BACKGROUND:Electromyographic biofeedback therapy has demonstrated unique advantages of non-invasive,real-time feedback,personalized treatment and promotion of neuroplasticity,and can promote the recovery of motor function in patients with spinal cord injury.OBJECTIVE:To review the current application status and therapeutic effects of electromyographic biofeedback combined with exercise therapy,robotic exoskeletons,and virtual reality technology in the recovery of motor function after spinal cord injury.METHODS:Relevant literature was retrieved from CNKI and PubMed databases up to May 2024.The search terms included"spinal cord injury,EMG biofeedback,physical therapy,robotic exoskeleton,VR,motor function,exercise"in both English and Chinese.Finally,71 articles were included for review.RESULTS AND CONCLUSION:Mechanisms by which electromyographic biofeedback therapy promotes spinal cord injury rehabilitation include promoting neural plasticity changes,strengthening neuromuscular connections and improving movement patterns.Electromyographic biofeedback,as an emerging tool for treating spinal cord injury,is often used in conjunction with other therapeutic methods,including exercise therapy,robotic exoskeletons,and VR,to promote the recovery of motor function after spinal cord injury.The effectiveness of combination therapy has been significantly improved.However,there are still some problems and challenges,such as the lack of detailed analysis of the mechanism,the lack of large-scale trials that provide strong evidence for combined efficacy,and the limited adaptability of the technology.Future research can focus on these aspects:to improve the personalization and accuracy of electromyographic biofeedback;to develop new rehabilitation equipment and expand the application areas of electromyographic biofeedback combined with more advanced technologies or engineering equipment;to apply electromyographic biofeedback to gait training systems,respiratory training systems,and limb-linkage rehabilitation systems,so as to improve the accuracy of the feedback and the effect of personalized treatment plans.At the same time,the ease of use and comfort of the equipment will be improved.

At present, robotic surgery system, as a cutting-edge technique in minimally invasive surgery, has become a crucial component in the training programs for outstanding surgeons. Given the relatively late start of this technique and immature faculty resources, there is an urgent need to optimize and improve the teaching philosophies and methodologies for robotic skill training in China, and Sino-foreign cooperation has emerged as a significant pathway to promote this reform. Taking the "International Robotic Surgery Training Center (IRSTC)" jointly established by The First Affiliated Hospital of Sun Yat-sen University and University of California as an example, this article provides a comprehensive analysis of collaboration background, construction of the training system, curriculum design, cooperation channels, and localization practices, in order to provide a reference and valuable experiences for Sino-foreign cooperation in clinical skill training.

BACKGROUND:Electromyographic biofeedback therapy has demonstrated unique advantages of non-invasive,real-time feedback,personalized treatment and promotion of neuroplasticity,and can promote the recovery of motor function in patients with spinal cord injury.OBJECTIVE:To review the current application status and therapeutic effects of electromyographic biofeedback combined with exercise therapy,robotic exoskeletons,and virtual reality technology in the recovery of motor function after spinal cord injury.METHODS:Relevant literature was retrieved from CNKI and PubMed databases up to May 2024.The search terms included"spinal cord injury,EMG biofeedback,physical therapy,robotic exoskeleton,VR,motor function,exercise"in both English and Chinese.Finally,71 articles were included for review.RESULTS AND CONCLUSION:Mechanisms by which electromyographic biofeedback therapy promotes spinal cord injury rehabilitation include promoting neural plasticity changes,strengthening neuromuscular connections and improving movement patterns.Electromyographic biofeedback,as an emerging tool for treating spinal cord injury,is often used in conjunction with other therapeutic methods,including exercise therapy,robotic exoskeletons,and VR,to promote the recovery of motor function after spinal cord injury.The effectiveness of combination therapy has been significantly improved.However,there are still some problems and challenges,such as the lack of detailed analysis of the mechanism,the lack of large-scale trials that provide strong evidence for combined efficacy,and the limited adaptability of the technology.Future research can focus on these aspects:to improve the personalization and accuracy of electromyographic biofeedback;to develop new rehabilitation equipment and expand the application areas of electromyographic biofeedback combined with more advanced technologies or engineering equipment;to apply electromyographic biofeedback to gait training systems,respiratory training systems,and limb-linkage rehabilitation systems,so as to improve the accuracy of the feedback and the effect of personalized treatment plans.At the same time,the ease of use and comfort of the equipment will be improved.

