Although global brain science research has progressed rapidly in recent decades, several fundamental questions in neuroscience remain unresolved. In particular, the physical mechanism underlying neural signal transmission remains controversial, and the carriers responsible for neural information storage and retrieval have not yet been fully clarified. These unresolved issues motivate us to re-examine the processes of neural information generation, transmission, integration, storage, and retrieval from multiple perspectives. A key observation is that neural electromagnetic activities are closely associated with time. Their duration, temporal structure, and dynamic evolution play crucial roles in neural information processing. In this work, we analyze neural electromagnetic activities from the perspective of temporal scales (referred to here as the “time course”). By reviewing and integrating findings from previous studies, we examine the characteristic time requirements and dynamic features of neural processes occurring at different stages of information processing. These stages include neural signal generation, signal transmission along axons, synaptic integration, synaptic plasticity, and memory formation and retrieval. Based on this temporal analysis, we outline a framework describing neural electromagnetic activities across a wide range of time scales, spanning from microseconds to minutes, hours, or even longer periods associated with long-term memory, which suggests that neural information processing involves multiple physical processes operating at different time levels. Rapid electromagnetic events may occur on microsecond scales, whereas electrophysiological phenomena such as action potentials typically last on the order of milliseconds. Longer time scales are associated with synaptic plasticity and memory-related processes. From this perspective, we propose that the physical carrier of neural information may be transient electromagnetic pulses with durations on the microsecond scale. In this framework, action potentials can be interpreted as the macroscopic electrophysiological manifestation of underlying electromagnetic processes triggered by ionic currents across neuronal membranes. Rather than being the fundamental neural signal itself, the action potential may represent a measurable membrane-level response associated with the successful activation of these electromagnetic events. Moreover, we discuss a possible mechanism for long-term memory storage. Considering the apparent temporal contradiction between the millisecond-scale excitation of neurons and the long-term persistence of memories, we believe that long-term memory information may be stored within neural network topologies formed by electrical synapse coupling. Such structures, referred to as electrically coupled memory networks (ECMNs), may enable neurons within the same network to respond rapidly and synchronously to stimuli, thereby facilitating efficient memory retrieval. Overall, this study emphasizes the importance of considering the temporal organization of neural electromagnetic activities when interpreting neural signaling mechanisms. It may provide new insights into the physical nature of neural information carriers and the mechanisms of memory storage and retrieval. Furthermore, highlighting the potential role of electromagnetic interactions in neural activity may contribute to the development of new theoretical frameworks and experimental approaches in neuroscience. Such perspectives may also offer valuable references for future research on neural coding, brain function mechanisms, and neuromodulation technologies.

Objective:This study aimed to integrate RNA-seq data to identify key genes associated with macrophage-ferroptosis and develop a prognostic model for hepatocellular carcinoma(HCC).Methods:We retrieved a dataset from the GEO database containing transcriptome data and clinical information for 163 samples.Macrophage-related genes were identified using WGCNA and immune infiltration analyses.Ferroptosis-related genes from the FerrDbV2 database were intersected with differentially expressed genes to obtain significant macrophage-ferroptosis-related genes.Hub genes were screened via protein interaction network construction,and key genes were identified using four machine learning algorithms.These genes exhibited significant expression differences between cancer and normal tissues and were closely linked to patient prognosis.ROC curve and KM survival analyses were performed,and expression levels were validated at the transcriptome and proteome levels.Results:Four key genes RRM2,KIF20A,PCK2,and PDK4 were identified and evaluated.RRM2 and KIF20A demonstrated high importance in classification prediction models and reliable performance in ROC and KM analyses(AUC＞0.9,P＜0.05).These genes regulate cancer cell proliferation/survival and macrophage polarization/function,influencing the tumor microenvironment and HCC progression.Conclusion:RRM2 and KIF20A regulate cancer cell proliferation and survival,modulate macrophage polarization and function,and influence the immune response in the tumor microenvironment.They can serve as prognostic biomarkers and potential immunotherapy targets for hepatocellular carcinoma.

