Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a ...Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a long reaction time.Digital PCR-free technologies,which mean the digital assay not relying on thermal cycling to amplify the signal for quantitative detection of nucleic acids at the singlemolecule level,include the digital isothermal amplification techniques(d IATs)and the digital clustered regularly interspaced short palindromic repeats(CRISPR)technologies.They combine the advantages of d PCR and IATs,which could be fast and simple,enabling absolute quantification of nucleic acids at a single-molecule level with minimum instrument,representing the next-generation molecular diagnostic technology.Herein,we systematically summarized the strategies and applications of various dIATs,including the digital loop-mediated isothermal amplification(dLAMP),the digital recombinase polymerase amplification(dRPA),the digital rolling circle amplification(dRCA),the digital nucleic acid sequencebased amplification(d NASBA)and the digital multiple displacement amplification(d MDA),and evaluated the pros and cons of each method.The emerging digital CRISPR technologies,including the detection mechanism of CRISPR and the various strategies for signal amplification,are also introduced comprehensively in this review.The current challenges as well as the future perspectives of the digital PCR-free technology were discussed.展开更多
Viral diseases are an important threat to crop yield,as they are responsible for losses greater than US$30 billion annually.Thus,understanding the dynamics of virus propagation within plant cells is essential for devi...Viral diseases are an important threat to crop yield,as they are responsible for losses greater than US$30 billion annually.Thus,understanding the dynamics of virus propagation within plant cells is essential for devising effective control strategies.However,viruses are complex to propagate and quantify.Existing methodologies for viral quantification tend to be expensive and time-consuming.Here,we present a rapid cost-effective approach to quantify viral propagation using an engineered virus expressing a fluorescent reporter.Using a microplate reader,we measured viral protein levels and we validated our findings through comparison by western blot analysis of viral coat protein,the most common approach to quantify viral titer.Our proposed methodology provides a practical and accessible approach to studying virus-host interactions and could contribute to enhancing our understanding of plant virology.展开更多
The notion of absolutely clean N-complexes is studied.We show that an N-complex X is absolutely clean if and only if X is Nexact and Z,(X)is an absolutely clean module for each n e Z and i=1,2,..,N.In particular,we pr...The notion of absolutely clean N-complexes is studied.We show that an N-complex X is absolutely clean if and only if X is Nexact and Z,(X)is an absolutely clean module for each n e Z and i=1,2,..,N.In particular,we prove that a bounded above N-complex X is absolutely clean if and only if X,is an absolutely clean module for each n e Z.We also show that under certain hypotheses,an Ncomplex X is Gorenstein AC-injective if and only if Z;(X)is a Gorenstein AC-injective module for each n e Z and t=1,2,.,N.展开更多
During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a com...During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a complex,unsteady flow phenomenon highly sensitive to inlet conditions such asMach and Reynolds numbers.The key features of three-dimensional blade stall can be effectively represented by the dynamic stall behavior of a pitching airfoil.In this study,we conduct an uncertainty quantification analysis of dynamic stall aerodynamics in high-Mach-number flows over pitching airfoils,accounting for uncertainties in inlet parameters.A computational fluid dynamics(CFD)model based on the compressible unsteady Reynolds-averagedNavier–Stokes(URANS)equations,coupledwith sliding mesh techniques,is developed to simulate the unsteady aerodynamic behavior and associated flow fields.To efficiently capture the aerodynamic responses while maintaining high accuracy,a multi-fidelity Co-Kriging surrogate model is constructed.This model integrates the precision of high-fidelity wind tunnel experiments with the computational efficiency of lower-fidelity URANS simulations.Its accuracy is validated through direct comparison with experimental data.Building upon this surrogate model,we employ interval analysis and the Sobol sensitivity method to quantify the uncertainty and parameter sensitivity of the unsteady aerodynamic forces resulting frominlet condition variability.Both the inlet Mach number and Reynolds number are treated as uncertain inputs,modeled using interval representations.Our results demonstrate that variations inMach number contribute far more significantly to aerodynamic uncertainty than those in Reynolds number.Moreover,the presence of dynamic stall vortices markedly amplifies the aerodynamic sensitivity to Mach number fluctuations.展开更多
