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 To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

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.

An assay was established for detection of toxigenic Clostridioides difficile by combining microfluidic chip analysis with immunochromatography,and its performance was evaluated and compared with those of the Xpert C.difficile/Epi and VIDAS CD AB tests.Primer pairs were designed according to the tcdB and tpi genes in C.difficile.The specificity,limit of detection,reproducibility,and stability were evaluated.A total of 215 stool samples from patients with diarrhea were collected and tested in parallel with the Xpert C.difficile/Epi,VIDAS CDAB,and our assay.C.difficile was isolated from samples,and the tcdB gene was identified when discrepant results were obtained from the three above assays.Our assay showed no cross-reaction with other diarrhea-associated pathogens.Its reproducibility was 100％in testing of two standard plasmids containing tcdB and tpi genes at two concentrations(105 and 102 copies/μL).Two standard plasmids were detected after the PCR and immunochromatography reagents had been stored for 3,6,9,and 12 months,and all the results were posi-tive.The limit of detection was 10 copies/μL for toxigenic C.difficile.Testing of 33 samples positive for C.difficile with our assay(33/215,15.3％)yielded findings statistically coherent with those of the Xpert C.difficile/Epi test(kappa value=0.965).The sensitivity,specificity,positive predictive value,and negative predictive value of our assay,with respect to Xpert C.difficile/Epi as the standard,were 94.3％,100.0％,100.0％,and 98.9％;these values were significantly higher than those of VIDAS CDAB(60.0％,98.9％,91.3％,and 92.7％)(Kappa=0.714,OR=157.50,95％CI:62.03-847.28,P=0.013).In conclusion,our newly developed assay is specific,stable,and reproducible,and may be used for rapid and accu-rate detection of toxigenic C.difficile.The assay could be used for C.difficile infection screening in outpatient and emergen-cy,community medical service center,and epidemiological settings.

Objective This study aimed to investigate the relationship between multiple inflammatory markers and poor outcome in patients with intracerebral hemorrhage,and to compare their predictive abilities.Methods We retrospectively analyzed the patients with intracerebral hemorrhage admitted to the Department of Neurology of the First Affiliated Hospital of Nanchang University from January 1,2015 to March 31,2023.According to the Modified Rankin Scale at 90 days after onset,the patients were divided into good outcome(mRS≤2 points)and poor outcome(mRS score≥3 points).Clinical information,laboratory examinations and follow-up data were compared between the two groups.Inflammatory markers include neutrophil to lymphocyte ratio(NLR),platelet to lymphocyte ratio(PLR),monocyte to high-density lipoprotein ratio(MHR),systemic inflammatory response index(SIRI),systemic immune-inflammation index(SII),white blood cell count to mean platelet volume ratio(WMR),lymphocyte to monocyte ratio(LMR),and systemic coagulation-inflammation index(SCI).Univariate and multivariate logistic regression analysis were used to analyze the predictors of poor prognosis after intracerebral hemorrhage,and receiver operating characteristic curve(ROC)was constructed to compare their predictive ability.Results A total of 510 patients with intracerebral hemorrhage were included.Of those,297(58.2%)had good outcome,and 213(41.8%)had poor outcome.Comparison of baseline characteristics demonstrated that patients with poor prognosis had higher levels of white blood cells,neutrophils,high-density lipoprotein,fibrinogen,NLR,PLR,SIRI,SII,WMR at admission,larger baseline hematoma volume and baseline perihematomal edema volume,a higher proportion of lobar hemorrhage,older age,and lower levels of platelets,lymphocytes,LMR,and SCI(P<0.05).Multivariate regression analysis showed that NLR(OR:1.081,95%CI:1.032～1.1131,P=0.001),SIRI(OR:1.089,95%CI:1.014～1.169,P=0.019),SII(OR:1.000,95%CI:1.000～1.001,P=0.011),WMR(OR:2.627,95%CI:1.267～5.445,P=0.009)were independently associated with poor prognosis in patients with ICH.In ROC analysis,the area under the curve of NLR(0.729,95%CI:0.685～0.774)was higher than SIRI(0.692,95%CI:0.645～0.738),SII(0.688,95%CI:0.641～0.735)and WMR(0.65,95%CI:0.602～0.698)for predicting poor outcomes.Conclusion NLR,SIRI,SII and WMR at admission are independently associated with poor outcomes in patients with intracerebral hemorrhage,and NLR has the strongest predictive ability.

