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Metabolic trajectory characterisation of xenobiotic-induced hepatotoxic lesions using statistical batch processing of NMR data : Nicholson Jeremy K., Holmes Elaine

Azmi, Jahanara (författare)
Griffin, Julian L (författare)
Antti, Henrik (författare)
Umeå universitet,Kemiska institutionen
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Shore, Richard F (författare)
Johansson, Erik (författare)
Nicholson, Jeremy K (författare)
Holmes, Elaine (författare)
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 (creator_code:org_t)
2002-01-21
2002
Engelska.
Ingår i: Analyst. - : Royal Society of Chemistry (RSC). ; 127, s. 271-6
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Multivariate statistical batch processing (BP) analysis of 1H NMR urine spectra was employed to establish time-dependent metabolic variations in animals treated with the model hepatotoxin, -naphthylisothiocyanate (ANIT). ANIT (100 mg kg-1) was administered orally to rats (n = 5) and urine samples were collected from dosed and matching control rats at time-points up to 168 h post-dose. Urine samples were measured via1H NMR spectroscopy and partial least squares (PLS) based batch processing analysis was used to interpret the spectral data, treating each rat as an individual batch comprising a series of timed urine samples. A model defining the mean urine profile over the 7 day study period was established, together with model confidence limits (±3 standard deviation), for the control group. Samples obtained from ANIT treated animals were evaluated using the control model. Time-dependent deviations from the control model were evident in all ANIT treated animals consisting of glycosuria, bile aciduria, an initial decrease in taurine levels followed by taurinuria and a reduction of tricarboxylic acid cycle intermediate excretion. BP provided an efficient means of visualising the biochemical response to ANIT in terms of both inter-animal variation and net variation in metabolite excretion profiles. BP also allowed multivariate statistical limits for normality to be established and provided a template for defining the sequence of time-dependent metabolic consequences of toxicity in NMR based metabonomic studies.

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