Osteoarthritis (OA), a highly prevalent degenerative joint disease worldwide, is defined by articular cartilage degradation, abnormal bone remodeling, and persistent chronic inflammation. It severely compromises patients’ quality of life, and currently, there is no radical cure. Abnormal mechanical stress is widely regarded as a core driver of OA pathogenesis, and the exploration of mechanical signal perception and transduction mechanisms has become crucial for deciphering OA’s pathophysiological processes. Piezo1, a key mechanosensitive cation channel belonging to the Piezo protein family, has recently gained significant attention due to its pivotal role in mediating cellular responses to mechanical stimuli in joint tissues. This review systematically examines Piezo1’s expression patterns, regulatory mechanisms, and pathological functions in OA, with a particular focus on its dual roles in modulating chondrocyte homeostasis and bone metabolism disorders, while also delving into the underlying molecular signaling pathways and potential therapeutic implications. Piezo1, consisting of approximately 2 500 amino acids and forming a unique trimeric propeller-like structure, is widely expressed in chondrocytes, osteocytes, mesenchymal stem cells, and synovial cells. It exhibits permeability to cations such as Ca²⁺, K⁺, and Na⁺, and directly responds to membrane tension changes induced by mechanical stimuli like fluid shear stress and mechanical overload. In OA patients and animal models, Piezo1 expression is significantly upregulated, especially in cartilage regions subjected to abnormal mechanical stress (e.g., human temporomandibular joint cartilage). This overexpression is closely associated with aggravated cartilage degeneration, increased chondrocyte apoptosis, accelerated cellular senescence, and intensified inflammatory responses. Mechanical overload and pro-inflammatory cytokines (e.g., IL-1β) are key inducers of Piezo1 upregulation: IL-1β activates the PI3K/AKT/mTOR signaling pathway to enhance Piezo1 expression, forming a pathogenic positive feedback loop that inhibits chondrocyte autophagy, promotes apoptosis, and further accelerates joint degeneration. Mechanistically, Piezo1 mediates OA progression through multiple interconnected pathways. When activated by mechanical stress, Piezo1 triggers excessive Ca²⁺ influx, leading to endoplasmic reticulum stress (ERS) and mitochondrial dysfunction, which directly induce chondrocyte apoptosis. This process involves the activation of downstream signaling cascades such as cGAS-STING and YAP-MMP13/ADAMTS5. YAP, a transcriptional regulator, upregulates the expression of matrix metalloproteinase 13 (MMP13) and aggrecanase (ADAMTS5), thereby accelerating cartilage matrix degradation. Additionally, Piezo1-driven Ca²⁺ overload promotes the accumulation of reactive oxygen species (ROS) and upregulates senescence markers (p16 and p21), accelerating chondrocyte senescence via the p38MAPK and NF-κB pathways. Senescent chondrocytes secrete senescence-associated secretory phenotype (SASP) factors (e.g., IL-6, IL-1β), further amplifying joint inflammation. In terms of bone metabolism, Piezo1 maintains joint homeostasis by promoting the differentiation of fibrocartilage stem cells into chondrocytes and balancing bone formation and resorption through regulating the FoxC1/YAP axis and RANKL/OPG ratio. Therapeutically, targeting Piezo1 shows promising potential. Preclinical studies have demonstrated that Piezo1 inhibitors (e.g., GsMTx4) can reduce joint damage and alleviate pain in OA mice. Simultaneously, siRNA-mediated co-silencing of Piezo1 and TRPV4 (another mechanosensitive channel) decreases intracellular Ca²⁺ concentration, inhibits chondrocyte apoptosis, and promotes cartilage repair. Conditional knockout of Piezo1 using Gdf5-Cre transgenic mice alleviates cartilage degeneration in post-traumatic OA models by downregulating MMP13 and ADAMTS5 expression. Despite existing challenges, such as off-target effects of inhibitors, inefficient local drug delivery, and interindividual genetic variability, strategies like developing selective Piezo1 antagonists, optimizing targeted nanocarriers, and combining Piezo1-targeted therapy with physical therapy provide viable avenues for clinical translation. The authors propose that Piezo1 serves as a critical therapeutic target for OA, and future research should focus on deciphering its context-dependent regulatory networks, developing tissue-specific intervention strategies, and validating their efficacy and safety in clinical trials to address the unmet medical needs of OA patients.

Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

ObjectiveTo observe the clinical efficacy of electroacupuncture in treatment of simple obesity patients and its effects on the metabolism-inflammation network. MethodsSeventy-two patients with simple obesity were randomly divided into a electroacupuncture group and a sham electroacupuncture group， with 36 patients in each group. In the electroacupuncture group， conventional acupuncture was applied at Zhongwan （CV 12）， bilateral Tianshu （ST 25）， bilateral Daheng （SP15）， Qihai （CV 6）， Guanyuan （CV 4）， bilateral Zusanli （ST 36） and Fenglong （ST 40）. The sham electroacupuncture group used placebo needle at same acupoints as the electroacupuncture group. Both groups were given sparse-dense waves with a frequency of 2/10 Hz， 30 minutes per session， 3 times a week， for a total of 8 weeks of treatment. The changes of human body parameters including body weight， body mass index （BMI）， waist circumference， and body fat percentage （BFP）， metabolic factors including serum fasting blood glucose （FBG）， triglyceride （TG）， total cholesterol （TC）， high density lipoprotein （HDL）， low density lipoprotein （LDL）， leptin， and ghrelin， and inflammatory factors including interleukin-6 （IL-6） and tumor necrosis factor α （TNF-α） were compared before and after treatment. Correlations between changes in leptin， ghrelin and inflammatory factors were further analyzed. ResultsWaist circumference was significantly reduced after treatment in both groups compared with baseline （P＜0.05）， and the post-treatment waist circumference was lower in the electroacupuncture group than in the sham electroacupuncture group （P＜0.05）； body weight， BMI and BFP decreased significantly after treatment compared to pretreatment levels in the electroacupuncture group （P＜0.05）. Serum leptin， IL-6 and TNF-α declined significantly after treatment in both groups versus baseline （P＜0.05）； the electroacupuncture group had lower post-treatment levels of leptin， IL-6 and TNF-α as well as larger pre-post changes than the sham group （P＜0.05）； ghrelin increased markedly after treatment in both groups （P＜0.05）， with higher post-treatment ghrelin and greater pre-post variation observed in the electroacupuncture group （P＜0.05）. In the electroacupuncture group， changes in ghrelin were negatively correlated with IL-6 and positively correlated with TNF-α （P＜0.01）； in the sham electroacupuncture group， ghrelin changes were negatively correlated with both IL-6 and TNF-α， whereas leptin changes were positively correlated with the two inflammatory markers （P＜0.01）. ConclusionElectroacupuncture can effectively improve clinical manifestations， as well as regulate serum metabolic and pro-inflammatory factors in patients with simple obesity， and discrepant correlation patterns of metabolism-inflammation are observed between the two groups.

This paper has summarized current studies on retinitis pigmentosa （RP） from two perspectives， which were disease mechanism insights from western medicine， and etiology， pathogenesis and therapeutic principles in traditional Chinese medicine （TCM）. From the perspective of western medicine， the understanding of RP has evolved from an early single-factor explanation focusing on pathogenic gene mutations to a more comprehensive， multifactorial model involving genetic abnormalities， photoreceptor cell degeneration， retinal pigment epithelium dysfunction， oxidative stress， inflammatory responses， microenvironmental imbalance， and vascular insufficiency. In TCM， RP is considered to be a disorder manifested in the eyes but rooted in dysfunction of the zang-fu （脏腑） organs. Its pathogenesis is primarily associated with congenital insufficiency， liver-kidney depletion， impaired spleen function of transportation and transformation， and stasis obstructing the meridians. The core pathological mechanism can be summarized as "deficiency complicated by stasis"， emphasizing holistic imbalance， dynamic disease progression， and syndrome differentiation and treatment. The differences and complementarities between the two medical systems in understanding disease progression are further discussed. RP is proposed to be more appropriately regarded as a complex disease characterized by long-term progression， stage-dependent evolution， and persistent decompensation. Western medicine contributes to elucidating the molecular mechanisms underlying RP and provides the foundation for targeted therapeutic interventions， whereas TCM offers a holistic perspective for understanding disease evolution through the assessment of overall functional status， disease-stage stratification， and long-term syndrome-based regulation.