BACKGROUND The Streptococcus salivarius(S.salivarius)group,which produces the enzyme urease has been identified as a potential contributor to ammonia production in the gut.Researchers have reported that patients with ...BACKGROUND The Streptococcus salivarius(S.salivarius)group,which produces the enzyme urease has been identified as a potential contributor to ammonia production in the gut.Researchers have reported that patients with minimal HE had an increased abundance of the S.salivarius group,which is a specific change in the gut microbiota that distinguishes them from healthy individuals.The correlation between the aggregation of specific bacterial species and fibrosis progression in chronic liver disease(CLD)is yet to be fully elucidated.AIM To quantify S.salivarius using digital PCR(dPCR)as a liver fibrosis marker of CLD.METHODS This study retrospectively analysed 52 patients with CLD.To quantify S.salivarius in patients with CLD using dPCR,we evaluated the specificity and sensitivity of S.salivarius bacterial load using dPCR for a type strain.Next,we evaluated the clinical usefulness of dPCR for S.salivarius load quantification for detecting liver fibrosis in patients with CLD.The liver fibrosis stage was categorized into mild and advanced fibrosis based on pathological findings.RESULTS The dPCR assay revealed that S.salivarius was highly positive for the tnpA gene.The lower limit of quantification for dPCR using the tnpA gene with a 1μL template comprising 1.28×102 CFU/mL was 4.3 copies.After considering the detection range in dPCR,we adjusted the extracted DNA concentration to 5.0×10-4 ng/μL from 200 mg stool samples.The median bacterial loads of S.salivarius in stool sample from patients with mild and advanced fibrosis were 1.9 and 7.4 copies/μL,respectively.The quantification of S.salivarius load was observed more frequently in patients with advanced fibrosis than in those with mild fibrosis(P=0.032).CONCLUSION Quantifying of S.salivarius load using digital PCR is a useful biomarker for liver fibrosis in patients with CLD.展开更多
In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a ...In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a distributed data source trust assessment management framework,a trust quantification model,and a dynamic adjustment mechanism are proposed.Themodel integrates the Analytic Hierarchy Process(AHP)and Dempster-Shafer(D-S)evidence theory to determine attribute weights and calculate direct trust values,while the PageRank algorithm is employed to derive indirect trust values.Thedirect and indirect trust values are then combined to compute the comprehensive trust value of the data source.Furthermore,a dynamic adjustment mechanism is introduced to continuously update the comprehensive trust value based on historical assessment data.By leveraging the collaborative efforts of multiple nodes in the distributed network,the proposed framework enables a comprehensive,dynamic,and objective evaluation of data source trustworthiness.Extensive experimental analyses demonstrate that the trust quantification model effectively handles large-scale data source trust assessments,exhibiting both strong trust differentiation capability and high robustness.展开更多
The direct and dissociative ionizations of oxygen molecule are investigated experimen-tally by electron collision with energies from 350 eV to 8000 eV.The absolute ionization cross sections for the product ions(O_(2)^...The direct and dissociative ionizations of oxygen molecule are investigated experimen-tally by electron collision with energies from 350 eV to 8000 eV.The absolute ionization cross sections for the product ions(O_(2)^(2+),O_(2)^(2+)O^(+),O^(2+),and their total)and two Coulomb explosion channels(O^(+)+O^(+)and O^(2+)+O^(+))are obtained by putting the data of O^(2+)on the scale of Ar+from O_(2)and Ar gases mixed with a fixed relative flow ratio of 1:1.The experimental errors are assessed by taking uncertainties of various factors into account.The present absolute cross sections are well consistent with the previous data in the overlapped energy range below 1000 eV.展开更多
Excessive Fe^(3+) ion concentrations in wastewater pose a long-standing threat to human health.Achieving low-cost,high-efficiency quantification of Fe^(3+) ion concentration in unknown solutions can guide environmenta...Excessive Fe^(3+) ion concentrations in wastewater pose a long-standing threat to human health.Achieving low-cost,high-efficiency quantification of Fe^(3+) ion concentration in unknown solutions can guide environmental management decisions and optimize water treatment processes.In this study,by leveraging the rapid,real-time detection capabilities of nanopores and the specific chemical binding affinity of tannic acid to Fe^(3+),a linear relationship between the ion current and Fe^(3+) ion concentration was established.Utilizing this linear relationship,quantification of Fe^(3+) ion concentration in unknown solutions was achieved.Furthermore,ethylenediaminetetraacetic acid disodium salt was employed to displace Fe^(3+) from the nanopores,allowing them to be restored to their initial conditions and reused for Fe^(3+) ion quantification.The reusable bioinspired nanopores remain functional over 330 days of storage.This recycling capability and the long-term stability of the nanopores contribute to a significant reduction in costs.This study provides a strategy for the quantification of unknown Fe^(3+) concentration using nanopores,with potential applications in environmental assessment,health monitoring,and so forth.展开更多
Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence t...Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence tomography(OCT)primarily rely on Doppler OCT(D-OCT)and OCT Angiography(OCTA),which measure axial blood vessel velocity or visualize the vascular architecture,respectively.However,these techniques have limitations in accurately quantifying the absolute velocity of red blood cells(RBCs).This study presents a novel method based on microsphere tracking,which enables precise quantification of absolute blood flow velocity along a blood vessel.In phantom experiments,freshly harvested blood mixed with microspheres was infused into a cellulose tube to simulate a single blood vessel.Experimental results,demon-strating an error margin of less than 10%,validated the effectiveness of this method.Blood flow velocities ranging from 0.472 mm/s to 18.9 mm/s were accurately measured.A preliminary in vivo examination of rabbit ear vessels was conducted,further validating the reliability of this method.This study presents a potential method for specific disease diagnosis by detecting tar-geted vessel flow velocity variations using swept-source optical coherence tomography(SS-OCT)combined with microsphere tracking.展开更多
Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular disease.However,the manual calculation of these parameters is challenging due to the high va...Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular disease.However,the manual calculation of these parameters is challenging due to the high variability among patients and the time-consuming nature of the process.In this study,the authors introduce a framework named MultiJSQ,comprising the feature presentation network(FRN)and the indicator prediction network(IEN),which is designed for simultaneous joint segmentation and quantification.The FRN is tailored for representing global image features,facilitating the direct acquisition of left ventricle(LV)contour images through pixel classification.Additionally,the IEN incorporates specifically designed modules to extract relevant clinical indices.The authors’method considers the interdependence of different tasks,demonstrating the validity of these relationships and yielding favourable results.Through extensive experiments on cardiac MR images from 145 patients,MultiJSQ achieves impressive outcomes,with low mean absolute errors of 124 mm^(2),1.72 mm,and 1.21 mm for areas,dimensions,and regional wall thicknesses,respectively,along with a Dice metric score of 0.908.The experimental findings underscore the excellent performance of our framework in LV segmentation and quantification,highlighting its promising clinical application prospects.展开更多
One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are ...One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.展开更多
For uncertainty quantification of complex models with high-dimensional,nonlinear,multi-component coupling like digital twins,traditional statistical sampling methods,such as random sampling and Latin hypercube samplin...For uncertainty quantification of complex models with high-dimensional,nonlinear,multi-component coupling like digital twins,traditional statistical sampling methods,such as random sampling and Latin hypercube sampling,require a large number of samples,which entails huge computational costs.Therefore,how to construct a small-size sample space has been a hot issue of interest for researchers.To this end,this paper proposes a sequential search-based Latin hypercube sampling scheme to generate efficient and accurate samples for uncertainty quantification.First,the sampling range of the samples is formed by carving the polymorphic uncertainty based on theoretical analysis.Then,the optimal Latin hypercube design is selected using the Latin hypercube sampling method combined with the"space filling"criterion.Finally,the sample selection function is established,and the next most informative sample is optimally selected to obtain the sequential test sample.Compared with the classical sampling method,the generated samples can retain more information on the basis of sparsity.A series of numerical experiments are conducted to demonstrate the superiority of the proposed sequential search-based Latin hypercube sampling scheme,which is a way to provide reliable uncertainty quantification results with small sample sizes.展开更多
Wheat powdery mildew caused by Blumeria graminis f.sp.tritici(Bgt)is an important disease worldwide.Detection of latent infection of leaves by the pathogen in late autumn is valuable for estimating the inoculum potent...Wheat powdery mildew caused by Blumeria graminis f.sp.tritici(Bgt)is an important disease worldwide.Detection of latent infection of leaves by the pathogen in late autumn is valuable for estimating the inoculum potential to assess disease risks in the spring.We developed a new tool for rapid detection and quantification of latent infection of seedlings by the pathogen.The method was based on recombinase polymerase amplification(RPA)coupled with an end-point detection via lateral flow device(LFD).The limit of detection is 100 agμL^(-1)of Bgt DNA,without noticeable interference from either other common wheat pathogens or wheat material(Triticum aestivum).It was evaluated on wheat seedlings for this accuracy and sensitivity in detecting latent infection of Bgt.We further extended this RPALFD assay to estimate the level of latent infection by Bgt based on imaging analysis.There was a strong correlation between the image-based and real-time PCR assay estimates of Bgt DNA.The present results suggested that this new tool can provide rapid and accurate quantification of Bgt in latently infected leaves and can be further development as an on-site monitoring tool.展开更多
Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous ...Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous fluorimetry-based probes have been developed to measure CMCs[3](Fig.S1).However,CMC measurements using these probes suffer from a time-consuming and laborious procedure and large uncertainties,primarily due to their poor photo-stabilities and highly fluctuating fluorescence backgrounds.展开更多
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,conv...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.展开更多
BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients a...BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients and their altered expression in the serum,proteomics techniques were deployed to detect the differentially expressed proteins(DEPs)of in the serum of GDM patients to further explore its pathogenesis,and find out possible biomarkers to forecast GDM occurrence.METHODS Subjects were divided into GDM and normal control groups according to the IADPSG diagnostic criteria.Serum samples were randomly selected from four cases in each group at 24-28 wk of gestation,and the blood samples were identified by applying iTRAQ technology combined with liquid chromatography-tandem mass spectrometry.Key proteins and signaling pathways associated with GDM were identified by bioinformatics analysis,and the expression of key proteins in serum from 12 wk to 16 wk of gestation was further verified using enzyme-linked immunosorbent assay (ELISA).RESULTS Forty-seven proteins were significantly differentially expressed by analyzing the serum samples between the GDMgravidas as well as the healthy ones. Among them, 31 proteins were found to be upregulated notably and the rest16 proteins were downregulated remarkably. Bioinformatic data report revealed abnormal expression of proteinsassociated with lipid metabolism, coagulation cascade activation, complement system and inflammatory responsein the GDM group. ELISA results showed that the contents of RBP4, as well as ANGPTL8, increased in the serumof GDM gravidas compared with the healthy ones, and this change was found to initiate from 12 wk to 16 wk ofgestation.CONCLUSION GDM symptoms may involve abnormalities in lipid metabolism, coagulation cascade activation, complementsystem and inflammatory response. RBP4 and ANGPTL8 are expected to be early predictors of GDM.展开更多
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 establi...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.展开更多
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 pro...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.展开更多
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 manag...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.展开更多
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 absorbe...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.展开更多
基金supported by the National Key Research and Development Program of China(Nos.2023YFC2307305,2021YFF0703300)the Shenzhen Medical Research Fund(No.B2303003)+3 种基金Shenzhen Research Funding Program(Nos.JCYJ20220818102014028,RCBS20210609104339043)National Natural Science Foundation of China(No.22174167)Guangdong Basic and Applied Basic Research(No.2024A1515011281)Fundamental Research Funds for the Central Universities(No.24qnpy087)from Sun Yat-sen University。
文摘Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a long reaction time.Digital PCR-free technologies,which mean the digital assay not relying on thermal cycling to amplify the signal for quantitative detection of nucleic acids at the singlemolecule level,include the digital isothermal amplification techniques(d IATs)and the digital clustered regularly interspaced short palindromic repeats(CRISPR)technologies.They combine the advantages of d PCR and IATs,which could be fast and simple,enabling absolute quantification of nucleic acids at a single-molecule level with minimum instrument,representing the next-generation molecular diagnostic technology.Herein,we systematically summarized the strategies and applications of various dIATs,including the digital loop-mediated isothermal amplification(dLAMP),the digital recombinase polymerase amplification(dRPA),the digital rolling circle amplification(dRCA),the digital nucleic acid sequencebased amplification(d NASBA)and the digital multiple displacement amplification(d MDA),and evaluated the pros and cons of each method.The emerging digital CRISPR technologies,including the detection mechanism of CRISPR and the various strategies for signal amplification,are also introduced comprehensively in this review.The current challenges as well as the future perspectives of the digital PCR-free technology were discussed.
