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For: Pang Z, Zhou G, Chong J, Xia J. Comprehensive Meta-Analysis of COVID-19 Global Metabolomics Datasets. Metabolites 2021;11:44. [PMID: 33435351 DOI: 10.3390/metabo11010044] [Cited by in Crossref: 10] [Cited by in F6Publishing: 36] [Article Influence: 10.0] [Reference Citation Analysis]
Number Citing Articles
1 Tedesco R, Scalabrin E, Malagnini V, Strojnik L, Ogrinc N, Capodaglio G. Characterization of Botanical Origin of Italian Honey by Carbohydrate Composition and Volatile Organic Compounds (VOCs). Foods 2022;11:2441. [PMID: 36010441 DOI: 10.3390/foods11162441] [Reference Citation Analysis]
2 Liu J, Li Z, Lu Q, Yu Y, Zhang S, Ke P, Zhang F, Li J. Metabolite profile of COVID-19 revealed by UPLC-MS/MS-based widely targeted metabolomics. Front Immunol 2022;13:894170. [DOI: 10.3389/fimmu.2022.894170] [Reference Citation Analysis]
3 Spick M, Lewis HM, Frampas CF, Longman K, Costa C, Stewart A, Dunn-Walters D, Greener D, Evetts G, Wilde MJ, Sinclair E, Barran PE, Skene DJ, Bailey MJ. An integrated analysis and comparison of serum, saliva and sebum for COVID-19 metabolomics. Sci Rep 2022;12:11867. [PMID: 35831456 DOI: 10.1038/s41598-022-16123-4] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Correia BSB, Ferreira VG, Piagge PMFD, Almeida MB, Assunção NA, Raimundo JRS, Fonseca FLA, Carrilho E, Cardoso DR. 1H qNMR-Based Metabolomics Discrimination of Covid-19 Severity. J Proteome Res 2022. [PMID: 35674498 DOI: 10.1021/acs.jproteome.1c00977] [Reference Citation Analysis]
5 de Fátima Cobre A, Surek M, Stremel DP, Fachi MM, Lobo Borba HH, Tonin FS, Pontarolo R. Diagnosis and prognosis of COVID-19 employing analysis of patients' plasma and serum via LC-MS and machine learning. Computers in Biology and Medicine 2022;146:105659. [DOI: 10.1016/j.compbiomed.2022.105659] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
6 Ceballos FC, Virseda-berdices A, Resino S, Ryan P, Martínez-gonzález O, Peréz-garcía F, Martin-vicente M, Brochado-kith O, Blancas R, Bartolome-sánchez S, Vidal-alcántara EJ, Albóniga-díez OE, Cuadros-gonzález J, Blanca-lópez N, Martínez I, Martinez-acitores IR, Barbas C, Fernández-rodríguez A, Jiménez-sousa MÁ. Metabolic Profiling at COVID-19 Onset Shows Disease Severity and Sex-Specific Dysregulation. Front Immunol 2022;13:925558. [DOI: 10.3389/fimmu.2022.925558] [Reference Citation Analysis]
7 Henglin M, Claggett BL, Antonelli J, Alotaibi M, Magalang GA, Watrous JD, Lagerborg KA, Ovsak G, Musso G, Demler OV, Vasan RS, Larson MG, Jain M, Cheng S. Quantitative Comparison of Statistical Methods for Analyzing Human Metabolomics Data. Metabolites 2022;12:519. [DOI: 10.3390/metabo12060519] [Reference Citation Analysis]
8 Oliveira LB, Mwangi VI, Sartim MA, Delafiori J, Sales GM, de Oliveira AN, Busanello ENB, Val FFAE, Xavier MS, Costa FT, Baía-da-Silva DC, Sampaio VS, de Lacerda MVG, Monteiro WM, Catharino RR, de Melo GC. Metabolomic Profiling of Plasma Reveals Differential Disease Severity Markers in COVID-19 Patients. Front Microbiol 2022;13:844283. [PMID: 35572676 DOI: 10.3389/fmicb.2022.844283] [Reference Citation Analysis]
9 Phuoc Long N, Heo DY, Park S, Thi Hai Yen N, Cho YS, Shin JG, Oh JY, Kim DH. Molecular perturbations in pulmonary tuberculosis patients identified by pathway-level analysis of plasma metabolic features. PLoS One 2022;17:e0262545. [PMID: 35073339 DOI: 10.1371/journal.pone.0262545] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
10 Albóniga OE, Jiménez D, Sánchez-Conde M, Vizcarra P, Ron R, Herrera S, Martínez-Sanz J, Moreno E, Moreno S, Barbas C, Serrano-Villar S. Metabolic Snapshot of Plasma Samples Reveals New Pathways Implicated in SARS-CoV-2 Pathogenesis. J Proteome Res 2022. [PMID: 35133846 DOI: 10.1021/acs.jproteome.1c00786] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
11 Xue J, Liu P, Guo G, Wang W, Zhang J, Wang W, Le T, Yin J, Ni D, Jiang H. Profiling of dynamic changes in non-volatile metabolites of shaken black tea during the manufacturing process using targeted and non-targeted metabolomics analysis. LWT 2022;156:113010. [DOI: 10.1016/j.lwt.2021.113010] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 5.0] [Reference Citation Analysis]
