As an essential component of the Materials Genome Initiative aiming to shorten the period of materials research and development, combinatorial synthesis and rapid characterization technologies have been playing a more...As an essential component of the Materials Genome Initiative aiming to shorten the period of materials research and development, combinatorial synthesis and rapid characterization technologies have been playing a more and more important role in exploring new materials and comprehensively understanding materials properties. In this review, we discuss the advantages of high-throughput experimental techniques in researches on superconductors. The evolution of combinatorial thin-film technology and several high-speed screening devices are briefly introduced. We emphasize the necessity to develop new high-throughput research modes such as a combination of high-throughput techniques and conventional methods.展开更多
Medical Data Mining published an article entitled Mapping the global research trends and hotspots on hypertensive nephropathy:A novel bibliometrics overview on 10 October 2025.The author confirmed this article’s proo...Medical Data Mining published an article entitled Mapping the global research trends and hotspots on hypertensive nephropathy:A novel bibliometrics overview on 10 October 2025.The author confirmed this article’s proof on 28 September 2025 without any questions.However,on 13 November 2025,the Editorial Office of Medical Data Mining noticed an inconsistency between the data presented in the main text and Figure 1.Specifically,erroneous Figure 1 states“a total of 56,691 literatures were obtained through database search”,while the main text in the Search results section states“According to the search term,a total of 59,220 publications were retrieved from the database.”The authors acknowledge that the original version of Figure 1 was incorrect and have provided the revised,correct version in this corrigendum.The authors would like to assert that there is no change in the body text of the article.展开更多
Nanjing’s determination to transform itself from a production base to a research center reflects China’s evolution toward higher-quality development.A refrigerator that thaws frozen meat in 10 minutes and then keeps...Nanjing’s determination to transform itself from a production base to a research center reflects China’s evolution toward higher-quality development.A refrigerator that thaws frozen meat in 10 minutes and then keeps it fresh,a cooker hood that remains clean even after 10 years without disassembling it for cleaning.展开更多
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and is the most prominent cause of dementia.In 2019,over 57.4million people were living with AD and other dementia subtypes,a number which is ex...Alzheimer's disease (AD) is a progressive neurodegenerative disorder and is the most prominent cause of dementia.In 2019,over 57.4million people were living with AD and other dementia subtypes,a number which is expected to increase to over 152.8 million in the next 25years.This ever-increasing burden has resulted in AD and other neurodegenerative diseases rising to one of the top 10 causes of death globally (O'Connell et al.,2024).展开更多
In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology bas...In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.展开更多
Throughout the contemporary Chinese history of geography,geographical engineering has consistently played a pivotal role as a fundamental scientific activity.It possesses its distinct ontological basis and value orien...Throughout the contemporary Chinese history of geography,geographical engineering has consistently played a pivotal role as a fundamental scientific activity.It possesses its distinct ontological basis and value orientation,rendering it inseparable from being merely a derivative of geographical science or technology.This paper defines geographical engineering and introduces its development history through the lens of Chinese geographical engineering praxises.Furthermore,it is highlighted the logical and functional consistency between the theory of human-earth system and the praxis of geographical engineering.Six modern cases of geographical engineering projects are presented in detail to demonstrate the points and characteristics of different types of modern geographical engineering.Geographical engineering serves as an engine for promoting integrated geography research,and in response to the challenge posed by fragmented geographies,this paper advocates for an urgent revitalization of geographical engineering.The feasibility of revitalizing geographical engineering is guaranteed because it aligns with China’s national strategies.展开更多
Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether ...Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether Large Language Models(LLMs)can play a role in this process.Design/methodology/approach:This article assesses which ChatGPT inputs(full text without tables,figures,and references;title and abstract;title only)produce better quality score estimates,and the extent to which scores are affected by ChatGPT models and system prompts.Findings:The optimal input is the article title and abstract,with average ChatGPT scores based on these(30 iterations on a dataset of 51 papers)correlating at 0.67 with human scores,the highest ever reported.ChatGPT 4o is slightly better than 3.5-turbo(0.66),and 4o-mini(0.66).Research limitations:The data is a convenience sample of the work of a single author,it only includes one field,and the scores are self-evaluations.Practical implications:The results suggest that article full texts might confuse LLM research quality evaluations,even though complex system instructions for the task are more effective than simple ones.Thus,whilst abstracts contain insufficient information for a thorough assessment of rigour,they may contain strong pointers about originality and significance.Finally,linear regression can be used to convert the model scores into the human scale scores,which is 31%more accurate than guessing.Originality/value:This is the first systematic comparison of the impact of different prompts,parameters and inputs for ChatGPT research quality evaluations.展开更多
