Related Experiment Video
Updated: May 28, 2026
11:07
High-Throughput Metabolic Profiling for Model Refinements of Microalgae
Published on: December 4, 2021
Metabolic changes in early childhood using LCModel with corrected water scaling method
Jun-ichi Takanashi1, Fuminori Somazawa, Katsuya Maruyama
1Department of Pediatrics, Kameda Medical Center, Kamogawa, Chiba, Japan. jtaka@kameda.jp
Journal of Magnetic Resonance Imaging : JMRI
|October 1, 2011
Summary
The unsuppressed water signal (UWS) and area of the unsuppressed water peak (AUW) can correct brain metabolite concentrations in infants. This method improves the accuracy of quantifying these metabolites in early childhood.
Area of Science:
- Neuroimaging
- Biochemistry
- Pediatric Medicine
Background:
- Magnetic Resonance Spectroscopy (MRS) is crucial for assessing brain metabolism.
- Quantifying brain metabolites in early infancy presents challenges due to developmental changes.
- Accurate metabolite quantification is vital for understanding infant brain development and disorders.
Purpose of the Study:
- To evaluate metabolic changes in the infant brain using LCModel-WS.
- To determine the utility of unsuppressed water signal (UWS) and area under the unsuppressed water peak (AUW) for correcting metabolite concentrations.
- To establish a reliable method for accurate metabolite quantification in early childhood.
Main Methods:
- MRS was conducted on a 1.5 Tesla MR scanner.
- Phantom studies assessed the linear relationship between UWS, AUW, and proton density (PD)/T2 decay.
- UWS and AUW were measured in 57 pediatric controls aged 2 weeks to 15 years.
Main Results:
- Phantom studies confirmed linear increases in UWS and AUW with PD and exp(-TE/T2).
- UWS and AUW were highest in infants under 2 years, stabilizing after age 4.
- AUW showed a linear correlation with UWS, enabling the development of correction ratios.
Conclusions:
- Both UWS and AUW serve as effective tools for correcting metabolite concentrations.
- These corrections significantly enhance the precision of metabolite quantification in young children.
- The findings provide a validated approach for improved pediatric neurochemical analysis.
Related Concept Videos
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
01:26Derivatives: Problem Solving
Temperature-Dependent Growth of Brook TroutThe growth of brook trout is closely influenced by water temperature. Experimental data demonstrate how trout weight changes over a 24-day period in response to varying water temperatures. At lower temperatures, such as 15.5 degrees Celsius, brook trout show significant weight gain. However, as the temperature increases, the amount of weight gained steadily decreases. At the highest temperature measured, 24.4 degrees Celsius, trout experience a net...
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
01:25Modeling with Differential Equations
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
01:21Design Example: Creating a Hydraulic Model of a Dam Spillway
Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
01:29Oxygen Requirements and Growth Patterns
Microorganisms exhibit diverse oxygen requirements and growth patterns driven by their metabolic strategies and environmental adaptations. Oxygen, while essential for many organisms, can also be toxic under certain conditions, shaping how microorganisms grow and survive.Oxygen Requirements of MicroorganismsMicroorganisms are classified based on their ability to use or tolerate oxygen:● Obligate aerobes like Mycobacterium tuberculosis need oxygen for energy production, as it serves as the...