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.

ObjectiveTo investigate the mechanism of action of remifentanil （RMZL） in alleviating lung ischemia-reperfusion injury （LIRI） in rats by inhibiting pyroptosis through modulating hypoxia inducible factor-1α （HIF-1α）/NOD-like receptor thermal protein domain associated protein 3 （NLRP3） pathway. MethodsRats were stochastically assigned into Control group， LIRI group， RMZL low-dose group， RMZL medium-dose group， RMZL high-dose group， and RMZL high-dose+HIF-1α activator dimethyloxallyl glycine （DMOG） group， with 18 rats in each group. Rats in Control group only had their left pulmonary hilum free and did not undergo ischemia-reperfusion treatment. Except for the Control group， LIRI models were constructed in all other groups. Rats in LIRI group were intraperitoneally injected with an equal amount of physiological saline 15 minutes before constructing LIRI model； rats in Control group were intraperitoneally injected with an equal amount of physiological saline 15 minutes before freeing left pulmonary hilum； rats in other groups were intraperitoneally injected with corresponding dose of drug 15 minutes before constructing LIRI model. The wet/dry weight ratio of lungs was calculated. HE staining was used to study lung tissue pathology. Immunofluorescence staining was used to detect the relative fluorescence intensity of gasdermin D （GSDMD） and NLRP3 double positive cells in lung tissue. ELISA was used to detect interleukin-1β and IL-18 in lung tissue. Western blot was used to detect HIF-1α， NLRP3， cysteine-aspartic protease-1 （Cleaved caspase-1）， and gasdermin D-N （GSDMD-N） proteins in lung tissue. ResultsCompared to the Control group， the LIRI group showed disordered alveolar structure， thickened alveolar septa， and abundant inflammatory cell infiltration in rats. The lung wet/dry weight ratio， relative fluorescence intensity of GSDMD and NLRP3 double positive cells in lung tissue， IL-1β， IL-18 levels， and HIF-1α， NLRP3， Cleaved caspase-1， and GSDMD-N proteins increased （P0.05）. For the LIRI group， rats in the RMZL low， medium， and high-dose groups displayed attenuated alveolar septal thickening and reduced inflammatory cell infiltration. The lung wet/dry weight ratio， relative fluorescence intensity of GSDMD and NLRP3 double positive cells in lung tissue， IL-1β， IL-18 levels， and HIF-1α， NLRP3， Cleaved caspase-1， and GSDMD-N proteins declined， and the RMZL high-dose group showed the most prominent trend （P0.05）. Compared with the RMZL high-dose group， rats in the RMZL high-dose+DMOG group exhibited thickened alveolar septa and more inflammatory cell infiltration， along with increased lung wet/dry weight ratio， relative fluorescence intensity of GSDMD and NLRP3 double positive cells in lung tissue， levels of IL-1β and IL-18， and protein expression of HIF-1α， NLRP3， Cleaved caspase-1， and GSDMD-N （P0.05）. ConclusionRMZL may inhibit pyroptosis in LIRI rats by suppressing HIF-1α/NLRP3 pathway.

Background/Aims: Biliary tract cancer (BTC) is a rare malignancy with poor prognosis. We investigated genomic determinants of clinical benefit from gemcitabine, cisplatin, and nab-paclitaxel (GAP) versus gemcitabine and cisplatin (GC) in advanced BTC. Methods: Clinical and genomic data using TruSight Oncology 500 were analyzed from patients treated with GAP (N=198) or GC (N=89) as first-line therapy. Results: With a median follow-up of 33.0 months, GAP modestly improved progression-free survival (PFS) (hazard ratio [HR] 0.764; 95% confidence interval [CI] 0.591–0.989) without significant overall survival (OS) difference compared to GC. Genomic profiling revealed frequent alterations in TP53 (35.2%), KRAS (16.4%), SMAD4 (10.5%), and TNFRSF14 (10.5%), involving RTK/RAS (44.3%), TP53 (41.8%), and PI3K (20.2%) pathways. Single-gene mutations did not predict treatment benefit. However, pathway-level analysis identified PI3K pathway activation as significantly associated with inferior PFS (HR 2.148; 95% CI 1.478–3.124) and OS (HR 2.096; 95% CI 1.413–3.109) in patients receiving GAP, an effect not observed with GC. Importantly, GAP conferred clinical benefit only in patients without PI3K pathway activation, while no survival advantage was seen in those with such alterations (Pinteraction=0.023 for PFS, Pinteraction=0.003 for OS). Similar results were obtained in the independent validation cohort treated with GAP (N=103) or GC (N=64) for BTC. Conclusions Genomic profiling using next-generation sequencing identified PI3K pathway activation as key molecular determinant that differentiates patient outcomes between GAP and GC treatments in advanced BTC.

