Inoculation of starter culture is a viable method to improve the quality of fermented foods,but its effect on the flavor metabolite profiles and the underlying mechanisms are still unclear.This study aimed to elucidat...Inoculation of starter culture is a viable method to improve the quality of fermented foods,but its effect on the flavor metabolite profiles and the underlying mechanisms are still unclear.This study aimed to elucidate the effects of starters(Lactiplantibacillus plantarum(LP)and Staphylococcus simulans(SS)individually or in combination(LS))on the flavor metabolite profiles of fermented sausages via metabolomics and genomics.L.plantarum markedly modified the composition of bacterial communities and made Lactobacillus spp.dominant in sausages(98.29%and 85.03%in LP and LS groups,respectively).Additionally,inoculation with a single starter,L.plantarum,and a mixed starter yielded similar non-volatile flavor metabolites,which were mainly characterized at the amino acid and peptide levels(relative intensities of 349.65 and 348.62 for the LP and LS groups,respectively).Meanwhile,the mixed starter group had the most volatile flavor metabolites(relative intensity of 34728.67),some of which were contributed by L.plantarum,such as ethyl acetate(relative intensities of 583.33 and 588.33 for the LP and LS groups,respectively)and benzaldehyde(relative intensities of 786.67 and 909.00 for the LP and LS groups,respectively),and several of which were generated by S.simulans,such as ethyl propionate(relative intensities of 214.67 and 136.67 for the SS and LS groups,respectively)and benzyl alcohol(relative intensities of 720.00 and 656.00 for the SS and LS groups,respectively).Furthermore,L.plantarum was found to possess more genes encoding peptidases(48)and carbohydrate-active enzymes(124),while S.simulans had more genes related to lipid hydrolysis(12).In conclusion,differences in the properties and combinations of indigenous strains play a crucial role in the generation of flavor metabolites in sausages.展开更多
As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency...As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency of exciton utilization and the overall performance of organic light-emit-ting devices are closely linked to the singlet-triplet energy gap(ΔE_(ST))of MR-TADF emitters.Identifying an economic and accu-rate theoretical approach to predictΔE_(ST)would be beneficial for high-throughput screening and facilitate the inverse design of MR-TADF molecules.In this study,we evaluated the S_(1)state energy(E(S_(1))),T_(1)state ener-gy(E(T_(1))),andΔE_(ST)using three different physical interpretations:adiabatic excitation ener-gy,vertical absorption energy,and vertical emission energy.We employed the time-depen-dent density functional theory(TDDFT)and delta self-consistent field(ΔSCF)methods to calculate E(S_(1)),E(T_(1)),andΔE_(ST)for 20 MR-TADF molecules reported in the literature.We compared these calculated values with experimental data obtained from fluorescence spec-troscopy at room-temperature(or 77 K)and phosphorescence spectroscopy conducted at 77 K.Our findings indicate that the vertical absorption energy at the S0 state minimum,deter-mined by theΔSCF method,accurately predicts the S_(1)state energy.Similarly,the vertical absorption energy at the S0 state minimum,calculated using the TDDFT method,effectively predicts the T_(1)state energy.TheΔE_(ST)derived from the difference between these two excita-tion energies exhibited the smallest mean absolute error of only 0.039 eV compared to the ex-perimental values.This combination represents the most accurate and cost-effective method reported to date for predicting theΔE_(ST)of MR-TADF molecules,and can be integrated into AI-driven inverse design workflows for new emitters.展开更多
This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learnin...This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learning anxiety and the moderating role of trust.Participants were Chinese university students(N=310,62%female,mean age=18.9,SD=0.8),of whom 15 completed interviews to both add to and to clarify the evidence from the surveys.Structural equation modeling results revealed that AI use had significant indirect effects on well-being through increased motivation and reduced language learning anxiety.Trust in AI significantly moderated both paths,amplifying the motivational benefits and anxiety reduction associated with AI use.Thematic analysis supported these results,identifying three experiential themes:(1)motivational empowerment through personalization,(2)anxiety regulation through safe practice and feedback,and(3)trust as the emotional bridge between AI and well-being.The study extends AI psychology applications by empirically linking technology engagement with affective outcomes and underscores the need for human-centered and trust-enhancing design in AI-supported education.From these findings,we conclude that adaptive,transparent,and autonomy-supportive AI systems promote self-determined motivation,emotional safety,and overall psychological health among EFL learners.展开更多
[Objective] This study was to find out a quick,simple,and low-cost method for the extraction of sorghum genomic DNA.[Method] Four plant genomic DNA extraction methods based on CTAB,including liquid nitrogen grinding m...[Objective] This study was to find out a quick,simple,and low-cost method for the extraction of sorghum genomic DNA.[Method] Four plant genomic DNA extraction methods based on CTAB,including liquid nitrogen grinding method（method I）,buffer grinding method（method II）,drying grinding method（method III）and directly grinding method（method IV）,were used to extract the sorghum genomic DNA from leaves;further the quantity and quality of the yielded DNA were detected by gel electrophoresis,SSR-PCR and SRAP-PCR.[Result] These four methods performed no remarkable difference in DNA product.The method I and method II produced DNA with higher purity and better integrity,which,especially from method I,is effective for SRAP-PCR and SSR-PCR.While the DNA extracted via method III and method IV had less integrality and lower purity,and only effective in SSR-PCR.[Conclusion] Enough amount of sorghum genomic DNA to perform tens of PCR could be quickly extracted using all these four methods.The DNA obtained via method I and method II had a broader application spectrum（SRAP,RAPD,ISSR and SSR）than that via method III and method IV which is only proper for PCR targeting small DNA fragments（SSR）.展开更多
