000167479 001__ 167479
000167479 005__ 20240229133542.0
000167479 0247_ $$2pmid$$apmid:33592132
000167479 0247_ $$2ISSN$$a0027-769X
000167479 0247_ $$2ISSN$$a1521-3803
000167479 0247_ $$2ISSN$$a1613-4125
000167479 0247_ $$2ISSN$$a1613-4133
000167479 0247_ $$2doi$$adoi: 10.1002/mnfr.202001141. 
000167479 0247_ $$2doi$$adoi: 10.1002/mnfr.202001141.
000167479 037__ $$aDKFZ-2021-00380
000167479 041__ $$aeng
000167479 082__ $$a540
000167479 1001_ $$aWedekind, Roland$$b0
000167479 245__ $$aPepper Alkaloids and Processed Meat Intake: Results From a randomized Trial and the EUROPEAN Prospective Investigation on Cancer and Nutrition (EPIC) Cohort.
000167479 260__ $$aWeinheim$$bWiley-VCH$$c2021
000167479 3367_ $$2DRIVER$$aarticle
000167479 3367_ $$2DataCite$$aOutput Types/Journal article
000167479 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1619614667_20848
000167479 3367_ $$2BibTeX$$aARTICLE
000167479 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000167479 3367_ $$00$$2EndNote$$aJournal Article
000167479 500__ $$a2021 Apr;65(7):e2001141
000167479 520__ $$aProcessed meat intake has been associated with adverse health outcomes. However, little is known about the type of processed meat more particularly responsible for these effects. This study aims to identify novel biomarkers for processed meat intake.In a controlled randomized cross-over dietary intervention study, 12 healthy volunteers consumed different processed and non-processed meats for 3 consecutive days each. Metabolomics analyses were applied on post-intervention fasting blood and urine samples to identify discriminating molecular features of processed meat intake. Nine and five pepper alkaloid metabolites, including piperine, were identified as major discriminants of salami intake in urine and plasma, respectively. This article is protected by copyright. All rights reserved CONCLUSION: Pepper alkaloids are major discriminants of intake for sausages which contain high levels of pepper used as ingredient. Further work is needed to assess if pepper alkaloids in combination with other metabolites may serve as biomarkers of processed meat intake.
000167479 536__ $$0G:(DE-HGF)POF4-313$$a313 - Krebsrisikofaktoren und Prävention (POF4-313)$$cPOF4-313$$fPOF IV$$x0
000167479 588__ $$aDataset connected to PubMed,
000167479 650_7 $$2Other$$aBiomarkers of intake
000167479 650_7 $$2Other$$ametabolomics
000167479 650_7 $$2Other$$apepper alkaloids
000167479 650_7 $$2Other$$apiperine
000167479 650_7 $$2Other$$aprocessed meat
000167479 7001_ $$aKeski-Rahkonen, Pekka$$b1
000167479 7001_ $$aRobinot, Nivonirina$$b2
000167479 7001_ $$aViallon, Vivian$$b3
000167479 7001_ $$aRothwell, Joseph A$$b4
000167479 7001_ $$aBoutron-Ruault, Marie-Christine$$b5
000167479 7001_ $$aAleksandrova, Krasimira$$b6
000167479 7001_ $$aWittenbecher, Clemens$$b7
000167479 7001_ $$aSchulze, Matthias B$$b8
000167479 7001_ $$aHalkjaer, Jytte$$b9
000167479 7001_ $$aRostgaard-Hansen, Agnetha Linn$$b10
000167479 7001_ $$0P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aKaaks, Rudolf$$b11$$udkfz
000167479 7001_ $$0P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4$$aKatzke, Verena$$b12$$udkfz
000167479 7001_ $$aMasala, Giovanna$$b13
000167479 7001_ $$aTumino, Rosario$$b14
000167479 7001_ $$ade Magistris, Maria Santucci$$b15
000167479 7001_ $$aKrogh, Vittorio$$b16
000167479 7001_ $$aSacerdote, Carlotta$$b17
000167479 7001_ $$aJakszyn, Paula$$b18
000167479 7001_ $$aWeiderpass, Elisabete$$b19
000167479 7001_ $$aGunter, Marc J$$b20
000167479 7001_ $$aHuybrechts, Inge$$b21
000167479 7001_ $$00000-0001-6651-6710$$aScalbert, Augustin$$b22
000167479 773__ $$0PERI:(DE-600)2160372-8$$a10.1002/mnfr.202001141.$$n7$$pe2001141$$tMolecular nutrition & food research$$v65$$x1613-4125$$y2021
000167479 909CO $$ooai:inrepo02.dkfz.de:167479$$pVDB
000167479 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aDeutsches Krebsforschungszentrum$$b11$$kDKFZ
000167479 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4$$aDeutsches Krebsforschungszentrum$$b12$$kDKFZ
000167479 9130_ $$0G:(DE-HGF)POF3-313$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vCancer risk factors and prevention$$x0
000167479 9131_ $$0G:(DE-HGF)POF4-313$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vKrebsrisikofaktoren und Prävention$$x0
000167479 9141_ $$y2021
000167479 915__ $$0StatID:(DE-HGF)3001$$2StatID$$aDEAL Wiley$$d2020-09-15$$wger
000167479 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bMOL NUTR FOOD RES : 2018$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2020-09-15
000167479 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2020-09-15
000167479 9201_ $$0I:(DE-He78)C020-20160331$$kC020$$lC020 Epidemiologie von Krebs$$x0
000167479 980__ $$ajournal
000167479 980__ $$aVDB
000167479 980__ $$aI:(DE-He78)C020-20160331
000167479 980__ $$aUNRESTRICTED