ropic 1:Regarding sustainable development and global public interests,what should international Al standards focus on?James Ong:Since 2019,I have witnessed the evolution of WAIC and found that a consensus on the philo...ropic 1:Regarding sustainable development and global public interests,what should international Al standards focus on?James Ong:Since 2019,I have witnessed the evolution of WAIC and found that a consensus on the philosophical and ethic level on advocating“AI for humanity”is necessary,since ethics factor carries more weight in standards development.I want to emphasize three points:AI assisting sustainable development,AI empowering a balanced global development,and human-AI coordination for preventing AI risks.展开更多
In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community ca...In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home(H2H)program that has been operating since 2017.In this follow on practice and policy article,we further elaborate on Singapore's H2H program and care model,and its supporting AI model for multiple readmission prediction,in the following ways:(1)by providing updates on the AI and supporting information systems,(2)by reporting on customer engagement and related service delivery outcomes including staff‐related time savings and patient benefits in terms of bed days saved,(3)by sharing lessons learned with respect to(i)analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants,(ii)balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables,and(iii)the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems,(4)by highlighting how this H2H effort supported broader Covid‐19 response efforts across Singapore's public healthcare system,and finally(5)by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards.For the convenience of the reader,some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.展开更多
This study aims to validate the Object-Oriented User Interface Customization(OOUIC)framework by employing Use Case Analysis(UCA)to facilitate the development of adaptive User Interfaces(UIs).The OOUIC framework advoca...This study aims to validate the Object-Oriented User Interface Customization(OOUIC)framework by employing Use Case Analysis(UCA)to facilitate the development of adaptive User Interfaces(UIs).The OOUIC framework advocates for User-Centered Design(UCD)methodologies,including UCA,to systematically identify intricate user requirements and construct adaptive UIs tailored to diverse user needs.To operationalize this approach,thirty users of Product Lifecycle Management(PLM)systems were interviewed across six distinct use cases.Interview transcripts were subjected to deductive content analysis to classify UI objects systematically.Subsequently,adaptive UIs were developed for each use case,and their complexity was quantitatively compared against the original system UIs.The results demonstrated a significant reduction in complexity across all adaptive UIs(Mean Difference,MD=0.11,t(5)=8.26,p<0.001),confirming their superior efficiency.The findings validate the OOUIC framework,demonstrating that UCD effectively captures complex requirements for adaptive UI development,while adaptive UIs mitigate interface complexity through object reduction and optimized layout design.Furthermore,UCA and deductive content analysis serve as robust methodologies for object categorization in adaptive UI design.Beyond eliminating redundant elements and prioritizing object grouping,designers can further reduce complexity by adjusting object dimensions and window sizing.This study underscores the efficacy of UCA in developing adaptive UIs and streamlining complex interfaces.Ultimately,UCD proves instrumental in gathering intricate requirements,while adaptive UIs enhance usability by minimizing object clutter and refining spatial organization.展开更多
Objective:To explore the effect of Diospyros kaki on cattle spermatozoa during chilling and cryopreservation.Methods: Five milliliter of blended Persimmon (Diospyros kaki) flesh was added to 45 mL TCF to obtain 10% st...Objective:To explore the effect of Diospyros kaki on cattle spermatozoa during chilling and cryopreservation.Methods: Five milliliter of blended Persimmon (Diospyros kaki) flesh was added to 45 mL TCF to obtain 10% stock solution. Kaki enriched extender (KEE) was prepared by adding to TCF in concentrations 0.0/5.0 mL (control, 0%), 0.5/4.5 mL (1%), 1/4 mL (2%), 1.5/3.5 mL (3%), 2.0/3.0 mL (4%), 2.5/2.5 mL (5%), 3.0/2.0 mL (6%), 3.5/1.5 mL (7%), 4.0/1.0 mL (8%), 4.5/0.5 mL (9%) and 5.0/0.0 mL (10%) to obtain a final volume 5 mL in each tube. Whole egg yolk