Aim To study the therapeutic effect of al-licin on senna-induced diarrhea in mice and to explore the underlying mechanism.Methods Forty-eight C57BL/6J mice were randomly divided into six groups:control,model,loperamide positive control group(2 mg·kg-1),allicin low-dose group(6 mg·kg-1),allicin medium-dose group(12 mg·kg-1)and allicin high-dose group(18 mg·kg-1).Except for the con-trol group,the diarrhea model was induced in the other groups by intragastric administration of senna leaf ex-tract.After drug administration,several diarrhea indi-ces were measured:the rate of loose stools,diarrhea index,accumulated frequency of loose stools at differ-ent time points within 5 hours,and small intestine pro-pelling rate.Serum levels of TNF-α and IL-6 were de-tected by ELISA.Serum NO content was determined u-sing the Griess method.The activities of SOD and CAT,as well as MDA content in the ileum and colon,were measured.The pathological changes and the ex-pression of mRNA related to intestinal barrier proteins in the ileum and colon were evaluated using HE stai-ning and RT-qPCR.Results Allicin improved diar-rhea symptoms in mice induced by senna leaf.It re-duced the rate of loose stools,diarrhea index,cumula-tive number of loose stools in five hours,and the intes-tinal propulsion rate.Allicin also protected the intesti-nal mucosa,decreased serum TNF-α and IL-6 levels,and lowered MDA content in the intestines.It in-creased serum NO levels and enhanced SOD and CAT activities in the intestines.Additionally,allicin upreg-ulated the mRNA expression of AQP1,AQP4,and ZO-1 in intestinal tissues.Conclusions Allicin has a significant therapeutic effect on senna-induced diarrhea in mice.The underlying molecular mechanisms may involve anti-inflammatory and antioxidant effects,in-creased NO content,and upregulation of mRNA ex-pression of aquaporins and tight-junction proteins.

Medical ultrasound technology is widely used for diagnosis and therapy in clinical practice.Ultrasound probes,which are directly contact with patients,pose a potential risk of pathogen transmission.This expert consen-sus was developed by a multidisciplinary team based on international guidelines,standards in China,and the results of a national survey,aiming to reduce the risk of healthcare-associated infection through standardizing reprocessing of medical ultrasound probes,and formulating consensus recommendations with the Delphi method.The consensus clarifies the reprocessing principles for three types of ultrasound probes of different infection risks:external-use ul-trasound probes,interventional percutaneous ultrasound probes,and internal-use ultrasound probes,puts forward systematic suggestions on the reprocessing standards and disinfection levels of ultrasound probe isolation covers and coupling agents,the reprocessing procedures and methods of ultrasound probes,as well as architectural layout and management of reprocessing,so as to provide a scientific prevention and control framework for ensuring ultrasound diagnosis and therapy safety.

Aim To identify the underlying target of bullatine A(BA)against rheumatoid arthritis(RA)u-sing limited proteolysis-small molecule mapping(LiP-SMap)drug target proteomics and to provide a scientif-ic basis for clinical application of Aconiti brachypodi Radix in the treatment of RA.Methods LiP-SMap drug target proteomics was employed to perform bioin-formatics analysis for comparing and validating the dif-ferential protein expression after BA intervention.A collagen-induced arthritis(CIA)model was estab-lished in DBA/1 mice using bovine type Ⅱ collagen.The mice were then divided into the CIA model group,methotrexate-positive control group(MTX group),and BA groups(10 mg·kg-1 and 20 mg·kg-1)based on their clinical scores.After drug intervention,the thera-peutic efficacy against RA was assessed by joint index scores and foot thickness measurements.Histopatholog-ical changes in the arthritic joints of CIA mice were e-valuated using hematoxylin and eosin(HE)staining.Enzyme-linked immunosorbent assay(ELISA)was employed to detect inflammatory cytokines interleukin-17(IL-17)and total IgG and IgG3 anti-collagen-spe-cific antibodies levels from the serum of CIA mice.Flow cytometry was used to detect the expression levels of intracellular Th17 cells(IL-17+CD4+T cells)and Th1 cells(IFN-γ+CD4+T cells).Fluorescent quanti-tative PCR was performed to detect the expression of genes related to differential proteins.Results The proteomic analysis identified Serpinb1a as a protein with strong binding affinity to BA,and KEGG enrich-ment analysis indicated IL-17 signaling pathway was a crucial pathway of BA in against RA.BA treatment significantly reduced clinical scores and foot thickness,improved local arthritis symptoms in CIA mice,and al-leviated inflammatory cell infiltration into arthritic joints(P＜0.05).Differential protein validation re-sults showed that BA had strong affinity with Serpinb1a(-5.92 kJ·mol-1)and downregulated the expres-sion of Serpinb1a mRNA.Furthermore,the administra-tion of BA markedly reduced serum IL-17 A levels from CIA mice,inhibited the expression of intracellular IL-17 A and IFN-γ cytokines in splenic CD4+T cells(P＜0.05),and significantly downregulated the transcrip-tional expression of IL-17F(P＜0.05).Conclusion BA exhibits therapeutic effects on collagen-induced arthritis,and its mechanism of action may involve the regulation of Serpinb1a and the IL-17 signaling path-way.