Purpose: To assess the accuracy of supraspinatus muscle fat fraction and atrophy measured on the Y-view compared with the newly proposed fossa-view sagittal MRI plane. Materials and Methods: This study included 84 patients (36 male; mean age, 65.1 ± 10.1 years) who underwent shoulder MRI with extended oblique sagittal T1-weighted and three-dimensional (3D) six-echo Dixon imaging between December 2020 and November 2022. The reference fat fraction was calculated by integrating voxel-wise Dixon values, while supraspinatus muscle volume was quantified using a 3D nnU-Net algorithm and normalized to the scapular volume to derive the standardized muscle index (SMI). Fat fraction and cross-sectional area were quantified on the Y-view and fossaview and compared with the reference values. Subgroup analyses were performed using fatty degeneration and retraction grades. Results: Agreement with the reference fat fraction was significantly higher for the fossa-view (intraclass correlation coefficient [ICC], 0.923) than for the Y-view (ICC, 0.822;p = 0.006). The fossa-view showed smaller deviations and narrower limits of agreement.For SMI, the Y-view (ICC, 0.782) showed higher agreement than the fossa-view (ICC, 0.694), although the difference was not statistically significant (p = 0.219). Subgroup analyses showed better Y-view performance at lower retraction grades and better fossa-view performance at higher grades, although the differences were not statistically significant (all p > 0.05). Conclusion Both planes reliably quantified the fat fraction with greater accuracy in the fossa-view. However, single-plane assessment of muscle atrophy was less reliable, underscoring the need for MRI evaluation of the entire muscle.

Alzheimer’s disease (AD) is pathologically characterized by cerebral amyloid β‑protein (Aβ) aggregation, neurofibrillary tangles and progressive cognitive deterioration. There is an urgent clinical demand for targeted therapeutic agents against AD, whereas the blood-brain barrier (BBB) acts as a critical physical barrier that blocks over 98% small-molecule drugs and nearly all biomacromolecules from entering brain parenchyma. Nanomedicine-based drug delivery systems (NDDSs) with tunable physicochemical properties can cross the BBB via multiple transcytosis pathways including adsorptive-mediated, receptor-mediated and transporter-mediated routes, opening a promising avenue for targeted AD treatment. A core academic viewpoint proposed herein is that robust in vitro endothelial penetration of nanocarriers cannot guarantee effective accumulation in brain target cells. Comprehensive evaluation of BBB-crossing delivery efficiency should not merely rely on in vitro permeability tests, but cover the full multi-step transcytosis cascade, cellular tropism in brain tissues and in vivo therapeutic outcomes. This review systematically sorts out diverse nanoplatforms applicable to BBB penetration for AD intervention. Inorganic nanomaterials such as gold and ceria nanoparticles possess large specific surface areas and intrinsic antioxidant capacity, which eliminate reactive oxygen species and hinder Aβ fibrillization. Liposomal formulations and solid lipid nanoparticles exhibit superior biocompatibility with biomimetic phospholipid bilayer architectures, capable of co-loading hydrophilic nucleic acids for Tau regulation and lipophilic Aβ inhibitors; relying on receptor-mediated transcytosis, they achieve sustained drug retention in the brain. Polymeric nanocarriers including nanogels and polyamidoamine dendrimers enable multi-target combinatorial therapy, and can be engineered to release cargo in response to inflammatory microenvironments, thereby suppressing excessive microglial activation and protecting neuronal mitochondria. Beyond conventional nanocarriers, this work elaborates two cutting-edge BBB-crossing delivery platforms: biomimetic nanosystems and metal-organic frameworks (MOFs). Biomimetic nanoparticles camouflaged with erythrocyte, platelet or macrophage membranes, as well as natural exosomes, evade immune clearance, prolong systemic circulation and inherently home to inflammatory lesions. Serving as “nano-decoys”, they neutralize Aβ neurotoxins and remodel cerebral inflammatory microenvironments simultaneously. MOFs feature high porosity and customizable pore channels for co-delivery of multiple therapeutics, and can be integrated with near-infrared photothermal and photooxidation modalities to facilitate focal brain lesion therapy. This review highlights a transformative paradigm shift in the field of BBB-targeted AD therapy: research focus has shifted from simply maximizing cerebral drug penetration toward active modulation and functional restoration of the BBB. Impaired BBB transporters intrinsically impede endogenous Aβ clearance. Accordingly, BBB-regulating nanocarriers are designed to remodel the low-density lipoprotein receptor-related protein 1 (LRP1) trafficking cascade, redirecting endocytic vesicles from lysosomal degradation to non-degradable transcytosis and restoring the intrinsic Aβ efflux capacity of the BBB. Distinct from conventional strategies that only exert local lesion inhibition, this systemic clearance strategy eliminates cerebral Aβ deposits by accelerating peripheral excretion.