This paper has summarized current studies on retinitis pigmentosa （RP） from two perspectives， which were disease mechanism insights from western medicine， and etiology， pathogenesis and therapeutic principles in traditional Chinese medicine （TCM）. From the perspective of western medicine， the understanding of RP has evolved from an early single-factor explanation focusing on pathogenic gene mutations to a more comprehensive， multifactorial model involving genetic abnormalities， photoreceptor cell degeneration， retinal pigment epithelium dysfunction， oxidative stress， inflammatory responses， microenvironmental imbalance， and vascular insufficiency. In TCM， RP is considered to be a disorder manifested in the eyes but rooted in dysfunction of the zang-fu （脏腑） organs. Its pathogenesis is primarily associated with congenital insufficiency， liver-kidney depletion， impaired spleen function of transportation and transformation， and stasis obstructing the meridians. The core pathological mechanism can be summarized as "deficiency complicated by stasis"， emphasizing holistic imbalance， dynamic disease progression， and syndrome differentiation and treatment. The differences and complementarities between the two medical systems in understanding disease progression are further discussed. RP is proposed to be more appropriately regarded as a complex disease characterized by long-term progression， stage-dependent evolution， and persistent decompensation. Western medicine contributes to elucidating the molecular mechanisms underlying RP and provides the foundation for targeted therapeutic interventions， whereas TCM offers a holistic perspective for understanding disease evolution through the assessment of overall functional status， disease-stage stratification， and long-term syndrome-based regulation.

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.

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.

ObjectiveTo investigate the effects and underlying mechanisms of polydatin in delaying the progression of colitis-associated colorectal cancer （CAC） by constructing an azoxymethane （AOM）/dextran sulfate sodium （DSS）-induced CAC mouse model and conducting in vitro experiments. MethodsFifty-four male C57BL/6J mice were randomly divided into normal， model， and polydatin groups （0.045 g·kg^-1）. The CAC mouse model was established using AOM/DSS， and samples were collected at 4， 7， and 10 weeks. Body weight change rate， disease activity index （DAI）， and tumor formation were assessed. Hematoxylin-eosin （HE） staining was used to observe pathological injury in intestinal tissues. Immunohistochemistry （IHC） was performed to detect zonula occludens-1 （ZO-1） expression in colonic tissues， and Western blot was used to detect the expression of E-cadherin， N-cadherin， and Vimentin in colonic epithelial cells. Real-time PCR was used to measure mRNA expression of interleukin-17A （IL-17A）， Wnt3a， β-catenin， T cell factor 1 （Tcf1）， E-cadherin， N-cadherin， and Vimentin in colonic tissues. Flow cytometry was used to analyze the proportion of CD8⁺T cells and the expression of exhaustion-related molecules in tumors. Human colon cancer DLD-1 cells were cultured in a polydatin-containing medium， and wound healing assays were performed to observe migration changes. Real-time PCR was used to detect mRNA expression of interleukin-17 receptor A （IL-17RA）， Wnt3a， β-catenin， Tcf1， E-cadherin， N-cadherin， and Vimentin in DLD-1 cells. ResultsCompared with the normal group， the model group at all three time points showed significantly decreased body weight change rate （P<0.01）， significantly shortened colon length （P<0.01）， and markedly increased DAI scores （P<0.01）. HE staining revealed significant inflammatory cell infiltration in the submucosa of the colon in the model group， accompanied by epithelial dysplasia. ZO-1 expression in colonic tissues was significantly reduced （P<0.01）. The mRNA expression of the pro-inflammatory factor IL-17A and key molecules of the Wnt/β-catenin pathway （Wnt3a， β-catenin， Tcf1） was significantly elevated （P<0.05）. The mRNA and protein expression of epithelial-mesenchymal transition （EMT） markers N-cadherin and Vimentin was significantly upregulated （P<0.05）， while E-cadherin expression was significantly downregulated （P<0.05）. The proportion of tumor-infiltrating CD8⁺T cells expressing immunosuppressive molecules （TIM-3， LAG-3， PD-1） was significantly increased （P<0.05）. Compared with the model group， the polydatin group showed significant improvement in body weight and DAI score （P<0.01）， as well as recovery of colon length and tissue injury. ZO-1 expression in colonic tissue was significantly increased （P<0.01）， while IL-17A， Wnt3a， β-catenin， Tcf1， N-cadherin， and Vimentin expression levels were significantly decreased （P<0.05）， and E-cadherin expression was significantly increased （P<0.01）. Tumor-infiltrating CD8⁺ T cells expressing immunosuppressive molecules were significantly reduced （P<0.05）. In vitro experiments showed that polydatin significantly inhibited migration of DLD-1 cells （P<0.01） and reversed the upregulation of IL-17RA， Wnt3a， β-catenin， N-cadherin， and Vimentin mRNA， as well as the downregulation of E-cadherin mRNA （P<0.05）. ConclusionPolydatin inhibits IL-17A secretion and IL-17RA expression， improves the immune microenvironment， blocks activation of the Wnt/β-catenin signaling pathway， suppresses EMT markers （N-cadherin and Vimentin）， and restores tight junction protein expression in intestinal epithelial cells， thereby delaying the progression from colitis to colorectal cancer in mice.