Aim To identify the underlying target of bullatine A(BA)against rheumatoid arthritis(RA)u-sing limited proteolysis-small molecule mapping(LiP-SMap)drug target proteomics and to provide a scientif-ic basis for clinical application of Aconiti brachypodi Radix in the treatment of RA.Methods LiP-SMap drug target proteomics was employed to perform bioin-formatics analysis for comparing and validating the dif-ferential protein expression after BA intervention.A collagen-induced arthritis(CIA)model was estab-lished in DBA/1 mice using bovine type Ⅱ collagen.The mice were then divided into the CIA model group,methotrexate-positive control group(MTX group),and BA groups(10 mg·kg-1 and 20 mg·kg-1)based on their clinical scores.After drug intervention,the thera-peutic efficacy against RA was assessed by joint index scores and foot thickness measurements.Histopatholog-ical changes in the arthritic joints of CIA mice were e-valuated using hematoxylin and eosin(HE)staining.Enzyme-linked immunosorbent assay(ELISA)was employed to detect inflammatory cytokines interleukin-17(IL-17)and total IgG and IgG3 anti-collagen-spe-cific antibodies levels from the serum of CIA mice.Flow cytometry was used to detect the expression levels of intracellular Th17 cells(IL-17+CD4+T cells)and Th1 cells(IFN-γ+CD4+T cells).Fluorescent quanti-tative PCR was performed to detect the expression of genes related to differential proteins.Results The proteomic analysis identified Serpinb1a as a protein with strong binding affinity to BA,and KEGG enrich-ment analysis indicated IL-17 signaling pathway was a crucial pathway of BA in against RA.BA treatment significantly reduced clinical scores and foot thickness,improved local arthritis symptoms in CIA mice,and al-leviated inflammatory cell infiltration into arthritic joints(P＜0.05).Differential protein validation re-sults showed that BA had strong affinity with Serpinb1a(-5.92 kJ·mol-1)and downregulated the expres-sion of Serpinb1a mRNA.Furthermore,the administra-tion of BA markedly reduced serum IL-17 A levels from CIA mice,inhibited the expression of intracellular IL-17 A and IFN-γ cytokines in splenic CD4+T cells(P＜0.05),and significantly downregulated the transcrip-tional expression of IL-17F(P＜0.05).Conclusion BA exhibits therapeutic effects on collagen-induced arthritis,and its mechanism of action may involve the regulation of Serpinb1a and the IL-17 signaling path-way.

Objective To develop dynamic prediction models based on multiple postnatal time points to support early diagnosis and individualized intervention for bronchopulmonary dysplasia(BPD)in preterm infants with gestational age<32 weeks.Methods Clinical data of 472 preterm infants with gestational age<32 weeks admitted to the Second Xiangya Hospital of Central South University between January 2016 and November 2020 were retrospectively analyzed.Multivariable logistic regression was applied to develop five independent prediction models at postnatal days 1,7,14,21,and 28.The performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Results Baseline characteristics such as gestational age and birth weight differed significantly between the BPD group(n=147)and the non-BPD group(n=325)(P<0.05).Predictors of BPD evolved across time points:on day 1,key predictors included gestational age,birth weight,Score for Neonatal Acute Physiology II(SNAP-II),invasive mechanical ventilation,and fraction of inspired oxygen>30%;by day 7,additional variables emerged,including fasting duration>2 days,mean feeding advancement rate<8.5 mL/(kg·d),neonatal respiratory distress syndrome,apnea of prematurity,and positive sputum culture;from day 14 onward,nutrition-and treatment-related indicators were incorporated additionally.The models demonstrated good discrimination at postnatal days 1,7,14,21,and 28,with AUCs of 0.917,0.927,0.939,0.944,and 0.968,respectively,and good calibration(Hosmer-Lemeshow P>0.05).Internal validation showed AUCs ranging from 0.899 to 0.958,indicating robust performance.Conclusions Dynamic postnatal prediction models incorporating indicators spanning perinatal factors,respiratory support,nutritional management,and therapeutic interventions demonstrate high predictive performance and facilitate dynamic risk assessment for BPD in preterm infants with gestational age<32 weeks.

