Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective This study investigated feasible cases and their significance in promoting the"generalized"development of inspection through digital-intelligent equipment.Methods A qualitative research approach was used,involving interviews conducted between February 2025 and March 2025 with experts in traditional Chinese medicine diagnostics,clinical research methodology,medical engineering integration,and related disciplines,using both online and offline methods.In accordance with the Consolidated Criteria for Reporting Qualitative Research,feasible cases involving the specific application of digital equipment in various parts of observation were collected through item enrichment.The significance of extending observation capabilities via these cases was analyzed,along with the overall implications of integrating digital technologies with traditional inspection method.Results Interviews were completed with 11 experts from domestic universities and research institutes in the fields of traditional Chinese medicine diagnosis,medical engineering integration,and related disciplines.A total of 78 feasible cases of digital-intelligent inspection were identified,along with 69 insights regarding the significance of enhancing the inspection capabilities.These insights were synthesized into two dimensions and 23 holistic meanings.The first dimension is to expand the scope of inspection,including obtaining internal environmental characteristics,observing external environmental characteristics,expanding thermodynamic characteristic data,and crossing time and space.The second dimension is to improve the quality of observation and diagnosis information collection and analysis,including 19 specific meanings,such as standardized collection environment,objective quantification,and refined observation.Conclusion Digital-intelligent equipment plays a significant role in expanding the scope of inspection content and achieving high-quality acquisition and analysis of extensive inspection information.These advancements extend and enrich the capabilities of traditional inspection method in traditional Chinese medicine.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

OBJECTIVE: To investigate the therapeutic potential of pseudolaric acid B (PAB) on non-alcoholic fatty liver disease (NAFLD) and its underlying molecular mechanism in vitro and in vivo. METHODS: Eight-week-old male C57BL/6J mice (n=32) were fed either a normal chow diet (NCD) or a high-fat diet (HFD) for 8 weeks. The HFD mice were divided into 3 groups according to a simple random method, including HFD, PAB low-dose [10 mg/(kg·d), PAB-L], and PAB high-dose [20 mg/(kg·d), PAB-H] groups. After 8 weeks of treatment, glucose metabolism and insulin resistance were assessed by oral glucose tolerance test (OGTT) and insulin tolerance test (ITT). Biochemical assays were used to measure the serum and cellular levels of total cholesterol (TC), triglycerides (TG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). White adipose tissue (WAT), brown adipose tissue (BAT) and liver tissue were subjected to hematoxylin and eosin (H&E) staining or Oil Red O staining to observe the alterations in adipose tissue and liver injury. PharmMapper and DisGeNet were used to predict the NAFLD-related PAB targets. Peroxisome proliferator-activated receptor alpha (PPARα) pathway involvement was suggested by Kyoto Encyclopedia of Genes and Genomes (KEGG) and search tool Retrieval of Interacting Genes (STRING) analyses. Luciferase reporter assay, cellular thermal shift assay (CETSA), and drug affinity responsive target stability assay (DARTS) were conducted to confirm direct binding of PAB with PPARα. Molecular dynamics simulations were applied to further validate target engagement. RT-qPCR and Western blot were performed to assess the downstream genes and proteins expression, and validated by PPARα inhibitor MK886. RESULTS: PAB significantly reduced serum TC, TG, LDL-C, AST, and ALT levels, and increased HDL-C level in HFD mice (P<0.01). Target prediction analysis indicated a significant correlation between PAB and PPARα pathway. PAB direct target binding with PPARα was confirmed through luciferase reporter assay, CETSA, and DARTS (P<0.05 or P<0.01). The target engagement between PAB and PPARα protein was further confirmed by molecular dynamics simulations and the top 3 amino acid residues, LEU321, MET355, and PHE273 showed the most significant changes in mutational energy. Subsequently, PAB upregulated the genes expressions involved in lipid metabolism and mitochondrial biogenesis downstream of PPARα (P<0.05 or P<0.01). Significantly, the PPARα inhibitor MK886 effectively reversed the lipid-lowering and PPARα activation properties of PAB (P<0.05 or P<0.01). CONCLUSION PAB mitigates lipid accumulation, ameliorates liver damage, and improves mitochondrial biogenesis by binding with PPARα, thus presenting a potential candidate for pharmaceutical development in the treatment of NAFLD.
Animals ; PPAR alpha/metabolism* ; Non-alcoholic Fatty Liver Disease/pathology* ; Male ; Mice, Inbred C57BL ; Lipid Metabolism/drug effects* ; Diterpenes/therapeutic use* ; Organelle Biogenesis ; Diet, High-Fat ; Humans ; Mice ; Liver/metabolism* ; Insulin Resistance ; Mitochondria/metabolism* ; Molecular Docking Simulation

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.