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Biomedical subjects

R Lamanna

Publications and source records attributed to R Lamanna.

7 recordsLinked to original sources

Milk identification of different species: 13C-NMR spectroscopy of triacylglycerols from cows and buffaloes' milks.

Triacylglycerols from cows and buffaloes' milk fat were investigated by 13C nuclear magnetic resonance (NMR) spectroscopy. By the addition of pure triacylglycerols standards, we identified the resonances of both milk fats, and the peaks were used for qualitative and quantitative analysis of acyl groups. Multivariate analysis treatment of triacylglycerols distribution and composition parameters enabled us to identify milk. This study shows that NMR can safely be used to quantitate milk fatty acid content, providing unique information for milk identification of different animal species.

Animals↗

Forced adhesive growth of K562 leukemic cells that normally grow in suspension induces variations in membrane lipids and energy metabolism: a proton NMR study.

The mechanisms responsible for the adhesion of cells onto a material's surface and the effects that that adhesion may have on cell structure and function are fundamental questions in biomaterials research. We recently demonstrated that the erythroleukemic cell line K562, which normally grows in suspension, can be induced to grow attached to a polylysine-coated solid surface in an anchorage-dependent manner. In this study, the effects of the growth of K562 cells onto polylysine were further investigated utilizing 500 MHz 1H-NMR spectroscopy. The NMR results showed that when K562 cells are grown attached to a positively-charged polylysine surface, there are alterations in lipids and energy metabolism. In particular, there was a 31% increase in phosphatidylcholine and a 15% decrease in each of its two precursors, glycerophosphatidylcholine and choline, as well as a 20% increase in CH2 lipids and a 7% decrease in CH3 lipids in treated cells compared to the controls. These results suggest that adhesive growth can induce strong variations in membrane structure, including the membrane fluidity of K562 cells. In addition, in cells attached to polylysine there was about a 10% decrease in creatine (together with phosphocreatine), a 20% increase in gamma-glutamate, a 15% increase in beta-glutamate, and a 24% decrease in lactate. This second set of results, which is closely related to energy metabolism, indicates that not only does adhesive growth induce changes in K562 cell membrane structure, but also in the utilization of energy in these cells. The data are discussed in view of the possible role played by surface charge in affecting cell structure and function in cells that come into direct contact with charged biopolymers.

Cell Adhesion↗

A new algorithm for NMR spectral normalization.

There is increasing use of high-resolution NMR spectroscopy to examine variations in cell metabolism and/or structure in response to numerous physical, chemical, and biological agents. In these types of studies, in order to obtain relative quantitative information, a comparison between signal intensities of control samples and treated or exposed ones is often conducted. The methods thus far developed for this purpose are not directly related to the overall intrinsic properties of the samples, but rather to the addition of external substances of known concentrations or to indirect measurement of internal substances. In this paper, a new method for quantitatively comparing the spectra of cell samples is presented. It depends on a normalization algorithm which takes into consideration all cell metabolites present in the sample. In particular, the algorithm is based on maximizing, by an opportune sign variable measure, the spectral region in which the two spectra are superimposed. The algorithm was tested by Monte Carlo simulations as well as experimentally by comparing two samples of known contents with the new method and with an older method using a standard. At the end, the algorithm was applied to real spectra of cell samples to show how it could be used to obtain qualitative and quantitative biological information.

Algorithms↗