Objective To develop dynamic prediction models based on multiple postnatal time points to support early diagnosis and individualized intervention for bronchopulmonary dysplasia(BPD)in preterm infants with gestational age<32 weeks.Methods Clinical data of 472 preterm infants with gestational age<32 weeks admitted to the Second Xiangya Hospital of Central South University between January 2016 and November 2020 were retrospectively analyzed.Multivariable logistic regression was applied to develop five independent prediction models at postnatal days 1,7,14,21,and 28.The performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Results Baseline characteristics such as gestational age and birth weight differed significantly between the BPD group(n=147)and the non-BPD group(n=325)(P<0.05).Predictors of BPD evolved across time points:on day 1,key predictors included gestational age,birth weight,Score for Neonatal Acute Physiology II(SNAP-II),invasive mechanical ventilation,and fraction of inspired oxygen>30%;by day 7,additional variables emerged,including fasting duration>2 days,mean feeding advancement rate<8.5 mL/(kg·d),neonatal respiratory distress syndrome,apnea of prematurity,and positive sputum culture;from day 14 onward,nutrition-and treatment-related indicators were incorporated additionally.The models demonstrated good discrimination at postnatal days 1,7,14,21,and 28,with AUCs of 0.917,0.927,0.939,0.944,and 0.968,respectively,and good calibration(Hosmer-Lemeshow P>0.05).Internal validation showed AUCs ranging from 0.899 to 0.958,indicating robust performance.Conclusions Dynamic postnatal prediction models incorporating indicators spanning perinatal factors,respiratory support,nutritional management,and therapeutic interventions demonstrate high predictive performance and facilitate dynamic risk assessment for BPD in preterm infants with gestational age<32 weeks.

Objective To investigate the value of fractional-order calculus(FROC)and continuous-time random-walk(CTRW)diffusion models based on readout segmentation of long variable echo-trains(RESOLVE)in identifying benign and malignant lesions in the head and neck.Methods A retrospective analysis was conducted on 61 patients pathologically confirmed head and neck lesions,including 19 benign lesions(BL)and 42 malignant lesions(ML).The ML were further divided into a lymphoma subgroup(LS)with 9 cases(14 lesions)and a non-lymphoma malignant lesion subgroup(MLS)with 33 cases.The parameters of DFROC,βFROC,μFROC,DCTRW,αCTRW and βCTRW were obtained from the two diffusion models;Independent sample t-tests or U tests were used to compare the differences in each parameter between benign and malignant groups and among various subgroups,and the receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of each parameter.Area under the curve(AUC)was compared by DeLong test.Results DFROC,μFROC,DCTRW and αCTRW showed significant differences between benign and malignant,BL and LS,BL and MLS and LS and MLS,with αCTRW showed the highest diagnostic efficacy;βFROC showed differences between BL and LS,BL and MLS,whileβCTRW did not show differences between benign and malignant groups,and among subgroups.Conclusion FROC and CTRW diffusion models based on RESOLVE can distinguish between benign and malignant head and neck lesions with multiple parameters,and provide metrics reflecting tissue heterogeneity.

Objective:This study aimed to integrate RNA-seq data to identify key genes associated with macrophage-ferroptosis and develop a prognostic model for hepatocellular carcinoma(HCC).Methods:We retrieved a dataset from the GEO database containing transcriptome data and clinical information for 163 samples.Macrophage-related genes were identified using WGCNA and immune infiltration analyses.Ferroptosis-related genes from the FerrDbV2 database were intersected with differentially expressed genes to obtain significant macrophage-ferroptosis-related genes.Hub genes were screened via protein interaction network construction,and key genes were identified using four machine learning algorithms.These genes exhibited significant expression differences between cancer and normal tissues and were closely linked to patient prognosis.ROC curve and KM survival analyses were performed,and expression levels were validated at the transcriptome and proteome levels.Results:Four key genes RRM2,KIF20A,PCK2,and PDK4 were identified and evaluated.RRM2 and KIF20A demonstrated high importance in classification prediction models and reliable performance in ROC and KM analyses(AUC＞0.9,P＜0.05).These genes regulate cancer cell proliferation/survival and macrophage polarization/function,influencing the tumor microenvironment and HCC progression.Conclusion:RRM2 and KIF20A regulate cancer cell proliferation and survival,modulate macrophage polarization and function,and influence the immune response in the tumor microenvironment.They can serve as prognostic biomarkers and potential immunotherapy targets for hepatocellular carcinoma.