A novel epileptic seizure prediction prediction model based on multichannel temporal and spatial feature extractions is presented.The model applies Stockwell transform to the original multichannel electroencephalogram(EEG)signals for extracting time-frequency components.To address the issue of insignificant difference between preseizure and interseizure time-frequency features,an adaptive feature module composing of ConvNeXt,SENet and pyramid pooling module is designed to enhance the ability of capturing key time-frequency features in each EEG channel.Meanwhile,a prediction model based on Bi-NLSTM is constructed to improve the spatiotemporal dependence between the time-frequency features of multichannel high-order EEG for further promoting the epilepsy classification performance.On the CHB-MIT dataset,the model has an accuracy,sensitivity,specificity and AUC of 96.0%,97.8%,96.8%and 0.987,respectively,and the false positive rate per hour decreased to 0.038,outperforming the existing mainstream methods.In addition,the effect of each component on the model performance is verified by ablation study.The proposed method improves the overall performance for seizure prediction effectively by optimizing local time-frequency feature extraction and enhancing multichannel spatiotemporal dependence.

Objective To understand the molecular epidemiological characteristics and hypervirulence evolution trend of ST11 carbapenem-resistant Klebsiella pneumoniae(CRKP)isolated from medical institutions in Shanghai,and provide scientific basis for formulating the prevention and control measures of drug-resistant organisms.Methods A total of 201 strains of CRKP isolated from 12 medical institutions in Shanghai from 2021 to 2022 were collected.Antimicrobial susceptibility testing and whole genome sequencing were performed.The concatenated data was used for multilocus sequencing typing(MLST),serum typing(wzi typing),as well as analysis of resistance and viru-lence genes.Results All 201 CRKP strains were multidrug-resistant organisms(MDROs).These strains were al-most completely resistant to carbapenems,cephalosporins,and quinolones.Drug resistance gene analysis showed that 93.03％of CRKP strains carried KPC gene.201 CRKP strains were divided into 6 ST types and 10 capsule wzi types,with ST11-KL64(n=104)being the dominant type,followed by ST15-KL19(n=54).52.24％(n=105)of CRKP carried rpmA/rpmA2+iucA+iutA+iroN genes.Conclusion CRKP isolated from medical institutions in Shanghai is mainly ST11-KL64 type with severe multidrug resistance,and more than half of the strains are hyper-virulent carbapenem-resistant Klebsiella pneumoniae(hv-CRKP).It is necessary to continuously strengthen the monitoring of the molecular characteristics of CRKP,so as to prevent outbreaks of healthcare-associated infection.

Objective To investigate the effects of neurotrophic factor Neuritin overexpression on the angiogenic effects of chicken embryonic allantoic membrane (CAM) and human umbilical vein endothelial cells (HUVECs),and to provide a new direction for the treatment of angiogenic diseases. Methods Thirty fresh yellow-skinned breeding eggs were selected to establish a CAM model,which were divided into three groups by randomized numerical table method:positive control group (bFGF),negative control group (NS) and experimental group (Neuritin),with 10 eggs in each group. The positive control group was loaded with 2500 U/mL of bFGF,the experimental group was loaded with 10 μg/mL of Neuritin protein,and the negative control group was loaded with NS. 10 μL loading volume was loaded into each group,and all CAMs were incubated at the same temperature,relative humidity,and time,and the vascular branching,number,and size of the CAMs in each group were recorded after 72 h of incubation. Fresh umbilical cords from healthy pregnant women were selected to produce primary HUVECs,which were divided into three groups:transfected with recombinant plasmid (HUVEC-neu group),transfected with empty vector (HUVEC-3.1 group),and untransfected (HUVEC group). Primary HUVECs in the HUVEC-neu group were transfected with the recombinant plasmid Neuritin,and those in the HUVEC-3.1 group were transfected with the empty vector. HUVEC-3.1 group was transfected with the empty vector plasmid,and HUVEC group was not given any special treatment,and all three groups received the same culture regimen. Western blot was used to detect the protein expression level of Neuritin in HUVEC-3.1 and HUVEC-neu groups. CCK-8 assay,cell scratch assay,Transwell assay,and tube formation assay were used to detect protein expression level of Neuritin in HUVEC-3.1 group and HUVEC-neu group,and HUVEC-neu groups for cell proliferation,migration and tube formation. Results (1) The number of CAM vessel branch points and microvessels in the experimental group was significantly increased compared with that in the negative control group (P<0.01),but there was no statistically significant difference in the number of large and medium-sized vessels between the two groups (P>0.05);(2) Neuritin was successfully overexpressed in HUVECs in the HUVEC-neu group. (3) Compared with the HUVEC-3.1 group,the proliferation vigor of cells in the HUVEC-neu group was decreased (P<0.05),but their migration and tube formation abilities were significantly enhanced (P<0.01). Conclusion Neuritin overexpression promotes angiogenesis and participates in the regulation of neovascularization by affecting cell prolif-eration,migration,and tube formation ability.

