ObjectiveThis paper aims to observe the syndrome improvement and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome）. MethodsThrough a multi-center randomized controlled methodology design，confirmed influenza cases were collected from October 2022 to April 2023 in the pediatrics department of eight hospitals，such as Dongfang Hospital of Beijing University of Chinese Medicine. A total of 180 children with influenza and heat accumulation in the lung and stomach syndrome conforming to the standard were recruited through the clinic. The sick children meeting the inclusion criteria were randomly divided into groups by a block-randomized method. The children in the experimental group were treated with Qingxuan Daozhi formula for five days，and those in the control group were treated with Oseltamivir Phosphate Granules for five days. The primary efficacy indicator was the negative conversion rate of influenza antigen detection. Secondary efficacy indicators were the Canadian acute respiratory illness and flu scale （CARIFS） and the incidence of complications，severe cases， and critical cases. Follow-up observation was conducted on the day of enrollment，48 hours after medication，72 hours after medication， and （6+1） d after medication. ResultsOne hundred and eighty participants were randomly assigned to the experimental group （90 cases） or the control group （90 cases）. All participants were followed up during the study. Comparison of influenza antigen detection results in the primary efficacy indicators showed that the average time of negative influenza antigen conversion in the experimental group was （5.29±1.25） d，and that in the control group was （5.40±1.68） d，without a statistically significant difference. After five days of intervention，52 cases in the experimental group and 51 cases in the control group converted to negative，without a statistically significant difference. CARIFS score results in the secondary efficacy indicators showed that during 72 hours after intervention，there were statistically significant differences between the experimental group and the control group in three dimensions， including headache，muscle soreness， and the need for extra care （P<0.05）. On the （6+1） days after the intervention，the differences in both the experimental group and the control group were statistically significant in 10 dimensions， including sore throat，bad sleep，uncomfortable feeling，poor spirit and fatigue，crying more than usual，the need for extra care，symptom，function，influence on parents，and total score （P<0.05）. The comparison results within the group in the dimensional scores of symptom， function， and influence on parents，as well as the CARIFS total score showed that with the delay of follow-up time，scores of both groups decreased significantly，with a statistically significant difference （P<0.01）. Inter-group comparison results showed that the mean score of the experimental group was higher than that of the control group at the time of enrollment. With the progress of intervention，the score of the experimental group was significantly decreased compared with that of the control group. At the end of follow-up，the mean score of the experimental group was lower than that of the control group，with no statistically significant difference. In terms of the incidence of complications，severe cases， and critical cases， there were no complications，severe cases， and critical cases in the two groups，without a statistically significant difference. ConclusionThe symptom improvement effect and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome） are not inferior to Oseltamivir Phosphate granules， and children's acceptance is better. It can be more widely used in clinical treatment of influenza in children （heat accumulation in the lung and stomach syndrome）.

Metabolic dysfunction-associated fatty liver disease （MAFLD） has become one of the most prevalent chronic liver diseases worldwide， posing a serious challenge to public health. In this context， the integration of artificial intelligence （AI）， especially intelligent diagnosis and treatment and digital health interventions based on machine learning， can break through the limitations of traditional methods， realize efficient screening of multi-dimensional data such as key genes， biomarkers， and biochemical metabolites， and achieve revolutionary breakthroughs in risk prediction， subtype identification， and therapeutic effect assessment for MAFLD. This article systematically reviews the ground-breaking application of machine learning models in driving the innovation of clinical diagnosis and precise risk prediction of MAFLD， conducts a comprehensive comparative analysis of digital health practice cases of MAFLD in China and globally， and deeply analyzes their advantages and limitations in terms of research subjects， interventions， and management team. Studies have shown that the deep integration of digital health and long-term management of MAFLD is becoming the key engine driving the transformation of disease management modes towards an intelligent， individualized， and precise era， but there are various ethical and technical issues that need to be addressed urgently.

