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SCImago
Q2
WOS
Q2
Impact factor
2.1
SJR
0.957
CiteScore
9.4
Categories
Artificial Intelligence
Cognitive Neuroscience
Experimental and Cognitive Psychology
Software
Areas
Computer Science
Neuroscience
Psychology
Years of issue
1999-2025
journal names
Cognitive Systems Research
COGN SYST RES
Top-3 citing journals

Lecture Notes in Computer Science
(896 citations)

Cognitive Systems Research
(758 citations)

IEEE Access
(419 citations)
Top-3 organizations

Vrije Universiteit Amsterdam
(38 publications)

National Research Nuclear University MEPhI
(16 publications)

University of Memphis
(14 publications)

Vrije Universiteit Amsterdam
(23 publications)

National Research Nuclear University MEPhI
(16 publications)

Lomonosov Moscow State University
(7 publications)
Top-3 countries
Most cited in 5 years
Found
Publications found: 12371
Q2

Determination of KGa‐1b and SHCa‐1 Δ′17O and δ18O via Laser Fluorination of Lithium Fluoride Clay Pellets
Gagnon C., Havel R., Chen J., Piccione G., Ibarra D.
ABSTRACTRationaleStable oxygen isotope measurements in silicate clays, such as smectite and kaolinite, provide crucial information for understanding Earth's climate history and environmental changes. Despite a growing interest in the oxygen isotope analysis of silicate clays and clay‐rich sediments, there lacks a consensus on the preparation and standardization of clay mineral samples. To improve the accuracy and interlaboratory comparisons of clay isotope measurements, especially those involving laser fluorination techniques, newly established kaolinite and smectite oxygen isotope standards are much needed.MethodsWe employed conventional nickel bomb fluorination combined with dual‐inlet isotope ratio mass spectrometry to establish precise δ18O and Δ′17O values for leached clay reference materials KGa‐1b and SHCa‐1, a kaolinite and a hectorite/smectite, respectively. We further measured leached KGa‐1b and SHCa‐1 pressed into pellets with a lithium fluoride as a binding agent for the laser fluorination method, allowing us to test the reproducibility between methods and utilize a standard laser chamber drift correction scheme.ResultsThe laser fluorination technique yielded highly precise and reproducible δ18O and Δ′17O measurements for the KGa‐1b and SHCa‐1, aligning with bomb values of δ18O. This confirms the method's reliability and comparability to conventional isotope measurement techniques while also stressing the importance of proper sample preparation and laser chamber drift corrections.ConclusionsThis study demonstrates that laser fluorination is an effective method for accurately measuring the stable oxygen isotope composition of silicate clays or clay‐rich sediments when corrected with known silicate clay standards. These methods offer a valuable methodology for future research and applications that will significantly improve our understanding of past climate and environmental conditions.
Q2

Rapid Proteomic Amelogenin Sex Estimation of Human and Cattle Remains Using Untargeted Evosep‐timsTOF Mass Spectrometry
Blacka C., Dowle A., Lisowski M., Alexander M., Hendy J., Penkman K., Mosely J.
ABSTRACTRationaleSex estimation by analysis of amelogenin peptides in archaeological and fossil material has recently been gaining great traction within the fields of archaeology and palaeontology. Current widely used proteomic amelogenin sex estimation methods are hindered by relatively long mass spectrometric run times, or targeting peptides specific to human amelogenin proteins. Untargeted, high‐throughput amelogenin sexing would be invaluable for a range of applications, from sex estimation of remains at mass grave sites to broadening the application of rapid amelogenin sexing to non‐hominin species for husbandry and evolutionary studies.MethodsA new acid etch protocol followed by Evosep‐LC‐TIMS‐TOF mass spectrometry is presented for amelogenin analysis, providing global peptide data through rapid mass spectrometric methods in under 20 min per sample (including sample preparation, mass spectrometric acquisition and data processing). This sampling protocol was developed on modern cattle (Bos taurus) teeth, before Evosep‐timsTOF partial validation with archaeological cattle and human (Homo sapiens) teeth, demonstrating the potential of straightforward application of this rapid amelogenin sexing method to a range of taxa.ResultsThe rapid Evosep‐LC‐TIMS‐TOF mass spectrometry methods gave comparable peptide counts to conventional long untargeted methods, while maintaining similar (or faster) acquisition times to those reported in methods targeting specific human amelogenin peptides. Implementation of the novel acid etch sampling approach also streamlined sample preparation without compromising peptide counts.ConclusionsRapid, untargeted Evosep‐LC‐TIMS‐TOF mass spectrometry was successfully implemented in sex estimation of modern and archaeological material from Bos taurus and Homo sapiens teeth. This demonstrates an advancement in low‐cost, high‐throughput amelogenin sex estimation, for both human and zooarchaeological applications.
Q2

Determination of K Isotope Compositions in Sedimentary Rocks and Their Implications for Discriminating Sediment Origin
Cui M., Moynier F., Su B., Hu Y.
ABSTRACTThe advent of a new generation of collision‐cell multicollector inductively‐coupled‐plasma mass‐spectrometers (CC–MC–ICP–MS), the Nu sapphire, has provided a new venue in achieving higher precision K isotopic compositions compared to the older generation of instruments. Here, we take advantage of this new technology to report the K isotopic compositions of eight sediment reference materials. The K isotopic compositions (reported as the δ41K representing the 41K/39K ratios) for these sediment reference materials span a range of 0.2‰: −0.42 ± 0.04‰ (BCSS‐1), −0.51 ± 0.07‰ (MESS‐1), and −0.43 ± 0.01‰ (MESS‐4) for three marine sediments, −0.35 ± 0.07‰ (NIST‐SRM 1646a) for estuarine sediment, −0.40 ± 0.06‰ (NIST‐SRM 2704) and −0.40 ± 0.05‰ (SWR‐3) for two river sediments, −0.55 ± 0.04‰ (NIST‐SRM 1d) for limestone, and −0.46 ± 0.00‰ (SBC‐1) for marine shale. The high‐precision K isotopic data presented herein provide a valuable reference for future quality control and interlaboratory comparisons. Data compilation reveals that biogenic sediments show extremely low K concentrations (K2O = 0.001–0.048 wt.%) and large K isotopic variations (δ41K = −1.88–0.94‰) with an average value of −0.001‰, whereas the abiogenic sediments are featured with light K isotopes (average δ41K value of −0.47‰) and high K concentrations (K2O = 0.52 ~ 4.29 wt.%). This finding suggests that the variation of K isotopes may serve as a useful tool for discriminating the various geneses of sediments.
Q2

Carbon and Nitrogen Isotopic Composition of Duplicate Diet of the Japanese
Yoshinaga J.
ABSTRACTRationaleCarbon and nitrogen stable isotope ratios (δ13C and δ15N) of whole diet have rarely been measured to date though the isotope ratios in human sample have been extensively used for diet and nutritional researches. In order to fully validate the isotope dietary analysis, isotopic information of whole diet is required.Methodsδ13C and δ15N of 150 duplicate diet samples collected in Japan during 2016–2017 were measured. Sixty‐five males and 85 females (mean age: 45 years) donated duplicate diet sample of which δ13C and δ15N were measured by element analyzer‐isotope ratio mass spectrometry.ResultsMean δ13C and δ15N of the 150 duplicate diets were −24.3 (1.1) ‰ and 3.58 (0.93) ‰, respectively, with no gender‐ and age‐dependent variation. δ15N of diet containing seafood (median: 3.60‰, n = 111) was significantly more elevated than that not containing seafood (3.01‰, n = 39). δ15N of Japanese diet is decreasing from 1990s to the present, which is consistent with the national statistics showing decreasing trend of seafood consumption of the Japanese. Contradictory to these observation, dietary δ15N was not elevated in diet samples from the elderlies though the diet of elderlies contained seafood more frequently than those of younger study participants.ConclusionThere were some uncertainties as to whether seafood is a major determinant of dietary δ15N of the Japanese. To further characterize dietary components that determine δ values, isotope ratio analysis of diet of known quantitative dietary components is warranted.
Q2

