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.

Objective:This study aims to investigate the expression of uridine diphosphate-glucose[]pyrophos-phorylase 2(UGP2)in breast cancer(BC)tissues and its oncogenic mechanism,assessing its potential value as a diag-nostic and prognostic biomarker for breast cancer.Methods:(1)Online database analysis was conducted to assess UGP2 mRNA and protein expression levels in breast cancer and explore their correlation with clinical characteristics.Im-munohistochemistry(IHC)was used to verify UGP2 expression in human breast cancer tumor tissues and evaluate its relationship with clinicopathological features.(2)Kaplan-Meier survival analysis and COX regression models were used to analyze the impact of UGP2 expression on breast cancer patient prognosis.(3)Bioinformatics methods were em-ployed to investigate the correlation between UGP2 and tumor immune cell infiltration,and to predict the biological func-tions and associated signaling pathways of UGP2 in breast cancer.Results:(1)The mRNA and protein expression levels of UGP2 were upregulated in breast cancer tissues(both P<0.05),and were negatively correlated with ER-positive and PR-positive status(OR<1,P<0.05),while positively correlated with Ki-67 levels and the triple-negative breast cancer(TNBC)subtype(OR>1,P<0.05).(2)Elevated expression levels of UGP2 were associated with poorer survival rates in breast cancer patients(both P<0.05)and were identified as an independent adverse prognostic factor for breast cancer(HR=1.40,P<0.05).(3)Functional analysis results suggested that UGP2 may promote tumor progression by regulating metabolism,hormone signaling,and the immune microenvironment.Additionally,UGP2 expression was negatively cor-related with NK cell activation status and positively correlated with the inhibitory state.Conclusion:UGP2 expression is elevated in breast cancer tissues and is closely associated with poor patient prognosis.It may promote cancer pro-gression through mechanisms such as metabolic reprogramming and immune suppression.UGP2 shows promise as a potential biomarker and therapeutic target in breast cancer,providing a basis for personalized treatment.

Utilizing network pharmacology, molecular docking, and cellular experimental validation, this study delved into the therapeutic efficacy and underlying mechanisms of matrine in combating senescence. Databases were utilized to predict targets related to the anti-senescence effects of matrine, resulting in the identification of 81 intersecting targets for matrine in the treatment of senescence. A protein-protein interaction(PPI) network was constructed, and key targets were screened based on degree values. Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were performed on the key targets to elucidate the critical pathways involved in the anti-senescence effects of matrine. Molecular docking was conducted between matrine and key targets. A senescence model was established using human umbilical vein endothelial cells(HUVECs) induced with hydrogen peroxide(H_2O_2). Following treatment with varying concentrations of matrine(0.5, 1, and 2 mmol·L~(-1)), cell viability was assessed by using the CCK-8. SA-β-galactosidase staining was employed to observe the positive rate of senescent cells. Flow cytometry was utilized to measure the apoptosis rate. Real-time quantitative PCR(RT-PCR) was utilized to measure the mRNA expression of apoptosis-related cysteine peptidase 3(CASP3), albumin(ALB), glycogen synthase kinase 3β(GSK3B), CD44 molecule(CD44), and tumor necrosis factor-α(TNF-α). Western blot was performed to detect the protein expression of tumor protein p53(p53), cyclin-dependent kinase inhibitor 1A(p21), cyclin-dependent kinase inhibitor 2A(p16), and retinoblastoma tumor suppressor protein(pRb) in the senescence signaling pathway, p38 protein kinase(p38), c-Jun N-terminal kinase(JNK), and extracellular regulated protein kinases(ERK) in the mitogen-activated protein kinase(MAPK) pathway, and phosphatidylinositol 3-kinase(PI3K) and protein kinase B(Akt) in the PI3K/Akt signaling pathway. The experimental results revealed that matrine significantly increased the viability of HUVECs(P<0.05), decreased the positive rate of senescent cells and the apoptosis rate(P<0.05), and reduced the mRNA expression levels of CASP3, ALB, GSK3B, CD44, and TNF-α(P<0.05). It also inhibited the protein expression of p53, p21, p16 and pRb in the senescence signaling pathway(P<0.05), upregulated the protein expression of p-PI3K/PI3K and p-Akt/Akt(P<0.05), and downregulated the protein expression of p-p38/p38, p-JNK/JNK, and p-ERK/ERK(P<0.05). Collectively, these findings suggest that matrine exerts an inhibitory effect on HUVECs senescence, and its mechanism involves the modulation of the senescence signaling pathway, MAPK pathway, and PI3K/Akt signaling pathway to suppress cell apoptosis and inflammation.
Humans ; Matrines ; Quinolizines/chemistry* ; Alkaloids/chemistry* ; Human Umbilical Vein Endothelial Cells/cytology* ; Cellular Senescence/drug effects* ; Network Pharmacology ; Molecular Docking Simulation ; Signal Transduction/drug effects* ; Protein Interaction Maps/drug effects* ; Cell Survival/drug effects* ; Apoptosis/drug effects* ; Drugs, Chinese Herbal/pharmacology*

