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.

Inflammation plays a pivotal role in the etiology and progression of various diseases. In traditional Chinese medicine, the whole plants of Thesium chinense Turcz. and its preparations (e.g. Bairui Granules) have been employed to manage inflammatory conditions. While flavonoids were previously considered the primary anti-inflammatory components, other potentially active constituents have been largely overlooked and not thoroughly investigated. This study presents a novel finding that the total alkaloids of T. chinense (BC-Alk) are potent active substances underlying the traditional and clinical applications of T. chinense and Bairui Granules as anti-inflammatory agents. UPLC-MS/MS analysis identified the composition of BC-Alk as quinolizidine alkaloids. The anti-inflammatory efficacy of BC-Alk was evaluated using a lipopolysaccharide (LPS)-induced lung inflammation model in mice. Results demonstrated that BC-Alk significantly mitigated LPS-induced lung inflammation, attenuated the overproduction of IL-1β and the overproduction of inflammatory factors (TNF-α), and ameliorated lung tissue hyperplasia in mice in vivo. Mechanistic studies in vitro revealed that BC-Alk upregulated the expression of Nrf2 and its downstream proteins NQO1 and glutamate-cystine ligase and modifier subunit (GCLM), inhibited NF-κB phosphorylation, and suppressed NLRP3 activation. Collectively, these findings indicate that BC-Alk exerts potent inhibitory effects against lung inflammation by modulating Nrf2, NF-κB, and NLRP3 pathways. This study provides new insights into the anti-inflammatory constituents of T. chinense and Bairui Granules.
Animals ; Lipopolysaccharides/adverse effects* ; Alkaloids/pharmacology* ; NF-kappa B/metabolism* ; NF-E2-Related Factor 2/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Mice ; Signal Transduction/drug effects* ; Anti-Inflammatory Agents/pharmacology* ; Male ; Mice, Inbred C57BL ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Pneumonia/genetics*

OBJECTIVE: To investigate the safety and efficacy of avatrombopag（AVA） combined with rhIL-11 in treating thrombocytopenia induced by chemotherapy in acute myeloid leukemia. METHODS: The clinical information of 8 patients in the real world who received avatrombopag combined with rhIL-11 in cancer treatment-induced thrombocytopenia(CTIT) after AML chemotherapy were retrospectively analyzed, and at the same time, 8 patients who received rhIL-11 only in CTIT after AML chemotherapy served as the control group, A preliminary observation was to summarize and compare the therapeutic efficacy and adverse effects between the two groups. RESULTS: D3 and D7 platelet counts were not significantly different between the observation group and the control group after treatment. The platelet counts in the observation group was significantly higher than those of the control group on the 10th day after treatment (P < 0.01). The adverse reactions, such as weakness, abdominal pain, fatigue, nausea and edema after treatment were mild in the observation group and the control group. Except for one patient in the observation group who had a history of cerebral infarction before the onset of the disease and was routinely taking antiplatelet drugs, no thrombosis events occurred in the patients in the observation and control groups during the period of administration of the drug, and the total incidence rate of adverse reactions was not significantly different between the two groups. CONCLUSION The combination of AVA and rhIL-11 can enhance platelet recovery in CTIT of AML patients after chemotherapy. Compared with the rhIL-11 alone group, the platelet recovery time in AVA+rhIL-11 group was significantly shorter, the platelet count on the 10th day after drug administration was significantly higher. No statistically significant difference in the total incidence rate of adverse reactions was observed between rhIL-11 alone group and AVA+rhIL-11 group.
Humans ; Leukemia, Myeloid, Acute/drug therapy* ; Thrombocytopenia/chemically induced* ; Interleukin-11/therapeutic use* ; Retrospective Studies ; Adult ; Thiophenes/therapeutic use* ; Platelet Count ; Female ; Male ; Middle Aged ; Thiazoles

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.

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.

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.

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.

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.

Cosmetics may be an important source of human exposure to per-and polyfluoroalkyl substances(PFASs),posing risks to human health.In this study,a nontarget screening method for PFASs in cosmetics was developed using ultra-high performance liquid chromatography-high-resolution mass spectrometry(UHPLC-Q-Orbitrap HRMS)based on the Kendrick mass defect(KMD).The sample was extracted by ultrasonic assisted extraction prior to being analyzed by UHPLC-Q-Orbitrap HRMS.Acquisition of HRMS data was achieved in both full scan and data-dependent(Full MS/dd MS2)mode.The data collected by HRMS were imported into an in-lab built R script for processing.Samples retained the mass spectra peaks with KMD values in the range of 0.85-1 or 0-0.15 for in-and out-of-library matching;when KMD deviation(δKMD)<0.001 and CF 2 mass error(δMS)<15 ppm,it was considered as a potential PFASs homologues.According to matches of parent ions(MS),fragment ions(MS2)and retention time(RT)with the in-house built PFASs database,the screened and identified potential PFASs were categorized to 5 confidence levels(CL1-CL5).A total of 15 kinds of PFASs homologues with confidence level of CL3 and above were screened from 13 cosmetics products and 8 cosmetic raw materials,including perfluoroalkyl alcohol,hydroperfluoroalkyl sulfonic acid,chloroperfluoroalkyl sulfonic acid,etc.with concentrations ranging from 1.9 ng/g to 98.1 ng/g.The nontarget screening method could be used to screen and identify PFASs homologues feasibly and therefore provided data basis for management and control of PFASs addition in cosmetics.