| 000 | 02637cam a2200277zu 4500 | ||
|---|---|---|---|
| 001 | 88831976 | ||
| 003 | FRCYB88831976 | ||
| 005 | 20250107103856.0 | ||
| 006 | m o d | ||
| 007 | cr un | ||
| 008 | 250107s2016 fr | o|||||0|0|||eng d | ||
| 020 | _a9780128003442 | ||
| 035 | _aFRCYB88831976 | ||
| 040 |
_aFR-PaCSA _ben _c _erda |
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| 100 | 1 | _aNicholson, Jeremy | |
| 245 | 0 | 1 |
_aMetabolic Phenotyping in Personalized and Public Healthcare _c['Nicholson, Jeremy'] |
| 264 | 1 |
_bElsevier Science _c2016 |
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| 300 | _a p. | ||
| 336 |
_btxt _2rdacontent |
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| 337 |
_bc _2rdamdedia |
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| 338 |
_bc _2rdacarrier |
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| 650 | 0 | _a | |
| 700 | 0 | _aNicholson, Jeremy | |
| 856 | 4 | 0 |
_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88831976 _qtext/html _a |
| 520 | _aMetabolic Phenotyping in Personalized and Public Healthcare provides information on the widespread recognition that a personalized or stratified approach to patient treatment may offer a more efficient and effective healthcare solution than phenotype-led approaches. In order to achieve that objective, a deep personal description is required at the level of the genome, proteome, metabolome, or preferably a combination of these aided by technology. This book, edited and written by the outstanding luminaries of this evolving field, evaluates metabolic profiling and its uses across personalized and population healthcare, while also covering the advent of new technology fields, such as surgical metabonomics. In addition, the text presents specific examples of where this technology has been used clinically and with efficacy, pointing towards a framework and protocol for usage as it hits the clinical mainstream.Translates the conjunction of new surgical tools for intraoperative, real-time, metabolite evaluation and direct analysis of biofluid samples into novel options for augmented clinical decision-makingDiscusses longitudinal sampling from individual patients for stratified medicine Covers high resolution analytical spectroscopy and sophisticated computational modelling for prediction of adverse reactions in critical care scenarios, prognostic evaluation of cancer from biofluidism, and prognostic prediction of metabolism or response of patients to pharmaceutical interventions Encapsulates recent technology options for broader population profiling considerations, in particular, the metabolome-wide association studies (MWAS) that aid the translational researcher in identifying metabolic patterns associated with disease Foreword written by Professor Dame Sally Davies who is the Chief Medical Officer for England | ||
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_c14577 _d14577 |
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