Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic neurons in the substantia nigra pars compacta and the pathological accumulation ofα‑synuclein. Although extensive progress has been made in elucidating its pathogenesis, current therapeutic approaches remain largely symptomatic, and effective disease-modifying treatments are still unavailable. Increasing evidence indicates that PD is driven by the interaction of multiple pathological processes, including neuroinflammation, iron homeostasis dysregulation and ferroptosis, endoplasmic reticulum (ER) stress, mitochondrial dysfunction, oxidative stress, and impaired protein homeostasis, which together contribute to neuronal vulnerability and degeneration. Fibroblast growth factors (FGFs) comprise a family of 22 ligands that play important roles in neural development, stress responses, metabolic regulation, and the maintenance of nervous system homeostasis. Recent studies have shown that several FGF family members, such as FGF1, FGF2, FGF9, and FGF21, exert neuroprotective effects in cellular and animal models of PD. These effects include the regulation of inflammatory responses, oxidative stress, iron homeostasis, cellular stress adaptation, and neuronal survival. Compared with therapeutic strategies targeting a single pathogenic pathway, FGFs appear to influence multiple disease-related processes, suggesting their potential relevance to the complex pathophysiology of PD. Experimental evidence indicates that altered FGF signaling may contribute to dopaminergic neuron dysfunction through the coordinated regulation of several interconnected mechanisms. FGFs have been reported to modulate neuroinflammation by affecting the activation of microglia and astrocytes, thereby influencing the inflammatory environment in the central nervous system. In addition, FGFs are involved in the regulation of iron homeostasis and ferroptosis, partly through antioxidant signaling pathways associated with NRF2, SLC7A11, and GPX4. Moreover, FGFs can alleviate ER stress and mitochondrial dysfunction by activating intracellular signaling pathways such as PI3K/AKT, AMPK-PGC-1α, as well as SIRT1-dependent programs, which support cellular energy metabolism and redox balance. Recent advances in single-cell and spatial transcriptomic studies further suggest that FGF signaling is not limited to neuron-intrinsic mechanisms but also involves interactions among different glial cell types. Altered FGF ligand-receptor communication between astrocytes and oligodendrocytes has been observed in PD models and is associated with increased susceptibility of dopaminergic neurons to oxidative stress and ferroptosis. These findings indicate that the biological effects of FGFs are influenced by cell type and disease stage and may vary under different pathological conditions. In this review, we summarize recent progress in understanding the roles of FGF family members in PD, with a focus on their involvement in iron homeostasis dysregulation and ferroptosis, neuroinflammation, cellular stress responses, and neuronal protection and regeneration. By integrating current evidence, this review aims to provide a clearer understanding of how FGFs participate in PD pathogenesis and to offer a theoretical basis for future studies exploring their potential value in disease-modifying therapeutic strategies.

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.

Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

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.

The pathogenesis of central precocious puberty(CPP)is due to the early initiation of the function of the hypothalamic-pituitary-gonadal axis,which is driven by the gonadotrophin-releasing hor-mone(GnRH)from the hypothalamus.The increase of GnRH secretion will promote the secretion of gon-adotropin by the pituitary gland,which leads to the development of reproductive organs and the secretion of sex hormones.The timing of puberty onset is influenced by the interaction between nutritional,envi-ronmental,and socioeconomic factors.In the study of pathogenic genes,loss-of-function mutations of MKRN3,LIN28 and DLK1 genes can lead to early onset of puberty,among which loss-of-function muta-tions of MKRN3 are one of the most common single-gene causes of familial CPP.Since 2013,when the MKRN3 mutation was first identified in five CPP families,the role of MKRN3 in adolescence has gradu-ally been discovered.MKRN3 is a member of the E3 ubiquitin ligase family and is expressed in the cen-tral nervous system of many eukaryotes.MKRN3 may act as an E3 ubiquitin ligase to inhibit GnRH activ-ity.Recently,more and more studies have explored the molecular mechanism of MKRN3 in CPP,revea-ling a variety of genes and proteins that interact with MKRN3.For example,MKRN3 can inhibit KISS1 and TAC3 activities,thereby affecting the expression of kisspeptin and neurokinin B to regulate GnRH se-cretion.MKRN3 also inhibited GNRH1 mRNA translation through PABPC1 ubiquitination.In addition,there are other targets such as MBD3,IGF2BP1 and NPTX1,all of which are involved in GnRH regula-tion downstream of MKRN3.Upstream of MKRN3,miR-30 can bind to three sites in the 3'-untranslated region of the MKRN3 gene to block MKRN3 transcription.Here we review the role of MKRN3 in the path-ogenesis of CPP and the research progress of its molecular mechanism,which will help to better under-stand the pathogenesis of CPP,provide new ideas and treatment methods for CPP-related fields in the fu-ture,and lay a theoretical foundation for further exploration of the molecular mechanism of MKRN3.

The overall revision of ISO 10555-1:2023 Intravascular catheters—Sterile and single-use catheters—Part 1:General requirements was introduced,which was compared with YY 0285.1-2017 Intravascular catheters—Sterile and sing-use catheters—Part 1:General requirements in terms of terminology definition,requirements and identification of nominal size.The new and changed contents of ISO 10555-1:2023 were interpreted,and references were provided for the develop-ment,inspection and testing and supervision of related products and for the future revision of YY 0285.1-2017 standard.[Chinese Medical Equipment Journal,2025,46(10):65-70]