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 observe the change patterns of functional connectivity(FC)of basal forebrain subregions in Alzheimer disease(AD)patients.Methods Totally 42 AD patients(AD group)and 41 healthy controls(HC group)were retrospectively enrolled.Seed-based FC analysis was performed on basal forebrain subregions(Ch123 and Ch4)based on their resting-state functional MRI data and compared between groups.Results Compared with HC group,FC between left Ch4 and left hippocampus as well as left posterior cingulate gyrus significantly decreased,but between right Ch4 and right precentral gyrus,as well as right postcentral gyrus increased in AD group(GRF correction,voxel level P＜0.001,cluster level P＜0.05).Meanwhile,FC between left Ch123 and left superior temporal gyrus,left insula,between right Ch123 and left superior temporal gyrus,left temporal pole significantly increased,while between right Ch123 and right orbital superior frontal gyrus,right orbital inferior frontal gyrus significantly decreased in AD group(GRF correction,voxel level P＜0.001,cluster level P＜0.05).Conclusion FC changes of different basal forebrain subregions in AD patients were various.

Objective To investigate the relationship between prolactin and mild cognitive impairment(MCI)in postmenopausal women with type 2 diabetes mellitus(T2DM).Methods A total of 319 postmenopausal women with T2DM who were hospitalized in the Department of Endocrinology,Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University were enrolled in this study from August 2016 to October 2023.All the patients were divided into two groups according whether they had MCI:T2DM group(n=161)and MCI group(n=158).Differences in clinical characteristics were compared between the two groups.Pearson correlation was used to analyze the correlation between sex hormones and cognitive domains,and Logistic regression analysis was used to evaluate the influencing factors for MCI development.Results Serum prolactin levels were significantly lower in the MCI group than in the T2DM group[(5.5±2.1)vs(7.2±2.9)μg/L,P<0.05].Serum prolactin level was positively correlated with mini-mental state examination score,Montreal cognitive assessment score,immediate memory score,visuopatial constructional score,attention score and hippocampal volume(P<0.05),and negatively correlated with processing speed test(time)and executive function test(time)(P<0.05).Logistic regression analysis demonstrated that serum prolactin level was an influencing factor for the risk of MCI in postmenopausal women with T2DM(OR 0.715,95%CI 0.605～0.845,P<0.01).Conclusions The decrease of serum prolactin level is associated with an increased risk of MCI in postmenopausal women with T2DM.

Objective To design a dynamic monitoring platform for mastering the changes of outpatient service in public tertiary grade A hospitals.Methods An outpatient dynamic monitoring platform was designed with B/S architecture and developed with Java platform,which used Oracle 11g database for data storage and hypertext transfer protocol encapsulated as WebAPI to realize data transmission with systems.There were five functional modules involved in the platform for patient flow monitoring,doctor attendance monitoring,public service monitoring,outpatient medical staff communication and data storage and analysis for decision making.Results The platform developed realized comprehensive monitoring and closed-loop management of the outpatient department,and enhanced the quality and efficiency of patient service.Conclusion The platform developed solves the problems of outpatient management in terms of monitoring and early warning,personnel communication and assisted decision making,and improves outpatient management in intellectualization and automation.[Chinese Medical Equipment Journal,2025,46(5):39-47]

Objective To investigate the relationship between prolactin and mild cognitive impairment(MCI)in postmenopausal women with type 2 diabetes mellitus(T2DM).Methods A total of 319 postmenopausal women with T2DM who were hospitalized in the Department of Endocrinology,Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University were enrolled in this study from August 2016 to October 2023.All the patients were divided into two groups according whether they had MCI:T2DM group(n=161)and MCI group(n=158).Differences in clinical characteristics were compared between the two groups.Pearson correlation was used to analyze the correlation between sex hormones and cognitive domains,and Logistic regression analysis was used to evaluate the influencing factors for MCI development.Results Serum prolactin levels were significantly lower in the MCI group than in the T2DM group[(5.5±2.1)vs(7.2±2.9)μg/L,P<0.05].Serum prolactin level was positively correlated with mini-mental state examination score,Montreal cognitive assessment score,immediate memory score,visuopatial constructional score,attention score and hippocampal volume(P<0.05),and negatively correlated with processing speed test(time)and executive function test(time)(P<0.05).Logistic regression analysis demonstrated that serum prolactin level was an influencing factor for the risk of MCI in postmenopausal women with T2DM(OR 0.715,95%CI 0.605～0.845,P<0.01).Conclusions The decrease of serum prolactin level is associated with an increased risk of MCI in postmenopausal women with T2DM.