was added to each tube to obtain KEE with 20% egg yolk (KEEY), all tubes were centrifuged to get rid of debris. Semen was added to the supernatants in other tubes. Extended semen was subjected to evaluation (motility, alive sperm and intact sperm membrane (HOST) %) in both chilled and cryopreserved semen. Conception rate was carried out.Results:Sperm motility was significantly (P<0.0001) kept high after 11 d of chilling with the concentration 1%, 2%, 3%, 4%, 5% as compared to the control (41.67±1.67, 41.67±1.67, 40.00±0.00, 41.67±1.67 and 41.67±1.67, respectively) and also non-significantly kept high at the other concentrations up to 9 d of chilling. Addition of KEE had significantly (P<0.0033) improved post thawing sperm motility % with the concentrations 1, 2, 3, 4, 5 and 6% as compared to the control (51.67±5.27, 55.00±3.16, 48.33±1.05, 45.00±3.96, 57.00±2.50, 55.00±5.00 and 43.33±5.11 respectively).While the other concentrations exhibit no effect. Addition of KEE maintained alive sperm%, abnormalities% and % of intact spermatozoa membranes (HOST %) as good as the control with all concentrations of kaki used in our study. The conception rate upon using frozen semen in insemination showed higher conception rate in concentrations of 2%, 4% and 6 % KEE in cattle.Conclusion: It could be concluded that some concentrations ofDiospyros kaki improved bull semen quality post-chilling and post-freezing.展开更多
Attribute reduction,also known as feature selection,for decision information systems is one of the most pivotal issues in machine learning and data mining.Approaches based on the rough set theory and some extensions w...Attribute reduction,also known as feature selection,for decision information systems is one of the most pivotal issues in machine learning and data mining.Approaches based on the rough set theory and some extensions were proved to be efficient for dealing with the problemof attribute reduction.Unfortunately,the intuitionistic fuzzy sets based methods have not received much interest,while these methods are well-known as a very powerful approach to noisy decision tables,i.e.,data tables with the low initial classification accuracy.Therefore,this paper provides a novel incremental attribute reductionmethod to dealmore effectivelywith noisy decision tables,especially for highdimensional ones.In particular,we define a new reduct and then design an original attribute reduction method based on the distance measure between two intuitionistic fuzzy partitions.It should be noted that the intuitionistic fuzzypartitiondistance iswell-knownas aneffectivemeasure todetermine important attributes.More interestingly,an incremental formula is also developed to quickly compute the intuitionistic fuzzy partition distance in case when the decision table increases in the number of objects.This formula is then applied to construct an incremental attribute reduction algorithm for handling such dynamic tables.Besides,some experiments are conducted on real datasets to show that our method is far superior to the fuzzy rough set based methods in terms of the size of reduct and the classification accuracy.展开更多
Artificial intelligence(AI)is the core technology of technological revolution and industrial transformation.As one of the new intelligent needs in the AI 2.0 era,financial intelligence has elicited much attention from...Artificial intelligence(AI)is the core technology of technological revolution and industrial transformation.As one of the new intelligent needs in the AI 2.0 era,financial intelligence has elicited much attention from the academia and industry.In our current dynamic capital market,financial intelligence demonstrates a fast and accurate machine learning capability to handle complex data and has gradually acquired the potential to become a'financial brain.'In this paper,we survey existing studies on financial intelligence.First,we describe the concept of financial intelligence and elaborate on its position in the financial technology field.Second,we introduce the development of financial intelligence and review state-of-the-art techniques in wealth management,risk management,financial security,financial consulting,and blockchain.Finally,we propose a research framework called FinBrain and summarize four open issues,namely,explainable financial agents and causality,perception and prediction under uncertainty,risk-sensitive and robust decision-making,and multi-agent game and mechanism design.We believe that these research directions can lay the foundation for the development of AI 2.0 in the finance field.展开更多