[Objective] This study aimed at comparing the four extraction methods of genomic DNA from Clematis fasciculiflora Franch and determining the optimal extraction method for extracting the genomic DNA from Clematis fasci...[Objective] This study aimed at comparing the four extraction methods of genomic DNA from Clematis fasciculiflora Franch and determining the optimal extraction method for extracting the genomic DNA from Clematis fasciculiflora Franch.[Method] Leavies of Clematis fasciculiflora Franch were used as materials for comparing the purity and concentration of extracted DNA and extracting time among the four extraction methods of genomic DNA including improved CTAB method Ⅰ,improved CTAB method Ⅱ,improved CTAB method Ⅲ and improved SDS method.[Result] The four extraction methods could all be successfully used for extracting the genomic DNA from Clematis fasciculiflora Franch.The purity of genomic DNA was the highest using improved CTAB method Ⅰ,with the longest extracting time;while the concentration of genomic DNA was the maximum using the improved SDS method,with the shortest extracting time and relatively low purity;the extracting time of improved CTAB method Ⅲ was the shortest.[Conclusion] This study had established the optimal extraction method for extracting the genomic DNA from Clematis fasciculiflora Franch and supported for the further research using molecular biological methods.展开更多
To rapidly obtain high-quality genomic DNA from Chenopodium quinoa Willd, the genomic DAN in different tissues （leaves, stems and roots） of Chenopodi- um quinoa Willd was extracted by modified CTAB method, SDS metho...To rapidly obtain high-quality genomic DNA from Chenopodium quinoa Willd, the genomic DAN in different tissues （leaves, stems and roots） of Chenopodi- um quinoa Willd was extracted by modified CTAB method, SDS method and high- salt Iow-pH method, respectively. The quality and yield of extracted DNA was deter- mined using agarose gel electrophoresis and UV spectrophotometry. At the same time, the PCR-SSR and SSCP molecular detection was also performed. The results showed that the gel test strips, without obvious decomposition, of all the extraction methods were relatively obvious; the genomic DNA yield extracted by modified CTAB method was highest, followed by that by SDS method, and the genomic DNA extracted by high-salt Iow-pH method was lowest： the genomic DNA yields extracted by different methods from Chenopodium quinoa Wiltd leaves were all high- er than those from roots and stems; the quality of Chenopodium quinoa Willd ge- nomic DNA extracted by modified CTAB method and high-salt Iow-pH method was better, and polyphenols, polysaccharides and other impurities were removed more completely. The PCR-SSR and SSCP detection results showed that the genomic DNA extracted by different methods from different tissues of Chenopodium quinoa Willd all could be better amplified, and high-quality strips could be obtained. So the Chenopodium quinoa Willd genomic DNA extracted by the three methods all can be used for subsequent molecular biology research.展开更多
[Objective] The paper was too explore and compare methods of DNA extraction from raw soybean milk.[Method] Taken the soybean milk purchased from market as the material,pyrolysis method,isopropanol precipitation method...[Objective] The paper was too explore and compare methods of DNA extraction from raw soybean milk.[Method] Taken the soybean milk purchased from market as the material,pyrolysis method,isopropanol precipitation method,CTAB method,SDS method,high-salt low-pH and guanidine isothiocyanate method,as well as their improved methods were used to extract genomic DNA,and the extraction effects of these methods were compared by detecting the DNA using optical density,agarosegel electrophoresis and polymerase chain reaction（PCR）methods.[Result] The genomic DNA extracted by all methods except isopropanol precipitation method could be used in PCR reaction.Meanwhile,the high DNA concentration and purity will be gained by different methods in the order of high-salt low-pH method,high-salt low-pH method,improved CTAB method,improved isopropanol precipitation method,guanidine isothiocyanate method and improved pyrolysis method.[Conclusion] These methods are simply to operate,fast to gain results,and suitable for the extraction of total DNA from raw soybean milk.展开更多
Reliable and accurate pre-implantation genetic diagnosis （PGD） of patient＇s embryos by next-generation sequencing （NGS） is dependent on efficient whole genome amplification （WGA） of a representative biopsy samp...Reliable and accurate pre-implantation genetic diagnosis （PGD） of patient＇s embryos by next-generation sequencing （NGS） is dependent on efficient whole genome amplification （WGA） of a representative biopsy sample. However, the performance of the current state of the art WGA methods has not been evaluated for sequencing. Using low template DNA （15 pg） and single cells, we showed that the two PCR-based WGA systems SurePlex and MALBAC are superior to the REPLI-g WGA multiple displacement amplification （MDA） system in terms of consistent and reproducible genome coverage and sequence bias across the 24 chromosomes, allowing better normalization of test to reference sequencing data. When copy number variation sequencing （CNV-Seq） was applied to single cell WGA products derived by either SurePlex or MALBAC amplification, we showed that known disease CNVs in the range of 3-15 Mb could be reliably and accurately detected at the correct genomic positions. These findings indicate that our CNV-Seq pipeline incorporating either SurePlex or MALBAC as the key initial WGA step is a powerful methodology for clinical PGD to identify euploid embryos in a patient＇s cohort for uterine transplantation,展开更多
Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
With marker and phenotype information from observed populations, genomic selection （GS） can be used to establish associations between markers and phenotypes. It aims to use genome-wide markers to estimate the effect...With marker and phenotype information from observed populations, genomic selection （GS） can be used to establish associations between markers and phenotypes. It aims to use genome-wide markers to estimate the effects of all loci and thereby predict the genetic values of untested populations, so as to achieve more comprehensive and reliable selection and to accelerate genetic progress in crop breeding. GS models usually face the problem that the number of markers is much higher than the number of phenotypic observations. To overcome this issue and improve prediction accuracy, many models and algorithms, including GBLUP, Bayes, and machine learning have been employed for GS. As hot issues in GS research, the estimation of non-additive genetic effects and the combined analysis of multiple traits or multiple environments are also important for improving the accuracy of prediction. In recent years, crop breeding has taken advantage of the development of GS. The principles and characteristics of current popular GS methods and research progress in hese methods for crop improvement are reviewed in this paper.展开更多
Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic dat...Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic data to identify biomarkers associated with immunotherapy responses and disease prognosis,thus providing strong support for personalized treatments.In radiomics,AI can analyze high-dimensional features from computed tomography(CT),magnetic resonance imaging(MRI),and positron emission tomography/computed tomography(PET/CT)images to discover imaging biomarkers associated with tumor heterogeneity,treatment response,and disease progression,thereby enabling non-invasive,real-time assessments for personalized therapy.Pathomics leverages AI for deep analysis of digital pathology images,and can uncover subtle changes in tissue microenvironments,cellular characteristics,and morphological features,and offer unique insights into immunotherapy response prediction and biomarker discovery.These AI-driven technologies not only enhance the speed,accuracy,and robustness of biomarker discovery but also significantly improve the precision,personalization,and effectiveness of clinical treatments,and are driving a shift from empirical to precision medicine.Despite challenges such as data quality,model interpretability,integration of multi-modal data,and privacy protection,the ongoing advancements in AI,coupled with interdisciplinary collaboration,are poised to further enhance AI’s roles in biomarker discovery and immunotherapy response prediction.These improvements are expected to lead to more accurate,personalized treatment strategies and ultimately better patient outcomes,marking a significant step forward in the evolution of precision medicine.展开更多
The low egg production of goose greatly limits the development of the industry.China possesses the most abundant goose breeds resources.In this study,genome resequencing data of swan goose(Anser cygnoides)and domestic...The low egg production of goose greatly limits the development of the industry.China possesses the most abundant goose breeds resources.In this study,genome resequencing data of swan goose(Anser cygnoides)and domesticated high and low laying goose breeds(Anser cygnoides domestiation)were used to identify key genes related to egg laying ability in geese and verify their functions.Selective sweep analyses revealed 416 genes that were specifically selected during the domestication process from swan geese to high laying geese.Furthermore,SNPs and Indels markers were used in GWAS analyses between high and low laying breed geese.The results showed that RTCB,BPIFC,SYN3,SYNE1,VIP,and ESR1 may be related to the differences in laying ability of geese.Notably,only ESR1 was identified simultaneously by GWAS and selective sweep analysis.The genotype of Indelchr3:54429172,located downstream of ESR1,was confirmed to affect the expression of ESR1 in the ovarian stroma and showed significant correlation with body weight at first egg and laying frequency of geese.CCK-8,EdU,and flow cytometry confirmed that ESR1 can promote the apoptosis of goose pre-hierarchical follicles ganulosa cells(phGCs)and inhibit their proliferation.Combined with transcriptome data,it was found ESR1 involved in the function of goose phGCs may be related to MAPK and TGF-beta signaling pathways.Overall,our study used genomic information from different goose breeds to identify an indel located in the downstream of ESR1 associated with goose laying ability.The main pathways and biological processes of ESR1 involved in the regulation of goose laying ability were identified by cell biology and transcriptomics methods.These results are helpful to further understand the laying ability characteristics of goose and improve the egg production of geese.展开更多