BACKGROUND:The biomechanical analysis of scoliosis cases is limited,with only independent analysis focusing on the spine or lower limbs,thus lacking a comprehensive evaluation of the multidimensional body.As a result,it becomes challenging to reflect the movement relationship between the trunk and lower limbs during daily activities,which hinders comprehensive clinical treatment guidance. OBJECTIVE:To explore the relationship between different segments of the spine and the kinematics/kinetics of the lower limbs during gait activities by measuring spinal kinematics in scoliosis patients,to provide a comprehensive and multi-level assessment of the biomechanical differences between scoliosis patients and the normal population,consequently offering evidence-based guidance for the prevention and treatment of scoliosis. METHODS:A cross-sectional study was conducted from July 2020 to June 2021 at the Rehabilitation Hospital Affiliated to Fujian University of Traditional Chinese Medicine in Fuzhou University City.A total of 28 scoliosis patients and 28 normal individuals in the same age group were included.Three-dimensional motion capture system was used to capture gait kinematic data at a sampling frequency of 100 Hz.Two force plates(AMTI 400600,sampling frequency 1 500 Hz)were embedded in a 10-meter-long 2.4-meter-wide level ground walkway(with an effective data collection length of 4 m)to collect kinetic data.The differences in spatial-temporal parameters,kinematics,and kinetics of gait between the two groups were compared.Immediately after inclusion,all subjects underwent full spinal X-ray measurements to compare the differences between the scoliosis and normal groups. RESULTS AND CONCLUSION:(1)Patients with scoliosis exhibited reduced relative rotational range of motion between the shoulder and trunk,as well as between the thorax and pelvis,compared to the normal group(P<0.05).However,the rotational range of motion in the pelvis was larger in patients with scoliosis compared to the normal group(P<0.05).(2)Patients with scoliosis showed decreased range of motion in the hip and knee joints,as well as reduced peak torque in hip joint flexion and extension,and lower peak values of ground reaction forces in the concave and convex directions,in comparison to the normal group(P<0.05).(3)Patients with scoliosis demonstrated greater asymmetry indices in knee joint range of motion,relative rotational range of motion between the shoulder and trunk,and between the thorax and pelvis,when compared to the normal group(P<0.05).(4)These findings illustrate a rigid movement pattern among the shoulder,thorax,and pelvis in patients with scoliosis during level walking.There is a reduction in range of motion in the hip and knee joints,as well as decreased peak torque values in hip joint flexion and extension,and ground reaction forces in the concave and convex directions.These characteristics can serve as foundational elements for assessing rehabilitation and developing treatment plans.

Meditation aims to guide individuals into a state of deep calm and focused attention, and in recent years, it has shown promising potential in the field of medical treatment. Numerous studies have demonstrated that electroencephalogram (EEG) patterns change during meditation, suggesting the feasibility of using deep learning techniques to monitor meditation states. However, significant inter-subject differences in EEG signals poses challenges to the performance of such monitoring systems. To address this issue, this study proposed a novel model-calibrated multi-source adversarial adaptation network (CMAAN). The model first trained multiple domain-adversarial neural networks in a pairwise manner between various source-domain individuals and the target-domain individual. These networks were then integrated through a calibration process using a small amount of labeled data from the target domain to enhance performance. We evaluated the proposed model on an EEG dataset collected from 18 subjects undergoing methamphetamine rehabilitation. The model achieved a classification accuracy of 73.09%. Additionally, based on the learned model, we analyzed the key EEG frequency bands and brain regions involved in the meditation process. The proposed multi-source domain adaptation framework improves both the performance and robustness of EEG-based meditation monitoring and holds great promise for applications in biomedical informatics and clinical practice.
Humans ; Electroencephalography/methods* ; Meditation ; Calibration ; Neural Networks, Computer ; Brain/physiology* ; Rest/physiology* ; Deep Learning ; Signal Processing, Computer-Assisted

