BACKGROUND Ampullary adenocarcinoma is a rare malignant tumor of the gastrointestinal tract.Currently,only a few cases have been reported,resulting in limited information on survival.AIM To develop a dynamic nomogram ...BACKGROUND Ampullary adenocarcinoma is a rare malignant tumor of the gastrointestinal tract.Currently,only a few cases have been reported,resulting in limited information on survival.AIM To develop a dynamic nomogram using internal and external validation to predict survival in patients with ampullary adenocarcinoma.METHODS Data were sourced from the surveillance,epidemiology,and end results stat database.The patients in the database were randomized in a 7:3 ratio into training and validation groups.Using Cox regression univariate and multivariate analyses in the training group,we identified independent risk factors for overall survival and cancer-specific survival to develop the nomogram.The nomogram was validated with a cohort of patients from the First Affiliated Hospital of the Army Medical University.RESULTS For overall and cancer-specific survival,12(sex,age,race,lymph node ratio,tumor size,chemotherapy,surgical modality,T stage,tumor differentiation,brain metastasis,lung metastasis,and extension)and 6(age;surveillance,epidemiology,and end results stage;lymph node ratio;chemotherapy;surgical modality;and tumor differentiation)independent risk factors,respectively,were incorporated into the nomogram.The area under the curve values at 1,3,and 5 years,respectively,were 0.807,0.842,and 0.826 for overall survival and 0.816,0.835,and 0.841 for cancer-specific survival.The internal and external validation cohorts indicated good consistency of the nomogram.CONCLUSION The dynamic nomogram offers robust predictive efficacy for the overall and cancer-specific survival of ampullary adenocarcinoma.展开更多
A distinctive feature of scholarly communities today is exploring topics and concepts in interdisciplinary and international contexts. This observation is increasingly apparent and visible in advancing our thinking an...A distinctive feature of scholarly communities today is exploring topics and concepts in interdisciplinary and international contexts. This observation is increasingly apparent and visible in advancing our thinking and policies related to human/environmental worlds at local, regional, and global scales. Maps are an important part of these innovative and ongoing research approaches. In this context, we consider urban forests a topic meriting more attention of scholars studying the geographic and environmental intersections of the natural sciences with the social sciences and humanities. We construct two innovative knowledge bases, one a conceptual framework based on major themes and concepts related to mapping urban forests using key words of the first 100 results of a Google Scholar query and a second using the number of Google Scholar hyperlinks about mapping urban forests in 244 capital cities. We discovered that the constructed world maps reveal vast global unevenness in our knowledge about urban forests in hyperlink numbers and ratios, results that merit further attention by disciplinary, international and interdisciplinary scholarly communities.展开更多
Objectives:Electronic health records(EHRs)offer valuable real-world data(RWD)for Chinese medicine research.However,significant methodological challenges remain in developing integrative Chinese-Western medicine(ICWM)d...Objectives:Electronic health records(EHRs)offer valuable real-world data(RWD)for Chinese medicine research.However,significant methodological challenges remain in developing integrative Chinese-Western medicine(ICWM)databases.This study aims to establish a best-practice methodological framework,referred to as BRIDGE,to guide the construction of ICWM databases using EHRs.Methods:We developed the methodological framework through a comprehensive process,including systematic literature review,synthesis of empirical experiences,thematic expert discussions,and consultation with an external panel to reach consensus.Results:The BRIDGE framework outlines 6 core components for ICWM-EHR database development:Overall design,database architecture,data extraction and linkage,data governance,data verification,and data quality evaluation.Key data elements include variables related to study population,treatment or exposure,outcomes,and confounders.These databases support various research applications,particularly in evaluating the effectiveness and safety of integrative therapies.To demonstrate its practical value,we developed an ICWM-EHR database on women’s reproductive lifespan,encompassing 2,064,482 patients.This database captures women’s health conditions across the life course,from reproductive age to older adulthood.Conclusions:The BRIDGE methodological framework provides a standardized approach to building high-quality ICWM-EHR databases.It offers a unique opportunity to strengthen the methodological rigor and real-world relevance of Chinese medicine research in integrated healthcare settings.展开更多
The characteristic databases in China face issues such as narrow resource coverage,low levels of standardization and normalization,and limited data sharing.To address these challenges,this paper proposes the concept o...The characteristic databases in China face issues such as narrow resource coverage,low levels of standardization and normalization,and limited data sharing.To address these challenges,this paper proposes the concept of characteristic databases alliance,using marine characteristic databases as a case for feasibility analysis and discussion.The paper outlines the development path for such alliances and offers recommendations for future growth,aiming to establish a collaborative platform for the development of characteristic databases.展开更多
The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,...The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,and CNKI,as well as Library of Congress,United States.展开更多