Background:Genotyping by sequencing(GBS)still has problems with missing genotypes.Imputation is important for using GBS for genomic predictions,especially for low depths,due to the large number of missing genotypes.Mi...Background:Genotyping by sequencing(GBS)still has problems with missing genotypes.Imputation is important for using GBS for genomic predictions,especially for low depths,due to the large number of missing genotypes.Minor allele frequency(MAF)is widely used as a marker data editing criteria for genomic predictions.In this study,three imputation methods(Beagle,IMPUTE2 and FImpute software)based on four MAF editing criteria were investigated with regard to imputation accuracy of missing genotypes and accuracy of genomic predictions,based on simulated data of livestock population.Results:Four MAFs(no MAF limit,MAF≥0.001,MAF≥0.01 and MAF≥0.03)were used for editing marker data before imputation.Beagle,IMPUTE2 and FImpute software were applied to impute the original GBS.Additionally,IMPUTE2 also imputed the expected genotype dosage after genotype correction(GcIM).The reliability of genomic predictions was calculated using GBS and imputed GBS data.The results showed that imputation accuracies were the same for the three imputation methods,except for the data of sequencing read depth(depth)=2,where FImpute had a slightly lower imputation accuracy than Beagle and IMPUTE2.GcIM was observed to be the best for all of the imputations at depth=4,5 and 10,but the worst for depth=2.For genomic prediction,retaining more SNPs with no MAF limit resulted in higher reliability.As the depth increased to 10,the prediction reliabilities approached those using true genotypes in the GBS loci.Beagle and IMPUTE2 had the largest increases in prediction reliability of 5 percentage points,and FImpute gained 3 percentage points at depth=2.The best prediction was observed at depth=4,5 and 10 using GcIM,but the worst prediction was also observed using GcIM at depth=2.Conclusions:The current study showed that imputation accuracies were relatively low for GBS with low depths and high for GBS with high depths.Imputation resulted in larger gains in the reliability of genomic predictions for GBS with lower depths.These results suggest that the application of IMPUTE2,based on a corrected GBS(GcIM)to improve genomic predictions for higher depths,and FImpute software could be a good alternative for routine imputation.展开更多
As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and s...As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and smart maintenance.While promising,both methods have issues that need to be addressed.For example,model-based methods are limited by low computational accuracy and a high computational burden,and data-driven methods always suffer from poor interpretability and redundant features.To address these issues,the concept of data-model fusion(DMF)emerges as a promising solution.DMF involves integrating model-based methods with data-driven methods by incorporating big data into model-based methods or embedding relevant domain knowledge into data-driven methods.Despite growing efforts in the field of DMF,a unanimous definition of DMF remains elusive,and a general framework of DMF has been rarely discussed.This paper aims to address this gap by providing a thorough overview and categorization of both data-driven methods and model-based methods.Subsequently,this paper also presents the definition and categorization of DMF and discusses the general framework of DMF.Moreover,the primary seven applications of DMF are reviewed within the context of smart manufacturing and digital engineering.Finally,this paper directs the future directions of DMF.展开更多
Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vi...Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.展开更多
The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytica...The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.展开更多
The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and e...The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and efficacy of drugs.Unlike the inherent molecular structures of active pharmaceutical ingredients(APIs)and excipients,the microstructures of pharmaceutical preparations are developed during the formulation process,presenting unique analytical challenges.In this review,we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations,including X-ray imaging(XRI),scanning electron microscopy(SEM),atomic force microscopy(AFM),Raman spectroscopy,infrared(IR)spectroscopy,and rheometer technology.Subsequently,we highlight the applications,advantages,and limitations of these methods.Finally,we discuss the current challenges and future perspectives in this field.This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations,offering new insights and potential advancements in their development.展开更多
With the continuous increase of aeroengine flight ceiling(>20 km),the thin atmosphere at high altitudes and the size effect all cause the compressor component inlet Reynolds number to decrease rapidly to a critical...With the continuous increase of aeroengine flight ceiling(>20 km),the thin atmosphere at high altitudes and the size effect all cause the compressor component inlet Reynolds number to decrease rapidly to a critical value(approximately 2.0×10^(5)),and the significant transition process on the blade/endwall surface leads to the sharp degradation of compressor performance,which seriously affects the engine fuel consumption and working stability at high altitudes.In this paper,the research progress on the internal flow mechanism and flow control methods of axial compressors at low Reynolds numbers is reviewed from the aspects of quantification and prediction of performance variation,flow loss mechanism related to separation and transition,efficient transition control and flow field organization.The development trend of the low-Reynolds-number effect of axial flow compressors is noted,and the difficulties and application prospects of aerodynamic design and efficient flow control methods for compressors under low Reynolds numbers at high altitudes are discussed.展开更多
基金supported by the Priority Academic Program Development of Jiangsu Higher Education Institution(PAPD).
