Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Adipose tissue macrophages (ATMs) are crucial immunomodulatory factors in the adipose tissue (AT) microenvironment, playing an irreplaceable role in maintaining the balance of the local immune system and regulating metabolic homeostasis. Under obese conditions, the excessive accumulation of lipids leads to abnormal expansion of adipose tissue, which further disrupts the homeostasis of the local microenvironment, including the imbalance of inflammatory factors, the occurrence of oxidative stress, and the damage of microcirculation. As an essential immune cell population in adipose tissue, ATMs are deeply involved in the occurrence and progression of metabolic disorders and multiple obesity-related diseases, and their functional abnormalities are closely related to the initiation and development of adipose tissue inflammation and systemic metabolic disorders. The interaction between ATMs and adipokines, including adiponectin, leptin, resistin and retinol-binding protein 4 (RBP4), acts as the core immunological and molecular mechanism linking adipose tissue inflammation to continuous disease deterioration, and this interaction is also a key research focus in the field of obesity-related diseases in recent years. This review discusses in detail the facilitating effect of the AT inflammatory microenvironment on the differentiation of peripheral monocytes into ATMs, elaborating on the specific molecular mechanisms by which various inflammatory mediators and abnormal metabolic products in the inflammatory microenvironment induce the differentiation of peripheral monocytes into functional ATMs. It also focuses on the regulatory mechanisms of chemokine-mediated ATM polarization and recruitment, including the specific roles of key chemokines like monocyte chemoattractant protein‑1 (MCP-1) and C‑X‑C motif chemokine ligand 10 (CXCL10) in mediating the recruitment of ATMs to adipose tissue, as well as the molecular pathways that regulate the switch between M1 pro-inflammatory phenotype and M2 anti-inflammatory phenotype of ATMs. In addition, this review explores the specific process by which ATMs trigger AT inflammation by secreting various pro-inflammatory factors such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-1β, which further amplify the local inflammatory response and disrupt the metabolic homeostasis of adipose tissue. Furthermore, it analyzes the specific binding patterns and molecular characteristics of adiponectin, leptin, resistin and RBP4 with ATM surface receptors, and clarifies how the activation of downstream immune signaling pathways, such as Janus kinase‑signal transducer and activator of transcription (JAK-STAT), nuclear factor‑κB (NF‑κB), and phosphatidylinositol 3‑kinase‑protein kinase B (PI3K-AKT), triggered by these binding processes, induces the occurrence and development of various obesity-related diseases, including insulin resistance, cancer, metabolic-associated steatohepatitis (MASH) and cardiovascular diseases. This paper highlights the unique and crucial role of the interaction between ATMs and adipokines in the occurrence and progression of obesity-related diseases, emphasizing that this interaction is a key link connecting local adipose tissue inflammation to systemic metabolic disorders. It further summarizes the potential therapeutic strategies targeting the ATM-adipokine axis, and comprehensively illustrates three major clinical application barriers, namely biological complexity, technical bottlenecks, and clinical translation obstacles, in the process of applying these therapeutic strategies. For each barrier, this review puts forward corresponding feasible solutions and clear research directions, which not only enrich the theoretical system of the ATM-adipokine axis in the field of obesity research, but also provide a solid theoretical basis and practical ideas for the clinical intervention, prevention and treatment of obesity and its related diseases.

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.

BACKGROUND: Knee osteoarthritis (OA) is still challenging to prevent or treat. Enhanced endoplasmic reticulum (ER) stress and increased pyroptosis in chondrocytes may be responsible for cartilage degeneration. This study aims to investigate the effect of ER stress on chondrocyte pyroptosis and the upstream regulatory mechanisms, which have rarely been reported. METHODS: The expression of the histone methyltransferase enhancer of zeste homolog 2 (EZH2), microRNA-142-3p (miR-142-3p), and high mobility group box 1 (HMGB1) and the levels of ER stress, pyroptosis, and metabolic markers in normal and OA chondrocytes were investigated by western blotting, quantitative polymerase chain reaction, immunohistochemistry, fluorescence in situ hybridization, fluorescein amidite-tyrosine-valine-alanine-aspartic acid-fluoromethyl ketone (FAM-YVAD-FMK)/Hoechst 33342/propidium iodide (PI) staining, lactate dehydrogenase (LDH) release assays, and cell viability assessments. The effects of EZH2, miR-142-3p, and HMGB1 on ER stress and pyroptosis and the hierarchical regulatory relationship between them were analyzed by chromatin immunoprecipitation, luciferase reporters, gain/loss-of-function assays, and rescue assays in interleukin (IL)-1β-induced OA chondrocytes. The mechanistic contribution of EZH2, miR-142-3p, and HMGB1 to chondrocyte ER stress and pyroptosis and therapeutic prospects were validated radiologically, histologically, and immunohistochemically in surgically induced OA rats. RESULTS: Increased EZH2 and HMGB1, decreased miR-142-3p, enhanced ER stress, and activated pyroptosis in chondrocytes were associated with OA occurrence and progression. EZH2 and HMGB1 exacerbated and miR-142-3p alleviated ER stress and pyroptosis in OA chondrocytes. EZH2 transcriptionally silenced miR-142-3p via H3K27 trimethylation, and miR-142-3p posttranscriptionally silenced HMGB1 by targeting the 3'-UTR of the HMGB1 gene. Moreover, ER stress mediated the effects of EZH2, miR-142-3p, and HMGB1 on chondrocyte pyroptosis. In vivo experiments mechanistically validated the hierarchical regulatory relationship between EZH2, miR-142-3p, and HMGB1 and their effects on chondrocyte ER stress and pyroptosis. CONCLUSIONS A novel EZH2/miR-142-3p/HMGB1 axis mediates chondrocyte pyroptosis and cartilage degeneration by regulating ER stress in OA, contributing novel mechanistic insights into OA pathogenesis and providing potential targets for future therapeutic research.
Enhancer of Zeste Homolog 2 Protein/genetics* ; Osteoarthritis, Knee/pathology* ; Chondrocytes/metabolism* ; Pyroptosis/physiology* ; HMGB1 Protein/genetics* ; MicroRNAs/metabolism* ; Endoplasmic Reticulum Stress/genetics* ; Humans ; Animals ; Rats ; Male ; Rats, Sprague-Dawley ; Middle Aged

