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.

With the rapid development of the biopharmaceutical field, the efficient and simultaneous extraction of multiple biological components from biological samples has become a critical process for advancing scientific research. The ability to simultaneously extract various molecular components such as metabolites, DNA, RNA, and proteins is pivotal for multi-omics studies, which aim to comprehensively understand the molecular mechanisms of biological systems. Traditional methods often extract these components separately, leading to challenges such as sample loss, time consumption, contamination, and inconsistencies across different data types. In contrast, simultaneous extraction techniques address these issues by maintaining the consistency of each biological component’s physiological state, improving data reliability and facilitating integration across omic platforms. This review systematically summarizes recent advances in simultaneous extraction technologies, focusing on methods such as methanol/chloroform extraction, TRIzol reagent extraction, and modified Folch extraction, which have shown significant promise in improving the efficiency and integrity of biological sample preparation. These methods offer various advantages, such as reduced sample volume requirements, decreased contamination risk, and enhanced extraction consistency, which are crucial for studies involving small sample sizes or precious clinical specimens. Among these, methanol/chloroform extraction stands out for its simplicity, low cost, and ability to extract a wide range of biological molecules. However, it does face limitations, such as its inefficiency in extracting lipids and potential RNA contamination. On the other hand, the TRIzol reagent method has become a widely adopted technique due to its ability to simultaneously isolate RNA, proteins, and metabolites from the same sample. Despite its effectiveness, the TRIzol method has limitations in RNA quality, especially when handling complex samples or those with high protein content. Modified Folch extraction, which combines liquid-liquid extraction with commercial kits, offers a highly efficient way to extract polar metabolites, lipids, RNA, DNA, and proteins from small tissue samples. This method has proven advantageous in terms of extraction yield, especially for challenging or rare samples, although it requires precise handling to avoid cross-contamination between phases. The integration of automated platforms, microfluidics, and high-throughput systems is another exciting avenue for improving simultaneous extraction. Automation facilitates large-scale, reproducible sample processing with minimal human error, while microfluidics provides high precision in sample handling and enables real-time monitoring of extraction efficiency. These innovations not only enhance the speed and reproducibility of sample preparation but also open new possibilities for single-cell analysis, where sample volumes are often limited, and extraction efficiency is critical. In addition to the technical aspects, the review also highlights the importance of optimizing extraction protocols for specific sample types, such as clinical tissues, plants, and microorganisms. For example, the challenge of extracting multiple components from cancer tissues, where sample degradation and contamination risks are high, can be mitigated by carefully selecting extraction reagents and minimizing sample handling steps. Similarly, in plant studies, where metabolite diversity is vast, the simultaneous extraction methods must be optimized to account for the unique composition of plant tissues, which often include complex secondary metabolites and cell wall components. Looking forward, the development of more efficient and standardized simultaneous extraction methods will be crucial for advancing multi-omics research. There is a growing need for protocols that can be tailored to specific research needs, ensuring both reproducibility and flexibility in diverse applications. Additionally, combining these extraction methods with high-resolution analytical techniques such as mass spectrometry and next-generation sequencing will further enhance the potential of multi-omics studies to provide comprehensive insights into biological systems. As these technologies continue to evolve, their application in personalized medicine, environmental research, and agriculture holds great promise for addressing critical scientific challenges. In conclusion, while simultaneous extraction technologies have made significant strides, several challenges remain in optimizing extraction efficiency, ensuring reproducibility, and reducing costs. Future research should focus on refining extraction protocols, developing innovative extraction reagents, and expanding the scope of these methods to cater to a broader range of biological samples. Ultimately, the continued integration of these advanced techniques will revolutionize the way biological samples are prepared, analyzed, and understood in the context of multi-omics research.

