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 analyze the clinical distribution characteristics and drug resistance of Enterobacter cloa-cae in Gansu Province from 2019 to 2023,providing reference for the prevention and control of E.cloacae infec-tions in this region.METHODS Data on the distribution and drug resistance of E.cloacae from hospitals in mem-ber units of the Gansu Antimicrobial Surveillance Network between 2019 and 2023 were collected.In vitro drug susceptibility testing was performed by the Kirby-Bauer disk diffusion(K-B)method,minimum inhibitory con-centration method,and fully automated instrumentation,followed by analysis of the susceptibility results.RESULTS From 2019 to 2023,a total of 402 490 bacterial strains were isolated and cultured in Gansu Province,including 17 417 strains of E.cloacae,with a detection rate of 4.33％.The bacteria were primarily iso-lated from sputum specimens(62.81％),followed by urine(7.37％)and wound pus specimens(6.07％).The de-partmental distribution was dominated by internal medicine(44.96％)and surgery(28.50％).The highest detec-tion rate was observed in the adult group(15-65 years,45.79％).E.cloacae exhibited varying degrees of resist-ance to over 20 antibacterial drugs,but the overall drug resistance rate showed a declining trend(P＜0.05).The highest drug resistance rate was observed for cefazolin(96.40％-98.38％),while the lowest was for tigecycline(0.44％—2.92％).Carbapenem-resistant E.cloacae demonstrated an increasing trend in drug resistance rates,with imipenem resistance ranging from 2.79％to 3.71％(P=0.044)and meropenem resistance ranging from 1.29％to 3.41％(P＜0.05).CONCLUSIONS The isolation rate of E.cloacae in Gansu Province remains stable,with a declining trend in drug resistance to multiple antibacterial drugs.However,the increasing drug resistance to carbapenems warrants attention.

Objective:To investigate the value of preoperative intestinal ultrasound parameters in predicting early postoperative recurrence（EPR）in patients with Crohn's disease（CD）.Methods:Ninety-five patients with CD who underwent I-stage intestinal resection at the Sixth Affiliated Hospital， Sun Yat-sen University from March 2015 to December 2020 were retrospectively enrolled. The patients were divided into EPR group （ n=50） and non-EPR （NEPR） group （ n=45） based on recurrence within one year postoperatively. Differences in preoperative intestinal ultrasound parameters including bowel wall thickness，bowel wall stratification， color Doppler grading， mesenteric fat hypertrophy （MFH） ， mesenteric lymphadenopathy， abscess/fistula， abdominal effusion， and clinical factors such as preoperative C-reactive protein （CRP） and erythrocyte sedimentation rate （ESR） were compared between the two groups. The predictive values of ultrasound parameters with statistically significant differences between the two groups were analyzed. Univariate and multivariate Logistic regression analyses were used to identify independent predictive factors associated with EPR in patients with CD. Results:During the 1-year follow-up，EPR occurred in 52.6%（50/95）patients with CD. Among clinical factors，preoperative CRP and ESR levels showed statistically significant differences between the EPR and NEPR groups（all P<0.05）. For ultrasound parameters，the incidences of mesenteric fat hypertrophy（MFH）and abscess/fistula were significantly higher in the EPR group than the NEPR group（all P<0.05）. MFH demonstrated a significantly higher AUC value for predicting EPR compared to abscess/fistula（0.797 vs.0.617， P=0.002）. Univariate Logistic analysis showed that CRP，ESR，MFH and abscess/fistula were candidate variables for diagnosing EPR（all P<0.05）. Multivariate Logistic regression analysis indicated that MFH（ OR=13.800， P<0.001）and the laboratory measure CRP（ OR=1.015， P=0.030）were effective predictive factors for EPR. Conclusions:Preoperative intestinal ultrasound parameter MFH may serve as a valuable predictor for assessing EPR risk in patients with CD.

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.

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.

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.

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.