Label-free quantification of differentially expressed proteins in mouse liver cancer cells with high and low metastasis rates by a SWATH acquisition method

Label-free quantification is a valuable tool for the analysis of differentially expressed proteins identified by mass spectrometry methods.Herein,we used a new strategy:data-dependent acquisition mode identification combined with label-free quantification by SWATH acquisition mode,to study the differentially expressed proteins in mouse liver cancer metastasis cells.A total of 1528 protein groups were identified,among which 1159 protein groups were quantified and 249 protein groups were observed as differentially expressed proteins(86 proteins up-regulated and 163 down-regulated).This method provides a commendable solution for the identification and quantification of differentially expressed proteins in biological samples.

A strategy with label-free quantification of the targeted peptides for quantitative peptidome analysis of human serum

Peptidomics draws more and more attention in discovering useful biomarkers for early diagnosis of disease. However, there is lack of efficient quantification strategy in peptidome analysis. In this study, a strategy with label-free quantification of the targeted endogenous peptides based on peak intensity using μUPLC-Q-TOF-MS/MS was developed for quantitative peptidome analysis of human serum. Different amounts of standard BSA tryptic digesting peptides were added into the same serum extracts for evaluation of the developed strategy, and it was observed that the average relative error of the targeted peptides was 6.42%, which was superior to the result obtained directly by commercially available software PLGS. It was also demonstrated that this quantification strategy could obviously increase the detection sensitivity of the peptide by DDA analysis. Then, this strategy was applied to comparatively analyze the peptides extracted from the serum of HCC or breast cancer patients and healthy individuals, respectively. Peptides with charge states up to 5 and molecular weight over 4000 can be reliably identified and quantified. This quantitative analysis method based on μUPLC-Q-TOF-MS/MS exhibited superior sensitivity than that by MALDI-TOF-MS commonly used in peptidome analysis. Finally, some interesting endogenous peptides related to corresponding diseases were successfully obtained.

Label-free quantification of peptides in solution by disposable patterned hydrophilic chip based MALDI imaging

Quantification of a mixture of peptides in solution was achieved by disposable patterned hydrophilic chip based matrix-assisted laser desorption/ionization mass spectrometric imaging（MALDI MSI）.Compared with other quantitative methods for peptides in solution, this method is label-free and does not require separation of the multiple components of the solution before analysis. Uniform hydrophilic spots and high mass accuracy measurements provided confident identification and quantitative analysis of imaged compounds. The linear correlation between concentration and grayscale of image in the range of 5 fmol/μ L to 1 pmol/μ L was obtained for all four peptides. Good sensitivity and excellent reproducibility were also achieved. The method expands the application of MALDI MSI from tissues to solutions.

Tb^(3+)-nucleic acid probe-based label-free and rapid detection of mercury pollution in food

Mercury is a threatening pollutant in food,herein,we developed a Tb^(3+)-nucleic acid probe-based label-free assay for mix-and-read,rapid detection of mercury pollution.The assay utilized the feature of light-up fluorescence of terbium ions(Tb^(3+))via binding with single-strand DNA.Mercury ion,Hg^(2+)induced thymine(T)-rich DNA strand to form a double-strand structure(T-Hg^(2+)-T),thus leading to fluorescence reduction.Based on the principle,Hg^(2+)can be quantified based on the fluorescence of Tb^(3+),the limit of detection was 0.0689μmol/L and the linear range was 0.1-6.0μmol/L.Due to the specificity of T-Hg^(2+)-T artificial base pair,the assay could distinguish Hg^(2+)from other metal ions.The recovery rate was ranged in 98.71%-101.34%for detecting mercury pollution in three food samples.The assay is low-cost,separation-free and mix-to-read,thus was a competitive tool for detection of mercury pollution to ensure food safety.

Label-free in-vivo classi-cation and tracking of red blood cells and platelets using Dynamic-YOLOv4 network

In-vivo flow cytometry is a noninvasive real-time diagnostic technique that facilitates continuous monitoring of cells without perturbing their natural biological environment,which renders it a valuable tool for both scientific research and clinical applications.However,the conventional approach for improving classification accuracy often involves labeling cells with fluorescence,which can lead to potential phototoxicity.This study proposes a label-free in-vivo flow cytometry technique,called dynamic YOLOv4(D-YOLOv4),which improves classification accuracy by integrating absorption intensity fluctuation modulation(AIFM)into YOLOv4 to demodulate the temporal features of moving red blood cells(RBCs)and platelets.Using zebrafish as an experimental model,the D-YOLOv4 method achieved average precisions(APs)of 0.90 for RBCs and 0.64 for thrombocytes(similar to platelets in mammals),resulting in an overall AP of 0.77.These scores notably surpass those attained by alternative network models,thereby demonstrating that the combination of physical models with neural networks provides an innovative approach toward developing label-free in-vivoflow cytometry,which holds promise for diverse in-vivo cell classification applications.

Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

Uncertainty quantification of mechanism motion based on coupled mechanism—motor dynamic model for ammunition delivery system

In this paper,a dynamic modeling method of motor driven electromechanical system is presented,and the uncertainty quantification of mechanism motion is investigated based on this method.The main contribution is to propose a novel mechanism-motor coupling dynamic modeling method,in which the relationship between mechanism motion and motor rotation is established according to the geometric coordination of the system.The advantages of this include establishing intuitive coupling between the mechanism and motor,facilitating the discussion for the influence of both mechanical and electrical parameters on the mechanism,and enabling dynamic simulation with controller to take the randomness of the electric load into account.Dynamic simulation considering feedback control of ammunition delivery system is carried out,and the feasibility of the model is verified experimentally.Based on probability density evolution theory,we comprehensively discuss the effects of system parameters on mechanism motion from the perspective of uncertainty quantization.Our work can not only provide guidance for engineering design of ammunition delivery mechanism,but also provide theoretical support for modeling and uncertainty quantification research of mechatronics system.

Ionically Imprinting-Based Copper(Ⅱ)Label-Free Detection for Preventing Hearing Loss

Copper is a microelement with important physiological functions in the body.However,the excess copper ion(Cu^(2+))may cause severe health problems,such as hair cell apoptosis and the resultant hearing loss.Therefore,the assay of Cu^(2+)is important.We integrate ionic imprinting technology(IIT)and structurally colored hydrogel beads to prepare chitosan-based ionically imprinted hydrogel beads(IIHBs)as a low-cost and high-specificity platform for Cu^(2+)detection.The IIHBs have a macroporous microstructure,uniform size,vivid structural color,and magnetic responsiveness.When incubated in solution,IIHBs recognize Cu^(2+)and exhibit a reflective peak change,thereby achieving label-free detection.In addition,benefiting from the IIT,the IIHBs display good specificity and selectivity and have an imprinting factor of 19.14 at 100μmol·L^(-1).These features indicated that the developed IIHBs are promising candidates for Cu^(2+)detection,particularly for the prevention of hearing loss.

Proteomic study of vitreous in proliferative diabetic retinopathy patients after treatment with aflibercept:a quantitative analysis based on 4D label-free technique

AIM:To identify different metabolites,proteins and related pathways to elucidate the causes of proliferative diabetic retinopathy(PDR)and resistance to anti-vascular endothelial growth factor(VEGF)drugs,and to provide biomarkers for the diagnosis and treatment of PDR.METHODS:Vitreous specimens from patients with diabetic retinopathy were collected and analyzed by Liquid Chromatography-Mass Spectrometry(LC-MS/MS)analyses based on 4D label-free technology.Statistically differentially expressed proteins(DEPs),Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway representation and protein interactions were analyzed.RESULTS:A total of 12 samples were analyzed.The proteomics results showed that a total of 58 proteins were identified as DEPs,of which 47 proteins were up-regulated and 11 proteins were down-regulated.We found that C1q and tumor necrosis factor related protein 5(C1QTNF5),Clusterin(CLU),tissue inhibitor of metal protease 1(TIMP1)and signal regulatory protein alpha(SIRPα)can all be specifically regulated after aflibercept treatment.GO functional analysis showed that some DEPs are related to changes in inflammatory regulatory pathways caused by PDR.In addition,protein-protein interaction(PPI)network evaluation revealed that TIMP1 plays a central role in neural regulation.In addition,CD47/SIRPαmay become a key target to resolve anti-VEGF drug resistance in PDR.CONCLUSION:Proteomic analysis is an approach of choice to explore the molecular mechanisms of PDR.Our data show that multiple proteins are differentially changed in PDR patients after intravitreal injection of aflibercept,among which C1QTNF5,CLU,TIMP1 and SIRPαmay become targets for future treatment of PDR and resolution of anti-VEGF resistance.