Objective To explore the value of 18F-flortaucipir tau PET combined with APOE ε4 genotype status for diagnosing mild cognitive impairment(MCI).Methods A total of 213 MCI patients(MCI group)and 402 healthy controls(HC group)were selected from Alzheimer's disease neuroimaging initiative(ADNI)database.The neuropsychological information,APOE ε4 gene carrier status,tau PET and high-resolution structural MRI data were recorded.The random forest algorithm was used to screen the most informative brain regions of tau PET for diagnosing MCI,and the efficacy of tau PET for distinguishing MCI with or without APOE ε4 gene and HC were compared.Results Amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus in turn were the important brain regions of tau PET for diagnosing MCI.The accuracy and the area under the curve(AUC)of tau PET standardized uptake value ratio(SUVR)model for identifying MCI with APOE ε4 gene and HC was 86.68％and 0.784,respectively,both higher than those for identifying MCI and HC,as well as MCI without APOE e4 gene and HC(with accuracy of 70.57％and 75.05％,and AUC of 0.711 and 0.609).Conclusion 18F-flortaucipir tau PET SUVR model established based on amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus could be used to diagnosing MCI.Combining with APOE ε4 gene could further improve its efficacy.

Objective To observe the functional connectivity and glucose metabolism of insular subregions in behavior variant of frontotemporal dementia(bvFTD)patients,also their correlations with cognitive function.Methods Thirty-eight bvFTD patients(bvFTD group)and 44 healthy individuals(control group)were retrospectively enrolled.The average time series signals of insular subregions were extracted as seed points based on functional MRI(fMRI)and 18F-FDG PET,then whole brain functional connectivity map was obtained.Meanwhile,the pons was selected as the reference brain region,and the standard uptake value ratio(SUVR)of insular subregions were calculated.The above parameters were compared between groups,and the correlations of SUVR of insular subregions with clinical cognitive function scale scores in bvFTD group were analyzed.Results Compared with control group,the functional connections between all insular subregions and bilateral frontal lobe,temporal lobe,anterior cingulate gyrus,anterior cingulate gyrus and middle cingulate gyrus,as well as between some subregions and bilateral parietal and occipital lobes were weakened in bvFTD group(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05).SUVR of all insular subregions significantly decreased(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05),which in right ventral agranular insula(vIa),dorsal agranular insula(dIa),dorsal dysgranular insula(dId)and left dorsal agranular insula(dIa)were negatively correlated with frontal behavioral inventory(FBI)score in bvFTD group(r=-0.452--0.330,all P＜0.05).Conclusion In bvFTD patients,the functional connectivity and glucose metabolism of insular subregions changed,and SUVR of right vIa,dIa,dId and left dIa were negatively correlated with FBI score.

Objective To observe the change patterns of functional connectivity(FC)of basal forebrain subregions in Alzheimer disease(AD)patients.Methods Totally 42 AD patients(AD group)and 41 healthy controls(HC group)were retrospectively enrolled.Seed-based FC analysis was performed on basal forebrain subregions(Ch123 and Ch4)based on their resting-state functional MRI data and compared between groups.Results Compared with HC group,FC between left Ch4 and left hippocampus as well as left posterior cingulate gyrus significantly decreased,but between right Ch4 and right precentral gyrus,as well as right postcentral gyrus increased in AD group(GRF correction,voxel level P＜0.001,cluster level P＜0.05).Meanwhile,FC between left Ch123 and left superior temporal gyrus,left insula,between right Ch123 and left superior temporal gyrus,left temporal pole significantly increased,while between right Ch123 and right orbital superior frontal gyrus,right orbital inferior frontal gyrus significantly decreased in AD group(GRF correction,voxel level P＜0.001,cluster level P＜0.05).Conclusion FC changes of different basal forebrain subregions in AD patients were various.