Combination of Metabolite Analysis and Network Pharmacology to Explore the Potential Anticough Mechanism of Protopine—A Marker in Zhi‐Ke‐Bao Tablets
Zou Q., Chen D., Liu C., Chen Z., Yang X., Xu R., Zhou Z., Chen J., Shi W., Zhang F.
ABSTRACTRationaleProtopine, an active alkaloid in Papaver somniferum L., was abundant in a well‐known anticough traditional Chinese medicine preparation—Zhi‐Ke‐Bao tablets. Till now, the metabolism feature and anticough mechanism of protopine have not been fully elucidated, restricting its further development.MethodsThe metabolites of protopine in rats were profiled by using ultra‐high performance liquid chromatography coupled with time‐of‐flight mass spectrometry, and its anticough targets and mechanism were predicted by network pharmacology.ResultsIn rats, a total of 19 metabolites were identified following ingestion of protopine (21 mg/kg/day, i.g.), including 4 in plasma, 6 in urine, 5 in feces, 10 in liver, 2 in spleen, 4 in lung, 3 in kidney, 3 in heart, and 3 in brain. The main metabolic features were ring‐opening, methylation, demethylation, glucuronidation, sulfation, and hydroxylation. Among them, methylation, sulfation, and hydroxylation of protopine in vivo were revealed for the first time. The network pharmacology results show that protopine and its metabolites regulate physiological activities by acting on STAT3, SRC, CASP3, MTOR, MMP9, ESR1, and other targets, involving PI3K‐Akt signaling pathway, FoxO signaling pathway, and TNF signaling pathway, etc.ConclusionsThe metabolic features of protopine and its potential mechanisms for anticough effects were outlined, providing data for further anticough pharmacological validation of protopine.
Q2

Fast Pyrolysis of Cigarette and Cigar Leaves: Differential Analysis of Their Heavy Products by Ultrahigh‐Resolution Mass Spectrometry
Zhu Z., Zhang C., Shi Y., Zou P., Ding N., Zong K., Jia L., Guo D.
ABSTRACTRationaleThe cigars have characteristic flavors in smoke when compared with cigarettes, and cigars from various origins also have a difference in taste. However, little information can be found about the difference in chemical components of smokes between cigar and cigarette as well as between cigars, so it is interesting to compare their pyrolysis product distribution.MethodsThe cigarette and cigar leaves were pyrolyzed in a microfluidized‐bed reactor, and the pyrolysis vapors were condensed and collected using cold traps. Mass spectrometric analysis of condensed liquids was performed utilizing electrospray ionization‐orbitrap mass spectrometry in both positive and negative ion modes.ResultsThe mass spectra of condensable pyrolysis products of three tobacco leaves were obtained by Orbitrap‐MS in both positive and negative ESI modes. The DBE values (to carbon atom number) and the relative distribution (to nitrogen or oxygen atom number) of different products were carefully compared and discussed.ConclusionThe main difference in pyrolysis products between cigarette and cigar leaves relates to N1–N2 class compounds in high‐mass range as well as highly unsaturated nitrogenated compounds, while the one between two cigar leaves is associated with CxHyOzN5–9 and C30‐50HyOzNw compounds. Besides, the oxygenated products that fall into the H/C > 2 and O/C < 1 ranges are also characteristic for Dominican cigar.
Q2

Pioneering Mass Spectrometry: A Tribute to My Mentor Jean‐François Muller and His Enduring Legacy
Frache G.
ABSTRACTProfessor Jean‐François Muller, a distinguished figure in the field of mass spectrometry, made significant contributions to the advancement of analytical chemistry and its applications. As the founding director of the Laboratory of Mass Spectrometry and Laser Chemistry at the University of Metz, Muller played a pivotal role in establishing Metz as a leading center for mass spectrometry research. His pioneering work, particularly in the development of matrix‐assisted laser desorption/ionization (MALDI) instrumentation and Fourier transform ion cyclotron resonance mass Spectrometry (FTICR MS), has had a profound impact on various scientific disciplines. This article commemorates Professor Muller's illustrious career and highlights his collaborative efforts with industrial partners such as Total, which led to groundbreaking advancements in MS analysis. I will delve into the key findings of my thesis which focused on instrumental developments for MALDI analysis and imaging, as well as personal reminiscences and the impact of his inspiring mentorship.
Q2

Systematic Analysis of the Chemical Components of Gentiana urnula Harry Sm Using SIRIUS and Liquid Chromatography High‐Resolution Mass Spectrometry
Yan Z., Ning J., Luo Z., Li D., Wang H., Xie X.
ABSTRACTRationaleGentiana urnula Harry Sm is a frequently utilized traditional Chinese medicine (TCM) with applications in the treatment of a range of ailments including jaundice, gastrointestinal ulcers, and influenza. Despite its widespread uses, there is a lack of comprehensive researches on the chemical composition.MethodsThis study integrated SIRIUS, quantitative structure‐retention relationship (QSRR), and liquid chromatography high‐resolution mass spectrometry (LC‐HRMS) to identify the compounds in Gentiana urnula Harry Sm.ResultsA total of 213 compounds were identified with high confidence based on retention time (tR), MS1, and MS/MS. Among the 213 compounds, 26 compounds were positively identified firstly in Gentiana urnula Harry Sm. More than 5000 compounds were classified based on MS/MS. Spatial distribution revealed the similarities in compound between roots and stems, while differences were observed between leaves and flowers.ConclusionsThis study lays the foundation for further investigations into the biological activity and pharmacological mechanism of Gentiana urnula Harry Sm.
Q2

Part B: SLICE‐MSI—A Machine Learning Interface for System Suitability Testing of Mass Spectrometry Imaging Platforms
Kibbe R., Mills Q., Sohn A., Muddiman D.
ABSTRACTRationaleThe field of mass spectrometry imaging is currently devoid of standardized protocols or commercially available products designed for system suitability testing of MSI platforms. Machine learning is an approach that can quickly and effectively identify complex patterns in data and use them to make informed classifications, but there is a technical barrier to implementing these algorithms. Here we package the machine learning algorithms into a user‐friendly interface to make community‐wide implementation of this protocol possible.MethodsThe software package is built entirely in the Python language using the PySimpleGUI library for the construction of the interface, Pandas and Numpy libraries for data formatting and manipulation, and the Scikit‐Learn library for the implementation of machine learning algorithms. Training data is collected on an instrument under clean and compromised conditions that can then be used to evaluate model performance and to train models prior to interrogating unknown samples before, during, or after experiments.ResultsDetailed instructions are provided for the effective use of the SLICE‐MSI software package to use machine learning to evaluate instrument condition of MSI platforms. File formatting and generalizable steps are clearly described to make the implementation of this package easy for multiple labs and different MSI platform configurations.ConclusionsIn this protocol, we demonstrate SLICE‐MSI, a machine learning graphical user interface for efficient and easy implementation of QC instrument classification of mass spectrometry imaging platforms.
Q2

