Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective:To investigate the predictive value of pre-infarction angina(PIA)combined with serum lipo-protein-associated phospholipase A2(Lp-PLA2)for no-reflow during primary percutaneous coronary interven-tion(PCI)in elderly patients with new-onset acute ST-segment elevation myocardial infarction(STEMI).Meth-ods:A total of 189 patients who hospitalized because of acute STEMI and underwent primary PCI within 12h in De-partment of Cardiology,Cangzhou People's Hospital between January 2018 and December 2022 were enrolled.Ac-cording to their TIMI blood flow during PCI,the patients were divided into no reflow group(n=42)and normal re-flow group(n=147).The baseline data were compared between two groups.Multivariate Logistic regression analy-sis was used to analyze the risk factors of no-reflow during PCI.The receiver operating characteristic(ROC)curve was plotted to evaluate the predictive value of PIA and Lp-PLA2 for no-reflow.Results:PI A occurred in 73 cases(38.6％),and no reflow occurred in 42 cases(22.2％)during primary PCI.Compared with patients in normal re-flow group,those in no reflow group had significant higher Lp-PLA2[(341.33±98.32)ng/ml vs.(261.95±75.21)ng/ml]and onset to reperfusion time[(7.02±1.28)h vs.(5.14±1.48)h],and significant lower incidence of PIA(23.8％ vs.42.9％)(P＜0.05 or＜0.01).Multivariate Logistic regression analysis showed that Lp-PLA2(OR=1.528,95％CI 1.028～2.030,P＜0.001),onset to reperfusion time(OR=2.602,95％CI 1.848～3.665,P＜0.001)were independent risk factors for no reflow during PCI in elderly STEMI patients,while PIA was an inde-pendent protective factor(OR=0.261,95％CI 0.101～0.671,P=0.005).The area under ROC curve of Lp-PLA2 combined PIA was 0.863(95％CI 0.806～0.909),which was significantly higher than those of Lp-PLA2[0.733(95％CI 0.664～0.794),Z=2.690,P=0.007]and PIA alone[0.609(95％CI 0.535～0.679),Z=5.657,P＜0.001].Conclusion:Pre-infarction angina has an important protective effect on no-reflow in STEMI patients.High Lp-PLA2 and absence of pre-infarction angina at admission may be good predictors of no-reflow during primary PCI in elderly patients with newly-onset acute STEMI,and it contributes to risk stratification of high risk patients.

Objective:To investigate the predictive value of pre-infarction angina(PIA)combined with serum lipo-protein-associated phospholipase A2(Lp-PLA2)for no-reflow during primary percutaneous coronary interven-tion(PCI)in elderly patients with new-onset acute ST-segment elevation myocardial infarction(STEMI).Meth-ods:A total of 189 patients who hospitalized because of acute STEMI and underwent primary PCI within 12h in De-partment of Cardiology,Cangzhou People's Hospital between January 2018 and December 2022 were enrolled.Ac-cording to their TIMI blood flow during PCI,the patients were divided into no reflow group(n=42)and normal re-flow group(n=147).The baseline data were compared between two groups.Multivariate Logistic regression analy-sis was used to analyze the risk factors of no-reflow during PCI.The receiver operating characteristic(ROC)curve was plotted to evaluate the predictive value of PIA and Lp-PLA2 for no-reflow.Results:PI A occurred in 73 cases(38.6％),and no reflow occurred in 42 cases(22.2％)during primary PCI.Compared with patients in normal re-flow group,those in no reflow group had significant higher Lp-PLA2[(341.33±98.32)ng/ml vs.(261.95±75.21)ng/ml]and onset to reperfusion time[(7.02±1.28)h vs.(5.14±1.48)h],and significant lower incidence of PIA(23.8％ vs.42.9％)(P＜0.05 or＜0.01).Multivariate Logistic regression analysis showed that Lp-PLA2(OR=1.528,95％CI 1.028～2.030,P＜0.001),onset to reperfusion time(OR=2.602,95％CI 1.848～3.665,P＜0.001)were independent risk factors for no reflow during PCI in elderly STEMI patients,while PIA was an inde-pendent protective factor(OR=0.261,95％CI 0.101～0.671,P=0.005).The area under ROC curve of Lp-PLA2 combined PIA was 0.863(95％CI 0.806～0.909),which was significantly higher than those of Lp-PLA2[0.733(95％CI 0.664～0.794),Z=2.690,P=0.007]and PIA alone[0.609(95％CI 0.535～0.679),Z=5.657,P＜0.001].Conclusion:Pre-infarction angina has an important protective effect on no-reflow in STEMI patients.High Lp-PLA2 and absence of pre-infarction angina at admission may be good predictors of no-reflow during primary PCI in elderly patients with newly-onset acute STEMI,and it contributes to risk stratification of high risk patients.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

