Pulsar polarization profiles form a very basic database for understanding the emission processes in a pulsar magnetosphere.After careful polarization calibration of the 19-beam L-band receiver and verification of beam...Pulsar polarization profiles form a very basic database for understanding the emission processes in a pulsar magnetosphere.After careful polarization calibration of the 19-beam L-band receiver and verification of beamoffset observation results,we obtain polarization profiles of 682 pulsars from observations by the Five-hundredmeter Aperture Spherical radio Telescope(FAST)duringthe Galactic Plane Pulsar Snapshot survey and other normal FAST projects.Among them,polarization profiles of about 460 pulsars are observed for the first time.The profiles exhibit diverse features.Some pulsars have a polarization position angle curve with a good S-shaped swing,some with orthogonal modes;some have components with highly linearly polarized components or strong circularly polarized components;some have a very wide profile,coming from an aligned rotator,and some have an interpulse from a perpendicular rotator;some wide profiles are caused by interstellar scattering.We derive geometric parameters for 190 pulsars from the S-shaped position angle curves or with orthogonal modes.We find that the linear and circular polarization or the widths of pulse profiles have various frequency dependencies.Pulsars with a large fraction of linear polarization are more likely to have a large Edot.展开更多
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
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
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
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
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
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
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
Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-pr...Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-property labels,and limited accessibility,hindering system-atic modeling across property prediction tasks.Here,we present OpenPoly,a curated experimental polymer database derived from extensive lit-erature mining and manual validation,comprising 3985 unique polymer-property data points spanning 26 key properties.We further develop a multi-task benchmarking framework that evaluates property prediction using four encoding methods and eight representative models.Our re-sults highlight that the optimized degree-of-polymerization encoding coupled with Morgan fingerprints achieves an optimal trade-off between computational cost and accuracy.In data-scarce condition,XGBoost outperforms deep learning models on key properties such as dielectric con-stant,glass transition temperature,melting point,and mechanical strength,achieving R2 scores of 0.65-0.87.To further showcase the practical utility of the database,we propose potential polymers for two energy-relevant applications:high temperature polymer dielectrics and fuel cell membranes.By offering a consistent and accessible benchmark and database,OpenPoly paves the way for more accurate polymer-property modeling and fosters data-driven advances in polymer genome engineering.展开更多
A strategy combining a tailored database and high-throughput activity screening that discover bioactive metabolites derived from Magnoliae Officinalis Cortex(MOC)was developed and implemented to rapidly profile and di...A strategy combining a tailored database and high-throughput activity screening that discover bioactive metabolites derived from Magnoliae Officinalis Cortex(MOC)was developed and implemented to rapidly profile and discover bioactive metabolites in vivo derived from traditional Chinese medicine(TCM).The strategy possessed four characteristics:1)The tailored database consisted of metabolites derived from big data-originated reference compound,metabolites predicted in silico,and MOC chemical profile-based pseudomolecular ions.2)When profiling MOC-derived metabolites in vivo,attentions were paid not only to prototypes of MOC compounds and metabolites directly derived from MOC compounds,as reported by most papers,but also to isomerized metabolites and the degradation products of MOC compounds as well as their derived metabolites.3)Metabolite traceability was performed,especially to distinguish isomeric prototypes-derived metabolites,prototypes of MOC compounds as well as phase I metabolites derived from other MOC compounds.4)Molecular docking was utilized for high-throughput activity screening and molecular dynamic simulation as well as zebrafish model were used for verification.Using this strategy,134 metabolites were swiftly characterized after the oral administration of MOC to rats,and several metabolites were reported for the first time.Furthermore,17 potential active metabolites were discovered by targeting the motilin,dopamine D2,and the serotonin type 4(5-HT4)receptors,and part bioactivities were verified using molecular dynamic simulation and a zebrafish constipation model.This study extends the application of mass spectrometry(MS)to rapidly profile TCM-derived metabolites in vivo,which will help pharmacologists rapidly discover potent metabolites from a complex matrix.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
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
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
