Objective: To evaluate the clinical efficacy and stability of a centric relation (CR)-guided approach combined with micro-implant anchorage and long traction hooks for root-controlled retraction of the maxillary anterior teeth in a patient with skeletal maxillary protrusion and dual bite, and to provide a reference for clinical practice. Methods: A case of a 29-year-old female patient with skeletal maxillary protrusion and an asymptomatic discrepancy between the maximum intercuspation position (MIP) and CR (dual bite) was reported. First, the CR was identified and obtained by cone beam computed tomography examination and clinical techniques, then was stabilized by glass ionomer bite registration and myofunctional training. Maintaining the CR, the maxillary micro-implants combined with long traction hooks were used to correct skeletal maxillary protrusion by facilitating maxillary anterior teeth retraction, and finally a new intercuspal occlusion was established to maintain long-term stability. A literature review was conducted to contextualize the treatment rationale and key steps. Results: Post-treatment, a coordinated and stable functional occlusion was established in CR without temporomandibular joint symptoms, and the condylar location was coordinated with the glenoid fossa. Controlled root retraction of the maxillary anterior segment and facial profile improvement were achieved. At 3-year follow-up, both occlusion in the CR and condylar positions remained stable. The literature review indicated that, in patients with CR-MIP discrepancy, prioritizing the identification and stabilization of CR is critical, and micro-implant anchorage with long traction hooks effectively facilitates maxillary anterior teeth retraction and profile improvement. Conclusion For skeletal maxillary protrusion with dual bite, a CR-first strategy combined with micro-implant anchorage and long-hook mechanics for root-controlled anterior retraction can concurrently improve stomatognathic function and facial aesthetics, demonstrating favorable mid- to long-term stability.

Ephedra can improve chronic obstructive pulmonary disease (COPD). Pseudoephedrine (PSE) is a main active ingredients of ephedra. It has anti-inflammatory pharmacological properties. Its effect on COPD and its possible mechanism have not been elucidated. The COPD rat model was constructed by systemic cigarette smoke exposure combined with lipopolysaccharide (LPS) tracheal instillation. BEAS-2B cells were treated using cigarette smoke extract; PSE was administered for treatment. The senescence level of rat lung tissue and bronchial epithelial cells was evaluated through staining, immunofluorescence and western blot.The mitochondrial damage of rats and BEAS-2B cells was detected by transmission electron microscopy, JC-1 probe, MitoSOX Red probe and kits. In addition, the lung function indexes of rats were detected by animal lung function analysis system. Hematoxylin and eosin (HE) staining analyzed the pathological damage. Enzyme-linked immunosorbent assay (ELISA), kit and immunohistochemistry were used to evaluate inflammation and oxidative stress. Western blot detected phosphoinositide 3-kinase/ protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) axis protein. PSE significantly reduced senescent cells, apoptosis rate and P21 level in rat lung tissue and BEAS-2B cells, significantly increased the levels of zonula occludens-1 (ZO-1) and adenosine triphosphate (ATP), restored mitochondrial structure, and visible mitochondrial cristae. It also inhibited reactive oxygen species (ROS) levels and mitochondrial excessive fission. PSE also significantly improved lung function in rats, increased mean alveolar number (MAN), reduced pro-inflammatory factors, and increased superoxide dismutase (SOD) levels. PSE markedly suppressed p-p85, p-AKT and p-mTOR protein expressions. In addition, the PI3K/AKT agonist 740Y-P weakened the effect of PSE on improving COPD. PSE inhibited PI3K/AKT/mTOR axis, improved lung tissue senescence, mitochondrial dysfunction and pathological damage, and reduced airway inflammation and oxidative stress damage, thereby alleviating COPD.

