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 develop a composite nutritional preparation that can effectively improve exercise performance under calorie restriction(CR)condition.Methods A total of 24 male C57BL/6J mice(weighing 23～26 g,8 weeks old)were randomly divided into control group(CON),CR,CR+basal nutrient group(CRN1),and CR+compound nutrient group(CRN2).All groups underwent moderate-intensity running training 5 d per week,for totally 3 weeks.The grip strength of the forelimbs were measured weekly,and in 3 weeks after training,exhaustion and post-exhaustion distance tests were conducted to evaluate exercise performance.Blood biochemical indicators,levels of skeletal muscle and liver redox biomarkers,and histopathological conditions were measured and observed.Results After 21 d of intervention,the CR group and CRN1 group had the post-exhaustion running distance prolonged by 278%and 289%,respectively,reduced blood glucose level,and decreased muscle mass,subcutaneous fat and epididymal fat mass when compared with the CON group(P<0.05).Compared with the CON group,the CRN1 and CRN2 groups demonstrated significantly higher gastrocnemius glycogen content.The CRN2 group obtained even longer post-exhaustion distance(increased by 52%and 36%respectively,compared with the CON group and CRN1 group,P<0.05),enhanced grip strength of the forelimbs(raised by 9%,17%and 15%,respectively than the CON,CR and CRN1 groups,P<0.05),elevated brown fat mass(compared to the CON group and CRN1 group,P<0.05),increased blood glucose level(compared to the CRN1 group,P<0.05),decreased blood low-density lipoprotein cholesterol level(compared to the CON and CR groups,P<0.05),and increased glutathione peroxidase content in the gastrocnemius muscle(compared to the CON group,P<0.05).Conclusion Supplementing with compound nutritional supplements in mice under CR can promote exercise performance,including improving fatigue recovery after exhaustive exercise and enhancing forelimb grip strength.

Objective Exploring the components of complex scenarios of healthcare surges triggered by major epidemics to provide a theorical basis for building resilience in healthcare organizations.Methods A hybrid analysis method is used to summarize macro-meso-micro multi-level and multi-source heterogeneous information,extract the elements of complex scenarios of medical surge and evaluate the rationality.Fault Tree Analysis method is used to clarify the logical relationship between various scenario elements and construct scenario reasoning paths.Results 10 scenario states,11 disaster-bearing,24 emergency management and 23 scenario results are summarized and extracted to form the key elements of complex surge scenarios.Among them,M4 expansion and coordinated scheduling of key positions,B2 conventional drug inventory emergency/insufficient core treatment drugs,B emergency medical material transportation breakage,S3 disease symptom spectrum shift to severe disease,R13 prevention and control awareness laxity,and M5 media information dissemination management are the key driving factors that promote a major turning point in the scenario.The most positive scenario result is the orderly operation of the medical service system,and the most negative scenario result is the paralysis of the medical service system.Conclusion Medical institutions need to improve emergency plans based on the complex evolution scenarios of medical surges and agile governance capabilities targeting key turning points,focus on dynamically expanding and scheduling personnel in key positions,strengthen material rotation and reserve mechanisms,maintain smooth emergency logistics channels,and improve efficient management of media and public opinion,so as to comprehensively improve overall resilience.

This study was aimed at investigating the effects of demethylase fat mass and obesity-associated protein(FTO)and methyltransferase methyltransferase like protein 3(METTL3),key molecules in N6-methyladenosine(m6A)modification,on the replication and proliferation of Japanese encephalitis virus(JEV).Recombinant lentiviruses were generated by packaging the FTO and green fluorescent protein into lentiviral vectors.Neuro2a cells,a mouse neuroblastoma cell line,were infected with the lentivirus,and stable FTO-expressing cell lines were obtained through puromycin selection.Successful overexpression of FTO was confirmed through fluorescence microscopy,real-time quantitative PCR,and western blot analysis.When Neuro2a cells overexpressing FTO were infected with JEV,the overexpression of FTO decreased JEV replication in the cells,and increased the expression of interferon(IFN)and related molecules.Additionally,treatment of JEV-infected Neuro2a cells with the METTL3-specific inhibitor STM2457 resulted in a dose-dependent decrease in JEV replication and viral protein expression.These findings suggested that lowering m6A methylation levels inhibits JEV replication,thus shedding light on the regulatory role of methylation modification in JEV replication.