Aim To explore the effect of the classical famous prescription Dahuang Zhechong pill(DHZCP)on relieving liver cirrhosis by regulating the stress fiber remodeling mediated by mechanistic signaling pathway and to explore the underlying mechanism.Methods Mice were randomly divided into the control group,model group,DHZCP low-dose group,DHZCP high-dose group,and Colchicine-positive control group.The liver cirrhosis mouse model was constructed by intrap-eritoneal injection of olive oil-solubilized CCl4.HE staining and serologic markers were used to reflect liver injury.Masson staining was used to evaluate collagen deposition in liver tissue.ELISA was applied to detect vasoactive molecules and cancer indicators.Atomic force microscopy was employed to detect liver tissue stiffness.Color Doppler diagnostic instrument was used to assess portal blood flow velocity.Western blot was utilized to detect ROCK2 expression and phosphoryla-tion of YAP,Cofilin,and MLC.Results The liver tis-sues in the model group had obvious inflammatory cell infiltration and collagen deposition,accompanied by significant elevation of serum transaminases and fibrosis indexes.Similarly,vasoactive molecules and cancer in-dicators were elevated,and the mechanoregulatory pro-tein ROCK2 expression and phosphorylation of Cofilin and MLC were elevated,with YAP being strongly de-phosphorylated.Both low and high doses of DHZCP re-versed the pathological changes,serological indices,and inhibited the activation of the stress fiber(SF)re-modeling mechanistic signaling pathway.Conclusion DHZCP effectively ameliorates liver tissue lesions in mice with liver cirrhosis,and its mechanism may be re-lated to the inhibition of SF remodeling mechanistic signaling pathway.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

The study was aimed at identifying the diversity of tick species in selected areas of Qinghai,to analyze the genetic differentiation characteristics of tick-borne spotted fever group rickettsiae(SFGR),and to provide the theoretical basis for SFGR prevention and control in the region.The 16S rRNA gene was used for molecular biological identification of 446 collected tick samples,and the infection characteristics of SFGR in tick samples were determined according to the SFGR outer membrane protein A(ompA)gene.Haplotype analysis,phylogenetic tree construction,and estimation of differentiation times for SFGR were conducted in DNASP v6,IQ-tree v2.2.0,and BEAST v2.7.4 software.The obtained 446 tick samples belonged to three categories:(1)Haemaphy-salis spp.,including Haemaphysalis qinghaiensis(n=192)and H.danieli(n=37);(2)Dermacentor spp.,including Dermacentor ever-estianus(n=121),D.nuttalli(n=55),and D.silvarum(n=36);and(3)Hyalomma marginatum(n=5).Rickettsia raoultii was de-tected in D.everestianus,D.silvarum,D.nuttalli,H.qinghaiensis,and H.danieli,with infection rates of 95.9%,80.6%,69.1%,4.1%,and 2.7%,respectively.R.sibirica subsp.sibirica BJ-90 was found only in D.silvarum and D.nuttalli,with infection rates of 5.6%and 1.8%,respectively.The Candidatus R.gannanii F107 was found in H.danieli and H.qinghaiensis,with infection rates of 16.2%and 7.8%,respectively.Ca.R.hongyuanensis was detected only in H.qinghaiensis,with a prevalence of 16.3%.The prevalence of R.aeschlimannii was 20%and 2.7%in Hy.marginatum and H.danieli,respectively.Haplotype and nucleotide polymorphism analy-ses revealed 13 haplotypes in R.raoultii,with haplotype H13 as the dominant haplotype(42/192);seven haplotypes in Ca.R.ganna-nii F107,with haplotype H4 as the dominant haplotype(4/18);and three haplotypes in Ca.R.hongyuanensis,with haplotype H1 as the dominant haplotype(11/13).The phylogenetic tree indicated that the sequences of R.raoultii in selected areas of Qinghai and R.rhipicephali clustered into one branch;Ca.R.hongyuanensis and Ca.R.gannanii F107 clustered into one branch;and R.sibirica subsp.sibirica BJ-90 clustered into one branch with R.sibirica.Estimates of differentiation time revealed that the mean differentiation time for the six Rickettsia was approximately 2 000 Mya(95%CI:1 999.08-2 001.02 Mya).The tick species distributed in selected ar-eas of Qinghai are diverse,and this study provides the first report of Hy.marginatum in Qinghai Province.SFGR significantly varied in prevalence among tick species and showed high genetic diversity.