With the rapid development of population aging in various countries around the world,the health and elderly care industry has been paid high attention.The standardization of smart health and elderly care technology and services is particularly important.This paper firstly reviewed the policies related to healthy elderly care in China.By analyzing the industrial standards and provincial standards issued,this paper focused on the policies proposed by the Shanghai Municipal Government for the standardization of smart health and elderly care,as well as the researches on the standard system and the construction of standard families.Shanghai group standards in the field of smart health and elderly care were summarized,including the guidelines for the construction of standard systems,elderly care service platforms,community elderly cafeterias,portable health monitoring terminals,indoor sports services,and home-based elderly care safety monitoring.A series of case analyses of the standardized implementation of the above aspects were also provided.Through standardization research and practice in recent years,it has been fully demonstrated that the standard research plays an important leading role in the field of smart health and elderly care.

Objective:To develop a convolutional neural network model of whole slide imaging of cerebrospinal fluid cells for rapid and accurate identification and classification of tumor cells in cerebrospinal fluid.Methods:A total of 8 692 cerebrospinal fluid cytology smears from Huashan Hospital Affiliated to Fudan University from January 2nd, 2019, to December 27th, 2024. As randomly assigned, the training set included 4 941 benign and 1 745 malignant samples, while the validation set comprised of 1 368 benign and 638 malignant samples. Whole-slide digital images were acquired using a cytopathology scanner, cells (clusters) were annotated for classification, and a deep learning model was constructed via tiled image patches for cell detection and classification. Model performance was evaluated using accuracy, sensitivity, specificity, and other indicators. The classification efficiency of manual microscopy was compared.Results:The model achieved a mean precision of 96.75% for cerebrospinal fluid cell classification. For malignant tumor cells, the classification accuracy was 96.61% (mAP=98.36%, AUC=0.97). Subtype classification accuracies for epithelial/epithelioid tumors and small round cell tumors were 97.13% (AUC=0.98) and 95.58% (AUC=0.93), respectively. Compared with manual microscopy, which took (9.70±0.82) minutes for classifying 200 cells, (18.27±1.21) minutes for 500 cells, and often exceeded 60 minutes or infeasible for full slides, the AI model took (3.46±0.49) seconds for 200 cells, (6.76±0.82) seconds for 500 cells, and a median of 48.57 seconds for full slides ( P<0.001), representing an efficiency improvement of approximately 161-170 times, significantly enhancing diagnostic efficiency. Conclusion:This fully automated hierarchical deep learning model enables efficient and accurate tumor cell identification and classification in CSF, providing an effective auxiliary tool for the rapid diagnosis of meningeal carcinomatosis.

To explore the understanding of the target population regarding the Get Active Questionnaire for Pregnancy(GAQ-P)and the Companion Health Care Provider Consultation Form for Prenatal Physical Activity(cHCP-CF-PPA)in the Chinese context,and to verify the consistency of the Chinese version of the prenatal physical activity dual screening questionnaire with the original version in terms of language expression,27 pregnant women and 12 healthcare providers were selected from Obstetrics and Gynecology Hospital,Fudan University during Aug and Oct 2023,and were interviewed using purposive sampling.Two rounds of cognitive interviews were conducted.The first round revealed that some respondents experienced ambiguities in understanding the meanings of 5 items in the questionnaire.Following modifications,the second round indicated that the revised items were consistent in meaning with the original questionnaire.Cognitive interviews can facilitate the adaptation of the prenatal physical activity dual screening questionnaire to the Chinese cultural context,improve the understanding of the questionnaire items among the target population,and promote the localization of the screening tool.

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

Non-steroidal anti-inflammatory drugs(NSAIDs),commonly utilized analgesics,are extensively employed for managing pain associated with musculoskeletal disorders or injuries.Recent clinical studies have demonstrated a heightened risk of bone stress injuries(BSI)in soldiers and athletes,particularly during high-intensity training,due to NSAID usage.Furthermore,the impact of NSAIDs on fracture healing is well-documented;however,the precise mechanism by which their use during training contributes to an increased incidence of stress bone injuries remains unclear.This article aims to summarize potential mechanisms through an extensive review of domestic and international literature in order to standardize the utilization and clinical management of NSAIDs,optimize pain management strategies,and prevent stress bone injuries or fractures in specific populations such as soldiers and elite athletes.