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.

This article reports a rare case of autoinflammatory disease presenting initially with skin induration and swelling after trauma as the initial manifestation, followed by progressive limb weakness. The patient was a middle-aged female who developed skin induration and swelling after trauma, which gradually progressed to limb weakness, dysarthria and bilateral facial paralysis, accompanied by livedo reticularis of the lower extremities, diffuse skin induration of the limbs, and beaded subcutaneous nodules in the right upper limb. The patient had a susceptibility to infection since childhood and a history of chronic livedo reticularis. Skin pathological examination revealed panniculitis. A comprehensive etiological screening for special infections and autoimmune diseases was completed with an unremarkable results, and whole-exome sequencing showed no abnormal findings. Following a multidisciplinary discussion combined with RNA sequencing results, the patient was diagnosed with an autoinflammatory disease, with a suspected type Ⅰ interferonopathy. Treatment with tofacitinib resulted in gradual improvement of clinical symptoms. This case highlights the importance of detailed medical history collection, systematic physical examination and multidisciplinary collaborative diagnosis and treatment, and underscores the pivotal role of molecular diagnosis in the confirmation of rare diseases. It can provide a reference for the clinical diagnosis and management of similar rare cases.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Objective: To explore the association between mental health status and adverse childhood experiences (ACEs) among sexual minority college students, so as to provide a scientific basis for mental health education and health promotion in universities. Methods: From January to February 2024, convenience and cluster sampling methods were used to select 1 792 college students from 11 colleges in Guangxi. A self reporting method was applied to identify 476 sexual minority individuals. The Symptom Check-List 90 (SCL-90) and the Simplified Chinese Adverse Childhood Experiences International Questionnaire (SC-ACE-IQ) were employed to assess mental health and ACEs. Multivariate Logistic regression analysis was conducted to examine the associations. Results: The detection rates of all psychological issues among sexual minority college students in Guangxi were significantly higher than those of non sexual minority college students ( χ 2=56.01-91.39, all P <0.01). Except for physical neglect, bullying, and community violence, sexual minority students exhibited higher reporting rates of other ACEs types compared to nonsexual minority students ( χ 2= 4.52-13.34, all P <0.05). The total ACEs score for college students was 1.00 (1.00, 2.00), while the SCL-90 total score was 96.00 (113.00, 160.00). Spearman correlation analysis revealed a positive correlation between ACEs total scores and SCL-90 total scores ( r=0.29, P <0.05). Additionally, all ACEs subscales, including emotional neglect, physical neglect, emotional abuse, sexual abuse, parental loss, domestic violence, and community violence were positively correlated with corresponding SCL-90 subscale scores ( r =0.05-0.22, all P <0.05). Multivariate Logistic regression analysis showed that family violence increased the risk of mental health issues for sexual minority students ( OR=1.61, 95%CI =1.26-2.09); emotional neglect ( OR= 1.05 , 95%CI =1.00-1.10), physical neglect ( OR=1.20, 95%CI =1.06-1.35), sexual abuse ( OR=1.49, 95%CI =1.15-1.93) increased mental health risks for non sexual minority students (all P <0.05). The cumulative effects of ACEs were all statistically significant in the total sample and both subgroups (all P <0.05). Conclusion Mental health status among sexual minority college students in Guangxi is associated with ACEs, and their well being requires active attention

Objective To investigate the alterations of cerebral blood flow(CBF)in type 2 diabetic mellitus(T2DM) patients without cognitive impairment by using arterial spin labeling(ASL)technique.Methods A total of 23 T2DM patients without cognitive impairment and 23 healthy controls(HC)matched by age,sex,and education attainment were recruited.Their clinical data were collected,and neuropsychological tests and cerebral magnetic resonance imaging were performed.Then,the outcomes of clinical features,neuropsychological tests,and global and regional CBF were compared between the two groups.The significant regional zCBF(z-transformed relative CBF)values were extracted and correlated with clinical data and neuropsychological scores in T2DM patients,controlling age,sex,and education.Results No significant difference was found in whole brain CBF between the two groups(P=0.155),while significantly higher CBF was identified in the left superior temporal gyrus and left insula in the T2DM group(Gaussian random field correction,initial threshold P < 0.001,cluster level P < 0.05).No correlation was observed between the significant regional zCBF values and the clinical data or the neuropsychological scores in T2DM patients(all P>0.05).Conclusion Alterations in cerebral hemodynamics may precede cognitive function changes in T2DM,suggesting that the ASL technique is promising for early monitoring of cerebral hemodynamic changes associated with cognitive impairment in patients with T2DM.
Humans ; Diabetes Mellitus, Type 2/physiopathology* ; Cerebrovascular Circulation ; Middle Aged ; Male ; Female ; Magnetic Resonance Imaging ; Case-Control Studies ; Cognitive Dysfunction ; Neuropsychological Tests ; Aged