基金Funding from Natural Sciences and Engineering Research Council of Canada award number RGPIN/4002-2020.
文摘Viral diseases are an important threat to crop yield,as they are responsible for losses greater than US$30 billion annually.Thus,understanding the dynamics of virus propagation within plant cells is essential for devising effective control strategies.However,viruses are complex to propagate and quantify.Existing methodologies for viral quantification tend to be expensive and time-consuming.Here,we present a rapid cost-effective approach to quantify viral propagation using an engineered virus expressing a fluorescent reporter.Using a microplate reader,we measured viral protein levels and we validated our findings through comparison by western blot analysis of viral coat protein,the most common approach to quantify viral titer.Our proposed methodology provides a practical and accessible approach to studying virus-host interactions and could contribute to enhancing our understanding of plant virology.
基金Supported by the National Natural Science Foundation of China (12061061)Fundamental Research Funds for the Central Universities (31920230173)+1 种基金Longyuan Young Talents of Gansu ProvinceYoung Talents Team Project of Gansu Province (2025QNTD49)。
文摘The notion of absolutely clean N-complexes is studied.We show that an N-complex X is absolutely clean if and only if X is Nexact and Z,(X)is an absolutely clean module for each n e Z and i=1,2,..,N.In particular,we prove that a bounded above N-complex X is absolutely clean if and only if X,is an absolutely clean module for each n e Z.We also show that under certain hypotheses,an Ncomplex X is Gorenstein AC-injective if and only if Z;(X)is a Gorenstein AC-injective module for each n e Z and t=1,2,.,N.
文摘During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a complex,unsteady flow phenomenon highly sensitive to inlet conditions such asMach and Reynolds numbers.The key features of three-dimensional blade stall can be effectively represented by the dynamic stall behavior of a pitching airfoil.In this study,we conduct an uncertainty quantification analysis of dynamic stall aerodynamics in high-Mach-number flows over pitching airfoils,accounting for uncertainties in inlet parameters.A computational fluid dynamics(CFD)model based on the compressible unsteady Reynolds-averagedNavier–Stokes(URANS)equations,coupledwith sliding mesh techniques,is developed to simulate the unsteady aerodynamic behavior and associated flow fields.To efficiently capture the aerodynamic responses while maintaining high accuracy,a multi-fidelity Co-Kriging surrogate model is constructed.This model integrates the precision of high-fidelity wind tunnel experiments with the computational efficiency of lower-fidelity URANS simulations.Its accuracy is validated through direct comparison with experimental data.Building upon this surrogate model,we employ interval analysis and the Sobol sensitivity method to quantify the uncertainty and parameter sensitivity of the unsteady aerodynamic forces resulting frominlet condition variability.Both the inlet Mach number and Reynolds number are treated as uncertain inputs,modeled using interval representations.Our results demonstrate that variations inMach number contribute far more significantly to aerodynamic uncertainty than those in Reynolds number.Moreover,the presence of dynamic stall vortices markedly amplifies the aerodynamic sensitivity to Mach number fluctuations.
