Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective:To compare the effects of intraoperative administration or non-administration of tranexamic acid (TXA) on early postoperative inflammatory response and clinical outcomes in elderly male patients with intertrochanteric femur fractures.Methods:A retrospective cohort study was conducted to analyze the clinical data of 92 elderly male patients with intertrochanteric femur fractures admitted to Zhongda Hospital Affiliated to Southeast University from January 2020 to December 2022, aged 62-96 years [(79.9±8.4)years]. According to the modified Evans classification, the fractures were classified as types I-III in 33 patients and types IV-V in 59. All the patients were treated with proximal femoral intramedullary nail fixation. Among them, 46 patients received intraoperative TXA (TXA group), while 46 patients did not (non-TXA group). The operative duration, intraoperative blood loss, length of postoperative hospital stay were compared between the two groups. The serum interleukin-6 (IL-6) levels and visual analogue scale (VAS) scores at 1, 3, 5, and 7 days postoperatively were detected. The complication rate and mortality within 1 year postoperatively were also compared between the two groups.Results:All the patients were followed up for 1-12 months [(10.9±2.8)months]. No significant difference was found in the operative duration between the groups ( P>0.05). The intraoperative blood loss and length of postoperative hospital stay were 150.0(100.0, 200.0)ml and (6.8±1.9)days in the TXA group, less or shorter than those in the non-TXA group [200.0(150.0, 262.5)ml and (7.7±2.0)days] ( P<0.05). At 1, 3, and 5 days postoperatively, the IL-6 levels in the TXA group were 84.5(66.3, 100.1)pg/ml, 48.9(36.8, 61.2)pg/ml, and 27.9(19.4, 37.5)pg/ml, which were all lower than those in the non-TXA group [110.3(83.1, 162.9)pg/ml, 63.7(44.2, 84.2)pg/ml, and 32.7(22.4, 42.9)pg/ml] ( P<0.05). No statistically significant difference in the IL-6 level was observed between the two groups at 7 days postoperatively ( P>0.05). At 1 and 3 days after operation, the VAS scores in the TXA group were (4.3±0.9)points and (2.5±0.9)points, lower than those in the non-TXA group [(6.8±1.2)points and (3.0±1.2)points] ( P<0.05). There were no statistically significant differences in VAS scores between the two groups at 5 and 7 days postoperatively ( P>0.05). The complication rate within one year after operation was 28% (13/46) in the TXA group, significantly lower than 50% (23/46) in the non-TXA group ( P<0.05). No significant difference was observed in the mortality within 1 year postoperatively between the two groups ( P>0.05). Conclusion:Compared with non-administration of TXA, intraoperative administration of TXA can effectively reduce the intraoperative blood loss, shorten the length of postoperative hospital stay, significantly lower early postoperative inflammation levels, reduce early postoperative pain intensity, and decrease the incidence of complications in elderly male patients with intertrochanteric femur fractures, with no significant difference in mortality within 1 year after operation between the two groups.

Severe open tibiofibular fractures account for approximately 28.1% of all open fractures. Among them, Gustilo-Anderson type IIIB/C fractures present significant clinical challenges due to associated bone and soft tissue defects, high infection rates, and risk of amputation. Inadequate preoperative assessment may lead to suboptimal emergency surgical planning or intraoperative complications. Historically, external fixation was often preferred, but this approach has been associated with limitations such as restricted joint mobility, delayed bone union, joint stiffness, and disuse osteoporosis, resulting in poor functional recovery. With advancements of debridement techniques, standardization of antibiotic use, and popularization of early soft tissue coverage, early internal fixation has gained broader acceptance. Nevertheless, controversies persist regarding the choice of fixation method, timing of definitive fixation, use of reamed versus unreamed intramedullary nailing, and necessity of fibular fixation. To standardize the diagnosis and early management of severe open tibiofibular fractures, reduce complication rates, and improve functional recovery, the Society of Microsurgery of the Chinese Medical Association organized a panel of domestic experts to develop the Evidence-based guideline for the diagnosis and early fixation of severe open tibiofibular fractures ( version 2025), using evidence-based methodology. The guidelines provided 12 recommendations covering diagnostic and early fixation strategies of severe open tibiofibular fractures, aiming to provide clinicians with scientifically grounded and standardized guidance.

