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 To investigate the mechanism of Shenling baizhu san （SLBZS） in ameliorating ulcerative colitis （UC）. METHODS Mice were randomly divided into normal group， model group， and low-， medium-， high-dose SLBZS groups （3， 6， 12 g/kg）， with 10 mice in each group. Except for the normal group， mice in other groups were given free access to 3% dextran sulfate sodium solution for 7 days to establish UC models. Simultaneously， mice in each group were intragastrically administered corresponding medicinal liquid or double-distilled water once a day for consecutive 7 days. After the last administration， the histopathological morphology of colon tissues was observed； the serum levels of inflammatory factors including tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β） and IL-18 were detected； the total bile acid contents in liver， gallbladder and colon tissues were determined； the expression level of NOD-like receptor family pyrin domain-containing protein 3 （NLRP3） in colon tissues was tested. The expression levels of flora metabolism-related proteins [G protein-coupled receptor 41（GPR41），GPR43，farnesoid X receptor （FXR）， G protein-coupled bile acid receptor 1 （TGR5）， flavin-containing monooxygenase 3 （FMO3）， cytochrome P450 family 27 subfamily A member 1 （CYP27A1）， CYP7A1] in liver or colon tissues， as well as the proteins related to Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB）/NLRP3 inflammatory axis [TLR4， NF-κB， phosphorylated NF-κB （p-NF-κB）， myeloid differentiation factor 88 （MyD88）， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， caspase-1] in colon tissues were measured. RESULTS Compared with the model group， the colon tissue injury and inflammatory cell infiltration were alleviated in medium- and high-dose SLBZS groups. The serum levels of TNF-α， IL-1β and IL-18， total bile acid contents in liver and colon tissues， as well as the protein expression levels of FMO3 and CYP7A1 in liver tissues， TLR4， p-NF-κB， NF-κB， MyD88， NLRP3， ASC and caspase-1 in colon tissues were significantly decreased （P＜0.05）. Meanwhile， the total bile acid content in gallbladder， the protein expression levels of GPR41 and GPR43 in colon tissues， along with CYP27A1， FXR and TGR5 in liver tissues were significantly increased （P＜0.05）. CONCLUSIONS SLBZS may relieve colonic inflammatory injury and ameliorate UC by regulating the expression of flora metabolism-related proteins and inhibiting the abnormal activation of TLR4/NF-κB/NLRP3 inflammatory axis.

Objective To evaluate the cost-utility of risdiplam in the treatment of pediatric spinal muscular atrophy （SMA） and analyze changes in patients’ out-of-pocket economic burden under the medical insurance scenarios. Methods A Markov model was developed from the healthcare system perspective to compare the long-term costs and quality-adjusted life years （QALYs） of risdiplam treatment versus conventional therapy. The incremental cost-utility ratio （ICUR） was calculated. One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to assess the robustness of the model. On this basis, health insurance scenarios were simulated to evaluate patients’ individual economic burden. Results Base-case analysis showed that risdiplam treatment generated additional health benefits but substantially increased medical costs. The resulting ICUR did not demonstrate a clear cost-utility advantage under the current willingness-to-pay threshold. Sensitivity analyses indicated that the model results were relatively robust, with drug costs and key utility parameters being the main drivers of economic outcomes. Health insurance scenario analysis demonstrated that increasing reimbursement levels and reducing patient copayment rates could significantly alleviate patients’ financial burden. Conclusion Risdiplam for pediatric SMA faces economic challenges under the current health insurance payment framework in China. However, optimizing health insurance reimbursement policies and developing multi-tiered healthcare security mechanisms may improve its affordability and accessibility.

Tissue repair requires the reconstruction of functional vascular networks to restore oxygen and nutrient delivery, eliminate metabolic waste, and maintain tissue homeostasis. Although biochemical factors such as growth factors and cytokines have been extensively studied in vascular regeneration, increasing evidence indicates that mechanical signals from the extracellular matrix (ECM) are equally important regulators of angiogenesis. Matrix stiffness, as a major biomechanical property of the tissue microenvironment, provides critical information that influences endothelial cell (EC) behavior and vascular remodeling through mechanotransduction. However, the biological effects of matrix stiffness are not universally defined as either pro- or anti-angiogenic, but are highly dependent on tissue context, cellular composition, disease progression, and the dynamic changes occurring during tissue repair. Therefore, understanding how matrix stiffness regulates vascular regeneration is essential for developing more precise strategies for tissue engineering and regenerative medicine. In this review, we summarize recent advances in the regulation of angiogenesis by matrix stiffness during tissue repair from multiple perspectives. First, we discuss the direct effects of matrix stiffness on EC behaviors, including differentiation, morphological remodeling, migration, proliferation, barrier maintenance, and vascular network formation. ECs sense mechanical alterations in the surrounding matrix through various mechanosensitive structures, including integrins, focal adhesion complexes, and mechanosensitive ion channels such as Piezo1 and TRPV proteins. These mechanical signals are subsequently transmitted through intracellular pathways involving FAK, RhoA/ROCK, MAPK, and Hippo-YAP/TAZ signaling, leading to cytoskeletal reorganization and transcriptional regulation. Through these mechanisms, matrix stiffness regulates endothelial functional states and determines the balance between regenerative vascular formation and pathological vascular remodeling. Beyond the direct regulation of ECs, we further highlight the importance of stiffness-mediated intercellular communication within the regenerative microenvironment. Matrix stiffness can regulate the behavior and secretory profiles of vascular-associated cells, including mesenchymal stem cells and macrophages, thereby indirectly affecting endothelial function through paracrine mechanisms. Changes in matrix mechanics influence the secretion of angiogenic factors, inflammatory cytokines, and extracellular vesicles from these cells, creating a mechanical regulation network that coordinates vascular regeneration. This perspective extends the traditional concept of matrix stiffness from a physical support structure to an active regulatory signal that integrates multiple cellular responses during tissue repair. Furthermore, we discuss the tissue-specific effects of matrix stiffness in vascular regeneration across different organs, including the aorta, lung, liver, and heart. Although excessive matrix stiffening is frequently associated with fibrosis and vascular dysfunction, the consequences of mechanical changes vary considerably among tissues. Moderate stiffness alterations may support endothelial activation and vascular stabilization in certain regenerative contexts, whereas persistent pathological stiffening can promote inflammation, endothelial dysfunction, and impaired vascular repair. These findings emphasize that the biological meaning of “soft” and “stiff” microenvironments should be interpreted according to specific tissue and experimental conditions rather than as universal mechanical classifications. Finally, we summarize current challenges and future perspectives in this field. A major limitation is the lack of standardized mechanical characterization among different studies, as stiffness measurements are influenced by material properties, testing methods, and experimental conditions, limiting direct comparison across research systems. Moreover, most existing models fail to fully reproduce the dynamic and viscoelastic properties of native ECM during tissue regeneration. Future studies should combine advanced biomaterials with standardized mechanical analysis, organoid models, and multi-omics approaches to establish more accurate mechanical regulatory maps. Overall, this review proposes that matrix stiffness is not merely a structural feature of tissues, but an active biological signal that regulates vascular regeneration through coordinated mechanotransduction and multicellular interactions. A deeper understanding of stiffness-mediated vascular regulation will provide new theoretical insights and therapeutic opportunities for improving tissue repair outcomes.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

