ABSTRACT
The majority of research in the biomedical sciences is carried out with the highest resolution accessible to the scientist, but, in the clinic, cost constraints necessitate the use of low-resolution devices. Here, we compare high- and low-resolution direct mass spectrometry profiling data and propose a simple pre-processing technique that makes high-resolution data suitable for the development of classification and regression techniques applicable to low-resolution data, while retaining high accuracy of analysis. This work demonstrates an approach to de-noising spectra to make the same representation for both high- and low-resolution spectra. This approach uses noise threshold detection based on the Tversky index, which compares spectra with different resolutions, and minimizes the percentage of resolution-specific peaks. The presented method provides an avenue for the development of analytical algorithms using high-resolution mass spectrometry data, while applying these algorithms in the clinic using low-resolution mass spectrometers.
ABSTRACT
On the basis of the analysis of the described cooling regime of biological objects during low temperature preservation it is suggested that an optimal regime should have non-linear dependence of the rate of temperature change in time. By approximation of several experimental cooling regimes it is found that the exponential description of this process is the most correct. Advantages of using the exponential cooling regime instead of the linear ones during their optimization are grounded. The theoretical premises of the exponential cooling regime realization are described.