文摘BACKGROUND The Streptococcus salivarius(S.salivarius)group,which produces the enzyme urease has been identified as a potential contributor to ammonia production in the gut.Researchers have reported that patients with minimal HE had an increased abundance of the S.salivarius group,which is a specific change in the gut microbiota that distinguishes them from healthy individuals.The correlation between the aggregation of specific bacterial species and fibrosis progression in chronic liver disease(CLD)is yet to be fully elucidated.AIM To quantify S.salivarius using digital PCR(dPCR)as a liver fibrosis marker of CLD.METHODS This study retrospectively analysed 52 patients with CLD.To quantify S.salivarius in patients with CLD using dPCR,we evaluated the specificity and sensitivity of S.salivarius bacterial load using dPCR for a type strain.Next,we evaluated the clinical usefulness of dPCR for S.salivarius load quantification for detecting liver fibrosis in patients with CLD.The liver fibrosis stage was categorized into mild and advanced fibrosis based on pathological findings.RESULTS The dPCR assay revealed that S.salivarius was highly positive for the tnpA gene.The lower limit of quantification for dPCR using the tnpA gene with a 1μL template comprising 1.28×102 CFU/mL was 4.3 copies.After considering the detection range in dPCR,we adjusted the extracted DNA concentration to 5.0×10-4 ng/μL from 200 mg stool samples.The median bacterial loads of S.salivarius in stool sample from patients with mild and advanced fibrosis were 1.9 and 7.4 copies/μL,respectively.The quantification of S.salivarius load was observed more frequently in patients with advanced fibrosis than in those with mild fibrosis(P=0.032).CONCLUSION Quantifying of S.salivarius load using digital PCR is a useful biomarker for liver fibrosis in patients with CLD.
基金funded by Haikou Science and Technology Plan Project(2022-007),in part by key Laboratory of PK System Technologies Research of Hainan,China.
文摘In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a distributed data source trust assessment management framework,a trust quantification model,and a dynamic adjustment mechanism are proposed.Themodel integrates the Analytic Hierarchy Process(AHP)and Dempster-Shafer(D-S)evidence theory to determine attribute weights and calculate direct trust values,while the PageRank algorithm is employed to derive indirect trust values.Thedirect and indirect trust values are then combined to compute the comprehensive trust value of the data source.Furthermore,a dynamic adjustment mechanism is introduced to continuously update the comprehensive trust value based on historical assessment data.By leveraging the collaborative efforts of multiple nodes in the distributed network,the proposed framework enables a comprehensive,dynamic,and objective evaluation of data source trustworthiness.Extensive experimental analyses demonstrate that the trust quantification model effectively handles large-scale data source trust assessments,exhibiting both strong trust differentiation capability and high robustness.
基金supported by the National Key Research and Development Program of China(No.2022YFA1602502)the National Natural Science Foundation of China(No.12127804).
文摘The direct and dissociative ionizations of oxygen molecule are investigated experimen-tally by electron collision with energies from 350 eV to 8000 eV.The absolute ionization cross sections for the product ions(O_(2)^(2+),O_(2)^(2+)O^(+),O^(2+),and their total)and two Coulomb explosion channels(O^(+)+O^(+)and O^(2+)+O^(+))are obtained by putting the data of O^(2+)on the scale of Ar+from O_(2)and Ar gases mixed with a fixed relative flow ratio of 1:1.The experimental errors are assessed by taking uncertainties of various factors into account.The present absolute cross sections are well consistent with the previous data in the overlapped energy range below 1000 eV.
基金supported by the National Natural Science Foundation of China(Nos.52303380,52025132,52273305,22205185,21621091,22021001,and 22121001)Fundamental Research Funds for the Central Universities(No.20720240041)+3 种基金the 111 Project(Nos.B17027 and B16029)the National Science Foundation of Fujian Province of China(No.2022J02059)the Science and Technology Projects of Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(No.RD2022070601)the New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘Excessive Fe^(3+) ion concentrations in wastewater pose a long-standing threat to human health.Achieving low-cost,high-efficiency quantification of Fe^(3+) ion concentration in unknown solutions can guide environmental management decisions and optimize water treatment processes.In this study,by leveraging the rapid,real-time detection capabilities of nanopores and the specific chemical binding affinity of tannic acid to Fe^(3+),a linear relationship between the ion current and Fe^(3+) ion concentration was established.Utilizing this linear relationship,quantification of Fe^(3+) ion concentration in unknown solutions was achieved.Furthermore,ethylenediaminetetraacetic acid disodium salt was employed to displace Fe^(3+) from the nanopores,allowing them to be restored to their initial conditions and reused for Fe^(3+) ion quantification.The reusable bioinspired nanopores remain functional over 330 days of storage.This recycling capability and the long-term stability of the nanopores contribute to a significant reduction in costs.This study provides a strategy for the quantification of unknown Fe^(3+) concentration using nanopores,with potential applications in environmental assessment,health monitoring,and so forth.
