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.

Abnormal synaptic plasticity is an early pathological feature of Alzheimer disease (AD). Synaptic damage and dysfunction initiate neuronal degeneration and death, ultimately leading to cognitive impairment. Traditional Chinese medicine (TCM) can effectively ameliorate cognitive dysfunction through multitarget regulation of synaptic plasticity. This review summarizes the mechanisms by which TCM, including active components, single herbs, and classical formulas, modulates synaptic plasticity, offering new insights for future research and clinical applications. Relevant experimental studies published between 2020 and 2024 were retrieved from major databases, including China National Knowledge Infrastructure, the National Science and Technology Library, Wanfang Data, Elsevier, ScienceDirect, PubMed, SpringerLink, and Web of Science. Network pharmacology and bioinformatics approaches were used to predict the therapeutic effects and mechanisms of TCM on AD-related synaptic plasticity. In total, 15 TCM single herbs and 11 TCM formulas were identified as enhancing AD-related synaptic plasticity. Additionally, 15 active ingredients targeting synaptic plasticity in AD were retrieved from TCM databases over the past decade. This review provides novel perspectives and strategic directions for future AD research and therapeutic development.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Objective: To investigate the molecular mechanism of Syk in phagocytosis induced by CD36 antibodies. Methods: In vitro, two CD36 monoclonal antibodies, GZ1 (IgG2a) and GZ4 (IgG1), at different concentrations were co-incubated with platelets from CD36-positive blood donors, and the affinity of the antibodies for platelets was assessed using flow cytometry. CD36 positive platelets from donors were labeled with Red-SE. The GZ1 and GZ4 antibodies were added together with dye-labeled platelets to peripheral blood from blood donors for phagocytosis experiments. The expression of the Spleen Tyrosine Kinase (Syk), P-Syk, P38 MAPK and P-P38 were detected using Western blot(WB). In the in vitro phagocytosis inhibition assay, Fcγ receptor (FcγR) antibodies or Syk inhibitor (R406) were pre-incubated with monocytes prior to performing the phagocytosis experiment. In vivo experiments were performed using female C57BL/6J mice. R406 was administered via intraperitoneal injection, followed by tail vein infusion of GZ1 or GZ4 antibodies. Additionally, a treatment group was set up in which the antibodies were infused first, followed by administration of R406. Changes in platelet counts were analyzed using a blood routine analyzer, and antibody binding to platelets was detected by flow cytometry. Results: GZ1 had higher affinity for CD36positive platelets than GZ4. The phagocytosis rate induced by GZ1 was significantly higher than that of GZ4 [(42.12±2.25)% vs (16.25±6.45)%, P<0.001]. Moreover, GZ1-mediated platelet phagocytosis mainly depends on FcγRⅠ of monocytes, while GZ4-mediated platelet phagocytosis mainly relies on FcγRⅡ of monocytes. WB results showed that the GZ1 group significantly upregulated the expression of Syk and phosphorylated Syk (P-Syk), and induced phosphorylation of the downstream P38 MAPK signaling pathway. Pretreatment of monocytes with R406 inhibited the phagocytosis of antibodyopsonized platelets by monocytes. After injecting GZ1 or GZ4 antibodies into C57BL/6 female mice through the tail vein, GZ1 mAbs had a stronger binding rate to the platelets compared with GZ4 mAbs, leading to a significant decrease in platelet count. After pre-injecting R406 into mice, the platelet count reduction in both the GZ1 and GZ4 groups was alleviated, and the binding rate of antibodies to platelets was also significantly reduced. However, administration of R406 after antibody injection failed to prevent the decrease in platelet counts in mice. Conclusion: This study indicates that Syk plays an important role in the phagocytosis of anti-CD36 opsonized platelets by monocytes/macrophages and is closely associated with the activation of the P38 MAPK signaling pathway.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

The electrocatalytic nitrate reduction reaction(NO3RR)presents a sustainable pathway for large-scale ammonia production,yet it faces significant challenges due to proton supply limitations caused by the high energy barrier for water dissociation,which slows ammonia(NH3)generation.Herein,a palladium(Pd)-modified copper-cobalt(CuCo)hollow fiber penetration electrode that enabled H2 injection through its hollow structures,thereby enhancing proton availability for NO3RR was developed.The active Pd component efficiently dissociated H2,facilitating active hydrogen(*H)spillover and speeding up the cascade NO3RR process on Cu and Co sites.As a result,a half-cell energy efficiency of 39.53%and an NH3 Faradaic efficiency(FE)of 97.11%±1.17%at-0.1 V(vs RHE)were achieved,comparable to state-of-the-art systems.Importantly,the H2-assisted approach prevented the oxidation of active Cu and Co phases,demonstrating exceptional stability with less than 5.6%decay in current density(267 mA/cm2)and retention of NH3 FE at 94.8%after over 70 h of electrolysis.These findings offered valuable insights into proton supply pathways and design of NO3RR electrodes.