Part A: Implementing an Analyte Panel and Sampling Protocol for Quality Control in Mass Spectrometry Imaging
Mills Q., Kibbe R., Sohn A., Percy A., Backiel K., Muddiman D.
ABSTRACTRationaleWhile quality control (QC) and system suitability testing (SST) methods are commonly employed in mass spectrometry, the field of mass spectrometry imaging (MSI) currently lacks any universally accepted QC/SST protocols. These methods can prevent the loss of precious samples due to suboptimal instrument conditions and/or data quality, but they are more challenging to implement on MSI platforms. Herein, a panel of analytes is conveniently analyzed in a setup that reflects a typical MSI imaging experiment, and guidance is provided for downstream QC/SST evaluation.MethodsThe analyte panel will be commercially available and consists of three pairs of unlabeled (NAT) analytes and their stable isotope–labeled (SIL) analogues; a deviation from the standard procedure is also included, which incorporates a polymer to expand m/z coverage. The NAT three‐plex (or four‐plex with the added polymer) is analyzed as a droplet on a slide, and the SIL three‐plex is doped into the electrospray solvent, isolating the NAT and SIL compounds to different source components. Datasets are collected on clean and compromised instruments to inform QC/SST software and later evaluate instrument conditions or isolated metrics of data quality.ResultsA procedure was created for QC/SST analysis on MSI platforms, which can be optionally paired with the freely available software Supervised Learning for Instrument Classification and Evaluation for Mass Spectrometry Imaging (SLICE‐MSI) to classify the condition of the instrument. The SIL data may be monitored separately during imaging experiments for continuous evaluation of electrospray stability. The protocol highlights areas that may be adapted for other ionization sources for widespread use.ConclusionsThe protocol described herein uses a panel of NAT and SIL compounds to offer an objective and accurate determination of QC/SST on MSI platforms.
Q2

Determination of Collisional Cross Section Using Microscale High‐Field Asymmetric Waveform ion Mobility Spectroscopy–Mass Spectrometry (FAIMS‐MS)
Krasnova K., Creaser C., Reynolds J.
ABSTRACTRationaleCollisional cross sections (CCS) are an important characteristic of gas‐phase ions that are measured using ion mobility‐mass spectrometry (IMS). Typically, CCS measurements are performed with drift‐tube IMS or travelling‐wave IMS. However. in a high‐field asymmetric waveform ion mobility (FAIMS) device, ion heating effects make CCS determination more challenging. This research explores whether CCS can be predicted with microscale FAIMS by using known CCS standards.MethodsAn Owlstone ultraFAIMS microscale FAIMS spectrometer was coupled to an Orbitrap Exactive mass spectrometer. Two different CCS standard mixtures (tetraalkylammonium halides [TAAHs] and poly‐DL‐alanine oligomers) were used to evaluate the system's potential to determine CCS. Test peptide bradykinin acetate and substance P were used to evaluate CCS determination accuracy for singly and doubly charged peptide species using external calibration with a series of poly‐DL‐alanine peptides for +1, +2 charge states.ResultsCalibrations with excellent correlation coefficients (R2 = 0.99) for both TAAHs and poly‐DL‐alanine were obtained. Good accuracy of determination was achieved for bradykinin [M + 2H]2+ with a ± 0.5% difference between experimental and published CCS at a dispersion field (DF) strength of 250 Td; the model proved less accurate for bradykinin [M + H]+ (±1.4% at 240 Td). The accuracy of determination for the [M + H]+ and [M + 2H]2+ ions of substance P was within ± 5% and ± 3% at 250 Td, respectively, while at higher DF values, accuracy decreased to approximately 5%.ConclusionsDistinct relationships were observed between CCS and transmission CF with both calibrants. Optimum accuracy was obtained at DF 240–260 Td. At lower DF, accuracy is reduced by insufficient resolution of analyte ions from solvent cluster adducts, while at higher DF values, poor transmission becomes a factor. Nevertheless, these data suggest microscale FAIMS can conduct CCS measurements with reasonable accuracy when the compound being measured has similar structural features to the CCS standards used.
Q2

Improved Protective Effects and Pharmacokinetics of Huperzine A Derivative H14 in Soman Poisoning: A Comparative Study With Huperzine A in Rats
Yang G., Cui Y., Zong X., Jin Q., Zhang Y., Li L., Liu D., Chen X., Wang C., Wei J.
ABSTRACTRationaleN‐[2‐Hydroxy‐3,5‐dimethylbenzilidene]‐Hup A (H14) is a derivative of huperzine A (Hup A) that demonstrates superior protective effects against soman (GD) compared to Hup A. This study aims to evaluate the protective efficacy of H14 pretreatment against GD in rats and to provide an analytical framework for the pharmacokinetic evaluation of H14 in experimental animals.MethodsThe study employed protective ratios (PR) as an evaluation criterion to assess the efficacy of H14 and Hup A in preventing GD in vivo. Liquid–liquid extraction techniques were utilized to extract H14 and its metabolite, Hup A, from plasma. The extracted plasma samples were then analyzed using an ultra‐high‐performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS) method for the simultaneous quantification of H14 and Hup A.ResultsThe PR values for the 6‐ and 12‐h Hup A groups were 1.26 and 1.08, respectively. In contrast, the 6, 12, and 24‐h H14 groups demonstrated PR values of 2.81, 1.98, and 1.18, respectively, indicating extended protective capabilities compared to Hup A. All validation parameters for the UHPLC–MS/MS method, including linearity, specificity, precision, accuracy, matrix effect, and stability, met the acceptance criteria established by FDA guidelines. The pharmacokinetic analysis indicates that H14, after conversion to Hup A in vivo, significantly extends the duration of Hup A concentrations in the body, leading to more effective prevention of GD poisoning compared to Hup A alone.ConclusionsH14 demonstrates superior efficacy in preventing GD poisoning compared to Hup A. Furthermore, this analytical approach offers a reliable and efficient method for the pharmacokinetic evaluation of H14 in experimental animals.
Q2

Covalent Organic Framework Nanofilm‐Assisted Laser Desorption Ionization Mass Spectrometry for the Determination of Benzophenone Derivatives in Personal Care Products
Yan L., Zheng W., Lin Z.
ABSTRACTRationalBenzophenone derivatives, commonly used as UV filters in personal care products (PCPs), are widely prevalent and raise concerns due to their endocrine‐disrupting effects. Sensitive and efficient analytical methods are in demand for their detection. In this study, we developed a TAPB‐DMTP‐covalent organic framework (COF) nanofilm‐assisted laser desorption ionization mass spectrometry (LDI‐MS) method for the quantitative analysis of 2,4‐dihydroxybenzophenone (BP‐1) in PCPs.MethodsThe TAPB‐DMTP‐COF nanofilm was synthesized on indium tin oxide (ITO) glass and utilized as an LDI‐MS substrate. The performance of TAPB‐DMTP‐COF nanofilm‐assisted LDI‐MS for analyzing small molecules (e.g., benzophenone derivatives, phthalates, amino acids, sugars, and nucleosides) was compared to conventional organic matrices (α‐cyano‐4‐hydroxycinnamic acid [CHCA], 2,5‐dihydroxybenzoic acid [DHB], and sinapinic acid [SA]). The reproducibility, salt resistance, sensitivity, and stability of the method were further evaluated. Finally, the technique was applied to quantify BP‐1 in PCPs.ResultsThe TAPB‐DMTP‐COF nanofilm‐assisted LDI‐MS provided stronger mass spectral signals and cleaner backgrounds for small molecules compared to CHCA, DHB, and SA. The method exhibited high reproducibility (RSD = 6.10%) and stability for up to 30 days. BP‐1 in PCPs was quantified with excellent linearity (1–20 μg/mL, r = 0.9993), a low detection limit (0.3 μg/mL), and recovery rates of 94.2%–104.4%, demonstrating the potential of TAPB‐DMTP‐COF nanofilm for sensitive and reliable small‐molecule analysis.ConclusionTAPB‐DMTP‐COF nanofilm‐assisted LDI‐MS offered the advantages of rapid analysis, clean backgrounds, and reproducibility for detecting small molecules, including benzophenone derivatives. This method successfully quantified BP‐1 in PCPs, highlighting its suitability for analyzing complex samples.
Q2