Objective:To explore the method for selecting characteristic prices of Chinese patent medicines based on informa-tion entropy theory.It involves analyzing the connotative differences among various price indicators and utilizing information entropy metrics to validate the scientific rigor of characteristic price selection so as to optimize the pricing model for Chinese patent medi-cines and improve the accuracy of price evaluation.Methods:A correlation analysis and information entropy calculation are con-ducted on the median price of the smallest preparation unit,average daily cost,and average course cost of TCM.It compares the information diversity and uncertainty of different pricing indicators.Results:The average daily cost exhibits the highest information diversity and uncertainty among all the pricing indicators examined.Conclusion:It is recommended that the average daily cost be used as the dependent variable for characteristic prices in TCM pricing research.This choice plays an important role in optimizing TCM pricing models and enhancing the accuracy of price evaluation.

Objective:To establish a scientific,systematic,and objective indicator system for the characteristic price variables of Traditional Chinese Patent Medicines(TCPM),providing a reference framework for the pricing mechanism of TCPM.Methods:The brainstorming method was initially used to screen related variable indicators.The Nominal Group Technique(NGT)and Delphi methods were applied to gather expert opinions,and SPSS 28.0 was employed for data statistical analysis.It led to the development of a TCPM characteristic price variable indicator system consisting of 6 dimensions,14 characteristic variables and 26 measurement indicators.Results:The authority coefficient of the experts exceeded 0.7,indicating the representativeness of the results.Expert opinions were generally concentrated.Based on the collected opinions and statistical analysis,the scope of selected TCPM characteristic price variables was preliminarily established.Conclusion:The TCPM characteristic price variable indicator system was initially developed.However,due to the complexity of the pricing mechanism and divergent expert opinions,further qualitative and quantitative research methods,along with a dynamic adjustment mechanism,are needed to verify and refine the system.

The National Essential Medicines System could protect public health and ensure access to essential medications.Although the current selection methods for China's National Essential Medicines Lists(NEMLs)are becoming more scientific and standardized,there are still problems such as much emphasis on expert experience and the lack of transparency of decision-making basis.To address these issues,it proposes an evidence-based decision-making pathway for NEMLs selection guided by clinical value.This approach ensures a strong integration of evidence and decision-making,offering valuable insights for improving the adjustment procedures and selection criteria of the NEMLs in China.

Chronic diseases constitute one of the most significant public health challenges globally.Addressing the coexistence of chronic conditions and fostering the development of positive adaptive behaviors is of utmost importance in enhancing self-management skills and healthcare outcomes.Selecting an appropriate theoretical model can offer valuable research insights and a robust framework for anticipating and intervening in patients' adaptive behaviors. Therefore, this paper summarizes the application of theoretical models pertinent to adaptive behaviors in patients with chronic diseases. It conducts a thorough analysis of the strengths and weaknesses of each theoretical model, considering aspects such as theoretical development, target application population, nursing interventions, and effect evaluation. Additionally, it proposes future prospects for the application of these models.In order to enhance awareness of disease adaptive behaviors and provide valuable insights for promoting the development and implementation of comprehensive health lifecycle care plans for chronic diseases.