OBJECTIVES: This study aimed to investigate the incidence, imaging characteristics, and clinical manifestations of the eruption failure of deciduous molars using panoramic radiographs to provide a foundation for diagnosis and treatment in this population. METHODS: This study retrospectively reviewed panoramic radiographs of children aged 4-8 years obtained from Stomatology Hospital, Zhejiang University School of Medicine between January 2021 and December 2023. A total of 31 331 subjects were included for the radiographic assessment of the tooth eruption failure of deciduous molars. Incidence, radiographic characteristics, and associated complications were documented. Statistical analysis was performed using SPSS 26.0. RESULTS: The incidence of the eruption failure of deciduous molars among children aged 4-8 years was 0.94% (296/31 331). The rate was 1.55 times higher in females than in males, demonstrating a significant gender difference (P<0.001). Among the affected deciduous molars, mandibular first deciduous molars accounted for 76.4%, followed by the mandibular second deciduous molars (13.8%), and the maxillary deciduous molars collectively comprised 9.8%. The severity of eruption disorders was significantly associated with the mesial and distal tilting of adjacent teeth and elongation of the antagonist (P<0.001). CONCLUSIONS The incidence of the eruption failure of deciduous molars in children aged 4-8 years was 0.94%, with a high prevalence in females and a predilection for the mandible, particularly the mandibular first deciduous molar. For deciduous molars with severe eruption failure, early intervention is crucial to mitigate complications such as malocclusion and space loss.
Humans ; Child ; Child, Preschool ; Tooth, Deciduous/diagnostic imaging* ; Female ; Molar/physiopathology* ; Male ; Retrospective Studies ; Tooth Eruption ; Radiography, Panoramic ; Incidence

With the advancements in artificial intelligence (AI), computational power, and surgical robotics, the analysis of surgical performance at the granular level of individual surgical gestures has become feasible. Surgical gestures, defined as the smallest independent units of inter-action between surgical instruments and tissues, offer a quantifiable framework for surgical skill assessment. Evidence suggests that the selection and execution of surgical gestures are strongly correlated with the expertise of the surgeon and patient outcomes, underscoring their significance in both surgical training and clinical practice. Moreover, the establishment of a standardized classifi-cation system for surgical gestures and the adoption of uniform terminology have the potential to improve communication efficiency during surgical education and training. The authors synthesize existing classification systems for surgical gestures, with a focus on their applications in diverse tasks such as suturing, exposure and dissection. By examining the latest advancements in AI models applied to surgical gesture, as well as the current research landscape of surgical gesture recognition in digestive surgery, the authors explore the potential applications of such technologies in assisting surgeons during operations in the future.

With the rapid development of minimally invasive techniques in surgery, arti-ficial intelligence (AI), particularly deep learning, is playing an increasingly important role in mini-mally invasive surgery. By automated analysis of surgical videos, AI can efficiently perform key tasks such as instrument recognition, surgical phase identification, action analysis, anatomical structure recognition, intraoperative diagnosis, adverse event monitoring and smart desmoking. These appli-cations provide essential support for real-time monitoring, surgical navigation and skill assessment during surgery. The authors summarize the current research progress of AI in minimally invasive surgery, including its applications in the fields of hepatobiliary and pancreatic surgery, as well as gastrointestinal surgery. It also explores the potential of AI in enhancing surgical safety, efficiency and skill assessment. By synthesizing the latest research achievements of AI technology in the field of surgery, as well as analyzing its technical challenges and risks, it aims to provide guidance for future innovations and clinical applications, promoting the advancement and implementation of AI in minimally invasive surgery.