Aim To explore the in vitro anti-human triple-negative breast cancer(TNBC)effect and mech-anism of Austocystin R.Methods MTT assay was used to evaluate the anti-tumor potential of Austocystin R for various human tumor cells and normal cells.Flow cytometry was employed to evaluate the influence on cell cycle progression.mRFP-GFP-LC3 adenovirus transfection was used to evaluate the autophagic flux process.Western blot assay was used to verify the effect of Austocystin R on the expression of related pro-teins.Results The results showed that Austocystin R significantly inhibited the proliferation of multiple tumor cells in a dose-dependent manner,especially for the MDA-MB-231 cells with an IC50 of 1.45μmol·L-1.In addition,Austocystin R increased the protein expression of PTEN,p53,p-p53,p27,p21,and down-regulated the expression of p-PI3K,p-AKT and p-mTOR.Austocystin R can significantly increase the proportion of S-phase MDA-MB-231 cells,inhibit the expression of Cyclin D1,CDK4,CDK6,Rb,Cyclin B1 and CDK1,and promote the expression of Cyclin E1 and CDK2.Austocystin R can promote the autophagic flux process of MDA-MB-231 cells,promote the expres-sion of LC3 Ⅰ/Ⅱ,p-Beclin-1,p-ULK1,HMGB-1 and Atg 14 proteins,and inhibit the expression of Beclin-1,ULK1,p62,ATG 3,ATG 4B,ATG 5,ATG 7,ATG 12,ATG 13 and ATG 16L1 proteins.Conclusion Austo-cystin R can exhibit its anti-TNBC activity by inhibi-ting the PI3K/AKT/mTOR signaling pathway,blocking the cell cycle at the S phase and inducing autophagic cell death.

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

Objective To investigate and compare the epidemiological characteristics of common respiratory viruses among influenza-like illness(ILI)and severe acute respiratory infection(SARI)cases in Huzhou,Zhejiang Province before and after the COVID-19 pandemic,so as to provide a basis for formulating and adjusting the prevention and control strategies for viral respiratory infectious diseases.Methods ILI and SARI cases at two influenza surveillance sentinel hospitals in Huzhou and had throat swab samples collected during Nov 2017 to Feb 2020(pre-COVID-19 pandemic period)and Dec 2022 to Apr 2024(post-COVID-19 mitigation phase)were selected as the participants.Seven common viral respiratory pathogens were tested,including influenza A virus(H1N1 and H3N2 subtypes),influenza B virus(Victoria lineage,FluB),respiratory syncytial virus(RSV),rhinovirus(HRV),adenovirus(ADV),and severe acute respiratory syndrome coronavirus-2(SARS-CoV-2).The positive rates of respiratory pathogens before and after the COVID-19 pandemic were compared across different age groups and different time.Results A total of 7 948 ILI samples and 2 294 SARI samples were included.The overall positive rate of ILI samples increased from 33.6%to 47.1%,primarily due to the increase in influenza and COVID-19 infections;the overall positive rate of SARI samples decreased from 31.4%to 24.8%,mainly due to the reduction in HRV and ADV infections.During the post-COVID-19 mitigation phase,SARS-CoV-2(22.1%),H3N2(12.7%),and FluB(6.0%)were the primary pathogens in ILI samples,while RSV(7.1%),H3N2(5.3%),and HRV(4.5%)dominated in SARI samples.During the post-COVID-19 mitigation phase,the influenza virus circulation period was shortened.Before the COVID-19 pandemic,RSV was mainly detected in autumn and winter,while during the post-COVID-19 mitigation phase,out-of-season RSV epidemics were observed in spring and summer.Co-infection rate in ILI cases increased significantly in the post-COVID-19 mitigation phase,predominantly consisting of co-infections of COVID-19 and influenza A virus,while co-infection rate in SARI cases showed a decline.Conclusion We found important epidemiological changes in respiratory viruses in Huzhou during the post-COVID-19 mitigation phase compared to pre-COVID-19 period,including increased positive rates of influenza and COVID-19,and disruptions to the seasonal patterns of influenza and RSV.The prevention and control strategies should be adjusted in a timely manner based on the monitoring data.