文摘Inoculation of starter culture is a viable method to improve the quality of fermented foods,but its effect on the flavor metabolite profiles and the underlying mechanisms are still unclear.This study aimed to elucidate the effects of starters(Lactiplantibacillus plantarum(LP)and Staphylococcus simulans(SS)individually or in combination(LS))on the flavor metabolite profiles of fermented sausages via metabolomics and genomics.L.plantarum markedly modified the composition of bacterial communities and made Lactobacillus spp.dominant in sausages(98.29%and 85.03%in LP and LS groups,respectively).Additionally,inoculation with a single starter,L.plantarum,and a mixed starter yielded similar non-volatile flavor metabolites,which were mainly characterized at the amino acid and peptide levels(relative intensities of 349.65 and 348.62 for the LP and LS groups,respectively).Meanwhile,the mixed starter group had the most volatile flavor metabolites(relative intensity of 34728.67),some of which were contributed by L.plantarum,such as ethyl acetate(relative intensities of 583.33 and 588.33 for the LP and LS groups,respectively)and benzaldehyde(relative intensities of 786.67 and 909.00 for the LP and LS groups,respectively),and several of which were generated by S.simulans,such as ethyl propionate(relative intensities of 214.67 and 136.67 for the SS and LS groups,respectively)and benzyl alcohol(relative intensities of 720.00 and 656.00 for the SS and LS groups,respectively).Furthermore,L.plantarum was found to possess more genes encoding peptidases(48)and carbohydrate-active enzymes(124),while S.simulans had more genes related to lipid hydrolysis(12).In conclusion,differences in the properties and combinations of indigenous strains play a crucial role in the generation of flavor metabolites in sausages.
基金support provided by the National Natural Science Foundation of China(No.22273043).
文摘As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency of exciton utilization and the overall performance of organic light-emit-ting devices are closely linked to the singlet-triplet energy gap(ΔE_(ST))of MR-TADF emitters.Identifying an economic and accu-rate theoretical approach to predictΔE_(ST)would be beneficial for high-throughput screening and facilitate the inverse design of MR-TADF molecules.In this study,we evaluated the S_(1)state energy(E(S_(1))),T_(1)state ener-gy(E(T_(1))),andΔE_(ST)using three different physical interpretations:adiabatic excitation ener-gy,vertical absorption energy,and vertical emission energy.We employed the time-depen-dent density functional theory(TDDFT)and delta self-consistent field(ΔSCF)methods to calculate E(S_(1)),E(T_(1)),andΔE_(ST)for 20 MR-TADF molecules reported in the literature.We compared these calculated values with experimental data obtained from fluorescence spec-troscopy at room-temperature(or 77 K)and phosphorescence spectroscopy conducted at 77 K.Our findings indicate that the vertical absorption energy at the S0 state minimum,deter-mined by theΔSCF method,accurately predicts the S_(1)state energy.Similarly,the vertical absorption energy at the S0 state minimum,calculated using the TDDFT method,effectively predicts the T_(1)state energy.TheΔE_(ST)derived from the difference between these two excita-tion energies exhibited the smallest mean absolute error of only 0.039 eV compared to the ex-perimental values.This combination represents the most accurate and cost-effective method reported to date for predicting theΔE_(ST)of MR-TADF molecules,and can be integrated into AI-driven inverse design workflows for new emitters.
文摘This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learning anxiety and the moderating role of trust.Participants were Chinese university students(N=310,62%female,mean age=18.9,SD=0.8),of whom 15 completed interviews to both add to and to clarify the evidence from the surveys.Structural equation modeling results revealed that AI use had significant indirect effects on well-being through increased motivation and reduced language learning anxiety.Trust in AI significantly moderated both paths,amplifying the motivational benefits and anxiety reduction associated with AI use.Thematic analysis supported these results,identifying three experiential themes:(1)motivational empowerment through personalization,(2)anxiety regulation through safe practice and feedback,and(3)trust as the emotional bridge between AI and well-being.The study extends AI psychology applications by empirically linking technology engagement with affective outcomes and underscores the need for human-centered and trust-enhancing design in AI-supported education.From these findings,we conclude that adaptive,transparent,and autonomy-supportive AI systems promote self-determined motivation,emotional safety,and overall psychological health among EFL learners.
基金Supported by Key Technology R&D Program of Tianjin(10ZCKFNC00100)National Key Technology R&D Program(2007BAD42B03)~~
文摘[Objective] This study was to find out a quick,simple,and low-cost method for the extraction of sorghum genomic DNA.[Method] Four plant genomic DNA extraction methods based on CTAB,including liquid nitrogen grinding method（method I）,buffer grinding method（method II）,drying grinding method（method III）and directly grinding method（method IV）,were used to extract the sorghum genomic DNA from leaves;further the quantity and quality of the yielded DNA were detected by gel electrophoresis,SSR-PCR and SRAP-PCR.[Result] These four methods performed no remarkable difference in DNA product.The method I and method II produced DNA with higher purity and better integrity,which,especially from method I,is effective for SRAP-PCR and SSR-PCR.While the DNA extracted via method III and method IV had less integrality and lower purity,and only effective in SSR-PCR.[Conclusion] Enough amount of sorghum genomic DNA to perform tens of PCR could be quickly extracted using all these four methods.The DNA obtained via method I and method II had a broader application spectrum（SRAP,RAPD,ISSR and SSR）than that via method III and method IV which is only proper for PCR targeting small DNA fragments（SSR）.