Assessing Matrix and Nonmatrix, Single, and Multipoint Calibration of Trace Elements Using LA‐ICP‐MS on a Tropical Speleothem
Sekhon N., Gao A., Mallick S., Partin J., Cardenas M. ., Ibarra D.
ABSTRACTRationaleSuites of trace elements are routinely used in speleothems as proxies to understand periods of past climate change. Laser ablation techniques are regularly implemented to acquire high resolution (50‐μm) trace element concentrations in carbonate archives for paleoclimatology. There exists limited research investigating Laser Ablation‐Inductively Coupled Plasma‐Mass Spectrometry (LA‐ICP‐MS) protocols using speleothem samples. This study investigates the difference between using matrix (carbonate) and nonmatrix (silicate) matched reference materials and the utility of 1‐point versus multiple point calibration curves.MethodsFollowing an extensive review of published literature on speleothem LA‐ICP‐MS analyses, we conducted two laser ablation experimental runs 8 months apart on a 2.7‐cm section of a natural speleothem using matrix and nonmatrix matched reference materials. We used a 193‐nm wavelength Analyte G2 laser attached to a X‐Series‐2 ICP‐MS, a silicate reference material, and three carbonate reference materials. Next, we calculated concentrations using a 1‐point calibration curve, a 2‐point calibration curve, and a 3‐point calibration curve.ResultsThe analysis of matrix and nonmatrix matched reference materials demonstrates that the trends of trace elements/Ca are minimally impacted by the matrix material of the standard. We also show that 2‐ and 3‐point calibration curves bracket the range of sample concentrations compared to a 1‐point (silicate) calibration curve. The calculated cave‐air temperatures using Mg/Ca concentrations fall within error of each other regardless of the calibration curve approach applied.ConclusionsOur experiments provide a proof of concept on the conventional setup of standards during LA‐ICP‐MS speleothem analysis. We suggest the use of at minimum a 2‐point (silicate plus carbonate or carbonates) calibration curve that crucially bracket the range of sample concentrations rather than relying on a 1‐point silicate standard that does not bracket the sample concentration. Finally, our results have implications for both speleothem studies that use LA‐ICP‐MS analytical techniques and additional carbonate archives.
Q2

