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Assessment of the Metabolic Effects of Isocaloric 2:1 Intermittent Fasting in Mice
Published on: November 27, 2019
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Correction to: Urinary metabolic profiling of asymptomatic acute intermittent porphyria using a rule-mining-based
Margaux Luck1,2,3,4, Caroline Schmitt5,6,7, Neila Talbi5,6,7
1INSERM U1147, Centre Universitaire des Saints Pères, Paris, France.
Summary
This study used a rule-mining algorithm for urinary metabolic profiling in asymptomatic acute intermittent porphyria (AIP). The findings help in understanding AIP metabolic patterns in individuals without symptoms.
Area of Science:
- Biochemistry
- Metabolomics
- Genetics
Background:
- Acute intermittent porphyria (AIP) is a rare genetic disorder.
- Asymptomatic AIP patients may have subtle metabolic alterations.
- Current diagnostic methods may not detect early metabolic changes.
Purpose of the Study:
- To investigate urinary metabolic profiles in asymptomatic AIP patients.
- To identify potential biomarkers for early detection of AIP.
- To apply a novel rule-mining algorithm for metabolic data analysis.
Main Methods:
- Urine samples were collected from asymptomatic AIP patients and healthy controls.
- Metabolomic analysis was performed using advanced analytical techniques.
- A rule-mining-based algorithm was employed to identify significant metabolic patterns.
Main Results:
- Distinct urinary metabolic profiles were observed in asymptomatic AIP patients.
- Specific metabolites and metabolic pathways were identified as potential indicators of AIP.
- The rule-mining algorithm successfully differentiated between AIP patients and controls.
Conclusions:
- Urinary metabolic profiling can reveal early signs of AIP in asymptomatic individuals.
- Rule-mining algorithms offer a powerful tool for analyzing complex metabolomic data.
- These findings may contribute to improved early diagnosis and management of AIP.
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