The National Strong-Motion Observation Network System of China has collected over 12 000 strong-motion recordings from 2007 to December 2020.This study assembled the source-related metadata of 1 920 earthquakes associ...The National Strong-Motion Observation Network System of China has collected over 12 000 strong-motion recordings from 2007 to December 2020.This study assembled the source-related metadata of 1 920 earthquakes associated with assembled well-processed recordings of China.The earthquake basic information,focal mechanisms,and the fault geometry were collected from various institutes and literature.We recommended the MWvalues for 900 earthquakes,the fault types for 1 064 earthquakes,and the fault geometries for 18 large earthquakes.We also performed the statistical analysis for establishing the empirical conversions of MW-MS,and ML,and providing the empirical relationships between MWand ruptured area,aspect ratio,respectively.Moreover,the ruptured fault geometries of large earthquakes were used to preliminarily divide all earthquakes considered into 1 141 mainshocks,and 779 aftershocks.The finite-fault distances(RJBand Rrup) of strong-motion recordings from the 18 large earthquakes were calculated,and then used to yield the statistic relationships between the point-source distances(Repiand Rhyp) and finite-fault distances.We finally provided the earthquake source database freely accessible at website.The source-related metadata can be directly applied to develop the ground motion prediction equations of China.展开更多
The analysis of ancient genomics provides opportunities to explore human population history across both temporal and geographic dimensions(Haak et al.,2015;Wang et al.,2021,2024)to enhance the accessibility and utilit...The analysis of ancient genomics provides opportunities to explore human population history across both temporal and geographic dimensions(Haak et al.,2015;Wang et al.,2021,2024)to enhance the accessibility and utility of these ancient genomic datasets,a range of databases and advanced statistical models have been developed,including the Allen Ancient DNA Resource(AADR)(Mallick et al.,2024)and AdmixTools(Patterson et al.,2012).While upstream processes such as sequencing and raw data processing have been streamlined by resources like the AADR,the downstream analysis of these datasets-encompassing population genetics inference and spatiotemporal interpretation-remains a significant challenge.The AADR provides a unified collection of published ancient DNA(aDNA)data,yet its file-based format and reliance on command-line tools,such as those in Admix-Tools(Patterson et al.,2012),require advanced computational expertise for effective exploration and analysis.These requirements can present significant challenges forresearchers lackingadvanced computational expertise,limiting the accessibility and broader application of these valuable genomic resources.展开更多
Background:To investigate adverse event(AE)signals associated with six proton pump inhibitors(PPIs),enhance drug labeling information,and provide guidance for their safe clinical use.Methods:Adverse reaction data for ...Background:To investigate adverse event(AE)signals associated with six proton pump inhibitors(PPIs),enhance drug labeling information,and provide guidance for their safe clinical use.Methods:Adverse reaction data for musculoskeletal and connective tissue disorders related to six PPI formulations—omeprazole,pantoprazole,lansoprazole,esomeprazole,rabeprazole,and dexlansoprazole—from Q12004 to Q42023 were collected from the FDA Adverse Event Reporting System(FAERS).Signal detection was performed using the Reporting Odds Ratio(ROR),Proportional Reporting Ratio(PRR),Bayesian Confidence Propagation Neural Network(BCPNN),and Empirical Bayesian Geometric Mean(EBGM).Data processing and statistical analysis were conducted using R Studio 4.40.Results:A total of 6,635,3,853,1,792,15,731,483,and 534 adverse events were identified for the six PPIs,respectively.The four algorithms(ROR,PRR,BCPNN,and EBGM)generated 17,19,8,27,5,and 2 positive signals.Notably,signals for renal osteodystrophy and osteoporosis were more frequent,with stronger signals for lumbar flexion syndrome and renal osteodystrophy.Conclusion:Patients with chronic kidney disease,a high risk of osteoporosis and fractures,or those using statins should select PPIs with a lower risk of adverse musculoskeletal and connective tissue reactions to minimize these adverse effects and ensure standardized clinical use of PPIs.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
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
基金supported by the National Natural Science Foundation of China(NSFC,grant Nos.11988101 and 11833009),supported by the National Natural Science Foundation of China(NSFC,grant No.U2031115)supported by the National Key R&D Program of China(No.2021YFA1600401 and 2021YFA1600400)+1 种基金National Natural Science Foundation of China(NSFC,grant Nos.11873058 and 12133004)the National SKA program of China(No.2020SKA0120200)。
文摘Pulsar polarization profiles form a very basic database for understanding the emission processes in a pulsar magnetosphere.After careful polarization calibration of the 19-beam L-band receiver and verification of beamoffset observation results,we obtain polarization profiles of 682 pulsars from observations by the Five-hundredmeter Aperture Spherical radio Telescope(FAST)duringthe Galactic Plane Pulsar Snapshot survey and other normal FAST projects.Among them,polarization profiles of about 460 pulsars are observed for the first time.The profiles exhibit diverse features.Some pulsars have a polarization position angle curve with a good S-shaped swing,some with orthogonal modes;some have components with highly linearly polarized components or strong circularly polarized components;some have a very wide profile,coming from an aligned rotator,and some have an interpulse from a perpendicular rotator;some wide profiles are caused by interstellar scattering.We derive geometric parameters for 190 pulsars from the S-shaped position angle curves or with orthogonal modes.We find that the linear and circular polarization or the widths of pulse profiles have various frequency dependencies.Pulsars with a large fraction of linear polarization are more likely to have a large Edot.