Single-pixel imaging(SPI)faces significant challenges in reconstructing high-quality images under complex real-world degradation conditions.This paper presents an innovative degradation model for the physical processe...Single-pixel imaging(SPI)faces significant challenges in reconstructing high-quality images under complex real-world degradation conditions.This paper presents an innovative degradation model for the physical processes in SPI,providing the first comprehensive and quantitative analysis of various SPI noise sources encountered in real-world applications.Especially,pattern-dependent global noise propagation and object jitter modelling methods for SPI are proposed.Subsequently,a deep-blind neural network is developed to remove the necessity of obtaining parameters of all the degradation factors in real-world image compensation.Our method can operate without degradation parameters and significantly improve the resolution and fidelity of SPI image reconstruction.The deep-blind network training is guided by the proposed comprehensive SPI degradation model that describes real-world SPI impairments,enabling the network to generalize across a wide range of degradation combinations.The experiment validates its advanced performance in real-world SPI imaging at ultra-low sampling rates.The proposed method holds great potential for applications in remote sensing,biomedical imaging,and privacy-preserving surveillance.展开更多
Synonym discovery is important in a wide variety of concept-related tasks,such as entity/concept mining and industrial knowledge graph(KG)construction.It intends to determine whether two terms refer to the same concep...Synonym discovery is important in a wide variety of concept-related tasks,such as entity/concept mining and industrial knowledge graph(KG)construction.It intends to determine whether two terms refer to the same concept in semantics.Existing methods rely on contexts or KGs.However,these methods are often impractical in some cases where contexts or KGs are not available.Therefore,this paper proposes a context-free prompt learning based synonym discovery method called ProSyno,which takes the world’s largest freely available dictionary Wiktionary as a semantic source.Based on a pre-trained language model(PLM),we employ a prompt learning method to generalize to other datasets without any fine-tuning.Thus,our model is more appropriate for context-free situation and can be easily transferred to other fields.Experimental results demonstrate its superiority comparing with state-of-the-art methods.展开更多
Aspergillus oryzae is widely used in traditional koji production,although its application in targeted savory design in plant-based foods remains limited.Here,we applied an AI-guided bioconversion framework integrating...Aspergillus oryzae is widely used in traditional koji production,although its application in targeted savory design in plant-based foods remains limited.Here,we applied an AI-guided bioconversion framework integrating sensory analysis and metabolomics to derive an umami-rich,chicken-like seasoning from cucumber and peanut.Bayesian optimization was used to refine the substrate ratio and incubation time,identifying 5%cucumber and 5%peanut incubated for 7 days as the optimal conditions.This formulation increased the intensities of umami and chicken-like flavor,reduced off-flavors,and enhanced savory perception when incorporated at 1%(w/w)into a neutral plant-protein nugget model.Untargeted LC-MS and GC-MS analyses identified 52 discriminant metabolites organized into coherent biochemical modules.Integrated chemometrics linked carbohydrate-derived substrates to fungal glutamate,succinate,and 5′-nucleotides,while phenylpropanoid and triterpenoid modules aligned with mushroom notes and the suppression of savory attributes.The results indicate that AI-directed A.oryzae bioconversion provides a basis for the mechanistically informed construction of umami flavor sys-tems from simple botanical substrates.展开更多
Dear Editor,Great progress has been made using artificial intelligence(AI) techniques in learning knowledge from biomedical databases in recent years, revolutionizing the study of many fields, such as protein structur...Dear Editor,Great progress has been made using artificial intelligence(AI) techniques in learning knowledge from biomedical databases in recent years, revolutionizing the study of many fields, such as protein structure prediction and protein design(Madani et al., 2023). However, there is massive biomedical knowledge not curated in the form of structured data but hidden in primary scientific literature.展开更多