Objective To establish an intelligent ICD coding management system to solve the current difficulties in hos-pital ICD coding management,reduce the error rate of information uploading,and improve the accuracy of coding.Methods An ICD coding management system was constructed,with the national clinical version of ICD coding as the main index system.The mapping relationship between the main index coding and the medical insurance version of ICD coding,as well as the hospital ver-sion of ICD coding,was established to achieve real-time maintenance and adjustment.In accordance with the requirements of na-tional public hospital performance evaluation and hospital level assessment,we will establish the ICD coding"label"function and knowledge base for evaluation indicators,embed them into electronic medical record system(EMR),and implement intelligent prompting functions for clinicians to facilitate systematic statistical analysis of data.Results After the establishment of the sys-tem,the error rate of mapping and uploading information such as disease diagnosis and procedures coding decreased significantly(1.2‰ vs 0.3‰,P＜0.05).The accuracy of the main discharge diagnosis and procedures coding has significantly improved(82％vs 91％,P＜0.05;78％vs 88％,P＜0.05).The satisfaction of clinicians and coders increased significantly(65％vs 82％,P＜0.05;79％vs 88％,P＜0.05).Conclusion This system can reduce the error rate of mapping and uploading infor-mation,improve the accuracy and completeness of coding,enhance the management level of ICD coding,and promote the high-quality development of medical care.

Objective To establish an intelligent ICD coding management system to solve the current difficulties in hos-pital ICD coding management,reduce the error rate of information uploading,and improve the accuracy of coding.Methods An ICD coding management system was constructed,with the national clinical version of ICD coding as the main index system.The mapping relationship between the main index coding and the medical insurance version of ICD coding,as well as the hospital ver-sion of ICD coding,was established to achieve real-time maintenance and adjustment.In accordance with the requirements of na-tional public hospital performance evaluation and hospital level assessment,we will establish the ICD coding"label"function and knowledge base for evaluation indicators,embed them into electronic medical record system(EMR),and implement intelligent prompting functions for clinicians to facilitate systematic statistical analysis of data.Results After the establishment of the sys-tem,the error rate of mapping and uploading information such as disease diagnosis and procedures coding decreased significantly(1.2‰ vs 0.3‰,P＜0.05).The accuracy of the main discharge diagnosis and procedures coding has significantly improved(82％vs 91％,P＜0.05;78％vs 88％,P＜0.05).The satisfaction of clinicians and coders increased significantly(65％vs 82％,P＜0.05;79％vs 88％,P＜0.05).Conclusion This system can reduce the error rate of mapping and uploading infor-mation,improve the accuracy and completeness of coding,enhance the management level of ICD coding,and promote the high-quality development of medical care.

To address the limitations of convolutional neural networks in global context modeling and the complexity of secondary computation in Transformer's self attention mechanism,an improved multi-direction-MambaUNet(MD-MambaUNet)based on MambaUNet is proposed.This network integrates with multi directional selective scanning module to extract spatial features from multiple directions of CT images,significantly improving the global context modeling capability.By introducing partial convolution and constructing a lightweight hybrid convolution module,the model's parameter count is significantly reduced,enabling the processing of large-scale medical image data at lower computational costs while maintaining high-level performance.Experiments are conducted on the LiTS2017 and 3DIRCADB public datasets.Compared with MambaUNet on the LiTS2017 dataset,MD-MambaUNet improves the Dice similarity coefficient for liver and tumor segmentation by 3.32%and 4.77%,reaching 95.36%and 76.93%,and increases intersection over union by 4.18%and 4.92%,reaching 91.43%and 69.74%,respectively.Compared with MambaUNet on the 3DIRCADB dataset,MD-MambaUNet improves the Dice similarity coefficient for liver and tumor segmentation by 2.08%and 2.21%,reaching 93.81%and 64.68%,and increases intersection over union by 0.79%and 3.13%,reaching 87.23%and 57.65%,respectively.Meanwhile,the parameter count is 13.71 M less than MambaUNet,making it possible for the model to be deployed in clinical scenarios.