Exploration of Active Substances and Its Potential Mechanism of Gancao Fuzi Decoction on Inflammatory Based on Metabolomics and Network Pharmacology
Geng W., Liu S., Dong H., Arachchige B., Qi D., Wang X.
ABSTRACTGancao Fuzi decoction (GCFZT) is a traditional Chinese formula, which has been commonly used in clinical practice to treat inflammatory diseases. However, the active substance of GCFZT in the treatment of inflammation is not fully clarified. In this study, we used orthogonal experiments to design different GCFZT formulations, resulting in a total of 16 GCFZT formulations. Subsequently, UPLC‐Q‐TOF‐MS/MS was used to analyze the chemical composition of different formulations, and the anti‐inflammatory activity differences of these formulations were evaluated through an LPS‐induced RAW264.7 inflammatory cell model. Combined with machine learning algorithms such as PLS‐DA and RF, four main active substances in GCFZT were screened. Finally, network pharmacology techniques were used to investigate the potential anti‐inflammatory mechanisms of these main active substances, and the results showed that GCFZT mainly regulates the expression of core targets such as ALOX5, NFKB1, and TLR4 through main active substances such as chlorogenic acid, riboflavin, and formononetin, thereby affecting the NF kappa B signaling pathway, the Toll‐like receptor signaling pathway, and the Th17 cell differentiation. This study provides a reference for the anti‐inflammatory mechanism of GCFZT and a scientific basis for its clinical application.
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32 citations, 0.15%
|
|
Complexity
31 citations, 0.14%
|
|
Human Factors
31 citations, 0.14%
|
|
International Journal of Information Technology
31 citations, 0.14%
|
|
Computers in Human Behavior
30 citations, 0.14%
|
|
Vision Research
29 citations, 0.13%
|
|
Behavior Research Methods
29 citations, 0.13%
|
|
IEEE Sensors Journal
28 citations, 0.13%
|
|
Advances in Computational Intelligence and Robotics
27 citations, 0.12%
|
|
Psychonomic Bulletin and Review
26 citations, 0.12%
|
|
Connection Science
26 citations, 0.12%
|
|
Concurrency Computation Practice and Experience
25 citations, 0.12%
|
|
Computer Methods and Programs in Biomedicine
25 citations, 0.12%
|
|
Acta Psychologica
25 citations, 0.12%
|
|
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
24 citations, 0.11%
|
|
IFIP Advances in Information and Communication Technology
24 citations, 0.11%
|
|
Frontiers in Artificial Intelligence
24 citations, 0.11%
|
|
Frontiers in Neurorobotics
23 citations, 0.11%
|
|
Neuroscience and Biobehavioral Reviews
23 citations, 0.11%
|
|
PeerJ Computer Science
23 citations, 0.11%
|
|
Scientific Programming
23 citations, 0.11%
|
|
Topoi
23 citations, 0.11%
|
|
Memory and Cognition
23 citations, 0.11%
|
|
International Journal of Imaging Systems and Technology
23 citations, 0.11%
|
|
KI - Künstliche Intelligenz
23 citations, 0.11%
|
|
Cognitive Neurodynamics
22 citations, 0.1%
|
|
ACM Computing Surveys
22 citations, 0.1%
|
|
Show all (70 more) | |
100
200
300
400
500
600
700
800
900
|
Citing publishers
1000
2000
3000
4000
5000
6000
|
|
Springer Nature
5109 citations, 23.51%
|
|
Elsevier
3908 citations, 17.99%
|
|
Institute of Electrical and Electronics Engineers (IEEE)
2805 citations, 12.91%
|
|
MDPI
1144 citations, 5.26%
|
|
Taylor & Francis
1010 citations, 4.65%
|
|
Wiley
915 citations, 4.21%
|
|
SAGE
564 citations, 2.6%
|
|
Frontiers Media S.A.
549 citations, 2.53%
|
|
Association for Computing Machinery (ACM)
459 citations, 2.11%
|
|
Hindawi Limited
429 citations, 1.97%
|
|
Cambridge University Press
364 citations, 1.68%
|
|
IGI Global
314 citations, 1.45%
|
|
Walter de Gruyter
169 citations, 0.78%
|
|
IOS Press
159 citations, 0.73%
|
|
Emerald
151 citations, 0.69%
|
|
IOP Publishing
139 citations, 0.64%
|
|
Public Library of Science (PLoS)
129 citations, 0.59%
|
|
World Scientific
118 citations, 0.54%
|
|
Oxford University Press
114 citations, 0.52%
|
|
John Benjamins Publishing Company
103 citations, 0.47%
|
|
Social Science Electronic Publishing
67 citations, 0.31%
|
|
Cold Spring Harbor Laboratory
64 citations, 0.29%
|
|
Tech Science Press
64 citations, 0.29%
|
|
The Royal Society
52 citations, 0.24%
|
|
Institution of Engineering and Technology (IET)
50 citations, 0.23%
|
|
AIP Publishing
48 citations, 0.22%
|
|
EDP Sciences
43 citations, 0.2%
|
|
JMIR Publications
39 citations, 0.18%
|
|
MIT Press
38 citations, 0.17%
|
|
PeerJ
33 citations, 0.15%
|
|
OpenEdition
24 citations, 0.11%
|
|
Trans Tech Publications
21 citations, 0.1%
|
|
American Psychological Association (APA)
21 citations, 0.1%
|
|
Bentham Science Publishers Ltd.
20 citations, 0.09%
|
|
American Institute of Mathematical Sciences (AIMS)
20 citations, 0.09%
|
|
Hogrefe Publishing Group
20 citations, 0.09%
|
|
American Society of Civil Engineers (ASCE)
19 citations, 0.09%
|
|
American Scientific Publishers
18 citations, 0.08%
|
|
American Physical Society (APS)
18 citations, 0.08%
|
|
China Science Publishing & Media
17 citations, 0.08%
|
|
SPIE-Intl Soc Optical Eng
17 citations, 0.08%
|
|
Proceedings of the National Academy of Sciences (PNAS)
16 citations, 0.07%
|
|
King Saud University
16 citations, 0.07%
|
|
Pleiades Publishing
15 citations, 0.07%
|
|
Alexandria University
15 citations, 0.07%
|
|
ASME International
15 citations, 0.07%
|
|
Hans Publishers
13 citations, 0.06%
|
|
University of Chicago Press
12 citations, 0.06%
|
|
Instrument Society of America
11 citations, 0.05%
|
|
Annual Reviews
11 citations, 0.05%
|
|
World Scientific and Engineering Academy and Society (WSEAS)
11 citations, 0.05%
|
|
Ovid Technologies (Wolters Kluwer Health)
10 citations, 0.05%
|
|
American Chemical Society (ACS)
10 citations, 0.05%
|
|
Academy of Management
10 citations, 0.05%
|
|
Tsinghua University Press
10 citations, 0.05%
|
|
Mary Ann Liebert
9 citations, 0.04%
|
|
Society for Judgment and Decision Making
9 citations, 0.04%
|
|
eLife Sciences Publications
9 citations, 0.04%
|
|
CAIRN
9 citations, 0.04%
|
|
Research Square Platform LLC
9 citations, 0.04%
|
|
Ediciones Universidad de Salamanca
8 citations, 0.04%
|
|
American Institute of Aeronautics and Astronautics (AIAA)
8 citations, 0.04%
|
|
S. Karger AG
8 citations, 0.04%
|
|
SciELO
8 citations, 0.04%
|
|
F1000 Research
8 citations, 0.04%
|
|
IntechOpen
8 citations, 0.04%
|
|
The Japanese Society for Artificial Intelligence
8 citations, 0.04%
|
|
Brill
6 citations, 0.03%
|
|
American Association for the Advancement of Science (AAAS)
6 citations, 0.03%
|
|
Consortium Erudit
6 citations, 0.03%
|
|
Equinox Publishing
6 citations, 0.03%
|
|
Guilford Publications
6 citations, 0.03%
|
|
University of Illinois Press
5 citations, 0.02%
|
|
Institute for Operations Research and the Management Sciences (INFORMS)