基金Supported by Applied Basic Research Project of Yunnan Province(2010ZC089)the948Project of National Forestry Bureau(2008-4-11)+1 种基金Sharing Platform Project of Provincial and Ministerial Key Subject,Key Laboratory and School Laboratory of Provincial Colleges and Universities in Yunnan ProvinceScience and Technology Innovation Fund of Southwest Forestry University~~
文摘[Objective] This study aimed at comparing the four extraction methods of genomic DNA from Clematis fasciculiflora Franch and determining the optimal extraction method for extracting the genomic DNA from Clematis fasciculiflora Franch.[Method] Leavies of Clematis fasciculiflora Franch were used as materials for comparing the purity and concentration of extracted DNA and extracting time among the four extraction methods of genomic DNA including improved CTAB method Ⅰ,improved CTAB method Ⅱ,improved CTAB method Ⅲ and improved SDS method.[Result] The four extraction methods could all be successfully used for extracting the genomic DNA from Clematis fasciculiflora Franch.The purity of genomic DNA was the highest using improved CTAB method Ⅰ,with the longest extracting time;while the concentration of genomic DNA was the maximum using the improved SDS method,with the shortest extracting time and relatively low purity;the extracting time of improved CTAB method Ⅲ was the shortest.[Conclusion] This study had established the optimal extraction method for extracting the genomic DNA from Clematis fasciculiflora Franch and supported for the further research using molecular biological methods.
基金Supported by National Natural Science Foundation of China(31301372)Key Project of Science and Technology Plan of Zhejiang Province(2011C12030)Innovation Training Project of Zhejiang Agriculture and Forestry University(201301004)~~
文摘To rapidly obtain high-quality genomic DNA from Chenopodium quinoa Willd, the genomic DAN in different tissues （leaves, stems and roots） of Chenopodi- um quinoa Willd was extracted by modified CTAB method, SDS method and high- salt Iow-pH method, respectively. The quality and yield of extracted DNA was deter- mined using agarose gel electrophoresis and UV spectrophotometry. At the same time, the PCR-SSR and SSCP molecular detection was also performed. The results showed that the gel test strips, without obvious decomposition, of all the extraction methods were relatively obvious; the genomic DNA yield extracted by modified CTAB method was highest, followed by that by SDS method, and the genomic DNA extracted by high-salt Iow-pH method was lowest： the genomic DNA yields extracted by different methods from Chenopodium quinoa Wiltd leaves were all high- er than those from roots and stems; the quality of Chenopodium quinoa Willd ge- nomic DNA extracted by modified CTAB method and high-salt Iow-pH method was better, and polyphenols, polysaccharides and other impurities were removed more completely. The PCR-SSR and SSCP detection results showed that the genomic DNA extracted by different methods from different tissues of Chenopodium quinoa Willd all could be better amplified, and high-quality strips could be obtained. So the Chenopodium quinoa Willd genomic DNA extracted by the three methods all can be used for subsequent molecular biology research.
基金Supported by Applied Basic Research Projects in Sichuan Province(2009JY0101)~~
文摘[Objective] The paper was too explore and compare methods of DNA extraction from raw soybean milk.[Method] Taken the soybean milk purchased from market as the material,pyrolysis method,isopropanol precipitation method,CTAB method,SDS method,high-salt low-pH and guanidine isothiocyanate method,as well as their improved methods were used to extract genomic DNA,and the extraction effects of these methods were compared by detecting the DNA using optical density,agarosegel electrophoresis and polymerase chain reaction（PCR）methods.[Result] The genomic DNA extracted by all methods except isopropanol precipitation method could be used in PCR reaction.Meanwhile,the high DNA concentration and purity will be gained by different methods in the order of high-salt low-pH method,high-salt low-pH method,improved CTAB method,improved isopropanol precipitation method,guanidine isothiocyanate method and improved pyrolysis method.[Conclusion] These methods are simply to operate,fast to gain results,and suitable for the extraction of total DNA from raw soybean milk.