Objective To investigate the correlation between skeletal muscle mass index(ASMI)and islet β cell reserve function in patients with newly diagnosed type 2 diabetes mellitus(T2DM).Methods A total of 100 patients with newly diagnosed T2DM were included in this study.All the patients were admitted to the Department of Endocrinology in the First People's Hospital of Yinchuan between June 2022 and November 2023.They were divided into two groups according to their skeletal muscle mass index(ASMI):patients with T2DM accompanied by sarcopenia(Sar,n=50)group,and patients with simple T2DM(T2DM,n=50)group.Additionally,a control(NC)group consisting of 50 healthy participants was selected.Fasting C-peptide levels,liver and kidney function,blood lipid profiles,and other indicators were assessed in all the individuals.The correlation between ASMI and other indicators was analyzed,and the influencing factors for ASMI and T2DM combined with sarcopenia were analyzed respectively.Results The levels of HbA1c,FPG,and TG were higher,while FC-P and Scr levels were lower in the T2DM group and Sar group compared with the NC group(P<0.05).FPG was higher,while ASMI,FC-P,BMI were lower in the Sar group than in the T2DM group(P<0.05).Spearman correlation analysis revealed a negative correlation between ASMI and FPG and HbA1c(P<0.05),whereas a positive correlation was observed with BMI,ALT,Scr,SUA and FC-P(P<0.05).Multiple linear regression analysis indicated that BMI,HbA1c and FC-P were influencing factors for ASMI(P<0.05).Furthermore,logistic regression analysis demonstrated that BMI,HbA1c,FC-P were influencing factors for T2DM with sarcopenia(P<0.05).Conclusions The level of ASMI may be related to the reserve function of islet β cells.

Objective:To analyze the learning curve of TiRobot-assisted lumbar pedicle screw fixation (LPSF) by cumulative sum (CUSUM) test method.Methods:The clinical data of 50 patients who underwent TiRobot-assisted LPSF from January 2020 to December 2022 in Beijing Friendship Hospital, Capital Medical University were retrospectively analyzed. CUSUM analysis and learning curve fitting were performed with robot usage time as the main indicator with the time for each step refined (robot registration time, path planning time and guide wire placement time), to select the best learning curve fitting model with the R2 value closest to 1. Using the turning point of the learning curve as the boundary, the learning curve was divided into two stages as learning stage and maturity stage, and then the observation indexes were compared between the two stages. Results:All 50 patients successfully completed the surgery without perioperative complications, with a total of 244 pedicle screws implanted. The total robot usage time and robot registration time showed a gradually decreasing trend with the increase of case number, and the learning curves were successfully fitted and reached their peaks at the seventeenth and thirteenth cases respectively. The entire learning process was divided into learning stage (17 cases) and maturity stage (33 cases) based on the turning point of the learning curve of total robot usage time. The path planning time and guide wire placement time did not show significant changes with the increase in the case number. The total robot usage time, robot registration time and the intraoperative blood loss in the learning stage were significantly higher than those in the maturity stage: (35.35 ± 1.58) min vs. (30.61 ± 0.43) min, (20.83 ± 1.56) min vs. (14.94 ± 0.29) min and 400 (150, 500) ml vs. 200 (110, 300) ml, the guide wire placement time of per screw was significantly lower than that in the maturity stage: 2.00 (1.83, 2.34) min/screw vs. 2.33 (2.13, 2.69) min/screw, and there were statistical differences ( P<0.05 or <0.01). There were no statistical difference in the path planning time, path planning time of per screw, guide wire placement time and the accuracy of screw placement between two stages ( P>0.05). Conclusions:TiRobot-assisted LPSF is a new technology with safety and effectiveness, and it has a relatively short learning curve. To achieve technological maturity, at least 17 surgeries are required with accumulated experience, and the robot registration is the main step of the learning process. After reaching maturity stage, the robot usage time is significantly shortened and intraoperative trauma is significantly reduced while the relatively high screw placement accuracy is ensured.

Objective To quantify the volume and movement of cardiac substructures by using coronary computed tomography angiography(CCTA)to provide guidance for the design of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.Methods Totally 18 female patients who received conventional chest plain scan and CCTA were selected to simulate the design process of radiotherapy plan for left breast cancer patients with internal mammary lymph nodes.Retrospective reconstruction of CCTA data was performed for each patient,with 10 phase images(with an interval of 10％)within a R-R cardiac cycle(10％-100％)to simulate the true range of motion of the heart.The heart,left atrium(LA),left ventricle(LV),right atrium(RA),right ventricle(RV),left anterior descending artery(LAD),left circumflex coronary artery(LCX)and right coronary artery(RCA)were contoured at each phase.The distances from the centroid position to the average position of LAD,LCX and RCA were measured at each phase in the superior-inferior(SI),anterior-posterior(AP)and left-right(LR).The average volume and range of volume changes of LA,LV,RA,RV and heart were analyzed within a cardiac cycle.The expansion margins of planning organs at risk volume(PRV)were calculated.SPSS 19.0 software was used for statistical analysis.Results The following average absolute displacements were found in SI,AP and LR coordinates:(1.8±0.7)mm,(1.2±0.5)mm and(1.5±0.5)mm for LAD,respectively;(2.1±0.7)mm,(1.5±0.6)mm and(1.9±0.7)mm for LCX,respectively;(1.6±0.5)mm,(2.2±0.9)mm and(2.2±0.8)mm for RCA,respectively.The volume changes of LA,LV,RA,RV and heart within a cardiac cycle ranged from 34.3 to 63.9 cm3,122.1 to 154.3 cm3,29.3 to 53.6 cm3,57.2 to 94.3 cm3 and 480.1 to 515.4 cm3,respectively.The theoretical expansion margins of LAD,LCX and RCA in all the three directions were within 2 mm.Conclusion The ranges of movement and volume changes of cardiac substructure are quantitati-vely displayed,and references are provided for the planning of deep inspiratory breath-holding radiation therapy for left breast cancer and the protection of organs at risk.[Chinese Medical Equipment Journal,2025,46(3):54-58]

