Citric Acid and the Excretion of Oestrone and Oestradiol

Edwards, Marian S.; Gray, C. H.; Wood, Mary E.

doi:10.1677/joe.0.0060440

Cited by 8 publications

(1 citation statement)

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“…The higher creatinine excretion in males is most likely related to a higher muscle mass as creatinine excretion from muscle is approximately 1 g/20 g of muscle (Selberg & Sel 2001). The excretion of citrate has been shown to correlate with circulating oestrogen levels (Edwards et al . 1950).…”

Section: Factors That Influence the Metabolomementioning

confidence: 99%

Understanding the metabolome – challenges for metabolomics

et al. 2008

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Metabolomics is a comprehensive method for metabolite assessment, measuring the overall metabolic signature of biological samples. This approach opens up many possibilities in areas such as new biomarker discovery and hypothesis generation. The application of metabolomics is growing rapidly but many challenges must first be addressed before it can reach its true potential. Metabolomics organisations are currently working towards guidelines for commonality in metabolomics experiments as development of optimal methodologies and study designs are needed. Blood and urine appear to be the most useful biofluids for nutrition research, but an array of biofluids, cells and tissues can be used. The key steps required for the successful understanding of metabolomics data are compound identification and biological interpretation. Many databases of compounds are available but are still under construction with much information remaining to be populated. An understanding of the effects of normal physiological variation on metabolic profiles is essential for accurate interpretation of profile changes, particularly in human studies, because of diversity in lifestyle and environmental factors. The effects of factors such as ethnicity, gender, age, body composition, health, dietary intake, physical activity, gut microflora and stress need to be further explored in order to advance the understanding of the human metabolome and therefore improve data interpretation.

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Section: Factors That Influence the Metabolomementioning

confidence: 99%