12 Valdés A, Moreno LO, Rello SR, Orduña A, Bernardo D, Cifuentes A. Metabolomics study of COVID-19 patients in four different clinical stages. Sci Rep 2022;12:1650. [PMID: 35102215 DOI: 10.1038/s41598-022-05667-0] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 9.0] [Reference Citation Analysis]
13 Sudhakar M, Winfred SB, Meiyazhagan G, Venkatachalam DP. Mechanisms contributing to adverse outcomes of COVID-19 in obesity. Mol Cell Biochem 2022. [PMID: 35084674 DOI: 10.1007/s11010-022-04356-w] [Cited by in Crossref: 6] [Article Influence: 6.0] [Reference Citation Analysis]
14 Tan C, Tao F, Xu P. Direct carbon capture for the production of high-performance biodegradable plastics by cyanobacterial cell factories. Green Chem . [DOI: 10.1039/d1gc04188f] [Reference Citation Analysis]
15 Pellegrino RM, Giulietti M, Alabed HBR, Buratta S, Urbanelli L, Piva F, Emiliani C. LipidOne: user-friendly lipidomic data analysis tool for a deeper interpretation in a systems biology scenario. Bioinformatics 2021:btab867. [PMID: 34971364 DOI: 10.1093/bioinformatics/btab867] [Reference Citation Analysis]
16 Ansone L, Briviba M, Silamikelis I, Terentjeva A, Perkons I, Birzniece L, Rovite V, Rozentale B, Viksna L, Kolesova O, Klavins K, Klovins J. Amino Acid Metabolism is Significantly Altered at the Time of Admission in Hospital for Severe COVID-19 Patients: Findings from Longitudinal Targeted Metabolomics Analysis. Microbiol Spectr 2021;9:e0033821. [PMID: 34878333 DOI: 10.1128/spectrum.00338-21] [Cited by in F6Publishing: 8] [Reference Citation Analysis]
17 Bauer W, Weber M, Diehl-wiesenecker E, Galtung N, Prpic M, Somasundaram R, Tauber R, Schwenk JM, Micke P, Kappert K. Plasma Proteome Fingerprints Reveal Distinctiveness and Clinical Outcome of SARS-CoV-2 Infection. Viruses 2021;13:2456. [DOI: 10.3390/v13122456] [Cited by in F6Publishing: 4] [Reference Citation Analysis]
18 Suntichaikamolkul N, Sangpong L, Schaller H, Sirikantaramas S. Genome-wide identification and expression profiling of durian CYPome related to fruit ripening. PLoS One 2021;16:e0260665. [PMID: 34847184 DOI: 10.1371/journal.pone.0260665] [Reference Citation Analysis]
19 Panebianco F, Nava V, Giarratana F, Gervasi T, Cicero N. Assessment of heavy- and semi-metals contamination in edible seaweed and dried fish sold in ethnic food stores on the Italian market. Journal of Food Composition and Analysis 2021;104:104150. [DOI: 10.1016/j.jfca.2021.104150] [Cited by in Crossref: 1] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
20 Ten-Doménech I, Moreno-Torres M, Castell JV, Quintás G, Kuligowski J. Extracting consistent biological information from functional results of metabolomic pathway analysis using the Mantel's test. Anal Chim Acta 2021;1187:339173. [PMID: 34753565 DOI: 10.1016/j.aca.2021.339173] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
21 Lorente JA, Nin N, Villa P, Vasco D, Miguel-Coello AB, Rodriguez I, Herrero R, Peñuelas O, Ruiz-Cabello J, Izquierdo-Garcia JL. Metabolomic diferences between COVID-19 and H1N1 influenza induced ARDS. Crit Care 2021;25:390. [PMID: 34781986 DOI: 10.1186/s13054-021-03810-3] [Cited by in F6Publishing: 4] [Reference Citation Analysis]
22 Spick M, Lewis HM, Wilde MJ, Hopley C, Huggett J, Bailey MJ. Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry. Metabolism 2021;126:154922. [PMID: 34715115 DOI: 10.1016/j.metabol.2021.154922] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
23 Lassen J, Nielsen KL, Johannsen M, Villesen P. Assessment of XCMS Optimization Methods with Machine-Learning Performance. Anal Chem 2021;93:13459-66. [PMID: 34585906 DOI: 10.1021/acs.analchem.1c02000] [Reference Citation Analysis]
24 Raines NH, Cheung MD, Wilson LS, Edberg JC, Erdmann NB, Schmaier AA, Berryhill TF, Manickas-Hill Z, Li JZ, Yu XG, Agarwal A, Barnes S, Parikh SM. NAD+ biosynthetic impairment and urinary metabolomic alterations observed in hospitalized adults with COVID-19-related acute kidney injury. Kidney Int Rep 2021. [PMID: 34541422 DOI: 10.1016/j.ekir.2021.09.001] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