The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and rev...The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.It reports the latest and the most creative results of important fundamental research in all aspects of chemistry and of developments with significant consequences across sub-disciplines.This journal is sponsored by Jilin University and mandated by the Ministry of Education of P.R.China.展开更多
The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and rev...The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.It reports the latest and the most creative results of important fundamental research in all aspects of chemistry and of developments with significant consequences across sub-disciplines.This journal is sponsored by Jilin University and mandated by the Ministry of Education of P.R.China.展开更多
The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF str...The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.展开更多
The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three ...The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three Combinations”).However,considering TCM's distinctive features of“syndrome differentiation and treatment”and“multicomponent formulations and complex mechanisms”,current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system.Moreover,significant obstacles persist in gathering human experience data,evaluating clinical efficacy,and controlling the quality of active ingredients,which impede the innovation process in TCM drug development.Network pharmacology,centered on the“network targets”theory,transcends the limitations of the conventional“single target”reductionist research model.It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions.This approach aligns with the holistic perspective of TCM,offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs.It is internationally recognized as a“next-generation drug research model”.To advance the research of new tools,methods,and standards for TCM evaluation and to overcome fundamental,critical,and cutting-edge technical challenges in TCM regulation,this consensus aims to explore the characteristics,progress,challenges,applicable pathways,and specific applications of network pharmacology as a new theory,method,and tool in TCM drug development.The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.展开更多
The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and rev...The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.展开更多
The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explore...The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explores the synergistic application of AI and HTE, highlighting their role in accelerating catalyst discovery, optimizing reaction parameters, and understanding structure-performance relationships. HTE facilitates the rapid preparation, characterization, and evaluation of diverse catalyst formulations, generating large datasets essential for AI model training. Machine learning algorithms, including regression models, neural networks, and active learning frameworks, analyze these datasets to uncover the underlying relationships between the data, predict performance, and optimize experimental workflows in real-time. Case studies across heterogeneous, homogeneous, and electrocatalysis demonstrate significant advancements, including improved reaction selectivity, enhanced material stability, and shorten discovery cycles. The integration of AI with HTE has significantly accelerated discovery cycles, enabling the optimization of catalyst formulations and reaction conditions. Despite these achievements, challenges remain, including reliance on researcher expertise, real-time adaptability, and the complexity of large-scale data analysis. Addressing these limitations through refined experimental protocols, standardized datasets, and interpretable AI models will unlock the full potential of AI-HTE integration.展开更多
Autonomous Transporta tion Research(中文刊名《自主交通研究》,简称ATRes期刊)是由武汉理工大学主办,水路交通控制全国重点实验室、国家水运安全工程技术研究中心、交通信息与安全教育部工程研究中心等协办,科爱出版社出版发行的英...Autonomous Transporta tion Research(中文刊名《自主交通研究》,简称ATRes期刊)是由武汉理工大学主办,水路交通控制全国重点实验室、国家水运安全工程技术研究中心、交通信息与安全教育部工程研究中心等协办,科爱出版社出版发行的英文开放获取式高水平学术期刊,国际标准连续出版物号:ISSN 3050-8622。展开更多
Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligen...Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.展开更多
Objective:To analyze the uses of research methodologies applied in nursing articles published in esteemed journals.Nursing research uses various methodologies to examine different aspects of the field.Understanding th...Objective:To analyze the uses of research methodologies applied in nursing articles published in esteemed journals.Nursing research uses various methodologies to examine different aspects of the field.Understanding the frequency and trends of these approaches is important.Methods:A comprehensive analysis of 697 peer-reviewed research articles(RAs)was conducted.These articles encompassed quantitative,qualitative,and mixed-methods designs.Results:The analysis revealed a dominance of quantitative methodologies(78%)among the examined RAs.Qualitative approaches were less prevalent(14%)but showed a growing presence.Mixed-methods studies constituted approximately 7% of the analyzed articles.Conclusions:This systematic exploration of research methodologies in nursing literature from 2018 and 2022 highlights the dynamic and diverse nature of research the field.This comprehensive understanding of research methodologies is a valuable guide for researchers,educators,and policymakers in shaping the future of nursing research.展开更多
