Objective To explore the feasibility and reference value of allogeneic lung transplantation and postoperative monitoring in miniature pigs for lung transplantation research. Methods Two miniature pigs (R1 and R2) underwent left lung allogeneic transplantation. Complement-dependent cytotoxicity tests and blood cross-matching were performed before surgery. The main operative times and partial pressure of arterial oxygen (PaO₂) after opening the pulmonary artery were recorded during surgery. Postoperatively, routine blood tests, biochemical blood indicators and inflammatory factors were detected, and pathological examinations of multiple organs were conducted. Results The complement-dependent cytotoxicity test showed that the survival rate of lymphocytes between donors and recipients was 42.5%-47.3%, and no agglutination reaction occurred in the cross-matching. The first warm ischemia times of D1 and D2 were 17 min and 10 min, respectively, and the cold ischemia times were 246 min and 216 min, respectively. Ultimately, R1 and R2 survived for 1.5 h and 104 h, respectively. Postoperatively, in R1, albumin (ALB) and globulin (GLB) decreased, and alanine aminotransferase increased; in R2, ALB, GLB and aspartate aminotransferase all increased. Urea nitrogen and serum creatinine increased in both recipients. Pathological results showed that in R1, the transplanted lung had partial consolidation with inflammatory cell infiltration, and multiple organs were congested and damaged. In R2, the transplanted lung had severe necrosis with fibrosis, and multiple organs had mild to moderate damage. The expression levels of interleukin-1β and interleukin-6 increased in the transplanted lungs. Conclusions The allogeneic lung transplantation model in miniature pigs may systematically evaluate immunological compatibility, intraoperative function and postoperative organ damage. The data obtained may provide technical references for subsequent lung transplantation research.

ObjectiveTo investigate the correlation between neutrophil-to-lymphocyte ratio （NLR）， platelet-to-lymphocyte ratio （PLR）， systemic immune-inflammation index （SII） and the severity of intrauterine adhesions （IUA）. MethodsThe retrospective study included 380 patients who underwent transcervical resection of adhesions （TCRA） from December 2019 to March 2025. Based on the American Fertility Society （AFS） classification， patients were divided into mild （n=61）， moderate （n=225）， and severe （n=94） groups. NLR， PLR， and SII were calculated from preoperative blood tests. Statistical analyses included Kruskal-Wallis test and ordinal Logistic regression. ResultsNLR， PLR， and SII were significantly higher in the severe IUA group compared to the mild group （P<0.05）， with SII showing the strongest predictive ability （OR=1.004， P=0.001）. The number of intrauterine procedures was an independent risk factor （OR=1.27/level， P=0.016）. The predictive model ［Logit（P）=-0.676+0.241×operation times+0.004×SII］ effectively identified severe IUA cases. ConclusionInflammatory markers （particularly SII） are correlated with IUA severity and may serve as non-invasive tools for clinical assessment.

Background: Malignant pleural effusion (MPE), a common complication of advanced cancers, is associated with poor prognosis and reduced quality of life. Although host–tumor interactions are known to drive MPE development, the associated immune dynamics during disease progression remain unclear. Using a Lewis lung carcinoma-induced MPE model in C57BL/6JNidfc mice, we systematically evaluated general parameters and immune cell changes at two-day intervals throughout disease progression. Results: The day of Lewis lung carcinoma cell injection into the pleural space was designated as day 0. By day 10 post-injection (p.i.), MPE-bearing mice exhibited ~ 10% body weight loss, marking the experimental endpoint. Pleural tumor mass and pleural effusion volume were minimal up to day 4 p.i. but increased sharply from day 6 onward.CD45⁺ immune cell counts rose over time, and days 6, 8, and 10 p.i. marked key stages of MPE progression. On day 6, B cells, T cells, and natural killer cells, but not macrophages and neutrophils, increased significantly compared to earlier timepoints. By day 8, all immune cell subsets except T cells exceeded day 6 levels, and at day 10, natural killer cell numbers declined while others continued to increase. Besides, the numbers of CD8⁺ T cells, Th1 cells, regulatory T cells, and M2 macrophages progressively increased from day 6 to 10. Based on these data, days 6 and 10 were defined as early and advanced MPE stages, respectively, with distinct immune phenotypes. In advanced MPE, CD8⁺ T cells displayed reduced IFN-γ, TNF-α, Granzyme B, Perforin, FasL, and Ki-67, but upregulated PD-1 and CTLA-4 relative to early stage. Similarly, Th1 cells showed decreased IFN-γ, TNF-α, and IL-2 production along with reduced Ki-67 expression. Advanced-stage M2 macrophages exhibited lower MHC-II levels and impaired phagocytosis, but higher PD-L1 and IL-10 production, while neutrophils showed reduced TNF-α release and phagocytic activity. Conclusions Our findings characterize the temporal immune dynamics associated with MPE progression in a mouse model, revealing a transition from an early immunostimulatory state to a late immunosuppressive state. This study enhances our understanding of MPE immunopathogenesis and provides a foundation for developing precise, stagespecific therapeutic strategies.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

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.