5 citations, 0.02%
|
|
American Speech Language Hearing Association
5 citations, 0.02%
|
|
Akademiai Kiado
5 citations, 0.02%
|
|
SAE International
5 citations, 0.02%
|
|
University of California Press
4 citations, 0.02%
|
|
Korean Society of Mechanical Engineers
4 citations, 0.02%
|
|
Arizona State University
4 citations, 0.02%
|
|
Association for Research in Vision and Ophthalmology (ARVO)
4 citations, 0.02%
|
|
National Academy of Sciences of Ukraine (Co. LTD Ukrinformnauka) (Publications)
4 citations, 0.02%
|
|
JVE International Ltd.
4 citations, 0.02%
|
|
Moscow State University of Psychology and Education
4 citations, 0.02%
|
|
Scientific Research Publishing
4 citations, 0.02%
|
|
Bristol University Press
4 citations, 0.02%
|
|
IMR Press
3 citations, 0.01%
|
|
3 citations, 0.01%
|
|
Royal Society of Chemistry (RSC)
3 citations, 0.01%
|
|
American Physiological Society
3 citations, 0.01%
|
|
Optica Publishing Group
3 citations, 0.01%
|
|
University of Warsaw
3 citations, 0.01%
|
|
Fuji Technology Press
3 citations, 0.01%
|
|
Johann Ambrosius Barth
3 citations, 0.01%
|
|
Information Processing Society of Japan
3 citations, 0.01%
|
|
3 citations, 0.01%
|
|
Shanghai Jiaotong University Press
3 citations, 0.01%
|
|
Korean Institute of Electrical Engineers
3 citations, 0.01%
|
|
NP Voprosy Ekonomiki
3 citations, 0.01%
|
|
Ain Shams University
3 citations, 0.01%
|
|
Show all (70 more) | |
1000
2000
3000
4000
5000
6000
|
Publishing organizations
5
10
15
20
25
30
35
40
|
|
Vrije Universiteit Amsterdam
38 publications, 2.84%
|
|
National Research Nuclear University MEPhI
16 publications, 1.2%
|
|
University of Memphis
14 publications, 1.05%
|
|
University of Michigan
13 publications, 0.97%
|
|
University of Turin
12 publications, 0.9%
|
|
Institute for High Performance Computing and Networking
12 publications, 0.9%
|
|
Rensselaer Polytechnic Institute
12 publications, 0.9%
|
|
Carnegie Mellon University
11 publications, 0.82%
|
|
University of Skövde
9 publications, 0.67%
|
|
McGill University
9 publications, 0.67%
|
|
University of Amsterdam
9 publications, 0.67%
|
|
Lomonosov Moscow State University
8 publications, 0.6%
|
|
Delft University of Technology
8 publications, 0.6%
|
|
Stanford University
8 publications, 0.6%
|
|
Ruhr University Bochum
8 publications, 0.6%
|
|
University of Groningen
8 publications, 0.6%
|
|
University of Bremen
8 publications, 0.6%
|
|
University of Sussex
8 publications, 0.6%
|
|
Radboud University Nijmegen
7 publications, 0.52%
|
|
Pennsylvania State University
7 publications, 0.52%
|
|
Taylor's University
6 publications, 0.45%
|
|
University of Edinburgh
6 publications, 0.45%
|
|
Ningbo University
6 publications, 0.45%
|
|
Institute of Cognitive Sciences and Technologies
6 publications, 0.45%
|
|
University of Maryland, College Park
6 publications, 0.45%
|
|
Indiana University Bloomington
6 publications, 0.45%
|
|
National Research Centre "Kurchatov Institute"
5 publications, 0.37%
|
|
Indian Institute of Technology Roorkee
5 publications, 0.37%
|
|
Anna University
5 publications, 0.37%
|
|
Delhi Technological University
5 publications, 0.37%
|
|
Shanghai Jiao Tong University
5 publications, 0.37%
|
|
Lund University
5 publications, 0.37%
|
|
Mepco Schlenk Engineering College
5 publications, 0.37%
|
|
Beijing University of Technology
5 publications, 0.37%
|
|
North China Electric Power University
5 publications, 0.37%
|
|
Northeastern University
5 publications, 0.37%
|
|
University of Manchester
5 publications, 0.37%
|
|
University of Southern California
5 publications, 0.37%
|
|
University of Siena
5 publications, 0.37%
|
|
University of Central Florida
5 publications, 0.37%
|
|
National Autonomous University of Mexico
5 publications, 0.37%
|
|
Albert Ludwig University of Freiburg
5 publications, 0.37%
|
|
Osnabrück University
5 publications, 0.37%
|
|
COMSATS University Islamabad
4 publications, 0.3%
|
|
Shanmugha Arts, Science, Technology & Research Academy
4 publications, 0.3%
|
|
Beihang University
4 publications, 0.3%
|
|
Sichuan University
4 publications, 0.3%
|
|
China University of Mining and Technology
4 publications, 0.3%
|
|
Technical University of Munich
4 publications, 0.3%
|
|
Hubei University of Technology
4 publications, 0.3%
|
|
Taiyuan University of Technology
4 publications, 0.3%
|
|
Shanxi University
4 publications, 0.3%
|
|
National Taiwan University
4 publications, 0.3%
|
|
University of Southampton
4 publications, 0.3%
|
|
University of Birmingham
4 publications, 0.3%
|
|
Zhongyuan University of Technology
4 publications, 0.3%
|
|
University of Trento
4 publications, 0.3%
|
|
Macquarie University
4 publications, 0.3%
|
|
Arizona State University
4 publications, 0.3%
|
|
Hong Kong Baptist University
4 publications, 0.3%
|
|
Rutgers, The State University of New Jersey
4 publications, 0.3%
|
|
George Mason University
4 publications, 0.3%
|
|
University of California, San Diego
4 publications, 0.3%
|
|
University of California, Merced
4 publications, 0.3%
|
|
Zhengzhou University
4 publications, 0.3%
|
|
University of Texas at Austin
4 publications, 0.3%
|
|
Vrije Universiteit Brussel
4 publications, 0.3%
|
|
University of Waterloo
4 publications, 0.3%
|
|
Utrecht University
4 publications, 0.3%
|
|
Leiden University
4 publications, 0.3%
|
|
Hokkaido University
4 publications, 0.3%
|
|
University of Bamberg
4 publications, 0.3%
|
|
University of Wisconsin–Madison
4 publications, 0.3%
|
|
Kitami Institute of Technology
4 publications, 0.3%
|
|
Temple University
4 publications, 0.3%
|
|
Universidad Carlos III de Madrid
4 publications, 0.3%
|
|
Universidad Complutense de Madrid
4 publications, 0.3%
|
|
Carleton University
4 publications, 0.3%
|
|
University of Cincinnati
4 publications, 0.3%
|
|
University of Colorado Boulder
4 publications, 0.3%
|
|
University of Texas at Arlington
4 publications, 0.3%
|
|
Moscow Institute of Physics and Technology
3 publications, 0.22%
|
|
Novosibirsk State University
3 publications, 0.22%
|
|
Russian State University for the Humanities
3 publications, 0.22%
|
|
Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences
3 publications, 0.22%
|
|
Amirkabir University of Technology
3 publications, 0.22%
|
|
Vellore Institute of Technology University
3 publications, 0.22%
|
|
University of Tübingen
3 publications, 0.22%
|
|
Bar-Ilan University
3 publications, 0.22%
|
|
Tongji University
3 publications, 0.22%
|
|
University of Electronic Science and Technology of China
3 publications, 0.22%
|
|
Katholieke Universiteit Leuven
3 publications, 0.22%
|
|
Ghent University
3 publications, 0.22%
|
|
Tampere University
3 publications, 0.22%
|
|
Karunya Institute of Technology and Sciences
3 publications, 0.22%
|
|
University of Helsinki
3 publications, 0.22%
|
|
Jordan University of Science and Technology