Background: In response to the limitations of logical empiricism, interpretivism emerged as a philosophical approach for developing nursing knowledge. This paper discusses interpretivist constructivism and its value t...Background: In response to the limitations of logical empiricism, interpretivism emerged as a philosophical approach for developing nursing knowledge. This paper discusses interpretivist constructivism and its value to qualitative nursing research. Methods: The paper synthesizes relevant literature on the importance of interpretivist constructivism in nursing research. It reviews the key elements of interpretivism, the principles of constructivism, the connection between the two approaches, the benefits and limitations of constructivism in nursing research, and the steps for conducting constructivist stroke nursing research. Results: Interpretivist constructivism emphasizes the importance of human experiences, interactions, and social contexts in knowledge development. It allows nurse researchers to adopt flexible, participant-driven approaches to explore and understand complex subjective human phenomena. This approach respects the unique perspectives and contexts of stakeholders, including patients, caregivers, healthcare professionals, and knowledge users. By following specific steps, constructivist researchers can improve the rigor, transparency, and validity of qualitative nursing research while reducing biases in interpreting the inherently subjective experiences of patients. Conclusion: A deeper understanding of the complexities of interpretivism and constructivism in qualitative research is essential. This paper provides a clear, comprehensive guide for effectively applying these approaches in qualitative nursing research.展开更多
Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design...Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design/methodology/approach:An exploratory survey is administered to researchers at the Sapienza University of Rome,one of Europe’s oldest and largest generalist universities.To measure metric-wiseness,we use attitude statements that are evaluated by a 5-point Likert scale.Moreover,we analyze documents of recent initiatives on assessment reform to shed light on how researchers’heterogeneous attitudes regarding and knowledge of bibliometric indicators are taken into account.Findings:We found great heterogeneity in researchers’metric-wiseness across scientific disciplines.In addition,within each discipline,we observed both supporters and critics of bibliometric indicators.From the document analysis,we found no reference to individual heterogeneity concerning researchers’metric wiseness.Research limitations:We used a self-selected sample of researchers from one Italian university as an exploratory case.Further research is needed to check the generalizability of our findings.Practical implications:To gain sufficient support for research evaluation practices,it is key to consider researchers’diverse attitudes towards indicators.Originality/value:We contribute to the current debate on reforming research assessment by providing a novel empirical measurement of researchers’knowledge and attitudes towards bibliometric indicators and discussing the importance of the obtained results for improving current research evaluation systems.展开更多
基金Project supported by the National Key Basic Research Program of China(Grant Nos.2015CB921000,2016YFA0300301,2017YFA0303003,and 2017YFA0302902)the National Natural Science Foundation of China(Grant Nos.11674374,11804378,and 11574372)+3 种基金the Beijing Municipal Science and Technology Project(Grant No.Z161100002116011)the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant Nos.QYZDB-SSW-SLH008 and QYZDY-SSW-SLH001)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB07020100)the Opening Project of Wuhan National High Magnetic Field Center(Grant No.PHMFF2015008)
文摘As an essential component of the Materials Genome Initiative aiming to shorten the period of materials research and development, combinatorial synthesis and rapid characterization technologies have been playing a more and more important role in exploring new materials and comprehensively understanding materials properties. In this review, we discuss the advantages of high-throughput experimental techniques in researches on superconductors. The evolution of combinatorial thin-film technology and several high-speed screening devices are briefly introduced. We emphasize the necessity to develop new high-throughput research modes such as a combination of high-throughput techniques and conventional methods.
文摘Medical Data Mining published an article entitled Mapping the global research trends and hotspots on hypertensive nephropathy:A novel bibliometrics overview on 10 October 2025.The author confirmed this article’s proof on 28 September 2025 without any questions.However,on 13 November 2025,the Editorial Office of Medical Data Mining noticed an inconsistency between the data presented in the main text and Figure 1.Specifically,erroneous Figure 1 states“a total of 56,691 literatures were obtained through database search”,while the main text in the Search results section states“According to the search term,a total of 59,220 publications were retrieved from the database.”The authors acknowledge that the original version of Figure 1 was incorrect and have provided the revised,correct version in this corrigendum.The authors would like to assert that there is no change in the body text of the article.
文摘Nanjing’s determination to transform itself from a production base to a research center reflects China’s evolution toward higher-quality development.A refrigerator that thaws frozen meat in 10 minutes and then keeps it fresh,a cooker hood that remains clean even after 10 years without disassembling it for cleaning.
文摘Alzheimer's disease (AD) is a progressive neurodegenerative disorder and is the most prominent cause of dementia.In 2019,over 57.4million people were living with AD and other dementia subtypes,a number which is expected to increase to over 152.8 million in the next 25years.This ever-increasing burden has resulted in AD and other neurodegenerative diseases rising to one of the top 10 causes of death globally (O'Connell et al.,2024).
基金financially supported by National Key R&D Program(2021YFF0701905)。
文摘In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.
基金Under the auspices of National Natural Science Foundation of China(No.42293270)。
文摘Throughout the contemporary Chinese history of geography,geographical engineering has consistently played a pivotal role as a fundamental scientific activity.It possesses its distinct ontological basis and value orientation,rendering it inseparable from being merely a derivative of geographical science or technology.This paper defines geographical engineering and introduces its development history through the lens of Chinese geographical engineering praxises.Furthermore,it is highlighted the logical and functional consistency between the theory of human-earth system and the praxis of geographical engineering.Six modern cases of geographical engineering projects are presented in detail to demonstrate the points and characteristics of different types of modern geographical engineering.Geographical engineering serves as an engine for promoting integrated geography research,and in response to the challenge posed by fragmented geographies,this paper advocates for an urgent revitalization of geographical engineering.The feasibility of revitalizing geographical engineering is guaranteed because it aligns with China’s national strategies.
文摘Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether Large Language Models(LLMs)can play a role in this process.Design/methodology/approach:This article assesses which ChatGPT inputs(full text without tables,figures,and references;title and abstract;title only)produce better quality score estimates,and the extent to which scores are affected by ChatGPT models and system prompts.Findings:The optimal input is the article title and abstract,with average ChatGPT scores based on these(30 iterations on a dataset of 51 papers)correlating at 0.67 with human scores,the highest ever reported.ChatGPT 4o is slightly better than 3.5-turbo(0.66),and 4o-mini(0.66).Research limitations:The data is a convenience sample of the work of a single author,it only includes one field,and the scores are self-evaluations.Practical implications:The results suggest that article full texts might confuse LLM research quality evaluations,even though complex system instructions for the task are more effective than simple ones.Thus,whilst abstracts contain insufficient information for a thorough assessment of rigour,they may contain strong pointers about originality and significance.Finally,linear regression can be used to convert the model scores into the human scale scores,which is 31%more accurate than guessing.Originality/value:This is the first systematic comparison of the impact of different prompts,parameters and inputs for ChatGPT research quality evaluations.
文摘The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.It reports the latest and the most creative results of important fundamental research in all aspects of chemistry and of developments with significant consequences across sub-disciplines.This journal is sponsored by Jilin University and mandated by the Ministry of Education of P.R.China.
文摘The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.It reports the latest and the most creative results of important fundamental research in all aspects of chemistry and of developments with significant consequences across sub-disciplines.This journal is sponsored by Jilin University and mandated by the Ministry of Education of P.R.China.
基金financial support from the National Key Research and Development Program of China(2021YFB 3501501)the National Natural Science Foundation of China(No.22225803,22038001,22108007 and 22278011)+1 种基金Beijing Natural Science Foundation(No.Z230023)Beijing Science and Technology Commission(No.Z211100004321001).
文摘The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.
基金supported by the National Medical Products Administration Commissioned Research Project (No.20211440216)the National Administration of Traditional Chinese Medicine Science and Technology Project (No.GZY-KJS-2024-03)+3 种基金the State Key Laboratory of Drug Regulatory Science Project (No.2023SKLDRS0104)the Basic Research Program Natural Science Fund-Frontier Leading Technology Basic Research Special Project of Jiangsu Province (No.BK20232014)the Programs Foundation for Leading Talents in National Administration of Traditional Chinese Medicine of China“Qihuang scholars”Projectthe Tianjin Administration for Market Regulation Science and Technology Key Projects (No.2022-W35)。
文摘The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three Combinations”).However,considering TCM's distinctive features of“syndrome differentiation and treatment”and“multicomponent formulations and complex mechanisms”,current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system.Moreover,significant obstacles persist in gathering human experience data,evaluating clinical efficacy,and controlling the quality of active ingredients,which impede the innovation process in TCM drug development.Network pharmacology,centered on the“network targets”theory,transcends the limitations of the conventional“single target”reductionist research model.It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions.This approach aligns with the holistic perspective of TCM,offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs.It is internationally recognized as a“next-generation drug research model”.To advance the research of new tools,methods,and standards for TCM evaluation and to overcome fundamental,critical,and cutting-edge technical challenges in TCM regulation,this consensus aims to explore the characteristics,progress,challenges,applicable pathways,and specific applications of network pharmacology as a new theory,method,and tool in TCM drug development.The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.
文摘The journal Chemical Research in Chinese Universities is a comprehensive academic journal in the field of chemistry,published bimonthly since 1984.The journal publishes research articles,letters/communications and reviews written by faculty members,researchers and postgraduates in universities,colleges and research institutes all over China and overseas.
基金supported by the Special Project of National Natural Science Foundation(42341204)the the National Natural Science Foundation of China(W2411009).