基金supported by the National Natural Science Foundation of China(62175156,81827807)the Science and Technology Commission of Shanghai Municipality(22S31903000)+3 种基金the Collaborative Innovation Project of Shanghai Institute of Technology(XTCX2022-27)the Shenzhen Basic Research Key Project(JCYJ20220818103212026)the Shenzhen Key Technology Project(JSGGZD20220822095200002)the Shenzhen Outstanding Scientific and Technological Innovation Talents Distinguished Young Scientists(RCJC20210609104443085).
文摘Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence tomography(OCT)primarily rely on Doppler OCT(D-OCT)and OCT Angiography(OCTA),which measure axial blood vessel velocity or visualize the vascular architecture,respectively.However,these techniques have limitations in accurately quantifying the absolute velocity of red blood cells(RBCs).This study presents a novel method based on microsphere tracking,which enables precise quantification of absolute blood flow velocity along a blood vessel.In phantom experiments,freshly harvested blood mixed with microspheres was infused into a cellulose tube to simulate a single blood vessel.Experimental results,demon-strating an error margin of less than 10%,validated the effectiveness of this method.Blood flow velocities ranging from 0.472 mm/s to 18.9 mm/s were accurately measured.A preliminary in vivo examination of rabbit ear vessels was conducted,further validating the reliability of this method.This study presents a potential method for specific disease diagnosis by detecting tar-geted vessel flow velocity variations using swept-source optical coherence tomography(SS-OCT)combined with microsphere tracking.
基金Hefei Municipal Natural Science Foundation,Grant/Award Number:2022009Suqian Guiding Program Project,Grant/Award Number:Z202309Suqian Traditional Chinese Medicine Science and Technology Plan,Grant/Award Number:MS202301。
文摘Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular disease.However,the manual calculation of these parameters is challenging due to the high variability among patients and the time-consuming nature of the process.In this study,the authors introduce a framework named MultiJSQ,comprising the feature presentation network(FRN)and the indicator prediction network(IEN),which is designed for simultaneous joint segmentation and quantification.The FRN is tailored for representing global image features,facilitating the direct acquisition of left ventricle(LV)contour images through pixel classification.Additionally,the IEN incorporates specifically designed modules to extract relevant clinical indices.The authors’method considers the interdependence of different tasks,demonstrating the validity of these relationships and yielding favourable results.Through extensive experiments on cardiac MR images from 145 patients,MultiJSQ achieves impressive outcomes,with low mean absolute errors of 124 mm^(2),1.72 mm,and 1.21 mm for areas,dimensions,and regional wall thicknesses,respectively,along with a Dice metric score of 0.908.The experimental findings underscore the excellent performance of our framework in LV segmentation and quantification,highlighting its promising clinical application prospects.
基金Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration under Grant No.2024B08。
文摘One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.
基金co-supported by the National Natural Science Foundation of China(Nos.51875014,U2233212 and 51875015)the Natural Science Foundation of Beijing Municipality,China(No.L221008)+1 种基金Science,Technology Innovation 2025 Major Project of Ningbo of China(No.2022Z005)the Tianmushan Laboratory Project,China(No.TK2023-B-001)。
文摘For uncertainty quantification of complex models with high-dimensional,nonlinear,multi-component coupling like digital twins,traditional statistical sampling methods,such as random sampling and Latin hypercube sampling,require a large number of samples,which entails huge computational costs.Therefore,how to construct a small-size sample space has been a hot issue of interest for researchers.To this end,this paper proposes a sequential search-based Latin hypercube sampling scheme to generate efficient and accurate samples for uncertainty quantification.First,the sampling range of the samples is formed by carving the polymorphic uncertainty based on theoretical analysis.Then,the optimal Latin hypercube design is selected using the Latin hypercube sampling method combined with the"space filling"criterion.Finally,the sample selection function is established,and the next most informative sample is optimally selected to obtain the sequential test sample.Compared with the classical sampling method,the generated samples can retain more information on the basis of sparsity.A series of numerical experiments are conducted to demonstrate the superiority of the proposed sequential search-based Latin hypercube sampling scheme,which is a way to provide reliable uncertainty quantification results with small sample sizes.