The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,...The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,and CNKI,as well as Library of Congress,United States.展开更多
The kagome lattice,characterized by a hexagonal arrangement of corner-sharing equilateral triangles,has garnered significant attention as a fascinating quantum material system that hosts exotic magnetic and electronic...The kagome lattice,characterized by a hexagonal arrangement of corner-sharing equilateral triangles,has garnered significant attention as a fascinating quantum material system that hosts exotic magnetic and electronic properties.The identification and characterization of this class of materials are critical for advancing our understanding of their role in emergent phenomena such as superconductivity.In this study,we developed a high-throughput screening framework for the systematic identification and classification of superconducting materials with kagome lattices,integrating them into established materials databases.Leveraging the Materials Project(MP)database and the MDR Super Con dataset,we analyzed over 150000 inorganic compounds and cross-referenced 26000 known superconductors.Using geometry-based structural modeling and experimental validation,we identified 129 kagome superconductors belonging to 17 distinct structural families,many of which had not previously been recognized as kagome systems.The materials are further classified into three categories in terms of topological flat bands,clean band structures,and coexisting magnetic or charge density wave(CDW)orderings.Based on these results,we established a database comprising 129 kagome superconductors,including the detailed crystallographic,electronic,and superconducting properties of these materials.展开更多
Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throug...Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems.Mass spectrometry(MS)has emerged as a powerful platform for the annotation and discovery of NPs.MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information.Additionally,the released annotation methodologies,based on a variety of informatics tools,continuously improve the ability to annotate the structure and properties of compounds.This review examines the current mainstream databases and annotation methodologies,focusing on their advantages and limitations.Prospects for future technological advancements are then discussed in terms of novel applications and research objectives.Through a systematic overview,this review aims to provide valuable insights and a reference for MS-based NPs annotation,thereby promoting the discovery of novel natural entities.展开更多
The unique long-range disordered atomic arrangement inherent in amorphous materials endows them with a range of superior properties,rendering them highly promising for applications in catalysis,medicine,and battery te...The unique long-range disordered atomic arrangement inherent in amorphous materials endows them with a range of superior properties,rendering them highly promising for applications in catalysis,medicine,and battery technology,among other fields.Since not all materials can be synthesized into an amorphous structure,the composition design of amorphous materials holds significant importance.Machine learning offers a valuable alternative to traditional“trial-anderror”methods by predicting properties through experimental data,thus providing efficient guidance in material design.In this study,we develop a machine learning workflow to predict the critical casting diameter,glass transition temperature,and Young's modulus for 45 ternary reported amorphous alloy systems.The predicted results have been organized into a database,enabling direct retrieval of predicted values based on compositional information.Furthermore,the applications of high glass forming ability region screening for specified system,multi-property target system screening and high glass forming ability region search through iteration are also demonstrated.By utilizing machine learning predictions,researchers can effectively narrow the experimental scope and expedite the exploration of compositions.展开更多
Osmanthus fragrans Lour.is a well-known aromatic plant widely used as a food ingredient due to its unique floral fragrance and bioactive compounds.To fully utilize O.fragrans resources,we established an O.fragrans mul...Osmanthus fragrans Lour.is a well-known aromatic plant widely used as a food ingredient due to its unique floral fragrance and bioactive compounds.To fully utilize O.fragrans resources,we established an O.fragrans multi-omics database called the O.fragrans Information Resource(OfIR:http://yanglab.hzau.edu.cn/OfIR/home/).OfIR is a convenient and comprehensive multi-omics database that efficiently integrates phenotype and genetic variation from 127 O.fragrans cultivars,and provides many easy-to-use analysis tools,including primer design,sequence extraction,multi-sequence alignment,GO and KEGG enrichment analysis,variation annotation,and electronic PCR.Two case studies were used to demonstrate its power to mine candidate genetic variation sites or genes associated with specific traits or regulatory networks.In summary,the multi-omics database OfIR provides a convenient and user-friendly platform for researchers in mining functional genes and contributes to the genetic breeding of O.fragrans.展开更多
Data are the backbone of science.This paper describes the construction of a complex database for social-ecological analysis in Mongolia.Funded through the National Science Foundation(NSF)Dynamics of Coupled Natural an...Data are the backbone of science.This paper describes the construction of a complex database for social-ecological analysis in Mongolia.Funded through the National Science Foundation(NSF)Dynamics of Coupled Natural and Human(CNH)Systems program,the Mongolian Rangelands and Resilience(MOR2)project focused on Mongolian pastoral systems,community adaptive capacity,and vulnerability to climate change.We examine the development of a complex,multi-disciplinary research database of data collected over a three-year period,both in the field and from other sources.This data set captures multiple types of data:ecological,hydrological and social science surveys;remotely-sensed data,participatory mapping,local documents,and scholarly literature.The content,structure,and organization of the database,development of data protocols and issues related to data access,sharing and long-term storage are described.We conclude with recommendations for long-term data management and curation from large multidisciplinary research projects.展开更多
Research into metamorphism plays a pivotal role in reconstructing the evolution of continent,particularly through the study of ancient rocks that are highly susceptible to metamorphic alterations due to multiple tecto...Research into metamorphism plays a pivotal role in reconstructing the evolution of continent,particularly through the study of ancient rocks that are highly susceptible to metamorphic alterations due to multiple tectonic activities.In the big data era,the establishment of new data platforms and the application of big data methods have become a focus for metamorphic rocks.Significant progress has been made in creating specialized databases,compiling comprehensive datasets,and utilizing data analytics to address complex scientific questions.However,many existing databases are inadequate in meeting the specific requirements of metamorphic research,resulting from a substantial amount of valuable data remaining uncollected.Therefore,constructing new databases that can cope with the development of the data era is necessary.This article provides an extensive review of existing databases related to metamorphic rocks and discusses data-driven studies in this.Accordingly,several crucial factors that need to be taken into consideration in the establishment of specialized metamorphic databases are identified,aiming to leverage data-driven applications to achieve broader scientific objectives in metamorphic research.展开更多
AI-driven materials databases are transforming research by integrating experimental and computational data to enhance discovery and optimization.Platforms such as Digital Catalysis Platform(DigCat)and Dynamic Database...AI-driven materials databases are transforming research by integrating experimental and computational data to enhance discovery and optimization.Platforms such as Digital Catalysis Platform(DigCat)and Dynamic Database of Solid-State Electrolyte(DDSE)demonstrate how machine learning and predictive modeling can improve catalyst and solid-state electrolyte development.These databases facilitate data standardization,high-throughput screening,and cross-disciplinary collaboration,addressing key challenges in materials informatics.As AI techniques advance,materials databases are expected to play an increasingly vital role in accelerating research and innovation.展开更多
BACKGROUND For locally advanced gallbladder cancer,previous clinical studies have demon-strated that chemotherapy results in significant survival benefits when compared to surgery alone.However,data demonstrating a si...BACKGROUND For locally advanced gallbladder cancer,previous clinical studies have demon-strated that chemotherapy results in significant survival benefits when compared to surgery alone.However,data demonstrating a similar survival benefit with early-stage gallbladder cancer is limited.This study seeks to evaluate the impact chemotherapy has on survival in patients with early-stage gallbladder cancer using a large,multi-institution database.AIM To investigate the survival benefit of chemotherapy in patients with stage II gallbladder cancer.METHODS We performed a retrospective multivariable analysis of the National Cancer Database from 2010 to 2017 to evaluate the effect that chemotherapy has on the survival of patients with stage II gallbladder cancer.Our objective was to de-termine if there were any statistically significant survival differences between those who received surgery and chemotherapy vs those who only underwent surgery.RESULTS Of the 899 patients with stage II gallbladder cancer,328 patients had undergone chemotherapy and surgery.The average overall survival for those who had surgery and chemotherapy vs only surgery was 52.6 months and 51.1 months,respectively.This difference was not statistically significant(P=0.2).In the secondary analysis,the surgical group who had a liver resection had better overall survival(P<0.0001).CONCLUSION Practitioners should carefully consider chemotherapy for early-stage gallbladder cancer,as risks may outweigh survival benefits,and surgeons should also consider liver resections as part of their surgical management.展开更多
Objective:This study aimed to investigate the changes in gene expression profiles of multiple myeloma(MM)cells after bortezomib treatment by analyzing the GEO database,thereby providing a theoretical foundation for su...Objective:This study aimed to investigate the changes in gene expression profiles of multiple myeloma(MM)cells after bortezomib treatment by analyzing the GEO database,thereby providing a theoretical foundation for subsequent research on HSP70.Methods:The GSE41929 dataset was selected from the GEO database.Screening and analysis were performed to identify differentially expressed genes between bortezomib-treated and non-treated MM cells.Results:After bortezomib treatment,126 genes in MM cells showed the most significant changes in expression(P<0.05,absolute value of logFC≥1.5).Based on the fold change and the most significant gene module,HSPA1B exhibited the most notable upregulation after HMOX1,followed by HSPA6 and DNAJB1.HSPA1B and HSPA6 are members of the HSP70 protein family,while DNAJB1 primarily interacts with HSP70 to stimulate its ATPase activity and negatively regulates the transcriptional activity of HSF1 induced by heat shock.Conclusion:HSP70 was the most significantly upregulated molecule in MM cells following bortezomib stimulation.展开更多
Objective To improve the accuracy and professionalism of question-answering(QA)model in traditional Chinese medicine(TCM)lung cancer by integrating large language models with structured knowledge graphs using the know...Objective To improve the accuracy and professionalism of question-answering(QA)model in traditional Chinese medicine(TCM)lung cancer by integrating large language models with structured knowledge graphs using the knowledge graph(KG)to text-enhanced retrievalaugmented generation(KG2TRAG)method.Methods The TCM lung cancer model(TCMLCM)was constructed by fine-tuning Chat-GLM2-6B on the specialized datasets Tianchi TCM,HuangDi,and ShenNong-TCM-Dataset,as well as a TCM lung cancer KG.The KG2TRAG method was applied to enhance the knowledge retrieval,which can convert KG triples into natural language text via ChatGPT-aided linearization,leveraging large language models(LLMs)for context-aware reasoning.For a comprehensive comparison,MedicalGPT,HuatuoGPT,and BenTsao were selected as the baseline models.Performance was evaluated using bilingual evaluation understudy(BLEU),recall-oriented understudy for gisting evaluation(ROUGE),accuracy,and the domain-specific TCM-LCEval metrics,with validation from TCM oncology experts assessing answer accuracy,professionalism,and usability.Results The TCMLCM model achieved the optimal performance across all metrics,including a BLEU score of 32.15%,ROUGE-L of 59.08%,and an accuracy rate of 79.68%.Notably,in the TCM-LCEval assessment specific to the field of TCM,its performance was 3%−12%higher than that of the baseline model.Expert evaluations highlighted superior performance in accuracy and professionalism.Conclusion TCMLCM can provide an innovative solution for TCM lung cancer QA,demonstrating the feasibility of integrating structured KGs with LLMs.This work advances intelligent TCM healthcare tools and lays a foundation for future AI-driven applications in traditional medicine.展开更多
In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics.Similarities and variations of components present significant analytical challenges.A two-dimensional(2...In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics.Similarities and variations of components present significant analytical challenges.A two-dimensional(2D)liquid chromatography-mass spectrometry(LC-MS)method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium(CMS).A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated.For efficient and high-accuracy screening of CMS,a targeted method based on a self-constructed high resolution(HR)mass spectrum database of CMS components was established.The database was built based on the commercial MassHunter Personal Compound Database and Library(PCDL)software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening.On this basis,the unknown peaks in the CMS chromatograms were deduced and assigned.The molecular formula,group composition,and origins of a total of 99 compounds,of which the combined area percentage accounted for more than 95%of CMS components,were deduced by this 2D-LC-MS method combined with the MassHunter PCDL.This profiling method was highly efficient and could distinguish hundreds of components within 3 h,providing reliable results for quality control of this kind of complex drugs.展开更多
Background:Exercise induces molecular changes that involve multiple organs and tissues.Moreover,these changes are modulated by various exercise parameters—such as intensity,frequency,mode,and duration—as well as by ...Background:Exercise induces molecular changes that involve multiple organs and tissues.Moreover,these changes are modulated by various exercise parameters—such as intensity,frequency,mode,and duration—as well as by clinical features like gender,age,and body mass index(BMI),each eliciting distinct biological effects.To assist exercise researchers in understanding these changes from a comprehensive perspective that includes multiple organs,diverse exercise regimens,and a range of clinical features,we developed Exercise Regulated Genes Database(ExerGeneDB),a database of exercise-regulated differential genes.Methods:ExerGeneDB aggregated publicly available exercise-related sequencing datasets and subjected them to uniform quality control and preprocessing.The data,encompassing a variety of types,were organized into a specialized database of exercise-regulated genes.Notably,Exer-GeneDB conducted differential analyses on this collected data,leveraging curated clinical information and accounting for important factors such as gender,age,and BMI.Results:ExerGeneDB has assembled 1692 samples from rats and mice as well as 4492 human samples.It contains data from various tissues and organs,such as skeletal muscle,blood,adipose tissue,intestine,heart,liver,spleen,lungs,kidneys,brain,spinal cord,bone marrow,and bones.ExerGeneDB features bulk ribonucleic acid sequencing(RNA-seq)(including non-coding RNA(ncRNA)and protein-coding RNA),microarray(including ncRNA and protein-coding RNA),and single cell RNA-seq data.Conclusion:ExerGeneDB compiles and re-analyzes exercise-related data with a focus on clinical information.This has culminated in the crea-tion of an interactive database for exercise regulation genes.The website for ExerGeneDB can be found at:https://exergenedb.com.展开更多
This paper analyzes the text of 3261 clauses of 20 RTAs signed by China,classifies them into 52 policy areas according to the international mainstream HMS method,and assigns them through coding.The clause depth of Ch...This paper analyzes the text of 3261 clauses of 20 RTAs signed by China,classifies them into 52 policy areas according to the international mainstream HMS method,and assigns them through coding.The clause depth of China’s RTAs is measured across three-dimensional systems(policy areas,clauses,and core clauses)and two generations of trade policy areas(WTO+,WTO-X,and all policy areas).It is observed that China’s RTAs exhibit greater depth in Industrial Products,Agricultural Products,TBT,Antidumping,Countervailing,and Investment,while showing comparatively less depth in Fiscal Policy,Innovation Policies,and related areas.展开更多
基金Supported by the Appropriate Technology Promotion Program in Chongqing,No.2023jstg005.
文摘BACKGROUND Ampullary adenocarcinoma is a rare malignant tumor of the gastrointestinal tract.Currently,only a few cases have been reported,resulting in limited information on survival.AIM To develop a dynamic nomogram using internal and external validation to predict survival in patients with ampullary adenocarcinoma.METHODS Data were sourced from the surveillance,epidemiology,and end results stat database.The patients in the database were randomized in a 7:3 ratio into training and validation groups.Using Cox regression univariate and multivariate analyses in the training group,we identified independent risk factors for overall survival and cancer-specific survival to develop the nomogram.The nomogram was validated with a cohort of patients from the First Affiliated Hospital of the Army Medical University.RESULTS For overall and cancer-specific survival,12(sex,age,race,lymph node ratio,tumor size,chemotherapy,surgical modality,T stage,tumor differentiation,brain metastasis,lung metastasis,and extension)and 6(age;surveillance,epidemiology,and end results stage;lymph node ratio;chemotherapy;surgical modality;and tumor differentiation)independent risk factors,respectively,were incorporated into the nomogram.The area under the curve values at 1,3,and 5 years,respectively,were 0.807,0.842,and 0.826 for overall survival and 0.816,0.835,and 0.841 for cancer-specific survival.The internal and external validation cohorts indicated good consistency of the nomogram.CONCLUSION The dynamic nomogram offers robust predictive efficacy for the overall and cancer-specific survival of ampullary adenocarcinoma.
文摘A distinctive feature of scholarly communities today is exploring topics and concepts in interdisciplinary and international contexts. This observation is increasingly apparent and visible in advancing our thinking and policies related to human/environmental worlds at local, regional, and global scales. Maps are an important part of these innovative and ongoing research approaches. In this context, we consider urban forests a topic meriting more attention of scholars studying the geographic and environmental intersections of the natural sciences with the social sciences and humanities. We construct two innovative knowledge bases, one a conceptual framework based on major themes and concepts related to mapping urban forests using key words of the first 100 results of a Google Scholar query and a second using the number of Google Scholar hyperlinks about mapping urban forests in 244 capital cities. We discovered that the constructed world maps reveal vast global unevenness in our knowledge about urban forests in hyperlink numbers and ratios, results that merit further attention by disciplinary, international and interdisciplinary scholarly communities.
基金supported by the National Key Research&Development Program of China(No.2024YFC3505800)the National Natural Science Foundation of China(Nos.82474334,82474335 and 72174132)+3 种基金National Science Fund for Distinguished Young Scholars(No.82225049)the Key Research&Development Projects of Sichuan Provincial Department of Science and Technology(Nos.2024YFFK0174 and 2024YFFK0152)1.3.5 Project for Disciplines of Excellence,West China Hospital,Sichuan University(Nos.ZYYC24010 and ZYGD23004)the Special Fund for Traditional Chinese Medicine of Sichuan Provincial Administration of Traditional Chinese Medicine(No.2024zd023).
文摘Objectives:Electronic health records(EHRs)offer valuable real-world data(RWD)for Chinese medicine research.However,significant methodological challenges remain in developing integrative Chinese-Western medicine(ICWM)databases.This study aims to establish a best-practice methodological framework,referred to as BRIDGE,to guide the construction of ICWM databases using EHRs.Methods:We developed the methodological framework through a comprehensive process,including systematic literature review,synthesis of empirical experiences,thematic expert discussions,and consultation with an external panel to reach consensus.Results:The BRIDGE framework outlines 6 core components for ICWM-EHR database development:Overall design,database architecture,data extraction and linkage,data governance,data verification,and data quality evaluation.Key data elements include variables related to study population,treatment or exposure,outcomes,and confounders.These databases support various research applications,particularly in evaluating the effectiveness and safety of integrative therapies.To demonstrate its practical value,we developed an ICWM-EHR database on women’s reproductive lifespan,encompassing 2,064,482 patients.This database captures women’s health conditions across the life course,from reproductive age to older adulthood.Conclusions:The BRIDGE methodological framework provides a standardized approach to building high-quality ICWM-EHR databases.It offers a unique opportunity to strengthen the methodological rigor and real-world relevance of Chinese medicine research in integrated healthcare settings.
文摘The characteristic databases in China face issues such as narrow resource coverage,low levels of standardization and normalization,and limited data sharing.To address these challenges,this paper proposes the concept of characteristic databases alliance,using marine characteristic databases as a case for feasibility analysis and discussion.The paper outlines the development path for such alliances and offers recommendations for future growth,aiming to establish a collaborative platform for the development of characteristic databases.
文摘The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,and CNKI,as well as Library of Congress,United States.
文摘The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,and CNKI,as well as Library of Congress,United States.
基金supported by the National Key Research and Development Program of China(Grant No.2018YFE0202600)the National Natural Science Foundation of China(Grant No.52272268)+3 种基金the Key Research Program of Frontier SciencesCAS(Grant No.QYZDJ-SSWSLH013)the Informatization Plan of Chinese Academy of Sciences(Grant No.CAS-WX2021SF-0102)the Youth Innovation Promotion Association of CAS(Grant No.2019005)。
文摘The kagome lattice,characterized by a hexagonal arrangement of corner-sharing equilateral triangles,has garnered significant attention as a fascinating quantum material system that hosts exotic magnetic and electronic properties.The identification and characterization of this class of materials are critical for advancing our understanding of their role in emergent phenomena such as superconductivity.In this study,we developed a high-throughput screening framework for the systematic identification and classification of superconducting materials with kagome lattices,integrating them into established materials databases.Leveraging the Materials Project(MP)database and the MDR Super Con dataset,we analyzed over 150000 inorganic compounds and cross-referenced 26000 known superconductors.Using geometry-based structural modeling and experimental validation,we identified 129 kagome superconductors belonging to 17 distinct structural families,many of which had not previously been recognized as kagome systems.The materials are further classified into three categories in terms of topological flat bands,clean band structures,and coexisting magnetic or charge density wave(CDW)orderings.Based on these results,we established a database comprising 129 kagome superconductors,including the detailed crystallographic,electronic,and superconducting properties of these materials.
基金supported by the National Natural Science Foundation of China(Nos.82274064,82374026,and 82204591)。
文摘Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems.Mass spectrometry(MS)has emerged as a powerful platform for the annotation and discovery of NPs.MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information.Additionally,the released annotation methodologies,based on a variety of informatics tools,continuously improve the ability to annotate the structure and properties of compounds.This review examines the current mainstream databases and annotation methodologies,focusing on their advantages and limitations.Prospects for future technological advancements are then discussed in terms of novel applications and research objectives.Through a systematic overview,this review aims to provide valuable insights and a reference for MS-based NPs annotation,thereby promoting the discovery of novel natural entities.
基金Project supported by funding from the National Natural Science Foundation of China(Grant Nos.52172258,52473227 and 52171150)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB0500200)。
文摘The unique long-range disordered atomic arrangement inherent in amorphous materials endows them with a range of superior properties,rendering them highly promising for applications in catalysis,medicine,and battery technology,among other fields.Since not all materials can be synthesized into an amorphous structure,the composition design of amorphous materials holds significant importance.Machine learning offers a valuable alternative to traditional“trial-anderror”methods by predicting properties through experimental data,thus providing efficient guidance in material design.In this study,we develop a machine learning workflow to predict the critical casting diameter,glass transition temperature,and Young's modulus for 45 ternary reported amorphous alloy systems.The predicted results have been organized into a database,enabling direct retrieval of predicted values based on compositional information.Furthermore,the applications of high glass forming ability region screening for specified system,multi-property target system screening and high glass forming ability region search through iteration are also demonstrated.By utilizing machine learning predictions,researchers can effectively narrow the experimental scope and expedite the exploration of compositions.
基金supported by research grants provided by the National Natural Science Foundation of China(Grant Nos.32101581,32271951,and 32372754)the Hubei Provincial Central Leading Local Special Project(Grant No.2022BGE263)+3 种基金the Key Research and Science and Technology Program of Hubei Province(Grant No.2021BBA098)the Hubei Province Natural Science Foundation(Grant Nos.2023AFB1063 and 2024AFB1057)the Innovation Team Project from Hubei University of Science and Technology(Grant No.2022T02)a PhD grant from the Hubei University of Science and Technology(Grant Nos.BK202002and BK202419).
文摘Osmanthus fragrans Lour.is a well-known aromatic plant widely used as a food ingredient due to its unique floral fragrance and bioactive compounds.To fully utilize O.fragrans resources,we established an O.fragrans multi-omics database called the O.fragrans Information Resource(OfIR:http://yanglab.hzau.edu.cn/OfIR/home/).OfIR is a convenient and comprehensive multi-omics database that efficiently integrates phenotype and genetic variation from 127 O.fragrans cultivars,and provides many easy-to-use analysis tools,including primer design,sequence extraction,multi-sequence alignment,GO and KEGG enrichment analysis,variation annotation,and electronic PCR.Two case studies were used to demonstrate its power to mine candidate genetic variation sites or genes associated with specific traits or regulatory networks.In summary,the multi-omics database OfIR provides a convenient and user-friendly platform for researchers in mining functional genes and contributes to the genetic breeding of O.fragrans.
基金supported by funds form the NSF Dynamics of Coupled and Human Systems(CNH)Program award BCS-1011801,The World Bank,USAID,American Association of University Women,Open Society Institute,Center for Collaborative Conservation,Colorado State University.
文摘Data are the backbone of science.This paper describes the construction of a complex database for social-ecological analysis in Mongolia.Funded through the National Science Foundation(NSF)Dynamics of Coupled Natural and Human(CNH)Systems program,the Mongolian Rangelands and Resilience(MOR2)project focused on Mongolian pastoral systems,community adaptive capacity,and vulnerability to climate change.We examine the development of a complex,multi-disciplinary research database of data collected over a three-year period,both in the field and from other sources.This data set captures multiple types of data:ecological,hydrological and social science surveys;remotely-sensed data,participatory mapping,local documents,and scholarly literature.The content,structure,and organization of the database,development of data protocols and issues related to data access,sharing and long-term storage are described.We conclude with recommendations for long-term data management and curation from large multidisciplinary research projects.
基金funded by the National Natural Science Foundation of China(No.42220104008)。
文摘Research into metamorphism plays a pivotal role in reconstructing the evolution of continent,particularly through the study of ancient rocks that are highly susceptible to metamorphic alterations due to multiple tectonic activities.In the big data era,the establishment of new data platforms and the application of big data methods have become a focus for metamorphic rocks.Significant progress has been made in creating specialized databases,compiling comprehensive datasets,and utilizing data analytics to address complex scientific questions.However,many existing databases are inadequate in meeting the specific requirements of metamorphic research,resulting from a substantial amount of valuable data remaining uncollected.Therefore,constructing new databases that can cope with the development of the data era is necessary.This article provides an extensive review of existing databases related to metamorphic rocks and discusses data-driven studies in this.Accordingly,several crucial factors that need to be taken into consideration in the establishment of specialized metamorphic databases are identified,aiming to leverage data-driven applications to achieve broader scientific objectives in metamorphic research.
文摘AI-driven materials databases are transforming research by integrating experimental and computational data to enhance discovery and optimization.Platforms such as Digital Catalysis Platform(DigCat)and Dynamic Database of Solid-State Electrolyte(DDSE)demonstrate how machine learning and predictive modeling can improve catalyst and solid-state electrolyte development.These databases facilitate data standardization,high-throughput screening,and cross-disciplinary collaboration,addressing key challenges in materials informatics.As AI techniques advance,materials databases are expected to play an increasingly vital role in accelerating research and innovation.
文摘BACKGROUND For locally advanced gallbladder cancer,previous clinical studies have demon-strated that chemotherapy results in significant survival benefits when compared to surgery alone.However,data demonstrating a similar survival benefit with early-stage gallbladder cancer is limited.This study seeks to evaluate the impact chemotherapy has on survival in patients with early-stage gallbladder cancer using a large,multi-institution database.AIM To investigate the survival benefit of chemotherapy in patients with stage II gallbladder cancer.METHODS We performed a retrospective multivariable analysis of the National Cancer Database from 2010 to 2017 to evaluate the effect that chemotherapy has on the survival of patients with stage II gallbladder cancer.Our objective was to de-termine if there were any statistically significant survival differences between those who received surgery and chemotherapy vs those who only underwent surgery.RESULTS Of the 899 patients with stage II gallbladder cancer,328 patients had undergone chemotherapy and surgery.The average overall survival for those who had surgery and chemotherapy vs only surgery was 52.6 months and 51.1 months,respectively.This difference was not statistically significant(P=0.2).In the secondary analysis,the surgical group who had a liver resection had better overall survival(P<0.0001).CONCLUSION Practitioners should carefully consider chemotherapy for early-stage gallbladder cancer,as risks may outweigh survival benefits,and surgeons should also consider liver resections as part of their surgical management.
基金The Innovation Capability Support Program for Medical Research Projects of Xi’an Science and Technology Bureau(23YXYJ0123)The Hospital Level Fund of the First Affiliated Hospital of Xi’an Medical University(XYYFY-2023-08)。
文摘Objective:This study aimed to investigate the changes in gene expression profiles of multiple myeloma(MM)cells after bortezomib treatment by analyzing the GEO database,thereby providing a theoretical foundation for subsequent research on HSP70.Methods:The GSE41929 dataset was selected from the GEO database.Screening and analysis were performed to identify differentially expressed genes between bortezomib-treated and non-treated MM cells.Results:After bortezomib treatment,126 genes in MM cells showed the most significant changes in expression(P<0.05,absolute value of logFC≥1.5).Based on the fold change and the most significant gene module,HSPA1B exhibited the most notable upregulation after HMOX1,followed by HSPA6 and DNAJB1.HSPA1B and HSPA6 are members of the HSP70 protein family,while DNAJB1 primarily interacts with HSP70 to stimulate its ATPase activity and negatively regulates the transcriptional activity of HSF1 induced by heat shock.Conclusion:HSP70 was the most significantly upregulated molecule in MM cells following bortezomib stimulation.
基金Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_2145).
文摘Objective To improve the accuracy and professionalism of question-answering(QA)model in traditional Chinese medicine(TCM)lung cancer by integrating large language models with structured knowledge graphs using the knowledge graph(KG)to text-enhanced retrievalaugmented generation(KG2TRAG)method.Methods The TCM lung cancer model(TCMLCM)was constructed by fine-tuning Chat-GLM2-6B on the specialized datasets Tianchi TCM,HuangDi,and ShenNong-TCM-Dataset,as well as a TCM lung cancer KG.The KG2TRAG method was applied to enhance the knowledge retrieval,which can convert KG triples into natural language text via ChatGPT-aided linearization,leveraging large language models(LLMs)for context-aware reasoning.For a comprehensive comparison,MedicalGPT,HuatuoGPT,and BenTsao were selected as the baseline models.Performance was evaluated using bilingual evaluation understudy(BLEU),recall-oriented understudy for gisting evaluation(ROUGE),accuracy,and the domain-specific TCM-LCEval metrics,with validation from TCM oncology experts assessing answer accuracy,professionalism,and usability.Results The TCMLCM model achieved the optimal performance across all metrics,including a BLEU score of 32.15%,ROUGE-L of 59.08%,and an accuracy rate of 79.68%.Notably,in the TCM-LCEval assessment specific to the field of TCM,its performance was 3%−12%higher than that of the baseline model.Expert evaluations highlighted superior performance in accuracy and professionalism.Conclusion TCMLCM can provide an innovative solution for TCM lung cancer QA,demonstrating the feasibility of integrating structured KGs with LLMs.This work advances intelligent TCM healthcare tools and lays a foundation for future AI-driven applications in traditional medicine.
基金support from the Science Research Program Project for Drug Regulation,Jiangsu Medical Products Administration,China(Grant No.:202207)the National Drug Standards Revision Project,China(Grant No.:2023Y41)+1 种基金the National Natural Science Foundation of China(Grant No.:22276080)the Foreign Expert Project,China(Grant No.:G2022014096L).
文摘In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics.Similarities and variations of components present significant analytical challenges.A two-dimensional(2D)liquid chromatography-mass spectrometry(LC-MS)method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium(CMS).A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated.For efficient and high-accuracy screening of CMS,a targeted method based on a self-constructed high resolution(HR)mass spectrum database of CMS components was established.The database was built based on the commercial MassHunter Personal Compound Database and Library(PCDL)software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening.On this basis,the unknown peaks in the CMS chromatograms were deduced and assigned.The molecular formula,group composition,and origins of a total of 99 compounds,of which the combined area percentage accounted for more than 95%of CMS components,were deduced by this 2D-LC-MS method combined with the MassHunter PCDL.This profiling method was highly efficient and could distinguish hundreds of components within 3 h,providing reliable results for quality control of this kind of complex drugs.
基金supported by grants from the National Natural Science Foundation of China(82225005, 82020108002 to JX,82200321 to QZ)Science and Technology Commission of ShanghaiMunicipality(23410750100,20DZ2255400,, 21XD1421300 to JX)+1 种基金the“Dawn”Program of Shanghai Educa-tion Commission(19SG34 to JX)Shanghai Sailing Program(21YF1413200 to QZ).
文摘Background:Exercise induces molecular changes that involve multiple organs and tissues.Moreover,these changes are modulated by various exercise parameters—such as intensity,frequency,mode,and duration—as well as by clinical features like gender,age,and body mass index(BMI),each eliciting distinct biological effects.To assist exercise researchers in understanding these changes from a comprehensive perspective that includes multiple organs,diverse exercise regimens,and a range of clinical features,we developed Exercise Regulated Genes Database(ExerGeneDB),a database of exercise-regulated differential genes.Methods:ExerGeneDB aggregated publicly available exercise-related sequencing datasets and subjected them to uniform quality control and preprocessing.The data,encompassing a variety of types,were organized into a specialized database of exercise-regulated genes.Notably,Exer-GeneDB conducted differential analyses on this collected data,leveraging curated clinical information and accounting for important factors such as gender,age,and BMI.Results:ExerGeneDB has assembled 1692 samples from rats and mice as well as 4492 human samples.It contains data from various tissues and organs,such as skeletal muscle,blood,adipose tissue,intestine,heart,liver,spleen,lungs,kidneys,brain,spinal cord,bone marrow,and bones.ExerGeneDB features bulk ribonucleic acid sequencing(RNA-seq)(including non-coding RNA(ncRNA)and protein-coding RNA),microarray(including ncRNA and protein-coding RNA),and single cell RNA-seq data.Conclusion:ExerGeneDB compiles and re-analyzes exercise-related data with a focus on clinical information.This has culminated in the crea-tion of an interactive database for exercise regulation genes.The website for ExerGeneDB can be found at:https://exergenedb.com.
基金General Project of Beijing Social Science Foundation,“Research on the Internal and External Strategic Alignment of Regional Trade Agreements and the High-Quality Construction of China(Beijing)Pilot Free Trade Zone”(Project No.:21GLB021)。
文摘This paper analyzes the text of 3261 clauses of 20 RTAs signed by China,classifies them into 52 policy areas according to the international mainstream HMS method,and assigns them through coding.The clause depth of China’s RTAs is measured across three-dimensional systems(policy areas,clauses,and core clauses)and two generations of trade policy areas(WTO+,WTO-X,and all policy areas).It is observed that China’s RTAs exhibit greater depth in Industrial Products,Agricultural Products,TBT,Antidumping,Countervailing,and Investment,while showing comparatively less depth in Fiscal Policy,Innovation Policies,and related areas.