Multi-Compartment SCFA Quantification in Human

Short-chain fatty acids (SCFA) play an important role in human biochemistry. They originate primarily from the digestive system through carbohydrates microbial fermentation. Most SCFA produced in the colon are absorbed by the intestinal wall and enter the bloodstream to be distributed throughout the body for multiple purposes. At the intestinal level, SCFA play a role in controlling fat storage and fatty acid metabolism. The effects of these beneficial compounds therefore concern overall health. They facilitate energy expenditure and are valuable allies in the fight against obesity and diabetes. SCFA are also involved in the regulation of the levels of several neurotransmitters such as GABA (γ-aminobutyric acid), glutamate, serotonin, dopamine, and norepinephrine. Their role is also highlighted in many inflammatory and neurodegenerative diseases such as Alzheimer’s disease (AD) or Parkinson’s disease (PD). To have a realistic picture of the distribution of SCFA in different biological compartments of the human body, we propose to study SCFA simultaneously in five human biological samples: feces, saliva, serum, cerebrospinal fluid (CSF), and urine, as well as in Dried Blood Spot (DBS). To evaluate their concentration and repeatability, we used 10 aliquots from pooled samples, analyzed by 3-nitrophenylhydrazine (3-NPH) derivation and liquid chromatography coupled with high sensitivity mass spectrometry (LC-QqQ-MS). We also evaluated the SCFA assay on Dried Blood Spot (DBS). In this work, we adapted the pre-analytical parts for each sample to be able to use a common calibration curve, thus facilitating multi-assay quantification studies and so being less time-consuming. Moreover, we proposed new daughter ions from the same neutral loss (43 Da) to quantify SCFAs, thus improving the sensitivity. In conclusion, our methodology, based on a unique calibration curve for all samples for each SCFA, is well-suited to quantified them in a clinical context.

Investigation on mechanical properties regulation of rock-like specimens based on 3D printing and similarity quantification

3D printing is widely adopted to quickly produce rock mass models with complex structures in batches,improving the consistency and repeatability of physical modeling.It is necessary to regulate the mechanical properties of 3D-printed specimens to make them proportionally similar to natural rocks.This study investigates mechanical properties of 3D-printed rock analogues prepared by furan resin-bonded silica sand particles.The mechanical property regulation of 3D-printed specimens is realized through quantifying its similarity to sandstone,so that analogous deformation characteristics and failure mode are acquired.Considering similarity conversion,uniaxial compressive strength,cohesion and stress–strain relationship curve of 3D-printed specimen are similar to those of sandstone.In the study ranges,the strength of 3D-printed specimen is positively correlated with the additive content,negatively correlated with the sand particle size,and first increases then decreases with the increase of curing temperature.The regulation scheme with optimal similarity quantification index,that is the sand type of 70/140,additive content of 2.5‰and curing temperature of 81.6℃,is determined for preparing 3D-printed sandstone analogues and models.The effectiveness of mechanical property regulation is proved through uniaxial compression contrast tests.This study provides a reference for preparing rock-like specimens and engineering models using 3D printing technology.

High-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer based on probability density evolution method

This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.

Quantification of the concrete freeze–thaw environment across the Qinghai–Tibet Plateau based on machine learning algorithms

The reasonable quantification of the concrete freezing environment on the Qinghai–Tibet Plateau(QTP) is the primary issue in frost resistant concrete design, which is one of the challenges that the QTP engineering managers should take into account. In this paper, we propose a more realistic method to calculate the number of concrete freeze–thaw cycles(NFTCs) on the QTP. The calculated results show that the NFTCs increase as the altitude of the meteorological station increases with the average NFTCs being 208.7. Four machine learning methods, i.e., the random forest(RF) model, generalized boosting method(GBM), generalized linear model(GLM), and generalized additive model(GAM), are used to fit the NFTCs. The root mean square error(RMSE) values of the RF, GBM, GLM, and GAM are 32.3, 4.3, 247.9, and 161.3, respectively. The R^(2) values of the RF, GBM, GLM, and GAM are 0.93, 0.99, 0.48, and 0.66, respectively. The GBM method performs the best compared to the other three methods, which was shown by the results of RMSE and R^(2) values. The quantitative results from the GBM method indicate that the lowest, medium, and highest NFTC values are distributed in the northern, central, and southern parts of the QTP, respectively. The annual NFTCs in the QTP region are mainly concentrated at 160 and above, and the average NFTCs is 200 across the QTP. Our results can provide scientific guidance and a theoretical basis for the freezing resistance design of concrete in various projects on the QTP.

