The pain-evoked potential electroencephalogram (EEG) is an effective electrophysiological indicator for pain assessment, yet its extraction is challenging due to interference from background activity and involuntary blinks. Although existing blink artifact-removal methods show efficacy, they face limitations such as the need for reference signals, neglect of individual differences, and reliance on user input, hindering their practical application in clinical pain assessments. In this paper, we propose a novel framework applying adaptive quadrature mirror filter banks (AQMFB) with discrete wavelet transform (DWT) to remove blink artifacts in pain EEG. Unlike traditional DWT methods that apply fixed wavelets across subjects, our method adapts wavelet construction based on the characteristics of EEG. Experimental results demonstrate that AQMFB-DWT outperforms four leading methods in removing blink artifacts with minimal distortion of pain information, all within an acceptable processing time. This technique is a valuable preprocessing step for enhancing the extraction of pain-evoked potentials.
Humans ; Artifacts ; Blinking/physiology* ; Electroencephalography/methods* ; Pain/diagnosis* ; Male ; Wavelet Analysis ; Adult ; Female ; Evoked Potentials/physiology* ; Young Adult ; Brain/physiopathology* ; Pain Measurement/methods* ; Signal Processing, Computer-Assisted

This study examines the progress and application of Artificial Intelligence (AI) in the prevention and control of infectious diseases within Chinese healthcare institutions. It analyzes the difficulties and challenges encountered during implementation to promote the intelligent transformation and upgrading of infectious disease prevention and control. The results indicate that AI technology has made progress in areas such as infectious disease surveillance and early warning, risk assessment and emergency response, screening and detection, image-based diagnosis and analysis, and health management. Nevertheless, significant challenges remain, including limited application depth and breadth, issues with data quality and privacy protection, insufficient technological maturity and interpretability, potential legal risks, and a shortage of interdisciplinary professionals. To advance the application of AI technology in infectious disease prevention and control and support the modernization of China′s relevant systems, recommendations include strengthening policy support, establishing data standards and robust privacy protection mechanisms, increasing R&D investment, refining laws and regulations, and enhancing the training of interdisciplinary talent.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Age-related macular degeneration(AMD)is a chronic degenerative retinal disease that severely impairs pa-tients central vision.Research indicates that the complement system is closely associated with the onset and progression of AMD,playing a key role in its pathogenesis,involving various factors such as genetic risk,inflammatory responses,and oxidative stress.This review summarizes the relationship between complement system activation and AMD,as well as re-cent clinical trials targeting complement-based therapies for AMD,with the aim of providing insights for both basic research and clinical treatment of AMD.

This study examines the progress and application of Artificial Intelligence (AI) in the prevention and control of infectious diseases within Chinese healthcare institutions. It analyzes the difficulties and challenges encountered during implementation to promote the intelligent transformation and upgrading of infectious disease prevention and control. The results indicate that AI technology has made progress in areas such as infectious disease surveillance and early warning, risk assessment and emergency response, screening and detection, image-based diagnosis and analysis, and health management. Nevertheless, significant challenges remain, including limited application depth and breadth, issues with data quality and privacy protection, insufficient technological maturity and interpretability, potential legal risks, and a shortage of interdisciplinary professionals. To advance the application of AI technology in infectious disease prevention and control and support the modernization of China′s relevant systems, recommendations include strengthening policy support, establishing data standards and robust privacy protection mechanisms, increasing R&D investment, refining laws and regulations, and enhancing the training of interdisciplinary talent.

The number of maintenance hemodialysis patients in China has been steadily increasing. With the continuous iteration of technological innovations, healthcare has entered a new phase of digital healthcare development. This paper summarizes the overview and development of digital healthcare and its application in patients with maintenance hemodialysis. It also discusses existing challenges and corresponding strategies, aiming to provide references for the development of digital healthcare in hemodialysis.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

The number of maintenance hemodialysis patients in China has been steadily increasing. With the continuous iteration of technological innovations, healthcare has entered a new phase of digital healthcare development. This paper summarizes the overview and development of digital healthcare and its application in patients with maintenance hemodialysis. It also discusses existing challenges and corresponding strategies, aiming to provide references for the development of digital healthcare in hemodialysis.

Age-related macular degeneration(AMD)is a chronic degenerative retinal disease that severely impairs pa-tients central vision.Research indicates that the complement system is closely associated with the onset and progression of AMD,playing a key role in its pathogenesis,involving various factors such as genetic risk,inflammatory responses,and oxidative stress.This review summarizes the relationship between complement system activation and AMD,as well as re-cent clinical trials targeting complement-based therapies for AMD,with the aim of providing insights for both basic research and clinical treatment of AMD.

Purpose/Significance To explore the application and predictive accuracy of various models in predicting the risk of ather-osclerosis in diabetic patients.Method/Process Based on the biochemical data table from the"Diabetes Complications Warning Dataset"provided by the National Population Health Science Data Center,MATLAB software is used to construct risk prediction models for diabe-tes-induced atherosclerosis.The models are built by using k-nearest neighbors(KNN),decision trees,backpropagation(BP)neural networks,and Naive Bayes algorithms,and which are subjected to comparative analysis.Result/Conclusion In terms of effectiveness,the predictive accuracy of Naive Bayes algorithm is the highest(61.6％),followed by the decision tree model(58.2％),the KNN mod-el(57.7％),and the BP neural network model(55.9％).The results of the confusion matrix and the receiver operating characteristic(ROC)curve indicate that the Naive Bayes model performs best.When comparing the models in terms of effectiveness,performance and stability,the Naive Bayes model is superior.