基金supported by grants awarded to Yuanqing Yao by the Key Program of the "Twelfth Five-year plan" of People’s liberation Army(No.BWS11J058)the National High Technology Research and Development Program(SS2015AA020402)
文摘Reliable and accurate pre-implantation genetic diagnosis （PGD） of patient＇s embryos by next-generation sequencing （NGS） is dependent on efficient whole genome amplification （WGA） of a representative biopsy sample. However, the performance of the current state of the art WGA methods has not been evaluated for sequencing. Using low template DNA （15 pg） and single cells, we showed that the two PCR-based WGA systems SurePlex and MALBAC are superior to the REPLI-g WGA multiple displacement amplification （MDA） system in terms of consistent and reproducible genome coverage and sequence bias across the 24 chromosomes, allowing better normalization of test to reference sequencing data. When copy number variation sequencing （CNV-Seq） was applied to single cell WGA products derived by either SurePlex or MALBAC amplification, we showed that known disease CNVs in the range of 3-15 Mb could be reliably and accurately detected at the correct genomic positions. These findings indicate that our CNV-Seq pipeline incorporating either SurePlex or MALBAC as the key initial WGA step is a powerful methodology for clinical PGD to identify euploid embryos in a patient＇s cohort for uterine transplantation,
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金supported by grants from the National High Technology Research and Development Program of China(2014AA10A601-5)the National Key Research and Development Program of China(2016YFD0100303)+5 种基金the National Natural Science Foundation of China(91535103)the Natural Science Foundations of Jiangsu Province(BK20150010)the Natural Science Foundation of the Jiangsu Higher Education Institutions(14KJA210005)the Open Research Fund of State Key Laboratory of Hybrid Rice(Wuhan University)(KF201701)the Science and Technology Innovation Fund Project in Yangzhou University(2016CXJ021)the Priority Academic Program Development of Jiangsu Higher Education Institutions and the Innovative Research Team of Universities in Jiangsu Province
文摘With marker and phenotype information from observed populations, genomic selection （GS） can be used to establish associations between markers and phenotypes. It aims to use genome-wide markers to estimate the effects of all loci and thereby predict the genetic values of untested populations, so as to achieve more comprehensive and reliable selection and to accelerate genetic progress in crop breeding. GS models usually face the problem that the number of markers is much higher than the number of phenotypic observations. To overcome this issue and improve prediction accuracy, many models and algorithms, including GBLUP, Bayes, and machine learning have been employed for GS. As hot issues in GS research, the estimation of non-additive genetic effects and the combined analysis of multiple traits or multiple environments are also important for improving the accuracy of prediction. In recent years, crop breeding has taken advantage of the development of GS. The principles and characteristics of current popular GS methods and research progress in hese methods for crop improvement are reviewed in this paper.
基金supported by the National Natural Science Foundation of China(Grant No.30800776)the State High-Tech Development Plan of China(Grant No.2008AA101002)the Recommend International Advanced Agricultural Science and Technology Plan of China(Grant No2011-G2A)
基金supported by grants from the National Natural Science Foundation of China(Grant No.82272008)The Science&Technology Development Fund of Tianjin Education Commission for Higher Education(Grant No.2021KJ194)Tianjin Key Medical Discipline(Specialty)Construction Project(Grant No.TJYXZDXK-009A).
文摘Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic data to identify biomarkers associated with immunotherapy responses and disease prognosis,thus providing strong support for personalized treatments.In radiomics,AI can analyze high-dimensional features from computed tomography(CT),magnetic resonance imaging(MRI),and positron emission tomography/computed tomography(PET/CT)images to discover imaging biomarkers associated with tumor heterogeneity,treatment response,and disease progression,thereby enabling non-invasive,real-time assessments for personalized therapy.Pathomics leverages AI for deep analysis of digital pathology images,and can uncover subtle changes in tissue microenvironments,cellular characteristics,and morphological features,and offer unique insights into immunotherapy response prediction and biomarker discovery.These AI-driven technologies not only enhance the speed,accuracy,and robustness of biomarker discovery but also significantly improve the precision,personalization,and effectiveness of clinical treatments,and are driving a shift from empirical to precision medicine.Despite challenges such as data quality,model interpretability,integration of multi-modal data,and privacy protection,the ongoing advancements in AI,coupled with interdisciplinary collaboration,are poised to further enhance AI’s roles in biomarker discovery and immunotherapy response prediction.These improvements are expected to lead to more accurate,personalized treatment strategies and ultimately better patient outcomes,marking a significant step forward in the evolution of precision medicine.
基金supported by the China Agriculture Research System of MOF and MARA(CARS-42-4)School Cooperation Project of Ya’an(21SXHZ0028)the Key Technology Support Program of Sichuan Province,China(2021YFYZ0014),for the financial support。
文摘The low egg production of goose greatly limits the development of the industry.China possesses the most abundant goose breeds resources.In this study,genome resequencing data of swan goose(Anser cygnoides)and domesticated high and low laying goose breeds(Anser cygnoides domestiation)were used to identify key genes related to egg laying ability in geese and verify their functions.Selective sweep analyses revealed 416 genes that were specifically selected during the domestication process from swan geese to high laying geese.Furthermore,SNPs and Indels markers were used in GWAS analyses between high and low laying breed geese.The results showed that RTCB,BPIFC,SYN3,SYNE1,VIP,and ESR1 may be related to the differences in laying ability of geese.Notably,only ESR1 was identified simultaneously by GWAS and selective sweep analysis.The genotype of Indelchr3:54429172,located downstream of ESR1,was confirmed to affect the expression of ESR1 in the ovarian stroma and showed significant correlation with body weight at first egg and laying frequency of geese.CCK-8,EdU,and flow cytometry confirmed that ESR1 can promote the apoptosis of goose pre-hierarchical follicles ganulosa cells(phGCs)and inhibit their proliferation.Combined with transcriptome data,it was found ESR1 involved in the function of goose phGCs may be related to MAPK and TGF-beta signaling pathways.Overall,our study used genomic information from different goose breeds to identify an indel located in the downstream of ESR1 associated with goose laying ability.The main pathways and biological processes of ESR1 involved in the regulation of goose laying ability were identified by cell biology and transcriptomics methods.These results are helpful to further understand the laying ability characteristics of goose and improve the egg production of geese.