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.
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.
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financially supported by the National Natural Science Foundation of China (Nos. 92372126,52373203)the Excellent Young Scientists Fund Program
文摘Advancing the integration of artificial intelligence and polymer science requires high-quality,open-source,and large-scale datasets.However,existing polymer databases often suffer from data sparsity,lack of polymer-property labels,and limited accessibility,hindering system-atic modeling across property prediction tasks.Here,we present OpenPoly,a curated experimental polymer database derived from extensive lit-erature mining and manual validation,comprising 3985 unique polymer-property data points spanning 26 key properties.We further develop a multi-task benchmarking framework that evaluates property prediction using four encoding methods and eight representative models.Our re-sults highlight that the optimized degree-of-polymerization encoding coupled with Morgan fingerprints achieves an optimal trade-off between computational cost and accuracy.In data-scarce condition,XGBoost outperforms deep learning models on key properties such as dielectric con-stant,glass transition temperature,melting point,and mechanical strength,achieving R2 scores of 0.65-0.87.To further showcase the practical utility of the database,we propose potential polymers for two energy-relevant applications:high temperature polymer dielectrics and fuel cell membranes.By offering a consistent and accessible benchmark and database,OpenPoly paves the way for more accurate polymer-property modeling and fosters data-driven advances in polymer genome engineering.
基金supported by the Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences,China(Grant Nos.:CI2023E002 and CI2021A04513)the National Natural Science Foundation of China(Grant Nos.:82204619 and 82274094)the Fundamental Research Funds for the Central Public Welfare Research Institutes,China(Grant Nos.:ZZ15-YQ-067 and ZZ16-ND-10-26).
文摘A strategy combining a tailored database and high-throughput activity screening that discover bioactive metabolites derived from Magnoliae Officinalis Cortex(MOC)was developed and implemented to rapidly profile and discover bioactive metabolites in vivo derived from traditional Chinese medicine(TCM).The strategy possessed four characteristics:1)The tailored database consisted of metabolites derived from big data-originated reference compound,metabolites predicted in silico,and MOC chemical profile-based pseudomolecular ions.2)When profiling MOC-derived metabolites in vivo,attentions were paid not only to prototypes of MOC compounds and metabolites directly derived from MOC compounds,as reported by most papers,but also to isomerized metabolites and the degradation products of MOC compounds as well as their derived metabolites.3)Metabolite traceability was performed,especially to distinguish isomeric prototypes-derived metabolites,prototypes of MOC compounds as well as phase I metabolites derived from other MOC compounds.4)Molecular docking was utilized for high-throughput activity screening and molecular dynamic simulation as well as zebrafish model were used for verification.Using this strategy,134 metabolites were swiftly characterized after the oral administration of MOC to rats,and several metabolites were reported for the first time.Furthermore,17 potential active metabolites were discovered by targeting the motilin,dopamine D2,and the serotonin type 4(5-HT4)receptors,and part bioactivities were verified using molecular dynamic simulation and a zebrafish constipation model.This study extends the application of mass spectrometry(MS)to rapidly profile TCM-derived metabolites in vivo,which will help pharmacologists rapidly discover potent metabolites from a complex matrix.