25 Zhou H, Liu J, Cui X, Xu L. Research on Influencing Factors of Adoption Behavior of Mobile Readers Based on Meta-Analysis. Mathematical Problems in Engineering 2021;2021:1-13. [DOI: 10.1155/2021/5082594] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
26 Angamuthu S, R. Ramaswamy C, Thangaswamy S, Sadhasivam DR, Nallaswamy VD, Subramanian R, Ganesan R, Raju A. Metabolic annotation, interactions and characterization of natural products of mango (Mangifera indica L.): 1H NMR based chemical metabolomics profiling. Process Biochemistry 2021;108:18-25. [DOI: 10.1016/j.procbio.2021.05.024] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
27 Castelli FA, Rosati G, Moguet C, Fuentes C, Marrugo-Ramírez J, Lefebvre T, Volland H, Merkoçi A, Simon S, Fenaille F, Junot C. Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests. Anal Bioanal Chem 2021. [PMID: 34432105 DOI: 10.1007/s00216-021-03586-z] [Cited by in Crossref: 1] [Cited by in F6Publishing: 7] [Article Influence: 1.0] [Reference Citation Analysis]
28 Mussap M, Fanos V. Could metabolomics drive the fate of COVID-19 pandemic? A narrative review on lights and shadows. Clin Chem Lab Med 2021. [PMID: 34332518 DOI: 10.1515/cclm-2021-0414] [Cited by in F6Publishing: 11] [Reference Citation Analysis]
29 Pang Z, Chong J, Zhou G, de Lima Morais DA, Chang L, Barrette M, Gauthier C, Jacques PÉ, Li S, Xia J. MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights. Nucleic Acids Res 2021;49:W388-96. [PMID: 34019663 DOI: 10.1093/nar/gkab382] [Cited by in Crossref: 16] [Cited by in F6Publishing: 530] [Article Influence: 16.0] [Reference Citation Analysis]
30 Banerjee A, Gokhale A, Bankar R, Palanivel V, Salkar A, Robinson H, Shastri JS, Agrawal S, Hartel G, Hill MM, Srivastava S. Rapid Classification of COVID-19 Severity by ATR-FTIR Spectroscopy of Plasma Samples. Anal Chem 2021;93:10391-6. [PMID: 34279898 DOI: 10.1021/acs.analchem.1c00596] [Cited by in F6Publishing: 10] [Reference Citation Analysis]
31 López-Hernández Y, Monárrez-Espino J, Oostdam AH, Delgado JEC, Zhang L, Zheng J, Valdez JJO, Mandal R, González FLO, Moreno JCB, Trejo-Medinilla FM, López JA, Moreno JAE, Wishart DS. Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19. Sci Rep 2021;11:14732. [PMID: 34282210 DOI: 10.1038/s41598-021-94171-y] [Cited by in F6Publishing: 8] [Reference Citation Analysis]
32 Bogunia-Kubik K, Wojtowicz W, Swierkot J, Mielko KA, Qasem B, Wielińska J, Sokolik R, Pruss Ł, Młynarz P. Disease Differentiation and Monitoring of Anti-TNF Treatment in Rheumatoid Arthritis and Spondyloarthropathies. Int J Mol Sci 2021;22:7389. [PMID: 34299006 DOI: 10.3390/ijms22147389] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
33 Sangpong L, Khaksar G, Pinsorn P, Oikawa A, Sasaki R, Erban A, Watanabe M, Wangpaiboon K, Tohge T, Kopka J, Hoefgen R, Saito K, Sirikantaramas S. Assessing Dynamic Changes of Taste-Related Primary Metabolism During Ripening of Durian Pulp Using Metabolomic and Transcriptomic Analyses. Front Plant Sci 2021;12:687799. [PMID: 34220909 DOI: 10.3389/fpls.2021.687799] [Cited by in Crossref: 1] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
34 Angoa-Pérez M, Zagorac B, Francescutti DM, Theis KR, Kuhn DM. Effects of gut microbiota remodeling on the dysbiosis induced by high fat diet in a mouse model of Gulf war illness. Life Sci 2021;279:119675. [PMID: 34081987 DOI: 10.1016/j.lfs.2021.119675] [Reference Citation Analysis]
35 Beale DJ, Shah R, Karpe AV, Hillyer KE, McAuley AJ, Au GG, Marsh GA, Vasan SS. Metabolic Profiling from an Asymptomatic Ferret Model of SARS-CoV-2 Infection. Metabolites 2021;11:327. [PMID: 34069591 DOI: 10.3390/metabo11050327] [Cited by in F6Publishing: 8] [Reference Citation Analysis]
36 Baranovicova E, Bobcakova A, Vysehradsky R, Dankova Z, Halasova E, Nosal V, Lehotsky J. The Ability to Normalise Energy Metabolism in Advanced COVID-19 Disease Seems to Be One of the Key Factors Determining the Disease Progression—A Metabolomic NMR Study on Blood Plasma. Applied Sciences 2021;11:4231. [DOI: 10.3390/app11094231] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]