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

BackgroundAs a high prevalence disorder， schizophrenia has caused significant burden to family and society due to the impairment of occupational and social function. Currently， the dominant vocational training model in China follows a paternalistic， clinician-led decision-making approach. Although it improves patients' social function to some extent， it undermines their autonomy and treatment adherence. Therefore， it is urgently necessary to explore a new intervention method to enhance treatment compliance and social function in patients. ObjectiveTo explore the impact of shared decision-making oriented vocational training on social function in hospitalized schizophrenia patients， so as to provide references for rehabilitation interventions. MethodsA total of 68 patients diagnosed with schizophrenia according to the International Classification of Diseases， tenth edition （ICD-10） criteria were consecutively enrolled from January to June 2024 at The Third People's Hospital of Wenjiang Distric， Chengdu. Participants were randomly allocated into the research group （n=34） and the control group （n=34） using a random number table method. Both groups received routine rehabilitation training， while the research group received shared decision-making oriented vocational training for 12 weeks， 2 times a week for 2 hours each time. Before and at the 4^th and 12^th week of intervention， two groups were evaluated by General Self-Efficacy Scale （GSES）， Stigma Scale for Mental Illness （SSMI）， Scale of Social function of Psychosis Inpatients （SSFPI） and Inpatient Psychiatric Rehabilitation Outcome Scale （IPROS）. ResultsA total of 63 participants completed the study， with 30 cases in the research group and 33 cases in the control group. Repeated measures ANOVA revealed statistically significant time effects and interaction effects in both groups for GSES， SSMI， SSFPI and IPROS scores （F=20.451， 16.022； 26.193， 12.944； 23.957， 5.023； 11.776， 3.985， P<0.05 or 0.01）， while no significant group effects were observed （F=0.188， 0.742， 1.878， 0.474， P>0.05）. At the 12^th week of intervention， there were statistically significant differences in GSES， SSMI， SSFPI and IPROS scores between the two groups. ConclusionShared decision-making oriented vocational training may help to improve social function in patients with schizophrenia. ［Funded by 2023 Chengdu Medical Research Project （number， 2023468）］

Objective To investigate the relationship between triglyceride glucose body mass index(TyG-BMI),high density lipoprotein cholesterol to Apolipoprotein A ratio(HAR),glycemic risk index(GRI)and diabetic retinopathy(DR).Methods A total of 159 patients with type 2 diabetes mellitus(T2DM)complicated with DR(the DR group)were divided into the non-proliferative retinopathy group(NPDR group,66 cases)and the proliferative retinopathy group(PDR group,93 cases)according to DR international clinical grading criteria,and 159 T2DM patients without DR were selected as the control group.Clinical information and baseline laboratory test results were recorded,and TyG-BMI,HAR and GRI were calculated.Multivariate Logistic regression analysis was conducted to analyze the related factors of the incidence of DR,and receiver operating characteristic(ROC)curve was used to analyze the diagnostic value of TyG-BMI,HAR and GRI for DR.Results The duration of T2DM,the proportion of hypertension,diabetic nephropathy and diabetic foot,levels of HbA1c,homeostasis model insulin resistance index(HOMA-IR),total cholesterol(TC),C-reactive protein(CRP),TyG-BMI,HAR and GRI were higher in the DR group than those in the control group(P<0.05).TyG-BMI,HAR and GRI were higher in the PDR group than those in the NPDR group(P<0.05).Multivariate Logistic regression analysis showed that the longer course of T2DM disease[OR(95%CI):2.781(1.398-5.534)],high TyG-BMI[2.036(1.169-3.546)],high HAR[1.890(1.090-3.280)]and high GRI[1.836(1.065-3.167)]were risk factors for DR(P<0.05).ROC curve analysis results showed that,the area under the curve(AUC)of combined TyG-BMI,HAR and GRI diagnosis of DR was higher than that of single diagnosis[0.940(0.908-0.964),0.864(0.821-0.900),0.796(0.747-0.839)and 0.836(0.790-0.875),all P<0.05].Conclusion The increased TyG-BMI,HAR and GRI in T2DM patients is associated with the onset and severity of DR,and which can be used to assess the risk of DR.