Objective To examine the significance of susceptible gene detection for hereditary cancer syndrome (HCS) among general population. Methods A total of 2 928 individuals undergoing routine health examinations in Healthcare Center of Zhongshan Hospital, Fudan University, from September 2021 to April 2024 were enrolled retrospectively. Next generation sequencing was employed to identify susceptible genes for HCS. American College of Medical Genetics and Genomics (ACMG) guideline was used to analyze the pathogenicity of variants. Clinical data, imagings, follow-up data were also collected. Results The overall mutation rate of HCS panel was 3.59% (105/2 928), with 0.61% (18/2 928) for MutY DNA glycosylase (MUTYH), 0.27% (8/2 928) for breast cancer susceptibility gene 1/2 (BRCA1/2) and 0.23% (7/2 928) for mismatch repair (MMR) genes. Conclusions Healthy individuals carrying tumor susceptible genes usually lack the relevant clinical phenotypes. Whether comprehensive testing needs to be carried out among healthy people remains to be further explored.

BACKGROUND: Immunosuppression is closely related to the pathogenesis of sepsis, but the underlying mechanisms have not yet been fully elucidated. In this study, we aimed to examine the role of the Sterile Alpha Motif, Src Homology 3 domain and nuclear localization signal 1 (SAMSN1) in sepsis and elucidate its potential molecular mechanism in sepsis induced immunosuppression. METHODS: RNA sequencing databases were used to validate SAMSN1 expression in sepsis. The impact of SAMSN1 on sepsis was verified using gene knockout mice. Flow cytometry was employed to delineate how SAMSN1 affects immunity in sepsis, focusing on immune cell types and T cell functions. Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated gene editing in RAW264.7 macrophages enabled interrogation of SAMSN1 's regulatory effects on essential macrophage functions, including cell proliferation and phagocytic capacity. The mechanism of SAMSN1 in the interaction between macrophages and T cells was investigated using the RAW264.7 cell line and primary cell lines. RESULTS: SAMSN1 expression was significantly increased in patients with sepsis and was positively correlated with sepsis mortality. Genetic deletion of Samsn1 in murine sepsis model improved T cell survival, elevated T cell cytolytic activity, and activated T cell signaling transduction. Concurrently, Samsn1 knockout augmented macrophage proliferation capacity and phagocytic efficiency. In macrophage, SAMSN1 binds to Kelch-like epichlorohydrin-associated protein 1 (KEAP1), causing nuclear factor erythroid 2-related factor 2 (NRF2) to dissociate from the KEAP1-NRF2 complex and translocate into the nucleus. This promotes the transcription of the coinhibitory molecules CD48/CD86/carcinoembryonic antigen related cell adhesion molecule 1 (CEACAM1), which bind to their corresponding receptors natural killer cell receptor 2B4/CD152/T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) on the surface of T cells, inducing T-cell exhaustion. CONCLUSIONS SAMSN1 deletion augmented adaptive T cell immunity and macrophage phagocytic-proliferative dual function. Furthermore, it mediates the KEAP1-NRF2 axis, which affects the expression of coinhibitory molecules on macrophages, leading to T-cell exhaustion. This novel immunosuppression mechanism potentially provides a candidate molecular target for sepsis immunotherapy.
Animals ; NF-E2-Related Factor 2/metabolism* ; Mice ; Macrophages/immunology* ; Sepsis/metabolism* ; Kelch-Like ECH-Associated Protein 1/genetics* ; T-Lymphocytes/immunology* ; Humans ; Signal Transduction/physiology* ; RAW 264.7 Cells ; Mice, Knockout ; Mice, Inbred C57BL ; Male ; Flow Cytometry ; T-Cell Exhaustion

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis