Tissue, urine and serum NMR metabolomics dataset from a 5/6 nephrectomy rat model of chronic kidney disease

Munsoor Ali Hanifa; Martin Skott; Raluca G Maltesen; Bodil Steen Rasmussen; Søren Nielsen; Jørgen Frøkiær; Troels Ring; Reinhard Wimmer

doi:10.1016/j.dib.2020.106567

Tissue, urine and serum NMR metabolomics dataset from a 5/6 nephrectomy rat model of chronic kidney disease

Munsoor Ali Hanifa, Martin Skott, Raluca G Maltesen, Bodil Steen Rasmussen, Søren Nielsen, Jørgen Frøkiær, Troels Ring, Reinhard Wimmer

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

3 Citationer (Scopus)

46 Downloads (Pure)

Abstract

Serum, urine and tissue from a rat model of chronic kidney disease (CKD) were analysed using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics methods, and compared with samples from sham operated rats. Both urine and serum were sampled at multiple timepoints, and the results have been reported elsewhere (https://doi.org/10.1007/s11306-019-1569-3[1]). The data could be useful to researchers working with human CKD or rat models of the disease. In addition, several different types of NMR spectra were recorded, including 1D NOESY, CPMG, and 2D J-resolved spectra, and the data could be useful for method comparison and algorithm development, both in terms of NMR spectroscopy and multivariate analysis.

Originalsprog	Engelsk
Artikelnummer	106567
Tidsskrift	Data in Brief
Vol/bind	33
Sider (fra-til)	106567
Antal sider	5
ISSN	2352-3409
DOI	https://doi.org/10.1016/j.dib.2020.106567
Status	Udgivet - 23 nov. 2020

Adgang til dokumentet

10.1016/j.dib.2020.106567Licens: CC BY 4.0

Hanifa et al (2020) Tissue, urine and serum NMR metabolomics datasetForlagets udgivne version, 298 KBLicens: CC BY 4.0

AUB Link

Søg efter materialet i Aalborg Universitetsbiblioteks søgemaskine

Andre filer og links

Link to publication in Scopus

3 Citationer
1 Ph.d.-afhandling

NMR-Based Metabolomics in Kidney and Lung Disease: investigating metabolite biomarkers in a rat chronic kidney disease model and in human lung injury
Hanifa, M. A., 2020, Aalborg Universitetsforlag. 117 s.
Publikation: Ph.d.-afhandling

Åben adgang
Fil

Citationsformater

@article{41cd9aae1a014bb2bd773ce0610f4dde,

title = "Tissue, urine and serum NMR metabolomics dataset from a 5/6 nephrectomy rat model of chronic kidney disease",

abstract = "Serum, urine and tissue from a rat model of chronic kidney disease (CKD) were analysed using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics methods, and compared with samples from sham operated rats. Both urine and serum were sampled at multiple timepoints, and the results have been reported elsewhere (https://doi.org/10.1007/s11306-019-1569-3[1]). The data could be useful to researchers working with human CKD or rat models of the disease. In addition, several different types of NMR spectra were recorded, including 1D NOESY, CPMG, and 2D J-resolved spectra, and the data could be useful for method comparison and algorithm development, both in terms of NMR spectroscopy and multivariate analysis.",

keywords = "5/6 Nephrectomy, Chronic kidney disease, Metabolomics, NMR, Rat",

author = "Hanifa, {Munsoor Ali} and Martin Skott and Maltesen, {Raluca G} and Rasmussen, {Bodil Steen} and S{\o}ren Nielsen and J{\o}rgen Fr{\o}ki{\ae}r and Troels Ring and Reinhard Wimmer",

note = "{\textcopyright} 2020 The Authors.",

year = "2020",

month = nov,

day = "23",

doi = "10.1016/j.dib.2020.106567",

language = "English",

volume = "33",

pages = "106567",

journal = "Data in Brief",

issn = "2352-3409",

publisher = "Elsevier",

}

TY - JOUR

T1 - Tissue, urine and serum NMR metabolomics dataset from a 5/6 nephrectomy rat model of chronic kidney disease

AU - Hanifa, Munsoor Ali

AU - Skott, Martin

AU - Maltesen, Raluca G

AU - Rasmussen, Bodil Steen

AU - Nielsen, Søren

AU - Frøkiær, Jørgen

AU - Ring, Troels

AU - Wimmer, Reinhard

PY - 2020/11/23

Y1 - 2020/11/23

N2 - Serum, urine and tissue from a rat model of chronic kidney disease (CKD) were analysed using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics methods, and compared with samples from sham operated rats. Both urine and serum were sampled at multiple timepoints, and the results have been reported elsewhere (https://doi.org/10.1007/s11306-019-1569-3[1]). The data could be useful to researchers working with human CKD or rat models of the disease. In addition, several different types of NMR spectra were recorded, including 1D NOESY, CPMG, and 2D J-resolved spectra, and the data could be useful for method comparison and algorithm development, both in terms of NMR spectroscopy and multivariate analysis.

AB - Serum, urine and tissue from a rat model of chronic kidney disease (CKD) were analysed using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics methods, and compared with samples from sham operated rats. Both urine and serum were sampled at multiple timepoints, and the results have been reported elsewhere (https://doi.org/10.1007/s11306-019-1569-3[1]). The data could be useful to researchers working with human CKD or rat models of the disease. In addition, several different types of NMR spectra were recorded, including 1D NOESY, CPMG, and 2D J-resolved spectra, and the data could be useful for method comparison and algorithm development, both in terms of NMR spectroscopy and multivariate analysis.

KW - 5/6 Nephrectomy

KW - Chronic kidney disease

KW - Metabolomics

KW - NMR

KW - Rat

UR - http://www.scopus.com/inward/record.url?scp=85097448659&partnerID=8YFLogxK

U2 - 10.1016/j.dib.2020.106567

DO - 10.1016/j.dib.2020.106567

M3 - Journal article

C2 - 33304964

SN - 2352-3409

VL - 33

SP - 106567

JO - Data in Brief

JF - Data in Brief

M1 - 106567

ER -

Tissue, urine and serum NMR metabolomics dataset from a 5/6 nephrectomy rat model of chronic kidney disease

Abstract

Adgang til dokumentet

AUB Link

Andre filer og links

Fingeraftryk

Publikation

NMR-Based Metabolomics in Kidney and Lung Disease: investigating metabolite biomarkers in a rat chronic kidney disease model and in human lung injury

Citationsformater