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.
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.
基金supported by the National Key R&D Program of China(Grant No.2019YFE0115700).
文摘The National Strong-Motion Observation Network System of China has collected over 12 000 strong-motion recordings from 2007 to December 2020.This study assembled the source-related metadata of 1 920 earthquakes associated with assembled well-processed recordings of China.The earthquake basic information,focal mechanisms,and the fault geometry were collected from various institutes and literature.We recommended the MWvalues for 900 earthquakes,the fault types for 1 064 earthquakes,and the fault geometries for 18 large earthquakes.We also performed the statistical analysis for establishing the empirical conversions of MW-MS,and ML,and providing the empirical relationships between MWand ruptured area,aspect ratio,respectively.Moreover,the ruptured fault geometries of large earthquakes were used to preliminarily divide all earthquakes considered into 1 141 mainshocks,and 779 aftershocks.The finite-fault distances(RJBand Rrup) of strong-motion recordings from the 18 large earthquakes were calculated,and then used to yield the statistic relationships between the point-source distances(Repiand Rhyp) and finite-fault distances.We finally provided the earthquake source database freely accessible at website.The source-related metadata can be directly applied to develop the ground motion prediction equations of China.
基金by the National Key Research and Development Program of China(2023YFC3303701-02 and 2024YFC3306701)the National Natural Science Foundation of China(T2425014 and 32270667)+3 种基金the Natural Science Foundation of Fujian Province of China(2023J06013)the Major Project of the National Social Science Foundation of China granted to Chuan-Chao Wang(21&ZD285)Open Research Fund of State Key Laboratory of Genetic Engineering at Fudan University(SKLGE-2310)Open Research Fund of Forensic Genetics Key Laboratory of the Ministry of Public Security(2023FGKFKT07).
文摘The analysis of ancient genomics provides opportunities to explore human population history across both temporal and geographic dimensions(Haak et al.,2015;Wang et al.,2021,2024)to enhance the accessibility and utility of these ancient genomic datasets,a range of databases and advanced statistical models have been developed,including the Allen Ancient DNA Resource(AADR)(Mallick et al.,2024)and AdmixTools(Patterson et al.,2012).While upstream processes such as sequencing and raw data processing have been streamlined by resources like the AADR,the downstream analysis of these datasets-encompassing population genetics inference and spatiotemporal interpretation-remains a significant challenge.The AADR provides a unified collection of published ancient DNA(aDNA)data,yet its file-based format and reliance on command-line tools,such as those in Admix-Tools(Patterson et al.,2012),require advanced computational expertise for effective exploration and analysis.These requirements can present significant challenges forresearchers lackingadvanced computational expertise,limiting the accessibility and broader application of these valuable genomic resources.
文摘Background:To investigate adverse event(AE)signals associated with six proton pump inhibitors(PPIs),enhance drug labeling information,and provide guidance for their safe clinical use.Methods:Adverse reaction data for musculoskeletal and connective tissue disorders related to six PPI formulations—omeprazole,pantoprazole,lansoprazole,esomeprazole,rabeprazole,and dexlansoprazole—from Q12004 to Q42023 were collected from the FDA Adverse Event Reporting System(FAERS).Signal detection was performed using the Reporting Odds Ratio(ROR),Proportional Reporting Ratio(PRR),Bayesian Confidence Propagation Neural Network(BCPNN),and Empirical Bayesian Geometric Mean(EBGM).Data processing and statistical analysis were conducted using R Studio 4.40.Results:A total of 6,635,3,853,1,792,15,731,483,and 534 adverse events were identified for the six PPIs,respectively.The four algorithms(ROR,PRR,BCPNN,and EBGM)generated 17,19,8,27,5,and 2 positive signals.Notably,signals for renal osteodystrophy and osteoporosis were more frequent,with stronger signals for lumbar flexion syndrome and renal osteodystrophy.Conclusion:Patients with chronic kidney disease,a high risk of osteoporosis and fractures,or those using statins should select PPIs with a lower risk of adverse musculoskeletal and connective tissue reactions to minimize these adverse effects and ensure standardized clinical use of PPIs.
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 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.