Diabetic retinopathy(DR)is a late-stage peripheral micro-neurovascular complication of chronic hyperglycemia, leading to blood-retinal barrier impairment and retinal dysfunction. Recent studies have found that diabetic neuroretinopathy(DN)may be one of the earliest events in diabetic retinal alterations. The main features include defective electroretinographic responses in newly diagnosed patients, early self-activation of microglia and Müller cells, reduced activity of neurotransmitters(e.g., DOPA/GABA), and early mitochondrial dysfunction, such as persistent Drp1-Fis1 fission and mtDNA methylation mismatches. Understanding the molecular basis of DN is essential for elucidating its pathogenesis and developing early treatments. This review summarizes pathological changes and mechanisms of retinal function, glial cells, neurotransmitters, mitochondria, and other factors in early diabetes mellitus, in order to provide a theoretical foundation for investigating early DN mechanisms and developing targeted therapies.

Objective To investigate the safety, economic benefits and psychological effects of day breast conserving surgery for breast cancer. Methods The demographic data and clinical data of breast cancer patients undergoing day (day surgery group) and ward (ward surgery group) breast conserving surgeries in West China Hospital of Sichuan University from March 2020 to June 2021 were retrospectively collected; the demographic data, clinical data, medical and related transportation costs, and preoperative and postoperative BREAST-Q scores of breast cancer patients undergoing day (day surgery group) and ward (ward surgery group) breast conserving surgery in West China Hospital of Sichuan University from June 2021 to June 2022 were prospectively collected. The safety, economic benefit, and psychological satisfaction of day surgery was analyzed. Results A total of 42 women with breast cancer were included in the retrospective study and 39 women with breast cancer were included in the prospective study. In both prospective and retrospective studies, the mean age of patients in both groups were <50 years. There were only statistical differences between the two groups in the aspects of hypertension (P=0.022), neoadjuvant chemotherapy (P=0.037) and postoperative pathological estrogen receptor (P=0.033) in the prospective study. In postoperative complications, there were no statistical differences in the surgical-related complications or anesthesia-related complications between the two groups in either the prospective study or the retrospective study (P>0.05). In terms of the overall cost, we found that the day surgery group was more economical than the ward surgery group in the prospective study (P=0.002). There were no statistical differences in postoperative psychosocical well-being, sexual well-being, satisfaction with breasts or chest condition between the two groups (P>0.05). Conclusion It is safe and reliable to carry out breast conserving surgery in day surgery center under strict management standards, which can save medical costs and will not cause great psychological burden to patients.