基金This study was funded by the Genomic Selection in Animals and Plants(GenSAP)research project financed by the Danish Council of Strategic Research(Aarhus,Denmark).Xiao Wang received Ph.D.stipends from the Technical University of Denmark(DTU Bioinformatics and DTU Compute),Denmark,and the China Scholarship Council,China.
文摘Background:Genotyping by sequencing(GBS)still has problems with missing genotypes.Imputation is important for using GBS for genomic predictions,especially for low depths,due to the large number of missing genotypes.Minor allele frequency(MAF)is widely used as a marker data editing criteria for genomic predictions.In this study,three imputation methods(Beagle,IMPUTE2 and FImpute software)based on four MAF editing criteria were investigated with regard to imputation accuracy of missing genotypes and accuracy of genomic predictions,based on simulated data of livestock population.Results:Four MAFs(no MAF limit,MAF≥0.001,MAF≥0.01 and MAF≥0.03)were used for editing marker data before imputation.Beagle,IMPUTE2 and FImpute software were applied to impute the original GBS.Additionally,IMPUTE2 also imputed the expected genotype dosage after genotype correction(GcIM).The reliability of genomic predictions was calculated using GBS and imputed GBS data.The results showed that imputation accuracies were the same for the three imputation methods,except for the data of sequencing read depth(depth)=2,where FImpute had a slightly lower imputation accuracy than Beagle and IMPUTE2.GcIM was observed to be the best for all of the imputations at depth=4,5 and 10,but the worst for depth=2.For genomic prediction,retaining more SNPs with no MAF limit resulted in higher reliability.As the depth increased to 10,the prediction reliabilities approached those using true genotypes in the GBS loci.Beagle and IMPUTE2 had the largest increases in prediction reliability of 5 percentage points,and FImpute gained 3 percentage points at depth=2.The best prediction was observed at depth=4,5 and 10 using GcIM,but the worst prediction was also observed using GcIM at depth=2.Conclusions:The current study showed that imputation accuracies were relatively low for GBS with low depths and high for GBS with high depths.Imputation resulted in larger gains in the reliability of genomic predictions for GBS with lower depths.These results suggest that the application of IMPUTE2,based on a corrected GBS(GcIM)to improve genomic predictions for higher depths,and FImpute software could be a good alternative for routine imputation.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grants(52275471 and 52120105008)the Beijing Outstanding Young Scientist Program,and the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and smart maintenance.While promising,both methods have issues that need to be addressed.For example,model-based methods are limited by low computational accuracy and a high computational burden,and data-driven methods always suffer from poor interpretability and redundant features.To address these issues,the concept of data-model fusion(DMF)emerges as a promising solution.DMF involves integrating model-based methods with data-driven methods by incorporating big data into model-based methods or embedding relevant domain knowledge into data-driven methods.Despite growing efforts in the field of DMF,a unanimous definition of DMF remains elusive,and a general framework of DMF has been rarely discussed.This paper aims to address this gap by providing a thorough overview and categorization of both data-driven methods and model-based methods.Subsequently,this paper also presents the definition and categorization of DMF and discusses the general framework of DMF.Moreover,the primary seven applications of DMF are reviewed within the context of smart manufacturing and digital engineering.Finally,this paper directs the future directions of DMF.
基金funded by the National Natural Science Foundation of China(No.41962016)the Natural Science Foundation of NingXia(Nos.2023AAC02023,2023A1218,and 2021AAC02006).
文摘Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.
基金supported by the National Natural Science Foundation of China(12172023).
文摘The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.
文摘The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and efficacy of drugs.Unlike the inherent molecular structures of active pharmaceutical ingredients(APIs)and excipients,the microstructures of pharmaceutical preparations are developed during the formulation process,presenting unique analytical challenges.In this review,we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations,including X-ray imaging(XRI),scanning electron microscopy(SEM),atomic force microscopy(AFM),Raman spectroscopy,infrared(IR)spectroscopy,and rheometer technology.Subsequently,we highlight the applications,advantages,and limitations of these methods.Finally,we discuss the current challenges and future perspectives in this field.This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations,offering new insights and potential advancements in their development.
基金co-supported by the National Natural Science Foundation of China(No.52306053)the Science Center for Gas Turbine Project,China(No.P2022-B-Ⅱ-005-001)the National Science and Technology Major Project of China(No.2017-Ⅱ-0010-0024)。
文摘With the continuous increase of aeroengine flight ceiling(>20 km),the thin atmosphere at high altitudes and the size effect all cause the compressor component inlet Reynolds number to decrease rapidly to a critical value(approximately 2.0×10^(5)),and the significant transition process on the blade/endwall surface leads to the sharp degradation of compressor performance,which seriously affects the engine fuel consumption and working stability at high altitudes.In this paper,the research progress on the internal flow mechanism and flow control methods of axial compressors at low Reynolds numbers is reviewed from the aspects of quantification and prediction of performance variation,flow loss mechanism related to separation and transition,efficient transition control and flow field organization.The development trend of the low-Reynolds-number effect of axial flow compressors is noted,and the difficulties and application prospects of aerodynamic design and efficient flow control methods for compressors under low Reynolds numbers at high altitudes are discussed.
