PubMed · 12500693
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
Janice M Horowitz. 2002-12-02. Stuffing yourself healthy.. https://pubmed.ncbi.nlm.nih.gov/12500693/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
The selenium (Se) content of 11 infant formulas had been determined using electrothermal and hydride generation atomic absorption spectrometry. The Se content ranged between 0.43 and 17.17 microg/100 g powder infant formulas with wide variations reaching 40.36-fold excess between the poorest RIRI-1 (0.43 microg/100 g) and Milupa-2 (17.2 microg/100 g powder). After reconstituting with water, the adequacies of the 11 studied infant formulas were evaluated with respect to Se supply. Based on the daily adequate intakes (AIs) of 15 and 20 microg Se for children 4-6 and 7-12 months old, respectively, four analyzed infant formulas were found to contain adequate Se content (>75% of the AIs), whereas the other seven formulas could satisfy 63% or less. In conclusion, the national regulation for the trace element (Se) contents in the infant formulas is highly warranted.
The electrical activity of the human stomach, which normally shows a frequency of about 0.05 Hz, may be studied non-invasively by either cutaneous electrogastrography (EGG) or surface magnetogastrography (MGG). Detection of changes in frequency with time may be useful to characterize gastric disorders. The fast Fourier transform (FFT) has been the most commonly used method for the automated spectral analysis of the signals obtained from the EGG or the MGG. We have used an autoregressive (AR) parametric spectrum estimator to analyse simulated signals of gastric electrical activity, and to evaluate the results of human studies using EGG and MGG. In comparison with the FFT, our results showed that the AR spectrum estimator provided more detailed qualitative information about frequency variations of short duration simulated signals than the FFT. In the human studies, the AR estimator was as good as the conventional FFT methods in detecting physiological changes in frequency and in identifying abnormal recordings. We conclude that the AR spectral estimator may provide a better qualitative analysis of frequency variations in small portions of the signal, and is as useful as the FFT to analyse human EGG or MGG studies.