With the rapid development of the biopharmaceutical field, the efficient and simultaneous extraction of multiple biological components from biological samples has become a critical process for advancing scientific research. The ability to simultaneously extract various molecular components such as metabolites, DNA, RNA, and proteins is pivotal for multi-omics studies, which aim to comprehensively understand the molecular mechanisms of biological systems. Traditional methods often extract these components separately, leading to challenges such as sample loss, time consumption, contamination, and inconsistencies across different data types. In contrast, simultaneous extraction techniques address these issues by maintaining the consistency of each biological component’s physiological state, improving data reliability and facilitating integration across omic platforms. This review systematically summarizes recent advances in simultaneous extraction technologies, focusing on methods such as methanol/chloroform extraction, TRIzol reagent extraction, and modified Folch extraction, which have shown significant promise in improving the efficiency and integrity of biological sample preparation. These methods offer various advantages, such as reduced sample volume requirements, decreased contamination risk, and enhanced extraction consistency, which are crucial for studies involving small sample sizes or precious clinical specimens. Among these, methanol/chloroform extraction stands out for its simplicity, low cost, and ability to extract a wide range of biological molecules. However, it does face limitations, such as its inefficiency in extracting lipids and potential RNA contamination. On the other hand, the TRIzol reagent method has become a widely adopted technique due to its ability to simultaneously isolate RNA, proteins, and metabolites from the same sample. Despite its effectiveness, the TRIzol method has limitations in RNA quality, especially when handling complex samples or those with high protein content. Modified Folch extraction, which combines liquid-liquid extraction with commercial kits, offers a highly efficient way to extract polar metabolites, lipids, RNA, DNA, and proteins from small tissue samples. This method has proven advantageous in terms of extraction yield, especially for challenging or rare samples, although it requires precise handling to avoid cross-contamination between phases. The integration of automated platforms, microfluidics, and high-throughput systems is another exciting avenue for improving simultaneous extraction. Automation facilitates large-scale, reproducible sample processing with minimal human error, while microfluidics provides high precision in sample handling and enables real-time monitoring of extraction efficiency. These innovations not only enhance the speed and reproducibility of sample preparation but also open new possibilities for single-cell analysis, where sample volumes are often limited, and extraction efficiency is critical. In addition to the technical aspects, the review also highlights the importance of optimizing extraction protocols for specific sample types, such as clinical tissues, plants, and microorganisms. For example, the challenge of extracting multiple components from cancer tissues, where sample degradation and contamination risks are high, can be mitigated by carefully selecting extraction reagents and minimizing sample handling steps. Similarly, in plant studies, where metabolite diversity is vast, the simultaneous extraction methods must be optimized to account for the unique composition of plant tissues, which often include complex secondary metabolites and cell wall components. Looking forward, the development of more efficient and standardized simultaneous extraction methods will be crucial for advancing multi-omics research. There is a growing need for protocols that can be tailored to specific research needs, ensuring both reproducibility and flexibility in diverse applications. Additionally, combining these extraction methods with high-resolution analytical techniques such as mass spectrometry and next-generation sequencing will further enhance the potential of multi-omics studies to provide comprehensive insights into biological systems. As these technologies continue to evolve, their application in personalized medicine, environmental research, and agriculture holds great promise for addressing critical scientific challenges. In conclusion, while simultaneous extraction technologies have made significant strides, several challenges remain in optimizing extraction efficiency, ensuring reproducibility, and reducing costs. Future research should focus on refining extraction protocols, developing innovative extraction reagents, and expanding the scope of these methods to cater to a broader range of biological samples. Ultimately, the continued integration of these advanced techniques will revolutionize the way biological samples are prepared, analyzed, and understood in the context of multi-omics research.

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.

The telomere structure in the cell nucleus is crucial for maintaining the stability and functions of chromosomes.Telomerase is a ribonucleoprotein reverse transcriptase,which catalyzes the elongation of telomeres using its own RNA as a template,thereby counteracting the shortening of telomeres caused by chromosome replication and cell division.Due to its overexpression in over 85％of malignant tumor cells,telomerase has emerged as a highly promising biomarker and a novel target for cancer therapy.In recent years,given the importance of precise quantification of telomerase activity in guiding medical diagnosis and treatment strategies,researchers have developed various high-performance telomerase detection techniques.Among these,electrochemical biosensing technique has cause much attention due to its high sensitivity,operational convenience,rapid response,and ease of miniaturization.This paper focused on the latest advances in electrochemical sensing technique for detection of telomerase activity,aiming to provide inspiration for designing novel telomerase activity detection strategies by elucidating three unique properties of telomerase primer extension products.

Adenosine triphosphate(ATP),as the core energy metabolism molecule in living systems,has dynamic changes closely related to fundamental physiological processes.To meet the urgent demand for spatiotemporal ATP detection in vivo and in situ,the development of highly sensitive multifunctional synchronous sensing fluorescent probes has become a recent research focus.These dual-function probes achieve fluorescence detection of dual targets by designing recognition sites for ATP alongside biological factors or microenvironment parameters such as reactive oxygen/nitrogen/sulfur species,metal ions,and enzymes,enabling physiological/pathological state correlation analysis through bioimaging.This paper systematically reviews recent advances in fluorescent probes for the collaborative detection of ATP and key biomolecules.It specifically examines probe construction strategies based on specific molecular recognition mechanisms(e.g.,metal coordination competition,electrostatic interactions,and host-guest recognition),multi-modal optical signal transduction mechanisms(ratiometric fluorescence,fluorescence lifetime,and photodynamic therapy),and their applications in pathological models such as oxidative stress monitoring,metal homeostasis imbalance,and enzyme activity co-detection.Finally,from the perspective of molecular probe engineering,current challenges and future research directions are proposed to provide methodological support for precise analysis of ATP-related life process regulation networks.

