# In Silico Investigation of the RBC Velocity Fluctuations in Ex Vivo Capillaries
## 6 Conclusions  
Here, an investigation of RBC transport in four different ex vivo capillaries with explicit RBC modeling is presented. The investigation includes a realistic comparison of capillary and cylindrical tubes, the tube hematocrit effect, and the RDW effect.  
The capillary circularity index is used to characterize ex vivo capillaries depending on their cross-sectional characteristics. Although \(I_{cc}\) can be used to anticipate the irregularity of the capillaries, we believe that this definition is still in its early stage, and more work should be conducted on this index to develop it for broader applications.  
It is evident that the use of cylindrical tubes overestimates the actual ht established in the capillary lumen, and this overestimation increases as \(I_{cc}\) decreases. The fluctuation of RBC velocity in tubes is much smaller than in the capillaries, resulting in a more uniform flow but at the cost of less realistic results. In relatively smaller capillaries with high \(I_{cc}\), such as S1 and S2, velocity fluctuations with respect to ht are significantly lower than in low-\(I_{cc}\) capillaries due to a more uniform flow field and a high confinement ratio, where RBCs are always forced to show parachuting behavior. Using RDW does not have a significant effect on individual RBC velocity fluctuations, but spatial RBC velocity shows an increase in low-\(I_{cc}\) cases, and CoV is mostly lower in RDW cases. Although velocity fluctuations on RDW cases are on a small scale, the effect of these fluctuations is observed only in a single capillary, whereas microcirculation is vast, and the observed fluctuations can cause a major difference in the downstream bifurcation events, and the hematocrit of the following capillaries, consequently the CTTH, the most important parameter for the oxygenation, can change drastically.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15147796/s1](https://www.mdpi.com/article/10.3390/app15147796/s1)]([https://www.mdpi.com/article/10.3390/app15147796/s1](https://www.mdpi.com/article/10.3390/app15147796/s1)).  
Conceptualization, E.C.; methodology, E.C.; software, E.C.; validation, E.C.; formal analysis, E.C.; investigation, E.C.; resources, E.C., O.E. and S.E.E.; data curation, E.C.; writing--original draft preparation, E.C.; writing--review and editing, E.C., O.E. and S.E.E.; visualization, E.C.; supervision, O.E. and S.E.E.; funding acquisition, E.C. and S.E.E. All authors have read and agreed to the published version of the manuscript.  
This study was partially funded by the Scientific and Technological Research Council of Turkey (TUBITAK) ARDEB 1002-B under grant no: M123777. The numerical calculations reported in this study were partially performed at TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA resources).  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The corresponding author appreciate the mentorship during his PhD studies from [PERSON] from the University of Edinburgh Institute of Multiscale Thermofluids; technical support from [PERSON] from the Computational Science Lab at the University of Amsterdam, who develops the code Hemocell [[https://github.com/UvaCsl/HemoCell](https://github.com/UvaCsl/HemoCell)]([https://github.com/UvaCsl/HemoCell](https://github.com/UvaCsl/HemoCell)) (accessed on 11 August 2023); and raw confocal imaging data from [PERSON] from the Institute of Neurological Sciences and Psychiatry, Hacettepe University, that were used for the generation of the stl files for this present study.  
The authors declare no conflicts of interest.