3 publications, 0.22%
|
|
Nankai University
3 publications, 0.22%
|
|
Technische Universität Dresden
3 publications, 0.22%
|
|
Capital Medical University
3 publications, 0.22%
|
|
Show all (70 more) | |
5
10
15
20
25
30
35
40
|
Publishing organizations in 5 years
5
10
15
20
25
|
|
Vrije Universiteit Amsterdam
23 publications, 5.91%
|
|
National Research Nuclear University MEPhI
16 publications, 4.11%
|
|
Lomonosov Moscow State University
7 publications, 1.8%
|
|
Institute for High Performance Computing and Networking
7 publications, 1.8%
|
|
University of Amsterdam
7 publications, 1.8%
|
|
Ningbo University
6 publications, 1.54%
|
|
National Research Centre "Kurchatov Institute"
5 publications, 1.29%
|
|
Delft University of Technology
4 publications, 1.03%
|
|
University of Turin
4 publications, 1.03%
|
|
University of Memphis
4 publications, 1.03%
|
|
Moscow Institute of Physics and Technology
3 publications, 0.77%
|
|
Russian State University for the Humanities
3 publications, 0.77%
|
|
Delhi Technological University
3 publications, 0.77%
|
|
University of Trento
3 publications, 0.77%
|
|
Ruhr University Bochum
3 publications, 0.77%
|
|
Universidad Complutense de Madrid
3 publications, 0.77%
|
|
Skolkovo Institute of Science and Technology
2 publications, 0.51%
|
|
National Research University Higher School of Economics
2 publications, 0.51%
|
|
Novosibirsk State University
2 publications, 0.51%
|
|
Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences
2 publications, 0.51%
|
|
Artificial Intelligence Research Institute
2 publications, 0.51%
|
|
Scientific Research Institute for System Analysis of NRC «Kurchatov Institute»
2 publications, 0.51%
|
|
Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences
2 publications, 0.51%
|
|
Koc University
2 publications, 0.51%
|
|
Middle East Technical University
2 publications, 0.51%
|
|
University of Delhi
2 publications, 0.51%
|
|
Vellore Institute of Technology University
2 publications, 0.51%
|
|
National Institute of Technology Durgapur
2 publications, 0.51%
|
|
University of Tübingen
2 publications, 0.51%
|
|
Harbin Institute of Technology
2 publications, 0.51%
|
|
China University of Mining and Technology
2 publications, 0.51%
|
|
University Malaysia Pahang Al-Sultan Abdullah
2 publications, 0.51%
|
|
Mepco Schlenk Engineering College
2 publications, 0.51%
|
|
Hubei University of Technology
2 publications, 0.51%
|
|
University of Skövde
2 publications, 0.51%
|
|
Chongqing University of Posts and Telecommunications
2 publications, 0.51%
|
|
Northeastern University
2 publications, 0.51%
|
|
Shanxi University
2 publications, 0.51%
|
|
University of Jyväskylä
2 publications, 0.51%
|
|
University of Manchester
2 publications, 0.51%
|
|
Queensland University of Technology
2 publications, 0.51%
|
|
University of Southampton
2 publications, 0.51%
|
|
Deakin University
2 publications, 0.51%
|
|
New York University
2 publications, 0.51%
|
|
Shandong University
2 publications, 0.51%
|
|
Autonomous University of Madrid
2 publications, 0.51%
|
|
National Autonomous University of Mexico
2 publications, 0.51%
|
|
Leiden University
2 publications, 0.51%
|
|
Amsterdam University Medical Center
2 publications, 0.51%
|
|
Erasmus University Medical Center
2 publications, 0.51%
|
|
Universidad Carlos III de Madrid
2 publications, 0.51%
|
|
University of Ontario Institute of Technology
2 publications, 0.51%
|
|
University of Exeter
2 publications, 0.51%
|
|
Artificial Intelligence Research Institute
2 publications, 0.51%
|
|
Université Paris Dauphine-PSL
2 publications, 0.51%
|
|
Paris Sciences et Lettres
2 publications, 0.51%
|
|
Bauman Moscow State Technical University
1 publication, 0.26%
|
|
Moscow Aviation Institute (National Research University)
1 publication, 0.26%
|
|
P.N. Lebedev Physical Institute of the Russian Academy of Sciences
1 publication, 0.26%
|
|
ITMO University
1 publication, 0.26%
|
|
Peter the Great St. Petersburg Polytechnic University
1 publication, 0.26%
|
|
Sirius University of Science and Technology
1 publication, 0.26%
|
|
![]() Sobolev Institute of Mathematics of the Siberian Branch of the Russian Academy of Sciences
1 publication, 0.26%
|
|
Serbsky National Medical Research Center for Psychiatry and Narcology
1 publication, 0.26%
|
|
Federal Research Center Computer Science and Control of the Russian Academy of Sciences
1 publication, 0.26%
|
|
Russian Biotechnological University
1 publication, 0.26%
|
|
Moscow State Linguistic University
1 publication, 0.26%
|
|
Northern Border University
1 publication, 0.26%
|
|
Amirkabir University of Technology
1 publication, 0.26%
|
|
Iran University of Science and Technology
1 publication, 0.26%
|
|
Boğaziçi University
1 publication, 0.26%
|
|
Birla Institute of Technology and Science, Pilani
1 publication, 0.26%
|
|
Kermanshah University of Technology
1 publication, 0.26%
|
|
University of Science and Culture
1 publication, 0.26%
|
|
Indian Institute of Technology Kharagpur
1 publication, 0.26%
|
|
Imam Abdulrahman Bin Faisal University
1 publication, 0.26%
|
|
Indian Institute of Technology Roorkee
1 publication, 0.26%
|
|
Indian Institute of Technology Bhubaneswar
1 publication, 0.26%
|
|
Indian Institute of Technology (Banaras Hindu University) Varanasi
1 publication, 0.26%
|
|
Jadavpur University
1 publication, 0.26%
|
|
Anna University
1 publication, 0.26%
|
|
Savitribai Phule Pune University
1 publication, 0.26%
|
|
Lovely Professional University
1 publication, 0.26%
|
|
Alagappa University
1 publication, 0.26%
|
|
National Institute of Technology Rourkela
1 publication, 0.26%
|
|
National Institute of Technology Silchar
1 publication, 0.26%
|
|
National Institute of Technology Srinagar
1 publication, 0.26%
|
|
Babasaheb Bhimrao Ambedkar University
1 publication, 0.26%
|
|
Istanbul Medeniyet University
1 publication, 0.26%
|
|
Islamic Azad University, Tehran
1 publication, 0.26%
|
|
Islamic Azad University, Science and Research Branch
1 publication, 0.26%
|
|
JSS Academy of Higher Education & Research
1 publication, 0.26%
|
|
Kalasalingam Academy of Research and Education
1 publication, 0.26%
|
|
Visvesvaraya Technological University
1 publication, 0.26%
|
|
Zonguldak Bülent Ecevit University
1 publication, 0.26%
|
|
Ton Duc Thang University
1 publication, 0.26%
|
|
Duy Tan University
1 publication, 0.26%
|
|
Guru Ghasidas Vishwavidyalaya
1 publication, 0.26%
|
|
Shanghai Jiao Tong University
1 publication, 0.26%
|
|
Tel Aviv University
1 publication, 0.26%
|
|
Show all (70 more) | |
5
10
15
20
25
|
Publishing countries
50
100
150
200
250
300
|
|
USA
|
USA, 271, 20.25%
USA
271 publications, 20.25%
|
China
|
China, 191, 14.28%
China
191 publications, 14.28%
|
United Kingdom
|
United Kingdom, 93, 6.95%
United Kingdom
93 publications, 6.95%
|
India
|
India, 85, 6.35%