To address the limitations of convolutional neural networks in global context modeling and the complexity of secondary computation in Transformer's self attention mechanism,an improved multi-direction-MambaUNet(MD-MambaUNet)based on MambaUNet is proposed.This network integrates with multi directional selective scanning module to extract spatial features from multiple directions of CT images,significantly improving the global context modeling capability.By introducing partial convolution and constructing a lightweight hybrid convolution module,the model's parameter count is significantly reduced,enabling the processing of large-scale medical image data at lower computational costs while maintaining high-level performance.Experiments are conducted on the LiTS2017 and 3DIRCADB public datasets.Compared with MambaUNet on the LiTS2017 dataset,MD-MambaUNet improves the Dice similarity coefficient for liver and tumor segmentation by 3.32%and 4.77%,reaching 95.36%and 76.93%,and increases intersection over union by 4.18%and 4.92%,reaching 91.43%and 69.74%,respectively.Compared with MambaUNet on the 3DIRCADB dataset,MD-MambaUNet improves the Dice similarity coefficient for liver and tumor segmentation by 2.08%and 2.21%,reaching 93.81%and 64.68%,and increases intersection over union by 0.79%and 3.13%,reaching 87.23%and 57.65%,respectively.Meanwhile,the parameter count is 13.71 M less than MambaUNet,making it possible for the model to be deployed in clinical scenarios.

The paper discusses the scientific connotation of"heart and brain co-dominating the mind",including the connotation of"heart and brain co-dominating the mind"in traditional Chinese medicine and the physiological and pathological relationship be-tween heart and brain in modern medicine.Based on the understanding of"heart and brain co-dominating the mind",this paper be-lieves that"restlessness of mind"is the core pathogenesis of insomnia,and regulating mind is the key to the acupuncture and moxibus-tion treatment of insomnia.The autonomic nervous system(ANS)is a bridge connecting the heart and brain,and is closely related to the central anatomy,neurotransmitters and physiological rhythms of sleep.The imbalance of ANS is highly consistent with the patho-genesis of"heart and brain restlessness"in traditional Chinese medicine.The Governor Vessel runs through the brain and the heart,and the"Governor Vessel regulating spirit acupuncture"can communicate the heart and brain,regulate ANS function,and thus im-prove sleep quality.

OBJECTIVE To observe the effect of electroacupuncture on insomnia symptoms and blood pressure levels in patients with hypertension and insomnia.METHODS A randomized controlled clinical trial was conducted.A total of 60 patients with hyper-tension and insomnia were enrolled in Jiangsu Province Hospital of Chinese Medicine from December 2021 to December 2022 and ran-domly divided into a treatment group and a control group at a ratio of 1:1,with 30 cases in each group.During the treatment period,2 cases dropped out of the control group and 1 case dropped out of the treatment group.Both groups of patients received sleep and hy-pertension health education and conventional hypertension drug treatment.The treatment group was given electroacupuncture interven-tion,and the control group was given sham electroacupuncture intervention.The treatment course of both groups was 4 weeks.Before and after treatment,the Pittsburgh Sleep Quality Index(PSQI),Insomnia Severity Index(ISI)scale and portable polysomnography(PPSG)were used to evaluate the changes in sleep quality of the two groups of patients;home blood pressure measurement(HBPM)was adopted to evaluate the changes in blood pressure levels of the two groups of patients.Spearman correlation analysis and linear re-gression analysis were used to study the relationship between blood pressure levels and PPSG parameters.RESULTS After treatment,only the sleep onset latency(SOL)and sleep efficiency(SE)of the control group were significantly improved(P<0.05);the PSQI,ISI scores,morning and night systolic blood pressure(SBP),and diastolic blood pressure(DBP)of the treatment group were signifi-cantly reduced(P<0.01),which was better than that of the control group(P<0.05,P<0.01);the sleep parameters of PPSG were significantly improved(P<0.01),which was better than that of the control group(P<0.05,P<0.01).The results of Spearman corre-lation analysis showed that the morning SBP level of patients before treatment was related to the wake time after sleep onset(WASO)and the number of micro-arousals(MAS).After treatment,the decrease in the morning SBP of patients was related to the reduction of MAS and the shortening of SOL.CONCLUSION Electroacupuncture can effectively improve the insomnia symptoms and blood pres-sure levels of patients with hypertension.Its therapeutic mechanism may be related to reducing the number of MAS and improving the degree of sleep fragmentation.

