RESUMEN
High-resolution flow cytometers (hFCM) are used for the detection of extracellular vesicles (EV) in various biological fluids. Due to the increased sensitivity of hFCM, new artifacts with the potential of interfering with data interpretation are introduced, such as detection of antibody aggregates. The aim of this study was to investigate the extent of aggregates in labels commonly used for the characterization of EVs by hFCM. Furthermore, we aimed to compare the efficacy of centrifugation and filtering treatments to remove aggregates, as well as to quantify the effect of the treatments in reducing aggregates. For this purpose, we labeled phosphate buffered saline (PBS) with fluorescently conjugated protein labels and antibodies after submitting them to 5, 10, or 30 min centrifugation, filtering or washed filtering. We investigated samples by hFCM and quantified the amount of aggregates found in PBS labeled with untreated and pre-treated labels. We found a varying amount of aggregates in all labels investigated, and further that filtering is most efficient in removing all but the smallest aggregates. Filtering protein labels can reduce the extent of aggregates; however, how much remains depends on the specific labels and their combination. Therefore, it is still necessary to include appropriate controls in a hFCM study of EVs.
RESUMEN
Tissue factor (TF)-bearing microvesicles (MVs) and exosomes may play a role in hemostasis and thrombosis. MVs may be quantified by flow cytometry (FC)-based detection of phosphatidylserine (PS)-positive submicron particles carrying specific antigens, although interference from lipoproteins complicates this approach. In this study, we evaluated the effect of food intake on blood levels of TF-bearing particles measured by FC and small extracellular vesicles (EVs) measured by a protein microarray-based test termed EV Array. Platelet-free plasma (PFP) was obtained from 20 healthy persons in the fasting state and 75 minutes after consumption of a meal. Postprandial changes in the concentration of PS-positive particles, including subgroups binding labeled antibodies against TF, CD41, CD146, and CD62E, respectively (FC), small EVs (EV Array), and TF antigen and procoagulant phospholipids (PPLs) were measured. Furthermore, we tested the effect on FC results of in vitro addition of lipoproteins to fasting PFP. We found significantly increased plasma concentrations of PS-positive particles and all examined subgroups postprandially, while no changes in small EVs, PPL, or TF antigen levels were found. Levels of all types of particles measured by FC were also elevated by lipoprotein spiking. In conclusion, meal consumption as well as in vitro addition of lipoproteins to fasting plasma induces increased levels of PS-positive particles as measured by FC, including TF-positive subtypes and subtypes exposing other antigens. While the observed postprandial increase may to some extent reflect elevated MV levels, our results indicate a substantial interference from lipoproteins.
RESUMEN
INTRODUCTION: It has been suggested that striking on the midfoot or forefoot, rather than the rearfoot, may lessen injury risk in the feet and lower limb. In previous studies, a disparity in distribution in footstrike patterns was found among elite-, sub-elite, and recreational runners. PURPOSE: The purpose of this study was to investigate the footstrike patterns among novice runners. METHODS: All runners were equipped with the same conventional running shoe. Participants were video filmed at 300 frames per second and the footstrike patterns were evaluated by two observers. The footstrike was classified as rearfoot, midfoot, forefoot, or asymmetrical. RESULTS: A total of 903 persons were evaluated. The percentages of rearfoot-, midfoot-, forefoot-, and asymmetrical footstrike among men were 96.9%, 0.4%, 0.9%, and 1.8%, respectively. Among women the percentages were 99.3%, 0%, 0%, and 0.7%, respectively. CONCLUSION: Nearly all novice runners utilize a rearfoot strike when taking up running in a conventional running shoe. Hereby, the footstrike patterns among novice runners deviate from footstrike patterns among elite and sub-elite runners.