As an important part of the cytoskeleton, microtubules play a crucial role in many cellular processes, such as cell division, intracellular transport, and maintaining cell morphology. The MAP1 family is an important family of microtubule-associated proteins, which includes three members: MAP1A, MAP1B, and MAP1S. These proteins are widely involved in the dynamic regulation of the cytoskeleton and play a key role in the development and function of the central nervous system, especially in the development and function of neurons. This study reviews the research progress of the MAP1 family, mainly focusing on the structure and function of MAP1 family members, and paying particular attention to their roles in neuronal development and regeneration, regulatory mechanisms, and neurodegenerative diseases.
Humans ; Animals ; Microtubule-Associated Proteins/classification* ; Neurons/cytology* ; Neurodegenerative Diseases/physiopathology* ; Microtubules/physiology* ; Cytoskeleton/physiology*

Polygonati Rhizoma demonstrates significant potential for addressing both chronic and hidden hunger. The supply of high-quality seedlings is a primary factor influencing the development of the Polygonati Rhizoma industry. Warm water soaking is often used in agriculture to promote the rapid germination of seeds, while its application and molecular mechanism in Polygonati Rhizoma have not been reported. To rapidly obtain high-quality seedlings, this study treated Polygonatum kingianum var. grandifolium seeds with sand storage at low temperatures, warm water soaking, and cultivation temperature gradients. The results showed that the culture at 25 ℃ or sand storage at 4 ℃ for 2 months rapidly broke the seed dormancy of P. kingianum var. grandifolium, while the culture at 20 ℃ or sand storage at 4 ℃ for 1 month failed to break the seed dormancy. Soaking seeds in 60 ℃ warm water further increased the germination rate, germination potential, and germination index. Specifically, the seeds soaked at 60 ℃ and cultured at 25 ℃ without sand storage treatment(Aa25) achieved a germination rate of 78. 67%±1. 53% on day 42 and 83. 40%±4. 63% on day 77. The seeds pretreated with sand storage at 4 ℃ for 2 months, soaked in 60 ℃ water, and then cultured at 25 ℃ achieved a germination rate comparable to that of Aa25 on day 77. Transcriptomic analysis indicated that warm water soaking might promote germination by triggering reactive oxygen species( ROS), inducing the expression of heat shock factors( HSFs) and heat shock proteins( HSPs), which accelerated DNA replication, transcript maturation, translation, and processing, thereby facilitating the accumulation and turnover of genetic materials. According to the results of indoor controlled experiments and field practices, maintaining a germination and seedling cultivation environment at approximately 25 ℃ was crucial for the one-year seedling cultivation of P. kingianum var. grandifolium.
Germination ; Seedlings/genetics* ; Water/metabolism* ; Seeds/metabolism* ; Polygonatum/genetics* ; Temperature ; Plant Proteins/genetics* ; Plant Dormancy

Sophorae Flavescentis Radix is one of the commonly used traditional Chinese medicine in China, and a large amount of pharmaceutical residue generated during its processing and production is discarded as waste, which not only wastes resources but also pollutes the environment. Therefore, elucidating the chemical composition of the residue of Sophorae Flavescentis Radix and the differences between the residue and Sophorae Flavescentis Radix itself is of great significance for the comprehensive utilization of the residue. This study, based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) technology combined with multivariate statistical methods, provides a thorough characterization, identification, and differential analysis of the overall components of Sophorae Flavescentis Radix and its residue. Firstly, 61 compounds in Sophorae Flavescentis Radix were rapidly identified based on their precise molecular weight, fragment ions, and compound abundance, using a self-constructed compound database. Among them, 41 compounds were found in the residue, mainly alkaloids and flavonoids. Secondly, through principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA), 15 key compounds differentiating Sophorae Flavescentis Radix from its residue were identified. These included highly polar alkaloids, such as oxymatrine and oxysophocarpine, which showed significantly reduced content in the residue, and less polar flavonoids, such as kurarinone and kuraridin, which were more abundant in the residue. In summary, this paper clarifies the overall composition, structure, and content differences between Sophorae Flavescentis Radix and its residue, suggesting that the residue of Sophorae Flavescentis Radix can be used as a raw material for the extraction of its high-activity components, with promising potential for development and application in cosmetics and daily care. This research provides a scientific basis for the future comprehensive utilization of Sophorae Flavescentis Radix and its residue.
Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Mass Spectrometry/methods* ; Sophora/chemistry* ; Flavonoids/chemistry* ; Alkaloids/chemistry*