ObjectiveThe frequency difference limen (FDL) serves as a fundamental metric utilized for effectively quantifying the precise perceptual capabilities of the central auditory system. However, traditional measurement methods rely heavily on the active behavioral responses of subjects and are consequently highly susceptible to the negative influence of confounding subjective factors. Furthermore, existing research paradigms frequently employ uniform stimulus configurations that overlook critical individual perceptual differences. Based on brain-computer interface (BCI) technology, this comprehensive study aims to establish an objective and quantitative evaluation method for auditory frequency discrimination by systematically analyzing and decoding the specific neural responses elicited at the exact threshold state. MethodsWe designed a personalized rapid serial auditory presentation (RSAP) paradigm customized based on each individual’s precise FDL. A cohort of eleven healthy participants was recruited to evaluate the paradigm using pure-tone sequences at a baseline frequency of 4 000 Hz. This experimental paradigm simulates a realistic auditory perception environment through the continuous presentation of acoustic stimuli, thereby allowing for an in-depth investigation into the specific neural representations evoked by weak frequency deviations at the threshold state. Given that auditory stimulus-evoked response features exhibit complex and differentiated spatiotemporal distribution patterns across multiple frequency domains, this study further deeply integrates the cross-scale feature interaction module with the dynamic spatiotemporal attention allocation strategy, innovatively proposing the Multi-Scale Spatial-Temporal Dual Attention Network (MS-STAMNet). Specifically, the network constructs parallel processing branches with multiple receptive fields and introduces a dynamic adaptive weighting strategy to precisely localize core neural activity signals, further deeply integrating multi-scale information through cross-branch feature information interaction to achieve robust single-trial decoding of weak auditory evoked responses. ResultsThe comprehensive electrophysiological data analysis demonstrated that subtle auditory frequency deviation stimuli presented at the threshold level successfully elicited pronounced N2 and P3 event-related potential features, reflecting pre-attentive mismatch detection and subsequent cognitive evaluation, which were prominently distributed over the frontal, central, and temporal regions of the scalp. In the complex time-frequency domain, the extracted neural response characteristics exhibited distinct, statistically significant event-related synchronization within both the low-frequency δ and θ frequency bands, which was simultaneously accompanied by a widespread, prominent event-related desynchronization within the higher α band. A comparative analysis of model performance demonstrated that MS-STAMNet achieved an average unweighted average recall (UAR) of (69.67±6.12)% and area under the curve (AUC) of 0.761 8±0.07, significantly outperforming the established baseline models such as EEGNet and PLNet. Furthermore, a distinct dissociation phenomenon was verified between neural decoding and behavioral performance through regression analysis (R²=0.016, P=0.709), indicating that this model can effectively capture the implicit features of subtle frequency deviations, even when they fail to trigger explicit conscious responses. Additionally, attention weight visualization analysis further reveals the highly accurate focus of the network on key features concentrated over the bilateral temporal and fronto-parietal regions. ConclusionThis study systematically and comprehensively uncovers the multi-dimensional spatiotemporal evolutionary patterns of complex neural responses processing subtle acoustic variations under long-sequence threshold auditory stimulation. Concurrently, it verifies the efficacy and robustness of the proposed MS-STAMNet architecture in accurately deciphering weak, single-trial electroencephalogram signals amidst complex background noise. Ultimately, these neurophysiological and algorithmic findings lay a solid theoretical and methodological foundation for the objective and quantitative evaluation of individual auditory cognitive capabilities in clinical applications, transcending the fundamental limitations of traditional behavioral paradigms and providing robust technical support for future auditory research and related clinical assessments.