Objective To propose a ventilator failure probability prediction method based on kernel ridge regression(KRR).Methods Firstly,the failure interval data of ventilators was collected and preprocessed to remove outliers.Secondly,the median rank method was used to estimate the failure probability.Finally,using the time data as the feature variable and the failure probability value as the target variable,a KRR model was established and trained by selecting the optimal kernel function and hyperparameter combination from radial basis kernel function,linear kernel function,polynomial kernel function,and S-type kernel function through grid search and cross-validation methods to predict ventilator failures.To verify the performance of the KRR model in predicting ventilator failure probability,it was compared with Weibull and its extended models.Results KRR achieved a coefficient of determination of 0.993 5,a mean squared error of 5.399 5×10-4,a root mean squared error of 0.023 2 and a mean absolute error of 0.018 3,outperforming Weibull and its extended models in prediction accuracy and error control.Conclusion The failure probability prediction method for ventilators based on KRR demonstrates exceptional performance in prediction accuracy and error control,and thus holds great potential for application.[Chinese Medical Equipment Journal,2025,46(5):73-77]

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 determine the prevalence, risk factors, and longitudinal associations of loneliness during mid- to late pregnancy with anxiety and depressive symptoms in late pregnancy.Methods:In this prospective cohort study, 1 107 pregnant women at 24-28 weeks' gestation were enrolled between June 2021 and December 2022. Psychological status was assessed during mid-pregnancy (24-28 weeks) and late pregnancy (≥32 weeks) using standardized electronic questionnaires, including the Revised University of California Los Angeles Loneliness Scale (UCLA) Loneliness Scale-Short Form (Cronbach's α=0.82), Patient Health Questionnaire-9 ( α=0.86), and Generalized Anxiety Disorder-7 ( α=0.88). Multivariate logistic regression identified independent risk factors for loneliness. Cross-lagged path models analyzed the longitudinal predictions between loneliness and anxiety/depressive symptoms. Results:The prevalence of loneliness decreased significantly from 10.8% (120/1 107) in mid-pregnancy to 4.8% (37/777) in late pregnancy ( χ2=21.81, P<0.001). Multivariate analysis identified independent risk factors for loneliness: age <30 years ( OR=1.70, 95% CI: 1.15-2.50), annual household income <50 000 CNY ( OR=2.53, 95% CI: 1.28-5.02), unemployment during pregnancy ( OR=1.57, 95% CI: 1.03-2.39), history of alcohol consumption ( OR=1.63, 95% CI: 1.03-2.56), and the presence of mid-pregnancy depressive ( OR=2.76, 95% CI: 1.51-5.04) and anxiety symptoms ( OR=1.65, 95% CI: 1.01-2.71) (all P<0.05). Cross-lagged path models indicated bidirectional associations between loneliness and both anxiety ( β=0.32, P<0.01) and depressive symptoms ( β=0.28, P<0.01). However, the predictive effect of loneliness on subsequent depressive and anxiety symptoms ( β=0.28-0.32) was substantially stronger than the reverse prediction (mid-pregnancy anxiety on late-pregnancy loneliness: β=0.12; mid-pregnancy depression on late-pregnancy loneliness: β=0.11). Loneliness demonstrated high temporal stability (autoregressive effects β=0.29-0.32). Conclusion:Loneliness in mid-pregnancy exhibits a symmetric bidirectional association with anxiety and depressive symptoms in late pregnancy, suggesting it may be a core driver in the development of these emotional symptoms. Younger maternal age (<30 years), low household income (<50 000 CNY/year), unemployment during pregnancy, and a history of alcohol consumption were associated with a higher risk of loneliness and should be prioritized for psychological screening and intervention.

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.