From the perspective of competitive endogenous RNA(ceRNA) constructed by metastasy-associated lung adenocarcinoma transcript 1(Malat1) and microRNA 16-5p(miR-16-5p), the improvement mechanism of Tonggu Xiaotong Capsules(TGXTC) on the imbalance and disorder of "cholesterol-iron" metabolism in chondrocytes of osteoarthritis(OA) was explored. In vivo experiments, 60 8-week-old C57BL/6 mice were acclimatized and fed for 1 week and then randomly divided into two groups: blank group(12 mice) and modeling group(48 mice). The animals in modeling group were anesthetized by 5% isoflurane inhalation, which was followed by the construction of OA model. They were then randomly divided into model group, TGXTC group, Malat1 overexpression group, and TGXTC+Malat1 overexpression(TGXTC+Malat1-OE) group, with 12 mice in each group. The structural changes of mouse cartilage tissues were observed by Masson staining after the intervention in each group. RT-PCR was employed to detect the mRNA levels of Malat1 and miR-16-5p in cartilage tissues. Western blot was used to analyze the protein expression of ATP-binding cassette transporter A1(ABCA1), sterol regulatory element-binding protein(SREBP), cytochrome P450 family 7 subfamily B member 1(CYP7B1), CCAAT/enhancer-binding protein homologous protein(CHOP), acyl-CoA synthetase long-chain family member 4(ACSL4), and glutathione peroxidase 4(GPX4) in cartilage tissues. In vitro experiments, mouse chondrocytes were induced by thapsigargin(TG), and the combination of Malat1 and miR-16-5p was detected by double luciferase assay. The fluorescence intensity of Malat1 in chondrocytes was determined by fluorescence in situ hybridization. The miR-16-5p inhibitory chondrocyte model was constructed. RT-PCR was used to analyze the levels of Malat1 and miR-16-5p in chondrocytes under the inhibition of miR-16-5p. Western blot was adopted to analyze the regulation of TG-induced chondrocyte proteins ABCA1, SREBP, CYP7B1, CHOP, ACSL4, and GPX4 by TGXTC under the inhibition of miR-16-5p. The results of in vivo experiments showed that,(1) compared with model group, TGXTC group exhibited a relatively complete cartilage layer structure. Compared with Malat1-OE group, TGXTC+Malat1-OE group showed alleviated cartilage surface damage.(2) Compared with model group, TGXTC group had a significantly decreased Malat1 mRNA level and an increased miR-16-5p mRNA level in mouse cartilage tissues(P<0.01).(3) Compared with the model group, the protein levels of ABCA1 and GPX4 in the cartilage tissue of mice in the TGXTC group increased, while the protein levels of SREBP, CYP7B1, CHOP and ACSL4 decreased(P<0.01). The results of in vitro experiments show that,(1) dual-luciferase was used to evaluate that miR-16-5p has a targeting effect on the Malat1 gene.(2)Compared with TG+miR-16-5p inhibition group, TG+miR-16-5p inhibition+TGXTC group had an increased mRNA level of miR-16-5p and an decreased mRNA level of Malat1(P<0.01).(3) Compared with TG+miR-16-5p inhibition group, TG+miR-16-5p inhibition+TGXTC group exhibited increased expression of ABCA1 and GPX4 proteins and decreased expression of SREBP, CYP7B1, CHOP, and ACSL4 proteins(P<0.01). The reasults showed that TGXTC can regulate the ceRNA of Malat1 and miR-16-5p to alleviate the "cholesterol-iron" metabolism disorder of osteoarthritis chondrocytes.
Animals ; MicroRNAs/metabolism* ; RNA, Long Noncoding/metabolism* ; Chondrocytes/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Mice, Inbred C57BL ; Mice ; Osteoarthritis/drug therapy* ; Iron/metabolism* ; Male ; Cholesterol/metabolism* ; Humans ; Capsules ; RNA, Competitive Endogenous