Liver cancer (LC) remains one of the most prevalent tumors globally. Despite considerable advancements in its clinical treatment in recent years, the global burden of this disease is projected to increase. According to World Health Organization statistics, the number of LC deaths worldwide in 2022 was 760,000, ranking third among all cancers. Therefore, there is an urgent need to delve deeper into the realms of LC diagnosis, prognosis, and treatment. Proteomics, as an emerging technology leveraging mass spectrometry (MS)-based protein identification, liquid chromatography separation, and bioinformatics-driven data integration, enables the systematic characterization of proteome dynamics to address critical challenges in LC research. These challenges include the discovery of diagnostic and prognostic biomarkers as well as therapeutic targets. By scrutinizing the expression of specific proteins in both normal and cancerous tissues through high-throughput protein microarrays, researchers can uncover novel biomarkers. The use of these biomarkers alone or in combination with established ones holds the potential to significantly advance the fields of LC diagnosis, prognosis, and treatment. In general, the application of proteomics has significantly promoted the development of LC research. In this review, we summarized the latest advancements in the application of proteomics in LC, with a particular focus on diagnosis, prognosis, and treatment. We also concluded selected protein markers, aiming to offer guidance for further applications and present additional therapeutic targets for LC.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most prevalent chronic liver disorder worldwide, characterized by complex molecular regulatory networks driving its pathogenesis. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), serve as critical regulators of gene expression and have been increasingly recognized for their pivotal roles in MASLD development. Rather than functioning in isolation, these ncRNAs form intricate regulatory networks that integrate and amplify disease signals across multiple cellular compartments and pathological stages. This review provides a comprehensive overview of how these ncRNA networks orchestrate MASLD progression, focusing on their roles in metabolic dysregulation, inflammation, and fibrosis. We further evaluate the diagnostic potential of circulating ncRNAs as stable, non-invasive biomarkers for disease stratification and monitoring, and discuss emerging therapeutic strategies targeting ncRNAs, including antisense oligonucleotides, synthetic mimics, and advanced delivery platforms such as lipid nanoparticles and engineered exosomes. Despite significant progress, challenges related to delivery efficiency, tissue specificity, and safety remain barriers to clinical translation. By synthesizing current knowledge of ncRNA networks in MASLD and highlighting opportunities for therapeutic intervention, this review provides a roadmap for translating ncRNAs into clinical applications for this increasingly prevalent metabolic liver disease.

ObjectiveTo investigate the expression level of HBV cccDNA in patients in the convalescence stage of hepatitis B virus-related acute-on-chronic liver failure （HBV-ACLF） and its correlation with HBV markers and liver histopathological changes. MethodsA total of 30 patients in the convalescence stage of HBV-ACL who were hospitalized in The Ninth Hospital of Nanchang from January 2015 to October 2023 were enrolled as liver failure group， and 9 patients with chronic hepatitis B （CHB）， matched for sex and age， were enrolled as control group. The content of HBV cccDNA in liver tissue was measured， and its correlation with clinical data and laboratory markers was analyzed. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and a one-way analysis of variance or the Kruskal-Wallis H test was used for comparison between multiple groups； the Fisher’s exact test was used for comparison of categorical data between groups. A Spearman correlation analysis was performed. ResultsThe liver failure group had a significantly lower content of HBV cccDNA in liver tissue than the control group （-0.92±0.70 log₁₀ copies/cell vs -0.13±0.91 log₁₀ copies/cell， t=2.761， P=0.009）. In the liver failure group， there was no significant difference in the content of HBV cccDNA in liver tissue between the HBeAg-positive patients and the HBeAg-negative patients （P>0.05）； there was no significant difference in the content of HBV cccDNA in liver tissue between the patients with different grades （G0-G2， G3， and G4） of liver inflammatory activity （P>0.05）； there was no significant difference in the content of HBV cccDNA in liver tissue between the patients with different stages （S0-S2， S3， and S4） of liver fibrosis （P>0.05）； there was no significant difference in the content of HBV cccDNA in liver tissue between the patients with negative HBV DNA and those with positive HBV DNA （P>0.05）. For the liver failure group， the content of HBV cccDNA in liver tissue was positively correlated with the content of HBV DNA in liver tissue （r=0.426， P=0.043） and was not significantly correlated with the content of HBV DNA in serum （P>0.05）. ConclusionThere is a significant reduction in the content of HBV cccDNA in liver tissue in the convalescence stage of HBV-ACLF. HBV cccDNA exists continuously and stably in liver tissue and can better reflect the persistent infection and replication of HBV than HBV DNA in serum and liver tissue.