Metabolic syndrome(MeS)is a major health problem associated with the high prevalence of obesity,diabetes,hypertension and dyslipidemia.Boswellia serrata resin(BS)is an old remedy reputed by its rich antioxidant compou...Metabolic syndrome(MeS)is a major health problem associated with the high prevalence of obesity,diabetes,hypertension and dyslipidemia.Boswellia serrata resin(BS)is an old remedy reputed by its rich antioxidant compounds.The present research aimed to assess the impact of microencapsulated BS if given in combination with probiotic bacteria(BAC)(Lactobacillus plantarum and Lactobacillus rhamnosus)which had anti-inflammatory and antioxidant activities to control the metabolic disorders associated with MeS.Water extract of BS was prepared,total phenolic,total antioxidants and HPLC were analyzed.BS extract was microencapsulated by spray drier and the microcapsules were characterized.BAC were suspended in MRS,cultivated and microencapsulated by freeze drying.Rats were randomly assigned to 5 groups(8/gp).The 1st group was negative control receiving basic diet(C),the 2nd group was positive control fed on HFD,the 3rd group was fed on HFD+BS(400 mg/kg),the 4th group was fed on HFD+BAC(1 ml containing 1011 CFU),the 5th group was fed on HFD+BS+BAC.After 8 weeks animals were sacrificed,the collected serum was analyzed for different biochemical parameters.The body organs and body fat weights were estimated and histopathological and immunohistochemical examinations were evaluated.Results showed the ability of BS in controlling most of the parameters related to MeS and improvement of histopathology findings in organs.BS and BAC acted in synergy in this effect.In conclusion,microencapsulated BS or its combination with Probiotic bacteria may control MeS and both acted as symbiotic in augmenting the improvement of MeS intact model.展开更多
Aldehyde oxidase(AOX)is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics.AOX-mediated metabolism can result in unexpected outcomes,such as the p...Aldehyde oxidase(AOX)is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics.AOX-mediated metabolism can result in unexpected outcomes,such as the production of toxic metabolites and high metabolic clearance,which can lead to the clinical failure of novel therapeutic agents.Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability.In this study,we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism.AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction,while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks.AOMP significantly outperformed the benchmark methods in both cross-validation and external testing.Using AOMP,we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability,which were validated through in vitro experiments.Furthermore,for the convenience of the community,we established the first online service for AOX metabolism prediction based on AOMP,which is freely available at https://aomp.alphama.com.cn.展开更多
文摘ropic 1:Regarding sustainable development and global public interests,what should international Al standards focus on?James Ong:Since 2019,I have witnessed the evolution of WAIC and found that a consensus on the philosophical and ethic level on advocating“AI for humanity”is necessary,since ethics factor carries more weight in standards development.I want to emphasize three points:AI assisting sustainable development,AI empowering a balanced global development,and human-AI coordination for preventing AI risks.
文摘In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home(H2H)program that has been operating since 2017.In this follow on practice and policy article,we further elaborate on Singapore's H2H program and care model,and its supporting AI model for multiple readmission prediction,in the following ways:(1)by providing updates on the AI and supporting information systems,(2)by reporting on customer engagement and related service delivery outcomes including staff‐related time savings and patient benefits in terms of bed days saved,(3)by sharing lessons learned with respect to(i)analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants,(ii)balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables,and(iii)the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems,(4)by highlighting how this H2H effort supported broader Covid‐19 response efforts across Singapore's public healthcare system,and finally(5)by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards.For the convenience of the reader,some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.
基金supported by the National Natural Science Foundation of China(Grant No.72301061).