基金supported by the funding from the National Natural Science Foundation of China(32072359)。
文摘Wheat powdery mildew caused by Blumeria graminis f.sp.tritici(Bgt)is an important disease worldwide.Detection of latent infection of leaves by the pathogen in late autumn is valuable for estimating the inoculum potential to assess disease risks in the spring.We developed a new tool for rapid detection and quantification of latent infection of seedlings by the pathogen.The method was based on recombinase polymerase amplification(RPA)coupled with an end-point detection via lateral flow device(LFD).The limit of detection is 100 agμL^(-1)of Bgt DNA,without noticeable interference from either other common wheat pathogens or wheat material(Triticum aestivum).It was evaluated on wheat seedlings for this accuracy and sensitivity in detecting latent infection of Bgt.We further extended this RPALFD assay to estimate the level of latent infection by Bgt based on imaging analysis.There was a strong correlation between the image-based and real-time PCR assay estimates of Bgt DNA.The present results suggested that this new tool can provide rapid and accurate quantification of Bgt in latently infected leaves and can be further development as an on-site monitoring tool.
基金supported by Shanghai Municipal Commission of Science and Technology,China(Grant No.:19XD1400300)the National Natural Science Foundation of China(Grant Nos.:821040821,82273867,and 82030107).
文摘Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous fluorimetry-based probes have been developed to measure CMCs[3](Fig.S1).However,CMC measurements using these probes suffer from a time-consuming and laborious procedure and large uncertainties,primarily due to their poor photo-stabilities and highly fluctuating fluorescence backgrounds.
基金The authors gratefully acknowledge the support from the National Natural Science Foundation of China(Grant No.42377174)the Natural Science Foundation of Shandong Province,China(Grant No.ZR2022ME198)the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(Grant No.Z020006).
文摘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.
基金This study was reviewed and approved by the Maternal and child health hospital of Hubei Province(Approval No.20201025).
文摘BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients and their altered expression in the serum,proteomics techniques were deployed to detect the differentially expressed proteins(DEPs)of in the serum of GDM patients to further explore its pathogenesis,and find out possible biomarkers to forecast GDM occurrence.METHODS Subjects were divided into GDM and normal control groups according to the IADPSG diagnostic criteria.Serum samples were randomly selected from four cases in each group at 24-28 wk of gestation,and the blood samples were identified by applying iTRAQ technology combined with liquid chromatography-tandem mass spectrometry.Key proteins and signaling pathways associated with GDM were identified by bioinformatics analysis,and the expression of key proteins in serum from 12 wk to 16 wk of gestation was further verified using enzyme-linked immunosorbent assay (ELISA).RESULTS Forty-seven proteins were significantly differentially expressed by analyzing the serum samples between the GDMgravidas as well as the healthy ones. Among them, 31 proteins were found to be upregulated notably and the rest16 proteins were downregulated remarkably. Bioinformatic data report revealed abnormal expression of proteinsassociated with lipid metabolism, coagulation cascade activation, complement system and inflammatory responsein the GDM group. ELISA results showed that the contents of RBP4, as well as ANGPTL8, increased in the serumof GDM gravidas compared with the healthy ones, and this change was found to initiate from 12 wk to 16 wk ofgestation.CONCLUSION GDM symptoms may involve abnormalities in lipid metabolism, coagulation cascade activation, complementsystem and inflammatory response. RBP4 and ANGPTL8 are expected to be early predictors of GDM.
基金the National Natural Science Foundation of China(Grant No.11472137).
文摘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.
基金supported by the National Natural Science Foundation of China(Grant Nos.11472137 and U2141246)。
文摘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.
基金supported by Shandong Provincial Natural Science Foundation(grant number:ZR2023MD036)Key Research and Development Project in Shandong Province(grant number:2019GGX101064)project for excellent youth foundation of the innovation teacher team,Shandong(grant number:2022KJ310)。
文摘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.
文摘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.