Multiple myeloma is a common and refractory hematological malignancy for which there is currently no radical treatment,and it is prone to relapse.Patients with relapsed and refractory myeloma have often been previously treated with multiple drugs including proteasome inhibitors and/or immunomodulatory drugs.Therefore,for such patients,the primary goal of treatment is to achieve disease control with acceptable toxicity and maintenance of quality of life.In this paper,the aim is to review the clinical effect of selinexor in treating patients with RRMM.As a novel treatment for RRMM,selinexor has a unique pharmacological mechanism that may further improve the clinical response rate of RRMM patients and enhance patients' quality of life.Although selinexor can cause a series of adverse reactions,most of these adverse reactions can be alleviated or disappear after clinical targeted treatment,and effective preventive measures can also minimize the occurrence of adverse reactions.In conclusion,selinexor has shown broad application prospects in RRMM patients,and further research will be conducted in the future to optimize the treatment regimen of selinexor,so that more RRMM patients can benefit from it.

Objective To explore the expression of Nudix hydrolase 5(NUDT5)protein in breast cancer tissues and its correlation with ultrasound signs and clinicopathological characteristics.Methods A total of 108 patients with breast cancer admitted to our hospital from October 2019 to April 2022 were selected as the research objects.Ultrasound examination was performed before operation to observe the ultrasound signs of patients.Immunohistochemical method was used to detect the expressions of estrogen receptor(ER),progesterone receptor(PR)and human epidermal growth factor receptor 2(HER-2)in breast cancer tissues,and the expression levels of NUDT5 protein in breast cancer tissues and adjacent tissues,and the relationships of NUDT5 protein expression with ultrasound signs and clinicopathological characteristics of patients were analyzed.Results Among 108 patients,there were 62 cases with ER positive,60 cases with PR positive,and 28 cases with HER-2 positive.The positive expression rate of NUDT5 protein in breast cancer tissues was higher than that in adjacent tissues(P<0.05).The positive expression rate of NUDT5 protein was higher in breast cancer tissues with microcalcification,blood flow imaging grade(grade 2 to 3)and lymph node metastasis(P<0.05).The positive expression of NUDT5 protein was correlated with histological grade,ER and HER-2(P<0.05).The expression of NUDT5 protein in breast cancer tissue was positively correlated with ER negative and HER-2 positive(rs=0.463,0.398,P<0.05).Conclusion The positive expression rate of NUDT5 protein in breast cancer tissues is higher than that in adjacent tissues,and its expression has a certain correlation with microcalcification,blood flow imaging grade(grade 2 to 3),lymph node metastasis in ultrasound signs and histological grade,ER,and HER-2 in clinicopathological characteristics.

Since the concept of artificial intelligence(AI)was proposed in 1956,medicine has been one of its core application fields.At present,AI technology has run through the whole diagnosis and treatment process,and has been extended to innovative scenarios such as drug research and development,surgical robots,and clinical trial optimization.Scenario application is the backbone of the technical system.Multimodal data fusion integrates heterogeneous data such as images,medical records,and genes,and federated learning realizes cross-institutional privacy protection and sharing.Deep learning achieved more than 90%sensitivity in imaging diagnosis for lung nodule detection,while generative AI accelerates drug molecule design.The core applications cover four major areas field:AI is more accurate than professional doctors in breast cancer and diabetic retinopathy screening;robotics shortens hospital stays and improves spinal screw placement accuracy;AI shortens the discovery cycle of drug targets;machine learning improves the efficiency of subject screening and enables real-time data monitoring.The application of AI in the medical field is first constrained by data quality and algorithm bias,and the"black box"characteristics of AI models and the ambiguity of responsibility attribution are the core obstacles to clinical implementation.This paper analyzes key technological breakthroughs and typical cases,discusses the application scenarios and challenges of AI in medicine,and aims to provide a reference for the future development of medical intelligence.