Enhancer-promoter communication is fundamental to the spatial and temporal control of gene expression. Cohesin-mediated loop extrusion has long been considered a major structural mechanism that brings distal regulatory elements into proximity with their target promoters. Recent findings from Aboreden et al. refine this view by showing that depletion of Nipped-B-like protein (NIPBL), a key regulator of cohesin loading and loop extrusion, markedly disrupts architectural chromatin loops, whereas many cis-regulatory contacts and broad post-mitotic transcriptional reactivation are only modestly affected. These observations suggest that loop extrusion is important, but not sufficient, for explaining productive regulatory communication. In this Comment, we discuss how transcriptional condensate-like assemblies may provide an additional biochemical and kinetic layer that helps convert regulatory proximity into transcriptional output. By locally enriching transcription factors, coactivators, mediator and RNA polymerase II(Pol II) around active loci, such regulatory hubs may stabilize productive enhancer-promoter encounters and modulate transcriptional activity. We further propose that transcriptional bursting provides a useful framework for understanding this conversion, because gene expression can be decomposed into burst frequency, burst duration and burst size. Integrating chromatin architecture, condensate organization and bursting dynamics may therefore provide a more complete view of how enhancer-promoter communication is re-established after mitosis and how regulatory proximity is converted into transcriptional output through mechanisms beyond loop extrusion.

Objective To analyze the correlation between tongue image features and the risk levels of disease in patients with idiopathic membranous nephropathy(IMN).Methods Based on IMN clinical research electronic data acquisition system,a cross-sectional study method was used to analyze the clinical diagnosis and treatment data of 135 IMN patients from Guangdong Provincial Hospital of Chinese Medicine.The patients were grouped according to the risk levels of disease,and then the correlation between the risk levels of disease and tongue image features was analyzed.During the description of tongue image features,TB is for tongue body,TC is for tongue coating,L is for luminance,a is for red-green axis,G is for the value of green,B is for the value of blue,and AUT is for the value of autocorrelation.Results The comparison of tongue image feature indicators of patients with different risk levels of IMN showed that:(1)the higher the level of disease risk of IMN patients,the greater the values of TB-L,TB-G and TB-B(P<0.05 or P<0.01).The values of tongue image indicator TB-a and TC-a of the patients with different risk levels of IMN were shown in decreasing sequence:low-risk group>high-risk group>middle-risk group>extremely-high-risk group(P<0.05).(2)Linear regression analysis showed that TB-L,TB-G,and TB-B were significantly increased in the high-risk group compared with those in the middle-and low-risk groups(P<0.05 or P<0.01),whereas there were no significant differences between the middle-risk group and low-risk group(P>0.05).(3)The results of correlation analysis showed that there was a positive correlation among most of the tongue image feature indicators(including TB-L,TB-G,TB-B,TB-AUT,TC-L,TC-G,and TC-B,etc.)and the risk level of disease,while TB-a was negatively correlated with the risk level of disease,and the differences were all statistically significant(P<0.05 or P<0.01).(4)All patients were treated with Chinese medicine and/or Chinese patent medicine,and 46.7%of patients were given hormones and immunosuppressants,and there was no statistically significant difference in the the use of hormones and immunosuppressants among various groups(P=0.637).Conclusion There is a correlation between the tongue image features of IMN patients and the risk level of disease,and the results will provide an objective reference for the assessment of illness state and traditional Chinese medicine(TCM)syndrome differentiation of IMN patients.With reference to the changes in the tongue image features,the illness state can be precisely identified,which is more accurate than the inspection of four diagnostic methods of TCM.

Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.