Objective To verify the efficacy of a domestic human DNA quantification kit based on real-time fluorescence quantitative PCR in detecting the total human DNA concentration,male DNA concen-tration in mixed male/female DNA samples,the degree of DNA degradation and inhibitor tolerance.Methods Samples with different concentrations,different male/female ratios,different concentrations of inhibitors,and different degradation degrees were tested using the domestic human DNA quantification kit based on real-time fluorescence quantitative PCR.This kit was compared with a similar product on the market and was applied to the detection of DNA from real cases.Results This human DNA quan-tification kit can effectively detect human DNA as low as 0.001 65 ng/μL,and 6.25 pg/μL of male DNA in mixed samples with a male-to-female ratio of 1∶15 000.Even when the sample contains as high as 400 ng/μL of humic acid or 1 000 μmol/L of hemin alone,the DNA concentration can still be accurately detected.The degradation index can effectively characterize the degradation degree of the sample.This kit has been successfully applied in forensic practice.Conclusion This human DNA quan-tification kit is accurate and reliable in detection.It can accurately reflect the degradation of DNA and inhibitor tolerance.It has good performance in quantitative accuracy,determination of the male/female ratio in mixed samples,and inhibitor tolerance.It has application potential in forensic case examination.

Objective To explore the predictive value of transforming growth factor beta 1(TGF-β1),chromobox homolog 7(CBX7),and soluble urokinase type plasminogen activator receptor(suPAR)for post-operative recurrence of cervical intraepithelial neoplasia after cervical conization.Methods A total of 200 pa-tients with cervical intraepithelial neoplasia admitted to the hospital from April 2020 to June 2023 were select-ed as the research subjects.All patients were treated with cervical conization.All patients were followed up for one year.According to the postoperative recurrence of cervical intraepithelial neoplasia patients after cervical conization,they were divided into the recurrence group and the non-recurrence group.Univariate and multiva-riate Logistic regression analyses were conducted to analyze the risk factors influencing the postoperative re-currence of cervical intraepithelial neoplasia after cervical conization.The receiver operating characteristic(ROC)curve was drawn to analyze the value of TGF-β1,CBX7 and suPAR in predicting the postoperative re-currence of cervical intraepithelial neoplasia after cervical conization.A nomogram model for predicting the postoperative recurrence of cervical intraepithelial neoplasia after cervical conization was established using R software and verified both internally and externally.The calibration curve and decision curve were used to ana-lyze the calibration ability and application value of the nomogram.Results The levels of TGF-β1,CBX7 and suPAR in the recurrence group were all higher than those in the non-recurrence group,and the difference was statistically significant(P<0.05).The results of multivariate Logistic analysis showed that TGF-β1,CBX7,and suPAR were all risk factors for postoperative recurrence of cervical intraepithelial neoplasia after cervical conization(P<0.05).The results of ROC curve analysis showed that the area under the curve(AUC)of the combined prediction of TGF-β1,CBX7,and suPAR for the postoperative recurrence of cervical intraepithelial neoplasia after cervical conization was higher than AUC of the individual detection of each index(Z=3.554,2.311,2.520,P<0.05).The correction curve of the nomogram model for predicting the postoperative recur-rence of cervical intraepithelial neoplasia after cervical conization approached the ideal curve(P=0.298,0.687).Conclusion The combination of TGF-β1,CBX7 and suPAR has certain value in predicting the postoperative recurrence of cervical intraepithelial neoplasia after cervical conization.

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.

ObjectiveUlcerative colitis is a prevalent immunoinflammatory disease. Th17/Treg cell imbalance and gut microbiota dysregulation are key factors in ulcerative colitis pathogenesis. The actin cytoskeleton contributes to regulating the proliferation, differentiation, and migration of Th17 and Treg cells. Wdr63, a gene containing the WD repeat domain, participates in the structure and functional modulation of actin cytoskeleton. Recent research indicates that WDR63 may serve as a regulator of cell migration and metastasis via actin polymerization inhibition. This article aims to explore the effect of Wdr63 deletion on Th17/Treg cells and ulcerative colitis. MethodsWe constructed Wdr63^-/- mice, induced colitis in mice using dextran sulfate sodium salt, collected colon tissue for histopathological staining, collected mesenteric lymph nodes for flow cytometry analysis, and collected healthy mouse feces for microbial diversity detection. ResultsCompared with wild-type colitis mice, Wdr63^-/- colitis mice had a more pronounced shortening of colonic tissue, higher scores on disease activity index and histological damage index, Treg cells decreased and Th17 cells increased in colonic tissue and mesenteric lymph nodes, a lower level of anti-inflammatory cytokine IL-10, and a higher level of pro-inflammatory cytokine IL-17A. In addition, WDR63 has shown positive effects on maintaining intestinal microbiota homeostasis. It maintains the balance of Bacteroidota and Firmicutes, promoting the formation of beneficial intestinal bacteria linked to immune inflammation. ConclusionWdr63 deletion aggravates ulcerative colitis in mice, WDR63 inhibits colonic inflammation likely by regulating Th17/Treg balance and maintains intestinal microbiota homeostasis.