Human umbilical cord blood cells suffer major modification by fixatives and anticoagulants.

Developing techniques for the tagless isolation of homogeneous cell populations in physiological-like conditions is of great interest in medical research. A particular case is Gravitational Field-Flow Fractionation (GrFFF), which can be run avoiding cell fixation, and that was already used to separate viable cells. Cell dimensions have a key role in this process. However, their dimensions under physiological-like conditions are not easily known since the most diffused measurement techniques are performed on fixed cells, and the fixation used to preserve tissues can alter the cell size. This work aims to obtain and compare cell size data under physiological-like conditions and in the presence of a fixative. We developed a new protocol that allows the analysis of blood cells in different conditions. Then, we applied it to obtain a dataset of human cord blood cell dimensions from 32 subjects, comparing two tubes with anticoagulants (EDTA and Citrate) and two tubes with different preservatives (CellRescue and CellSave). We analyzed a total of 2071 cells by using confocal microscopy bio-imaging to assess dimensions (cellular and nuclear) and morphology. Cell diameter measured does not differ when using the different anticoagulants, except for the increase reported for monocyte in the presence of citrate. Instead, cell dimensions differ when comparing anticoagulants and cell preservative tubes, with a few exceptions. Cells characterized by high cytoplasm content show a reduction in their size, while morphology appears always preserved. In a subgroup of cells, 3D reconstruction was performed. Cell and nucleus volumes were estimated using different methods (specific 3D tool or reconstruction from 2D projection). We found that some cell types benefit from a complete 3D analysis because they contain non-spherical structures (mainly for cells characterized by poly-lobated nucleus). Overall, we showed the effect of the preservatives mixture on cell dimensions. Such an effect must be considered when dealing with problems highly dependent on cell size, such as GrFFF. Additionally, such information is crucial in computational models increasingly being employed to simulate biological events.