文摘This study aims to validate the Object-Oriented User Interface Customization(OOUIC)framework by employing Use Case Analysis(UCA)to facilitate the development of adaptive User Interfaces(UIs).The OOUIC framework advocates for User-Centered Design(UCD)methodologies,including UCA,to systematically identify intricate user requirements and construct adaptive UIs tailored to diverse user needs.To operationalize this approach,thirty users of Product Lifecycle Management(PLM)systems were interviewed across six distinct use cases.Interview transcripts were subjected to deductive content analysis to classify UI objects systematically.Subsequently,adaptive UIs were developed for each use case,and their complexity was quantitatively compared against the original system UIs.The results demonstrated a significant reduction in complexity across all adaptive UIs(Mean Difference,MD=0.11,t(5)=8.26,p<0.001),confirming their superior efficiency.The findings validate the OOUIC framework,demonstrating that UCD effectively captures complex requirements for adaptive UI development,while adaptive UIs mitigate interface complexity through object reduction and optimized layout design.Furthermore,UCA and deductive content analysis serve as robust methodologies for object categorization in adaptive UI design.Beyond eliminating redundant elements and prioritizing object grouping,designers can further reduce complexity by adjusting object dimensions and window sizing.This study underscores the efficacy of UCA in developing adaptive UIs and streamlining complex interfaces.Ultimately,UCD proves instrumental in gathering intricate requirements,while adaptive UIs enhance usability by minimizing object clutter and refining spatial organization.
文摘Objective:To explore the effect of Diospyros kaki on cattle spermatozoa during chilling and cryopreservation.Methods: Five milliliter of blended Persimmon (Diospyros kaki) flesh was added to 45 mL TCF to obtain 10% stock solution. Kaki enriched extender (KEE) was prepared by adding to TCF in concentrations 0.0/5.0 mL (control, 0%), 0.5/4.5 mL (1%), 1/4 mL (2%), 1.5/3.5 mL (3%), 2.0/3.0 mL (4%), 2.5/2.5 mL (5%), 3.0/2.0 mL (6%), 3.5/1.5 mL (7%), 4.0/1.0 mL (8%), 4.5/0.5 mL (9%) and 5.0/0.0 mL (10%) to obtain a final volume 5 mL in each tube. Whole egg yolk was added to each tube to obtain KEE with 20% egg yolk (KEEY), all tubes were centrifuged to get rid of debris. Semen was added to the supernatants in other tubes. Extended semen was subjected to evaluation (motility, alive sperm and intact sperm membrane (HOST) %) in both chilled and cryopreserved semen. Conception rate was carried out.Results:Sperm motility was significantly (P<0.0001) kept high after 11 d of chilling with the concentration 1%, 2%, 3%, 4%, 5% as compared to the control (41.67±1.67, 41.67±1.67, 40.00±0.00, 41.67±1.67 and 41.67±1.67, respectively) and also non-significantly kept high at the other concentrations up to 9 d of chilling. Addition of KEE had significantly (P<0.0033) improved post thawing sperm motility % with the concentrations 1, 2, 3, 4, 5 and 6% as compared to the control (51.67±5.27, 55.00±3.16, 48.33±1.05, 45.00±3.96, 57.00±2.50, 55.00±5.00 and 43.33±5.11 respectively).While the other concentrations exhibit no effect. Addition of KEE maintained alive sperm%, abnormalities% and % of intact spermatozoa membranes (HOST %) as good as the control with all concentrations of kaki used in our study. The conception rate upon using frozen semen in insemination showed higher conception rate in concentrations of 2%, 4% and 6 % KEE in cattle.Conclusion: It could be concluded that some concentrations ofDiospyros kaki improved bull semen quality post-chilling and post-freezing.
基金funded by Hanoi University of Industry under Grant Number 27-2022-RD/HD-DHCN (URL:https://www.haui.edu.vn/).
文摘Attribute reduction,also known as feature selection,for decision information systems is one of the most pivotal issues in machine learning and data mining.Approaches based on the rough set theory and some extensions were proved to be efficient for dealing with the problemof attribute reduction.Unfortunately,the intuitionistic fuzzy sets based methods have not received much interest,while these methods are well-known as a very powerful approach to noisy decision tables,i.e.,data tables with the low initial classification accuracy.Therefore,this paper provides a novel incremental attribute reductionmethod to dealmore effectivelywith noisy decision tables,especially for highdimensional ones.In particular,we define a new reduct and then design an original attribute reduction method based on the distance measure between two intuitionistic fuzzy partitions.It should be noted that the intuitionistic fuzzypartitiondistance iswell-knownas aneffectivemeasure todetermine important attributes.More interestingly,an incremental formula is also developed to quickly compute the intuitionistic fuzzy partition distance in case when the decision table increases in the number of objects.This formula is then applied to construct an incremental attribute reduction algorithm for handling such dynamic tables.Besides,some experiments are conducted on real datasets to show that our method is far superior to the fuzzy rough set based methods in terms of the size of reduct and the classification accuracy.