文摘The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explores the synergistic application of AI and HTE, highlighting their role in accelerating catalyst discovery, optimizing reaction parameters, and understanding structure-performance relationships. HTE facilitates the rapid preparation, characterization, and evaluation of diverse catalyst formulations, generating large datasets essential for AI model training. Machine learning algorithms, including regression models, neural networks, and active learning frameworks, analyze these datasets to uncover the underlying relationships between the data, predict performance, and optimize experimental workflows in real-time. Case studies across heterogeneous, homogeneous, and electrocatalysis demonstrate significant advancements, including improved reaction selectivity, enhanced material stability, and shorten discovery cycles. The integration of AI with HTE has significantly accelerated discovery cycles, enabling the optimization of catalyst formulations and reaction conditions. Despite these achievements, challenges remain, including reliance on researcher expertise, real-time adaptability, and the complexity of large-scale data analysis. Addressing these limitations through refined experimental protocols, standardized datasets, and interpretable AI models will unlock the full potential of AI-HTE integration.
文摘Autonomous Transporta tion Research(中文刊名《自主交通研究》,简称ATRes期刊)是由武汉理工大学主办,水路交通控制全国重点实验室、国家水运安全工程技术研究中心、交通信息与安全教育部工程研究中心等协办,科爱出版社出版发行的英文开放获取式高水平学术期刊,国际标准连续出版物号:ISSN 3050-8622。
文摘Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.
文摘Objective:To analyze the uses of research methodologies applied in nursing articles published in esteemed journals.Nursing research uses various methodologies to examine different aspects of the field.Understanding the frequency and trends of these approaches is important.Methods:A comprehensive analysis of 697 peer-reviewed research articles(RAs)was conducted.These articles encompassed quantitative,qualitative,and mixed-methods designs.Results:The analysis revealed a dominance of quantitative methodologies(78%)among the examined RAs.Qualitative approaches were less prevalent(14%)but showed a growing presence.Mixed-methods studies constituted approximately 7% of the analyzed articles.Conclusions:This systematic exploration of research methodologies in nursing literature from 2018 and 2022 highlights the dynamic and diverse nature of research the field.This comprehensive understanding of research methodologies is a valuable guide for researchers,educators,and policymakers in shaping the future of nursing research.
文摘Background: In response to the limitations of logical empiricism, interpretivism emerged as a philosophical approach for developing nursing knowledge. This paper discusses interpretivist constructivism and its value to qualitative nursing research. Methods: The paper synthesizes relevant literature on the importance of interpretivist constructivism in nursing research. It reviews the key elements of interpretivism, the principles of constructivism, the connection between the two approaches, the benefits and limitations of constructivism in nursing research, and the steps for conducting constructivist stroke nursing research. Results: Interpretivist constructivism emphasizes the importance of human experiences, interactions, and social contexts in knowledge development. It allows nurse researchers to adopt flexible, participant-driven approaches to explore and understand complex subjective human phenomena. This approach respects the unique perspectives and contexts of stakeholders, including patients, caregivers, healthcare professionals, and knowledge users. By following specific steps, constructivist researchers can improve the rigor, transparency, and validity of qualitative nursing research while reducing biases in interpreting the inherently subjective experiences of patients. Conclusion: A deeper understanding of the complexities of interpretivism and constructivism in qualitative research is essential. This paper provides a clear, comprehensive guide for effectively applying these approaches in qualitative nursing research.
基金supported by the Sapienza Universitàdi Roma Sapienza Awards no.6H15XNFS.
文摘Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design/methodology/approach:An exploratory survey is administered to researchers at the Sapienza University of Rome,one of Europe’s oldest and largest generalist universities.To measure metric-wiseness,we use attitude statements that are evaluated by a 5-point Likert scale.Moreover,we analyze documents of recent initiatives on assessment reform to shed light on how researchers’heterogeneous attitudes regarding and knowledge of bibliometric indicators are taken into account.Findings:We found great heterogeneity in researchers’metric-wiseness across scientific disciplines.In addition,within each discipline,we observed both supporters and critics of bibliometric indicators.From the document analysis,we found no reference to individual heterogeneity concerning researchers’metric wiseness.Research limitations:We used a self-selected sample of researchers from one Italian university as an exploratory case.Further research is needed to check the generalizability of our findings.Practical implications:To gain sufficient support for research evaluation practices,it is key to consider researchers’diverse attitudes towards indicators.Originality/value:We contribute to the current debate on reforming research assessment by providing a novel empirical measurement of researchers’knowledge and attitudes towards bibliometric indicators and discussing the importance of the obtained results for improving current research evaluation systems.