Objective:To prepare nanoscale docetaxel-loaded lipid microbubbles(DLLM),characterize their physical and chemical properties,evaluate their biosafety and anti-tumor effects in vitro,and explore their potential as a targeted delivery system for chemotherapeutic drugs.Methods:DLLM was prepared by thin film hydration method.The morphology,particle size and distribution were characterized by transmission electron microscopy,scanning electron microscopy and particle size analyzer.The drug encapsulation efficiency was determined by high performance liquid chromatography.Human hepatoma HepG2 cells were used as a model to set up the control group(Control group),the docetaxel group(DOC group),the docetaxel-loaded lipid microbubbles group(DLLM group)and the docetaxel-loaded lipid microbubbles+ultrasound group(DLLM+US group).The cell morphology was observed by optical microscope,the cell survival rate was detected by CCK-8 method,and the apoptosis was detected by flow cytometry.The biocompatibility of microbubbles and their mediated ultrasound-enhanced anti-tumor effect were evaluated.Results:The prepared DLLM was regular spherical,with a particle size distribution range of 200-600 nm,an average particle size of 380 nm,and an encapsulation efficiency of 80.3％±2.6％.The cell viability of the DOC group and the DLLM+US group was significantly lower than that of the Control group(P＜0.01),and the apoptosis rate was significantly increased(P＜0.01).The cell viability of the DLLM+US group was lower than that of the DOC group(P＜0.05),and the apoptosis rate was higher than that of the DOC group(P＜0.05).There was no significant difference in cell viability and apoptosis rate between the DLLM group and the Control group(P＞0.05).Conclusions:The nano-scale DLLM prepared in this experiment has uniform particle size,high encapsulation efficiency,good stability and biocompatibility.DLLM can enhance the killing and pro-apoptotic effects of docetaxel on HepG2 cells under ultrasound irradiation.

Objective To explore the influencing factors of acute kidney injury in severe burn patients,and to construct a visual risk nomogram model.Methods A total of 390 patients with severe burn admitted to the Institute of Burn Frostbite and Tissue Function Reconstruction of Chinese People's Armed Police Force Specialty Medical Center from January 2018 to January 2022 were collected as an internal training data set,and 50 patients with severe burn admitted from February to December 2022 were collected as an external validation data set.The 390 patients of the internal training data set were divided into the acute kidney injury group and the non-acute kidney injury group according to the occurrence of acute kidney injury,and the baseline data of patients in the two groups were compared.Univariate and multivariate Logistic regression were used to analyze the risk factors of acute kidney injury in severe burn patients of the internal training data set,and a nomogram model was drawn.Subsequently,the model was verified both internally and externally.Kaplan-Meier analysis and Log-rank test were used to compare the 90-day survival rate of patients between the acute kidney injury group and the non-acute kidney injury group.Results The burn area(OR=1.18,95%CI:1.06 to 2.36,P=0.004),sequential organ failure assessment(SOFA)score(OR=1.81,95%CI:1.21 to 5.92,P<0.001),inhalation injury(OR=3.21,95%CI:1.23 to 6.35,P<0.001),neutrophil to lymphocyte ratio(NLR)(OR=1.22,95%CI:1.05 to 3.65,P<0.001)and albumin(ALB)(OR=0.78,95%CI:0.57 to 0.92,P=0.011)were the independent risk factors for the development of acute kidney injury in severe burn patients.The nomogram model was established by the above factors.The area under the receiver operating characteristic curve(AUC)of the internal training data set was 0.833(95%CI:0.752 to 0.935),the sensitivity was 81.2%,and the specificity was 83.2%.The AUC of the external validation data set was 0.842(95%CI:0.762 to 0.912),the sensitivity 87.2%,and the specificity was 78.7%.The 90-day survival rate of patients in the acute kidney injury group after burns was significantly lower than that in the non-acute kidney injury group(P<0.001).Conclusion Larger burn area,higher SOFA score,combined inhalation injury,increased NLR,and decreased ALB level are the risk factors for the occurrence of acute kidney injury in severe burn patients,which are related to the 90-day survival rate of patients after burns.The nomogram model based on the risk factors can provide certain reference for clinical individualized prevention and treatment of acute kidney injury in severe burn patients.