India
85 publications, 6.35%
|
Germany
|
Germany, 73, 5.46%
Germany
73 publications, 5.46%
|
Netherlands
|
Netherlands, 65, 4.86%
Netherlands
65 publications, 4.86%
|
Italy
|
Italy, 62, 4.63%
Italy
62 publications, 4.63%
|
Canada
|
Canada, 55, 4.11%
Canada
55 publications, 4.11%
|
Japan
|
Japan, 39, 2.91%
Japan
39 publications, 2.91%
|
Russia
|
Russia, 38, 2.84%
Russia
38 publications, 2.84%
|
Mexico
|
Mexico, 34, 2.54%
Mexico
34 publications, 2.54%
|
France
|
France, 30, 2.24%
France
30 publications, 2.24%
|
Australia
|
Australia, 26, 1.94%
Australia
26 publications, 1.94%
|
Sweden
|
Sweden, 26, 1.94%
Sweden
26 publications, 1.94%
|
Brazil
|
Brazil, 23, 1.72%
Brazil
23 publications, 1.72%
|
Spain
|
Spain, 22, 1.64%
Spain
22 publications, 1.64%
|
Republic of Korea
|
Republic of Korea, 20, 1.49%
Republic of Korea
20 publications, 1.49%
|
Iran
|
Iran, 17, 1.27%
Iran
17 publications, 1.27%
|
Poland
|
Poland, 15, 1.12%
Poland
15 publications, 1.12%
|
Malaysia
|
Malaysia, 12, 0.9%
Malaysia
12 publications, 0.9%
|
Turkey
|
Turkey, 12, 0.9%
Turkey
12 publications, 0.9%
|
Belgium
|
Belgium, 11, 0.82%
Belgium
11 publications, 0.82%
|
Finland
|
Finland, 11, 0.82%
Finland
11 publications, 0.82%
|
Denmark
|
Denmark, 10, 0.75%
Denmark
10 publications, 0.75%
|
Singapore
|
Singapore, 10, 0.75%
Singapore
10 publications, 0.75%
|
Austria
|
Austria, 9, 0.67%
Austria
9 publications, 0.67%
|
Portugal
|
Portugal, 6, 0.45%
Portugal
6 publications, 0.45%
|
Israel
|
Israel, 6, 0.45%
Israel
6 publications, 0.45%
|
Morocco
|
Morocco, 6, 0.45%
Morocco
6 publications, 0.45%
|
Pakistan
|
Pakistan, 6, 0.45%
Pakistan
6 publications, 0.45%
|
Greece
|
Greece, 5, 0.37%
Greece
5 publications, 0.37%
|
Saudi Arabia
|
Saudi Arabia, 5, 0.37%
Saudi Arabia
5 publications, 0.37%
|
Egypt
|
Egypt, 4, 0.3%
Egypt
4 publications, 0.3%
|
Norway
|
Norway, 4, 0.3%
Norway
4 publications, 0.3%
|
Slovakia
|
Slovakia, 4, 0.3%
Slovakia
4 publications, 0.3%
|
Chile
|
Chile, 4, 0.3%
Chile
4 publications, 0.3%
|
Switzerland
|
Switzerland, 4, 0.3%
Switzerland
4 publications, 0.3%
|
South Africa
|
South Africa, 4, 0.3%
South Africa
4 publications, 0.3%
|
Algeria
|
Algeria, 3, 0.22%
Algeria
3 publications, 0.22%
|
Hungary
|
Hungary, 3, 0.22%
Hungary
3 publications, 0.22%
|
Indonesia
|
Indonesia, 3, 0.22%
Indonesia
3 publications, 0.22%
|
Jordan
|
Jordan, 3, 0.22%
Jordan
3 publications, 0.22%
|
Iraq
|
Iraq, 3, 0.22%
Iraq
3 publications, 0.22%
|
Colombia
|
Colombia, 3, 0.22%
Colombia
3 publications, 0.22%
|
Tunisia
|
Tunisia, 3, 0.22%
Tunisia
3 publications, 0.22%
|
Czech Republic
|
Czech Republic, 3, 0.22%
Czech Republic
3 publications, 0.22%
|
Vietnam
|
Vietnam, 2, 0.15%
Vietnam
2 publications, 0.15%
|
Ireland
|
Ireland, 2, 0.15%
Ireland
2 publications, 0.15%
|
UAE
|
UAE, 2, 0.15%
UAE
2 publications, 0.15%
|
Serbia
|
Serbia, 2, 0.15%
Serbia
2 publications, 0.15%
|
Slovenia
|
Slovenia, 2, 0.15%
Slovenia
2 publications, 0.15%
|
Ukraine
|
Ukraine, 1, 0.07%
Ukraine
1 publication, 0.07%
|
Estonia
|
Estonia, 1, 0.07%
Estonia
1 publication, 0.07%
|
Argentina
|
Argentina, 1, 0.07%
Argentina
1 publication, 0.07%
|
Bangladesh
|
Bangladesh, 1, 0.07%
Bangladesh
1 publication, 0.07%
|
Bulgaria
|
Bulgaria, 1, 0.07%
Bulgaria
1 publication, 0.07%
|
Ghana
|
Ghana, 1, 0.07%
Ghana
1 publication, 0.07%
|
Lebanon
|
Lebanon, 1, 0.07%
Lebanon
1 publication, 0.07%
|
Liechtenstein
|
Liechtenstein, 1, 0.07%
Liechtenstein
1 publication, 0.07%
|
Luxembourg
|
Luxembourg, 1, 0.07%
Luxembourg
1 publication, 0.07%
|
Nigeria
|
Nigeria, 1, 0.07%
Nigeria
1 publication, 0.07%
|
Oman
|
Oman, 1, 0.07%
Oman
1 publication, 0.07%
|
Peru
|
Peru, 1, 0.07%
Peru
1 publication, 0.07%
|
Rwanda
|
Rwanda, 1, 0.07%
Rwanda
1 publication, 0.07%
|
Romania
|
Romania, 1, 0.07%
Romania
1 publication, 0.07%
|
Thailand
|
Thailand, 1, 0.07%
Thailand
1 publication, 0.07%
|
Sri Lanka
|
Sri Lanka, 1, 0.07%
Sri Lanka
1 publication, 0.07%
|
Show all (37 more) | |
50
100
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200
250
300
|
Publishing countries in 5 years
10
20
30
40
50
60
|
|
China
|
China, 57, 14.65%
China
57 publications, 14.65%
|
Russia
|
Russia, 33, 8.48%
Russia
33 publications, 8.48%
|
Netherlands
|
Netherlands, 28, 7.2%
Netherlands
28 publications, 7.2%
|
India
|
India, 26, 6.68%
India
26 publications, 6.68%
|
USA
|
USA, 25, 6.43%
USA
25 publications, 6.43%
|
Mexico
|
Mexico, 23, 5.91%
Mexico
23 publications, 5.91%
|
United Kingdom
|
United Kingdom, 17, 4.37%
United Kingdom
17 publications, 4.37%
|
Germany
|
Germany, 15, 3.86%
Germany
15 publications, 3.86%
|
Italy
|
Italy, 13, 3.34%
Italy
13 publications, 3.34%
|
Spain
|
Spain, 9, 2.31%
Spain
9 publications, 2.31%
|
Canada
|
Canada, 9, 2.31%
Canada
9 publications, 2.31%
|
France
|
France, 8, 2.06%
France
8 publications, 2.06%
|
Australia
|
Australia, 8, 2.06%
Australia
8 publications, 2.06%
|
Sweden
|
Sweden, 8, 2.06%
Sweden
8 publications, 2.06%
|
Turkey
|
Turkey, 7, 1.8%
Turkey
7 publications, 1.8%
|
Iran
|
Iran, 6, 1.54%
Iran
6 publications, 1.54%
|
Japan
|
Japan, 6, 1.54%
Japan
6 publications, 1.54%
|
Brazil
|
Brazil, 4, 1.03%
Brazil
4 publications, 1.03%
|
Denmark
|
Denmark, 3, 0.77%
Denmark
3 publications, 0.77%
|
Malaysia
|
Malaysia, 3, 0.77%
Malaysia
3 publications, 0.77%
|
Republic of Korea
|
Republic of Korea, 3, 0.77%
Republic of Korea
3 publications, 0.77%
|
Tunisia
|
Tunisia, 3, 0.77%
Tunisia
3 publications, 0.77%
|
Finland
|
Finland, 3, 0.77%
Finland
3 publications, 0.77%
|
Chile
|
Chile, 3, 0.77%
Chile
3 publications, 0.77%
|
Portugal
|
Portugal, 2, 0.51%
Portugal
2 publications, 0.51%
|
Vietnam
|
Vietnam, 2, 0.51%
Vietnam
2 publications, 0.51%
|
Israel
|
Israel, 2, 0.51%
Israel
2 publications, 0.51%
|
Indonesia
|
Indonesia, 2, 0.51%
Indonesia
2 publications, 0.51%
|
Morocco
|
Morocco, 2, 0.51%
Morocco
2 publications, 0.51%
|
Norway
|
Norway, 2, 0.51%
Norway
2 publications, 0.51%
|
Poland
|
Poland, 2, 0.51%
Poland
2 publications, 0.51%
|
Saudi Arabia
|
Saudi Arabia, 2, 0.51%
Saudi Arabia
2 publications, 0.51%
|
Ukraine
|
Ukraine, 1, 0.26%
Ukraine
1 publication, 0.26%
|
Bangladesh
|
Bangladesh, 1, 0.26%
Bangladesh
1 publication, 0.26%
|
Belgium
|
Belgium, 1, 0.26%
Belgium
1 publication, 0.26%
|
Ghana
|
Ghana, 1, 0.26%
Ghana
1 publication, 0.26%
|
Egypt
|
Egypt, 1, 0.26%
Egypt
1 publication, 0.26%
|
Jordan
|
Jordan, 1, 0.26%
Jordan
1 publication, 0.26%
|
Oman
|
Oman, 1, 0.26%
Oman
1 publication, 0.26%
|
Peru
|
Peru, 1, 0.26%
Peru
1 publication, 0.26%
|
Singapore
|
Singapore, 1, 0.26%
Singapore
1 publication, 0.26%
|
Slovenia
|
Slovenia, 1, 0.26%
Slovenia
1 publication, 0.26%
|
Switzerland
|
Switzerland, 1, 0.26%
Switzerland
1 publication, 0.26%
|
South Africa
|
South Africa, 1, 0.26%
South Africa
1 publication, 0.26%
|
Show all (14 more) | |
10
20
30
40
50
60
|
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