基金Project supported by the National Natural Science Foundation of China(No.U1509221)the National Key Technology R&D Program of China(No.2015BAH07F01)the Zhejiang Provincial Key R&D Program,China(No.2017C03044)
文摘Artificial intelligence(AI)is the core technology of technological revolution and industrial transformation.As one of the new intelligent needs in the AI 2.0 era,financial intelligence has elicited much attention from the academia and industry.In our current dynamic capital market,financial intelligence demonstrates a fast and accurate machine learning capability to handle complex data and has gradually acquired the potential to become a'financial brain.'In this paper,we survey existing studies on financial intelligence.First,we describe the concept of financial intelligence and elaborate on its position in the financial technology field.Second,we introduce the development of financial intelligence and review state-of-the-art techniques in wealth management,risk management,financial security,financial consulting,and blockchain.Finally,we propose a research framework called FinBrain and summarize four open issues,namely,explainable financial agents and causality,perception and prediction under uncertainty,risk-sensitive and robust decision-making,and multi-agent game and mechanism design.We believe that these research directions can lay the foundation for the development of AI 2.0 in the finance field.
基金National Natural Science Foundation of China(62305184)Science,Technology and Innovation Commission of Shenzhen Municipality(JCYJ20241202123919027)+1 种基金Science,Technology and Innovation Commission of Shenzhen Municipality(WDZC20220818100259004)Basic and Applied Basic Research Foundation of Guangdong Province(2023A1515012932).
文摘Single-pixel imaging(SPI)faces significant challenges in reconstructing high-quality images under complex real-world degradation conditions.This paper presents an innovative degradation model for the physical processes in SPI,providing the first comprehensive and quantitative analysis of various SPI noise sources encountered in real-world applications.Especially,pattern-dependent global noise propagation and object jitter modelling methods for SPI are proposed.Subsequently,a deep-blind neural network is developed to remove the necessity of obtaining parameters of all the degradation factors in real-world image compensation.Our method can operate without degradation parameters and significantly improve the resolution and fidelity of SPI image reconstruction.The deep-blind network training is guided by the proposed comprehensive SPI degradation model that describes real-world SPI impairments,enabling the network to generalize across a wide range of degradation combinations.The experiment validates its advanced performance in real-world SPI imaging at ultra-low sampling rates.The proposed method holds great potential for applications in remote sensing,biomedical imaging,and privacy-preserving surveillance.
基金supported by the National Key R&D Program of China(2023YFC3304104)the National Natural Science Foundation of China(Grant No.62172094).
文摘Synonym discovery is important in a wide variety of concept-related tasks,such as entity/concept mining and industrial knowledge graph(KG)construction.It intends to determine whether two terms refer to the same concept in semantics.Existing methods rely on contexts or KGs.However,these methods are often impractical in some cases where contexts or KGs are not available.Therefore,this paper proposes a context-free prompt learning based synonym discovery method called ProSyno,which takes the world’s largest freely available dictionary Wiktionary as a semantic source.Based on a pre-trained language model(PLM),we employ a prompt learning method to generalize to other datasets without any fine-tuning.Thus,our model is more appropriate for context-free situation and can be easily transferred to other fields.Experimental results demonstrate its superiority comparing with state-of-the-art methods.