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 explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective:To evaluate the cumulative live birth rate (CLBR) and cost-effectiveness of fixed versus adjusted follicle-stimulation hormone (FSH) dosages in infertile women with different ovarian responses during their first assisted reproductive technology (ART) cycle.Methods:A retrospective real-world cohort study was conducted on 5 419 infertile women who underwent their first ART treatment at the Department of Reproductive Medicine of the First Affiliated Hospital of Nanjing Medical University between January 2013 and December 2017. All patients received an individualized starting dosage of gonadotropin. Based on whether FSH dosages were adjusted during controlled ovarian stimulation (COS), patients were divided into fixed-dosage group ( n=2 061) and adjusted-dosage group ( n=3 358). Clinical outcomes and FSH cost-effectiveness were compared between the two groups across different ovarian response groups, with CLBR as the primary outcome. Propensity score matching (PSM) and multivariable logistic regression were used to adjust for potential confounders. Results:FSH dosage adjustments were found in 62.0% (3 358/5 419) of cycles during COS. After PSM, baseline characteristics were comparable between the two groups (all P>0.05). After adjusting for confounders using multivariable logistic regression, FSH dosage adjustment was not significantly associated with CLBR ( OR=1.06, 95% CI: 0.94-1.20, P=0.332). Compared with the adjusted-dosage group, the fixed-dosage group showed no significant differences in CLBR in poor-, normal-, and high-responder groups (all P>0.05). The incidence of ovarian hyperstimulation syndrome (OHSS) did not differ significantly between the two groups ( P>0.05). In poor-, normal-, and high-responder groups, the total FSH dosages in the fixed-dose group [1 350 (375, 1 825) U, 1 200 (375, 1 500) U and 525 (375, 1 128) U, respectively] were significantly lower than those in the adjusted-dose group [1 875 (1 425, 2 294) U, P=0.001; 1 425 (450, 1 875) U, P<0.001; 600 (375, 1 425) U, P=0.020]. Similarly, average FSH costs in different ovarian response groups in the fixed-dosage group [4 725.0 (1 312.5, 6 387.5) yuan, 4 200.0 (1 312.5, 5 250.0) yuan and 1 837.5 (1 312.5, 3 947.3) yuan, respectively] were significantly lower than those in the adjusted-dosage group [6 562.5 (4 987.5, 8 028.1) yuan, P=0.001; 4 987.5 (1 575.0, 6 562.5) yuan, P<0.001; 2 100.0 (1 312.5, 4 987.5) yuan, P=0.020]. For normal-responders, the FSH cost per high-quality embryo in the fixed-dosage group [1 365.0 (875.0, 2 537.5) yuan] was significantly lower than that in the adjusted-dosage group [2 056.3 (1 268.8, 3 412.5) yuan, P<0.001]. Conclusion:FSH dosage adjustment during COS is not associated with CLBR or the incidence of OHSS. However, the fixed-dose group exhibited lower total FSH dosages and costs across different ovarian response populations. In the context of ART being covered by medical insurance, fixed FSH dosage may represent a more cost-effective ovarian stimulation protocol.

Objective:To analyze the clinical and ultrasonographic characteristics of papillary thyroid carcinoma(PTC)and explore their correlation with cervical lymph node metastasis(CLNM),thereby constructing a nomogram pre-diction model for assessing the risk of CLNM in PTC.Methods:A total of 553 patients(corresponding to 553 nod-ules)with papillary thyroid carcinoma(PTC),confirmed by postoperative pathology,who underwent ultrasonography and had complete clinical data at the Second Hospital of Shandong University between December 2019 and December 2022,were included.228 patients(228 nodules)hadcervical lymph node metastasis,and 325 patients(325 nodules)were without cervical lymph node metastasis.All patients were categorized into metastasis and non-metastasis groups based on the presence or absence of cervical lymph node metastasis.These groups were then randomly di-vided into training and validation sets in a 7:3 ratio.Differences in clinical and ultrasonographic characteristics between the two groups were compared,and a nomogram was constructed.Results:Univariate analysis revealed statistically significant differences between the metastasis group and the non-metastasis group in terms of age,presence of Hashimoto's thyroiditis,multifocality,taller-than-wide shape,calcification,capsular contact,and blood flow(P<0.05).Logistic regression analysis in the training set indicated that age,presence of Hashimoto's thyroiditis,multifocality,taller-than-wide shape,calcification,and blood flow were associated with lymph node metastasis in papillary thyroid carcinoma(PTC)(P<0.05).These indicators were incorporated into a nomogram model,which demonstrated high predictive performance,good calibration,and significant clinical utility in both the training and validation sets.Conclu-sion:The nomogram prediction model,constructed based on clinical and ultrasonographic features,effectively predicts the risk of cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Patients who were older,had concomitant Hashimoto's thyroiditis,or exhibited a nodule aspect ratio≥1 were less likely to have concurrent CLNM.Conversely,patients presenting with multiple nodules,nodules with microcalcifications,or nodules demonstrating central or rich/peripheral vascularity were more likely to have concurrent CLNM.