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.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

A mounting body of research suggests that circRNAs significantly contribute to the develop-ment of myocardial fibrosis.The microarray results of human circular RNA expression profile indicated that circHERC4_041 expression increased in the myocardium of patients with heart failure,RT-qPCR a-nalysis confirmed that the myocardial expression level of circHERC4_041 in individuals with heart failure were considerably elevated compared to that in healthy organ donors.Fluorescence in situ hybridization(FISH)confirmed that circHERC4_041 was abundant in the cytoplasm of human cardiomyocyte AC16.Overexpression of circHERC4_041 in mouse myocardial fibroblasts(mCFs)mediated by adenovirus in-hibited the expression of fibrosis-related proteins in mCFs.Experiments involving cell proliferation,wound healing,and Transwell assays demonstrated that overexpression of circHERC4_041 suppressed the growth and mobility of mCFs(P＜0.001).Sequence analysis results suggested that circHERC4_041 con-tains potential ribosome entry sequence(IRES)and open reading frame(ORF).Western blot confirmed that circHERC4_041 could translate the 516 amino acid HERC4-516aa protein,which was mainly located in the cytoplasm of the cell.Cell functional experiments confirmed that circHERC4_041 inhibited the fi-brotic phenotype of mCFs by specifically translating HERC4-516aa(P＜0.05).The specific interaction between HERC4-516aa and transglutaminase 2(TGM2)was confirmed by IP-MS screening and Co-IP i-dentification.Further results found that the degradation of TGM2 was promoted through proteasome path-way.The overexpression of TGM2 in mCFs facilitated by adenoviral vectors could counteract the suppres-sive effects of HERC4-516aa on the fibrotic phenotype of mCFs.Therefore,this study confirmed that the HERC4-516aa protein translated by circHERC4_041 can specifically bind to TGM2 to inhibit the fibrotic phenotype of myocardial fibroblasts.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

OBJECTIVE: To investigate the effect of daratumumab, lenalidomide and dexamethasone on quality of life in transplant-ineligible (TIE) patients with newly diagnosed multiple myeloma (NDMM). METHODS: The clinical data of 93 TIE NDMM patients in our hospital from January 2020 to December 2022 were retrospectively analyzed. The patients were divided into D-Rd group (48 cases) and Rd group (45 cases) according to treatment regimen. The patients in Rd group were treated with lenalidomide and dexamethasone, while those in D-Rd group were treated with daratumumab on the basis of Rd group. The QLQ-C30 and EQ-5D VAS scores of the two groups were compared at baseline and after 3, 6 and 12 treatment cycles. The last follow-up date was June 30, 2023, and overall survival (OS) was compared between the two groups. RESULTS: The median follow-up period in the D-Rd group was 21 (7-38) months, and the median OS was 34 months, while that in the Rd group was 16 (5-35) months, and the median OS was 28 months. There was significant difference in OS between the two groups ( P <0.05). After 3, 6 and 12 treatment cycles, the QLQ-C30 score and EQ-5D VAS score of the two groups were significantly improved (all P <0.05). After 3 and 12 treatment cycles, the QLQ-C30 score and EQ-5D VAS score of D-Rd group were significantly higher than those of Rd group (all P <0.05). There were no significant differences in the improvement of QLQ-C30 GHS and pain scores between the two groups of patients with age <75 years and ECOG 0-1 score after 3, 6 and 12 treatment cycles (P >0.05). In D-Rd group of patients with age≥75 years, the improvement of QLQ-C30 GHS scores after 3 and 12 treatment cycles and QLQ-C30 pain scores after 3, 6 and 12 treatment cycles was significantly superior to that in Rd group (all P <0.05). In D-Rd group of patients with ECOG 2 scores, the improvement of QLQ-C30 GHS and pain scores after 3, 6 and 12 treatment cycles was significantly superior to that in Rd group (all P <0.05). CONCLUSION Daratumumab, lenalidomide, and dexamethasone can significantly improve OS in TIE NDMM patients without decrease of quality of life, especially in those with age≥75 years or ECOG 2 scores.
Humans ; Multiple Myeloma/drug therapy* ; Lenalidomide/therapeutic use* ; Quality of Life ; Dexamethasone/therapeutic use* ; Retrospective Studies ; Antibodies, Monoclonal/therapeutic use* ; Female ; Male ; Middle Aged ; Aged ; Stem Cell Transplantation

OBJECTIVE: To investigate the clinical efficacy of moxibustion (Mox) combined with low-dose tadalafil (TAD) in the treatment of diabetes mellitus-induced erectile dysfunction (DMED) with the syndrome of Qi deficiency and blood stasis. METHODS: According to the inclusion and exclusion criteria, we selected 90 patients with DMED for this trial and equally randomized them into a Mox, a TAD, and a Mox combined with TAD (Mox+TAD) group to be treated by mild Mox applied to the acupoints Zusanli, Sanyinjiao and Yinlingquan qd alt, oral medication with low-dose TAD at 5 mg per dose qd, and combination of the above two therapies, respectively, all for 4 weeks. We obtained from the patients their IIEF-5 scores, traditional Chinese medicine (TCM) symptoms scores, Erectile Hardness Scale (EHS) scores, corpus cavernosal hemodynamic indexes, and the peak systolic velocity (PSV), end diastolic velocity (EDV) and resistance index (RI) of the corpus cavernosal arteries before and after treatment, and compared them among the three groups. RESULTS: The total effectiveness rate was significantly higher in the Mox+TAD (90.0%) than in the Mox (46.7%) and TAD groups (60.0%) (P< 0.05). Compared with the baseline, the IIEF-5 and EHS scores were increased, while the TCM symptoms scores decreased in all the three groups after treatment, more significantly in the Mox+TAD group than in the other two (P< 0.05). And the PSV and RI were remarkably increased, while the EDV decreased (P< 0.05) in all the three groups (P< 0.05) after treatment, with PSV even higher in the Mox+TAD than in the Mox and TAD groups (P< 0.05). CONCLUSION Moxibustion combined with tadalafil has a definite efficacy and safety for the treatment of DMED, which can effectively improve the erectile function of the patients by increasing penile blood supply, benefiting qi and activating blood circulation.
Humans ; Male ; Tadalafil ; Erectile Dysfunction/etiology* ; Moxibustion ; Middle Aged ; Prospective Studies ; Adult ; Carbolines/administration & dosage* ; Diabetes Complications/therapy* ; Aged ; Treatment Outcome ; Combined Modality Therapy

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Atrial fibrillation (AF) is the most common arrhythmia in clinical practice. It has a high prevalence and poor prognosis. The application of antiarrhythmic drugs and even surgery cannot completely treat the disease, and there are many sequelae. AF can be classified into the category of "palpitation" in Chinese medicine according to its symptoms. Acupuncture has a significant effect on AF. The authors find that an important mechanism of acupuncture in AF treatment is to regulate the cardiac vagus nerve. Therefore, this article intends to review the distribution and function of vagus nerve in the heart, the application and the regulatroy effect for the treatment of AF.
Atrial Fibrillation/physiopathology* ; Humans ; Acupuncture Therapy ; Vagus Nerve/physiology* ; Animals