The paper discusses the scientific connotation of"heart and brain co-dominating the mind",including the connotation of"heart and brain co-dominating the mind"in traditional Chinese medicine and the physiological and pathological relationship be-tween heart and brain in modern medicine.Based on the understanding of"heart and brain co-dominating the mind",this paper be-lieves that"restlessness of mind"is the core pathogenesis of insomnia,and regulating mind is the key to the acupuncture and moxibus-tion treatment of insomnia.The autonomic nervous system(ANS)is a bridge connecting the heart and brain,and is closely related to the central anatomy,neurotransmitters and physiological rhythms of sleep.The imbalance of ANS is highly consistent with the patho-genesis of"heart and brain restlessness"in traditional Chinese medicine.The Governor Vessel runs through the brain and the heart,and the"Governor Vessel regulating spirit acupuncture"can communicate the heart and brain,regulate ANS function,and thus im-prove sleep quality.

OBJECTIVE: To construct and validate a predictive model for the therapeutic effect of acupuncture at Tongdu Yangxin prescription (acupoint prescription for promoting the circulation of the governor vessel and nourishing the heart) on insomnia, so as to develop an open-access interactive artificial intelligence (AI)-assisted decision-making platform. METHODS: Clinical data of 139 insomnia patients treated with Tongdu Yangxin acupuncture therapy were included. All the patients had received acupuncture at Baihui (GV20), Yintang (GV24⁺), bilateral Shenmen (HT7), and bilateral Sanyinjiao (SP6); and electric stimulation was attached to Baihui (GV20) and Yintang (GV24⁺), using a continuous wave and a frequency of 2 Hz. The treatment was delivered once every other day, 3 treatments a week, and for 2 consecutive weeks. Patients with Pittsburgh sleep quality index (PSQI) score reduction rate <50% were classified as the "no response group", and those with ≥50% were as the "response group". Outliers were addressed using the 1.5×IQR rule, and missing values were imputed via predictive mean matching. Key features were selected by intersecting the feature importance results from eXtreme Gradient Boosting (XGBoost) and random forest algorithms. After balancing class distribution using the Synthetic Minority Over-sampling Technique (SMOTE), 20% of the data was reserved as a validation set. The remained data underwent the stratified sampling iterations to generate 200 pairs of 3∶1 training-test sets, which was employed for training and internal validation of 8 machine learning algorithms. The optimal algorithm and data partitioning strategy were selected to construct the final model, followed by external validation. The best-performing model was deployed online via Streamlit to create an interactive AI platform. RESULTS: Key predictive features for model construction included insomnia duration, the total PSQI score, PSQI sleep efficiency subscore, the proportion of N1 and N2 sleep stages in total sleep duration, and the maximum pulse rate during sleep. The CatBoost-based model achieved an AUC of 0.92, the average precision of 0.77, and accuracy, average recall, and average F1-score of 0.75 on the test set. On the validation set, it attained an AUC of 0.84, with accuracy, average precision, average recall, and average F1-score all at 0.72, demonstrating robust predictive performance. An interactive AI platform was subsequently developed (https://tdyx-catboost.streamlit.app/). CONCLUSION This study successfully establishes and validates a CatBoost-based efficacy prediction model for Tongdu Yangxin acupuncture therapy in treatment of insomnia. The developed AI platform provides data-driven decision support for acupuncture-based insomnia management.
Humans ; Sleep Initiation and Maintenance Disorders/physiopathology* ; Acupuncture Therapy ; Male ; Acupuncture Points ; Female ; Middle Aged ; Adult ; Artificial Intelligence ; Aged ; Young Adult