Tibial plateau fracture is a fracture involving the proximal articular surface of the tibia, and its injury mechanism is complex, the fracture morphology is different, and it is often accompanied by different degrees of soft tissue injury, which is difficult to diagnose and treat. In recent years, the research hotspot has focused on solving the reduction and fixation of the posterior lateral column of the tibial plateau, because it has been clinically found that the residual sagittal plane after tibial plateau fracture is insufficient reduction or loss of reduction leads to knee joint dysfunction. The posterior inclination angle of the tibial plateau is an important parameter to describe the sagittal alignment of the tibia. In the natural state, the posterior tibial slope(PTS) is altered to involve the soft tissues around the knee joint such as anterior cruciate ligament(ACL) and posterior cruciate ligament(PCL), which affects the stability of the knee joint. In total knee arthroplasty(TKA), choosing the appropriate PTS can effectively increase the prosthesis survival rate, improve the flexion and extension knee efficacy, which is beneficial to knee joint stability. In the field of orthopedic trauma, correction of sagittal deformity is equally important, following the principle of "reverse mechanism of injury". Quantitative evaluation of postoperative sagittal realignment of tibial plateau fractures and investigation of the effect of sagittal realignment on long-term outcomes and complications are still poorly understood and require further clinical and biomechanical studies.
Humans ; Tibial Fractures/physiopathology* ; Fracture Fixation, Internal/methods* ; Tibial Plateau Fractures

Objective To investigate the mechanism of hippocampal neuronal plasticity of newborn neurons in the hippocampus by which exercise improves the fear and anxiety symptoms of post-traumatic stress disorder(PTSD).Methods Totally 40 C57BL/6J male mice were randomly divided into by control group(Ctrl)and PTSD group,the PTSD group was divided into a no-exercise group(PTSD),a low-intensity exercise group(L)and a high-intensity exercise group(H).The PTSD model mice were constructed by combining conditioned plantar-foot shock(CF)and single-session sustained stress(SPS).After the exercise intervention,the fear and anxiety levels of the mice were assessed using the conditioned fear test and the elevated cross maze test;Subsequently,the densities of the newborn mature neurons in dentate gyrus(DG)of hippocampus were detected by immunofluorescent double-labelling staining,and the newborn neuron morphology was marked by injecting retrovirus pRetro-U6-EF1-EGFP-3xFLAG-WPRE in DG of hippocampus to observe its morphology.The morphology of the newborn neurons was labelled to observe their dendritic length and the number of branch points;Meanwhile,the concentration level of adiponctin(APN)in the hippocampal area was determined by ELISA.Results The result showed that both high and low-intensity exercise interventions significantly reduced the freezing time of PTSD mice in the conditioned fear test,and in the elevated cross maze experiment,the residence time and the number of entries in the open arm of the mice in the H group increased significantly compared with those in the PTSD group,while the residence time and the number of entries in the closed arm were significantly reduced.In addition,both high and low-intensity exercise interventions significantly increased the surface density and dendritic length of newborn mature neurons in the hippocampal DG region of PTSD mice,and high-intensity exercise significantly increased the number of dendritic branching points,and the density of newborn mature neurons in the H group was more significantly increased compared with that in the L group.At the same time,the hippocampal APN concentration increased significantly in both L and H groups compared with the PTSD group,and it was more significant in the H group.Conclusion Exercises have an ameliorative effect on anxiety and fear symptoms in PTSD mice,and at the same time,it can increase hippocampal neuroplasticity and adiponctin secretion in PTSD mice,suggesting that the improvement of fear and anxiety symptoms in PTSD by exercise may be related to the increase of hippocampal neuroplasticity and APN secretion,and the improvement effect is better with high-intensity exercise.

Family with sequence similarity 3 member A(FAM3A),a novel mitochondrial protein,plays a pivotal role in hepatic glucose and lipid metabolism by enhancing ATP synthesis and secretion and mod-ulating the ATP-P2 receptor-Akt signaling pathway.Dysregulation of FAM3A is closely associated with the pathogenesis of non-alcoholic fatty liver disease(NAFLD)and type 2 diabetes mellitus(T2DM).In this study,targeting FAM3A as a therapeutic candidate,we conducted virtual screening to identify 47 small-molecule compounds with potential binding activity.Surface plasmon resonance(SPR)analysis re-vealed three compounds exhibiting high binding affinity to FAM3 A.Further structural characterization of the FAM3A-compound complexes,combined with intermolecular interaction analysis,elucidated the binding mode of the lead compound Index 2(taxifolin)to FAM3A at atomic resolution.These findings provide critical insights into the molecular mechanisms underlying ligand-FAM3A interactions and deliver valuable chemical scaffolds for the development of therapeutics targeting NAFLD and T2DM.This work establishes a foundation for advancing drug discovery efforts focused on FAM3A-mediated metabolic disor-ders.

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.