Revolutionizing disease diagnosis and management:Open-access magnetic resonance imaging datasets a challenge for artificial intelligence driven liver iron quantification

Artificial intelligence(AI),particularly machine learning(ML)and deep learning(DL)techniques,such as convolutional neural networks(CNNs),have emerged as transformative technologies with vast potential in healthcare.Body iron load is usually assessed using slightly invasive blood tests(serum ferritin,serum iron,and serum transferrin).Serum ferritin is widely used to assess body iron and drive medical management;however,it is an acute phase reactant protein offering wrong interpretation in the setting of inflammation and distressed patients.Magnetic resonance imaging is a non-invasive technique that can be used to assess liver iron.The ML and DL algorithms can be used to enhance the detection of minor changes.However,a lack of open-access datasets may delay the advancement of medical research in this field.In this letter,we highlight the importance of standardized datasets for advancing AI and CNNs in medical imaging.Despite the current limitations,embracing AI and CNNs holds promise in revolutionizing disease diagnosis and treatment.

基于label-free定量蛋白质组学方法筛选沉默CHAF1B基因后心肌细胞差异表达蛋白及调控网络分析

目的分析沉默染色质装配因子1亚基B(chromatin assembly factor 1 subunit B,CHAF1B)基因后心肌细胞中差异表达蛋白,预测CHAF1B基因调控网络,为寻找促进心肌细胞修复的潜在治疗靶点提供参考。方法采用转染和蛋白质印迹法筛选沉默CHAF1B基因的有效小干扰RNA(small interfering RNA,siRNA)。应用有效siRNA沉默人源心肌AC16细胞CHAF1B基因后,采用细胞活力检测方法检测细胞活力;提取总蛋白质进行定量、还原、烷基化和胰蛋白酶裂解成肽段,利用高效液相串联质谱法鉴定肽段;搜索UniProt蛋白库筛选差异表达的蛋白质进行基因本体(Gene Ontology,GO)富集分析、京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路富集和蛋白质互作网络(protein-protein interaction networks,PPI)分析。结果siRNA有效沉默CHAF1B基因后,心肌细胞存活明显受到抑制;label-free定量蛋白质组学方法鉴定结果显示,共有69个差异表达蛋白质,其中50个表达显著上调(差异倍数≥2,P<0.05),19个表达显著下调(差异倍数≤0.5,P<0.05)。GO分析显示,差异表达蛋白质主要参与大分子复合亚基体、细胞组分生物合成和组装等生物学过程,分布在细胞质和囊泡等区域,发挥蛋白质结合等分子功能。KEGG通路富集和PPI分析显示,差异表达蛋白质参与的信号通路包括蛋白酶体、氨酰tRNA生物合成、胞吞、嘧啶代谢和氨基酸生物合成等10条信号途径;表达显著上调的蛋白质如蛋白酶体亚单位A2和B7、26 S蛋白酶体调节亚单位6B和10B参与蛋白酶体途径,丝氨酸、甘氨酸、谷氨酰胺和赖氨酸tRNA合成酶介导氨酰tRNA生物合成;表达显著下调的蛋白质包括骨架相关蛋白2/3复合体亚单位3和热休克70蛋白1样参与胞吞作用,核糖核苷-二磷酸还原酶大亚基介导嘧啶代谢等通路。实时荧光定量聚合酶链式反应结果证实,转染CHAF1B siRNA后心肌细胞中合成骨架相关蛋白2/3复合体亚单位3的基因ARPC3和氨酰tRNA生物合成关键基因QARS1的mRNA水平均显著降低。结论CHAF1B为心肌细胞存活的关键蛋白质,参与调控心肌细胞的胞吞和氨基酸生物合成等多种生物学过程,参考其调控网络可帮助寻找促进心肌细胞修复的干预环节。

Label-free,background-free detection of nucleic acid with immobilization-free heterogeneous biosensor and one-pot hybridization chain reaction amplification

Although immobilization-free and label-free electrochemical DNA(E-DNA)biosensors have engaged tremendous interest due to their superior properties,such as easy operation,time-saving and cost-saving,most of them are fabricated in homogeneous modes and usually produce high background current.In the present work,we proposed a new immobilization-free and label-free heterogeneous E-DNA assay based on a dual-blocker-aided multibranched hybridization chain reaction(HCR)for one-pot nucleic acid detection with zero background.The target nucleic acid triggers the HCR involving cascaded hybridization between two metastable hairpins,resulting in the generation of HCR products with multibranched arms,which can be captured onto the electrode viaπ-πstacking interactions between multibranched arms and reduced graphene oxide(rGO).Prior to the incubation process with an electrode,two blockers are designed to prohibit the nonspecific absorption of unreacted hairpin probes.Thus,an immobilization-free and label-free heterogeneous electrochemical assay for one-pot nucleic acid detection with zero background is readily realized.This strategy also presents additional merits of simplicity and cheap cost,since probe immobilization,signal tag labeling,and multiple incubation processes are avoided.Therefore,the as-proposed effective and versatile biosensor has great potential to be applied in nucleic acid-related practical biosensing.