Objective::To evaluate the diagnostic efficacy and clinical application of the Obstetrical Chinese Disseminated Intravascular Coagulation (DIC) Scoring System (OCDSS).Methods::This study is a retrospective study that collected 1063 cases from Wuhan Union Hospital, Yichang Central People’s Hospital, and the Central Hospital of Enshi Tujia and Miao Autonomous Prefecture between July 2017 and June 2024. These cases were divided into DIC and non-DIC groups based on score standard. Diagnosis of DIC, the rate of hysterectomy, neonatal mortality, and severe asphyxia are the main outcome measures. All the laboratory indicators are all determined by clinical laboratory department of the hospital. Data were expressed as mean ± standard deviation or median (interquartile range) and frequencies. Independent sample t-test or non-parametric test were used to compare measurement data, while the chi-square test was used for count data. Receiver operating characteristic (ROC) curve and area under curve (AUC) were used to test the predictive accuracy. Using univariate and multivariate logistic regression analysis to study the high-risk factors. P < 0.050 indicates a statistical significance. Results::Of 1063 participants in this study, 29 participants (2.73%) were diagnosed with obstetrical DIC by OCDSS score standard, and all the participants were diagnosed as DIC with underlying disease. When the Takao, Clark, and Erez score standard is the "gold standard", the OCDSS score standard always shows good sensitivity and specificity, with all the AUC over 0.75. OCDSS score standard also has better predictive of hysterectomy (68.18%, 91.07%, 0.872), severe neonatal asphyxia and death (79.17%, 75.07%, 0.842) than the other three score standards. All the indicators included in the OCDSS score standard contributed to the DIC diagnosis (all the P < 0.001). The indicators in the DIC group were more abnormal than the non-DIC group (all the P < 0.001). Conclusion::OCDSS is a first score standard, especially for pregnancies, it considers the underlying disease, clinical symptoms, and laboratory results. This score system shared a good diagnosis performance for DIC in the Chinese population and may help clinicians make timely decisions.

Objective:To investigate the effect of concentrated growth factor (CGF) on the biological performance of human dental pulp stem cells (hDPSCs) under oxidative stress status induced by hydrogen peroxide (H 2O 2). Methods:The hDPSCs were isolated by using tissue block separation method from healthy permanent teeth extracted for orthodontic reason. hDPSCs surface markers CD34, CD45, CD90 and CD105 were detected by flow cytometry. Alkaline phosphatase (ALP), alizarin red S (ARS), oil red O staining and colony formation assay were used to identify hDPSCs. After the cell counting kit-8 (CCK-8) detection, the optimal H 2O 2 concentration was used to construct the hDPSCs oxidative stress model. CGF conditioned medium was prepared by repeated freeze-thaw methods. After CCK-8 detection, the optimum CGF concentration was chosen for the subsequent experiments. The hDPSCs were divided into control group, H 2O 2 (only H 2O 2 processing), H 2O 2+CGF group (H 2O 2 processing in combination with the CGF) and CGF group (only CGF processing). Subsequent experiments were performed according to these groups. The oxidative stress model was verified by reactive oxygen species, β-galactosidase staining and Western blotting. The effects of CGF on the proliferation and migration of hDPSCs under oxidative stress status were detected by CCK-8 and cell scratch assay, respectively. ALP activity and ARS staining were used to detect the effect of CGF on the osteogenic differentiation of hDPSCs under oxidative stress status. The mRNA expression levels of odontogenesis related genes were detected by real-time fluorescence quantitative PCR (RT-qPCR), and the expression levels of odontogenesis and osteogenesis related proteins were detected by Western blotting. Results:Isolated hDPSCs showed positive expression of mesenchymal stem cells surface markers of CD90, CD105, and negative expression of hematopoietic stem cells surface markers CD34, CD45. The hDPSCs were proved to have the capacity of osteogenic, adipogenic differentiation and clone formation. The optimal concentration to construct the oxidative stress model was 200 μmol/L H 2O 2. Twenty percent CGF was the optimal concentration for subsequent experiments. Compared with the control group, the expression of aging protein p53 was significantly up-regulated from (0.82±0.12) to (1.19±0.14) in H 2O 2 group ( P<0.05), with deepened β-galactosidase staining and increased fluorescence intensity of reactive oxygen species. The proliferative capacity of cells in H 2O 2+CGF group on day 1, 3, 5 and 7 (0.23±0.01, 0.50±0.02, 1.60±0.07, 1.80±0.21) were all higher than in H 2O 2 group (0.15±0.01, 0.14±0.02, 0.50±0.03, 0.90±0.09) ( P<0.05). Cell healing capacity of cells in H 2O 2+CGF group at 12 h and 24 h [(47±7)%, (58±44)%] also increased compared with the H 2O 2 group [(36±2)%, (44±2)%] ( P<0.05), and similar results in the activity of ALP and the formation of mineralized nodules. On day 28, the mRNA expressions of dentin sialophosphoprotein (0.52±0.16) and dental matrix protein 1 (DMP-1) (0.39±0.13) in H 2O 2 group were all significantly lower than those in H 2O 2+CGF group (0.96±0.24, 0.83±0.30, respectively) and CGF group (1.12±0.18, 1.23±0.19, respectively) ( P<0.05). On day 28, the expressions of odontogenesis related protein DMP-1 (0.27±0.04) and osteogenesis related protein Runt-related transcription factor-2 (0.42±0.15) in H 2O 2 group were all significantly lower than those in H 2O 2+CGF group (0.66±0.18, 0.68±0.04) and CGF group (1.15±0.13, 1.06±0.19, respectively) ( P<0.05). Conclusions:H 2O 2 can induce oxidative stress in hDPSCs, while CGF can promote proliferation, migration, odontogenic and osteogenic differentiation of hDPSCs under oxidative stress status.

Accurate pain assessment is a prerequisite for pain management.However,pain is a relatively subjective feeling greatly affected by the environment,education,and emotional state.Therefore,in diagnosing and treating pain,it is necessary not only to assess the subjective feelings of patients,but also to have stable and reliable objective indicators to evaluate the pain status of different patients.At present,there are many clinical tools for assessing and monitoring pain.This paper introduces the commonly used subjective assessment tools(single-dimensional pain assessment scale,multi-dimensional pain assessment scale)and objective assessment tools(surgical pleth index,analgesia and nociception index,nociceptive level index,and biomarkers),and analyzes their advantages and disadvantages,so as to provide reference for future clinical pain assessment.