original and mirror point clouds(X,Y),established correspondences between key points in the X and Y point clouds based on these feature vectors,and calculated rotation and translation matrices using singular value decomposi-tion(SVD).Utilizing the MDGR-Net model,intelligent registration of the original and mirror point clouds were achieved,resulting in a combined point cloud.The principal component analysis(PCA)algorithm was applied to this combined point cloud to obtain the symmetry reference plane associated with the MDGR-Net methodology.Model evaluation for the translation and rotation matrices on the test set was performed using the coefficient of determination(R2).Angle error evaluations for the three-dimensional maxillofacial symmetry reference planes were constructed using the MDGR-Net-associated method and the"ground truth"iterative closest point(ICP)-associated method were conducted on 200 cases in the inter-nal test set and 40 cases in an external test set.Results:Based on testing with the three-dimensional maxillofacial data from the 200-case internal test set,the MDGR-Net model achieved an R2 value of 0.91 for the rotation matrix and 0.98 for the translation matrix.The average angle error on the internal and external test sets were 0.84°±0.55° and 0.58°±0.43°,respectively.The construction of the three-dimensional maxillofacial symmetry reference plane for 40 clinical cases took only 3 seconds,with the model performing optimally in the patients with skeletal Class Ⅲ malocclusion,high angle cases,and Angle Class Ⅲ orthodontic patients.Conclusion:This study proposed the MDGR-Net association method based on intelligent point cloud registration as a novel solution for constructing three-dimensional maxillo-facial symmetry reference planes in clinical dental applications,which can significantly enhance diagnos-tic and therapeutic efficiency and outcomes,while reduce expert dependence.