运用Real-time quantification PCR方法建立副溶血性弧菌在即食虾中的生长预测模型

运用Real-time quantification PCR(real-time qPCR)方法建立副溶血性弧菌在即食虾中生长预测模型。首先构建质粒标准品,梯度稀释后建立标准曲线,然后用Real-time qPCR方法检测虾中副溶血性弧菌的数量,最后建立37℃下即食虾中副溶血性弧菌生长预测模型,并与传统涂布计数方法进行比较。结果表明,Real-time qPCR方法和传统计数方法均可建立Gmopertz模型、Logistic模型和Richards模型,模型拟合的相关系数R2均在0.9以上。基于Real-timeqPCR方法省时省力、特异性好等优点,用Real-time qPCR方法建立微生物预测模型是未来预测微生物学领域的一种发展趋势。

基于label-free技术的梅花鹿(Cervus nippon)茸角蛋白组分比较

旨在探究不同生长时期梅花鹿鹿茸的蛋白质组分信息,为鹿茸有效活性物质的挖掘提供理论依据。本研究利用label-free蛋白质组学技术及生物信息学方法对不同生长时期(10、20、40、60、130与360天)梅花鹿茸角蛋白质组分进行比较研究。结果显示,梅花鹿茸角含有丰富的蛋白质,10、20、40、60、130与360天蛋白质含量依次为65.35、70.90、74.00、82.25、56.00、28.02mg·g^-1。应用label-free蛋白质组学技术共鉴定出636种梅花鹿茸角蛋白质,其中218种蛋白质为显著差异表达,主要参与了蛋白质合成、发育、细胞骨架、转运等生物学过程。不同生长阶段茸角的蛋白质表达有各自的特点,为梅花鹿茸角药理活性成分的筛选及茸角相关产品的开发奠定理论基础。

Real-Time PCR Technique and Its Application in Quantification of Plant Nucleic Acid Molecules

Real-time PCR is a closed DNA amplification system that skillfully integrates biochemical, photoelectric and computer techniques. Fluorescence data acquired once per cycle provides rapid absolute quantification of initial template copy numbers as PCR products are generated. This technique significantly simplifies and accelerates the process of producing reproducible quantification of nucleic acid molecules. It not only is a sensitive, accurate and rapid quantitative method, but it also provides an easier way to calculate the absolute starting copy number of nucleic acid molecules to be tested. Together with molecular bio-techniques, like microarray, real-time PCR will play a very important role in many aspects of molecular life science such as functional gene analysis and disease molecular diagnostics. This review introduces the detailed principles and application of the real-time PCR technique, describes a recently developed system for exact quantification of AUX/IAA genes In Arabidopsis, and discusses the problems with the real-time PCR process.

Proteomic Analysis of Chrysanthemum Lateral Buds after Removing Apical Dominance Based on Label-Free Technology

Studying the genetic basis and regulatory mechanism of chrysanthemum lateral bud outgrowth is of great significance for reduction the production cost of cut chrysanthemum.To clarify the molecular basis of lateral bud elongation after removal of apical dominance in chrysanthemum,label-free quantification analysis was used to analyze the proteome changes after apical bud removal.Quantitative real-time PCR(qPCR)was used to analyze the changes in the expression of three plant hormone-related genes.A total of 440 differentially expressed proteins were successfully identified at three time points during the lateral bud elongation.The number of differentially expressed proteins in the three stages(24 h/0 h,48 h/0 h,48 h/24 h)were 219,332,and 97,respectively.The difference in expressed proteins in the three comparison stages mainly involves RNA processing and modification;translation,ribosomal structure and biogenesis;Posttranslational modification,protein turnover,and chaperones.Path analysis showed that there was various physiological activities in the process of lateral bud dormancy breaking and elongation,which involved energy metabolism,biosynthesis,signal transduction and stress response in the growth process of lateral buds.qPCR indicated that the expression of cytokinin synthesis related gene was significantly increased after the removal of apical dominance,while the expression of strigolactones synthesis related gene experiences a dramatic fall to promote the development of the lateral buds.However,there was a drop before a slight increase in the expression of the auxin synthesis related gene,which was mainly due to the removal of apical dominance that led to the loss of indoleacetic acid in the main stem.However,with formation of the new apical source,indoleacetic acid can be released again.