文摘Aspergillus oryzae is widely used in traditional koji production,although its application in targeted savory design in plant-based foods remains limited.Here,we applied an AI-guided bioconversion framework integrating sensory analysis and metabolomics to derive an umami-rich,chicken-like seasoning from cucumber and peanut.Bayesian optimization was used to refine the substrate ratio and incubation time,identifying 5%cucumber and 5%peanut incubated for 7 days as the optimal conditions.This formulation increased the intensities of umami and chicken-like flavor,reduced off-flavors,and enhanced savory perception when incorporated at 1%(w/w)into a neutral plant-protein nugget model.Untargeted LC-MS and GC-MS analyses identified 52 discriminant metabolites organized into coherent biochemical modules.Integrated chemometrics linked carbohydrate-derived substrates to fungal glutamate,succinate,and 5′-nucleotides,while phenylpropanoid and triterpenoid modules aligned with mushroom notes and the suppression of savory attributes.The results indicate that AI-directed A.oryzae bioconversion provides a basis for the mechanistically informed construction of umami flavor sys-tems from simple botanical substrates.
基金supported by the National Natural Science Foundation of China(T2225002,82273855)Lingang Laboratory(LG202102-01-02)the National Key Research and Development Program of China(2022YFC3400504)。
文摘Dear Editor,Great progress has been made using artificial intelligence(AI) techniques in learning knowledge from biomedical databases in recent years, revolutionizing the study of many fields, such as protein structure prediction and protein design(Madani et al., 2023). However, there is massive biomedical knowledge not curated in the form of structured data but hidden in primary scientific literature.
基金funded this work through internal project No 12050210.
文摘Metabolic syndrome(MeS)is a major health problem associated with the high prevalence of obesity,diabetes,hypertension and dyslipidemia.Boswellia serrata resin(BS)is an old remedy reputed by its rich antioxidant compounds.The present research aimed to assess the impact of microencapsulated BS if given in combination with probiotic bacteria(BAC)(Lactobacillus plantarum and Lactobacillus rhamnosus)which had anti-inflammatory and antioxidant activities to control the metabolic disorders associated with MeS.Water extract of BS was prepared,total phenolic,total antioxidants and HPLC were analyzed.BS extract was microencapsulated by spray drier and the microcapsules were characterized.BAC were suspended in MRS,cultivated and microencapsulated by freeze drying.Rats were randomly assigned to 5 groups(8/gp).The 1st group was negative control receiving basic diet(C),the 2nd group was positive control fed on HFD,the 3rd group was fed on HFD+BS(400 mg/kg),the 4th group was fed on HFD+BAC(1 ml containing 1011 CFU),the 5th group was fed on HFD+BS+BAC.After 8 weeks animals were sacrificed,the collected serum was analyzed for different biochemical parameters.The body organs and body fat weights were estimated and histopathological and immunohistochemical examinations were evaluated.Results showed the ability of BS in controlling most of the parameters related to MeS and improvement of histopathology findings in organs.BS and BAC acted in synergy in this effect.In conclusion,microencapsulated BS or its combination with Probiotic bacteria may control MeS and both acted as symbiotic in augmenting the improvement of MeS intact model.
基金supported by the National Natural Science Foundation of China(T2225002,82273855 to Mingyue Zheng)Lingang Laboratory(LG202102-01-02 to Mingyue Zheng)+1 种基金the National Key Research and Development Program of China(2022YFC3400504 to Mingyue Zheng)the open fund of state key laboratory of Pharmaceutical Biotechnology,Nanjing University,China(KF-202301 to Mingyue Zheng).
文摘Aldehyde oxidase(AOX)is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics.AOX-mediated metabolism can result in unexpected outcomes,such as the production of toxic metabolites and high metabolic clearance,which can lead to the clinical failure of novel therapeutic agents.Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability.In this study,we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism.AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction,while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks.AOMP significantly outperformed the benchmark methods in both cross-validation and external testing.Using AOMP,we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability,which were validated through in vitro experiments.Furthermore,for the convenience of the community,we established the first online service for AOX metabolism prediction based on AOMP,which is freely available at https://aomp.alphama.com.cn.
