Next, we repeated the experiment in a range of urea concentrations to derive the full depolymerization curve of the αSyn fibrils. First, we tested fibrils of the αSyn tryptophan-containing mutant (F94W) to obtain a higher signal-to-noise ratio compared to the wild type in the intrinsic fluorescence-based detection system. We analyzed F94W αSyn fibrils equilibrated in a range of urea concentrations from 0 to 5.4 M using FIDA (Figure ). For each sample, a buffer with the matching concentration of urea was used as surrounding of the sample plug to avoid artifacts from dilution or viscosity gradients. In low concentrations of urea, the resulting Taylorgrams were characteristic of the two-component system described above, i.e., sum of asymmetrical and Gaussian peaks (Figure ). The amplitude of the former gradually decreased and completely disappeared at high urea concentrations (> 2.28 M), indicating complete fibril dissociation. Similar to the experiments described above, the monomer diffusion in the complex mixture was mostly unaffected by the larger species and behaved in a predictable manner which could be accurately modelled and analyzed (Figure ). Conversely, the signal from protein aggregates was less reproducible due to the unspecific self-interaction or interaction with the capillary surface resulting in signal spikes or delayed elution (sometimes appearing in the washing step). Therefore, we concluded that absolute quantification of monomers, rather than relative quantification of fibrils and monomer is a more robust and reproducible approach and used it for further analysis. We verified that florescence and hydrodynamic radius of the monomer are not affected by the The quantification of monomer was carried out in several different ways. First, we removed the signal contribution from the fibrils by subtracting a manually generated linear baseline connecting the hypothetical intersections of the two distinct peaks and integrated the remaining monomer peak to obtain the corresponding area (SI figure 3, SI table ). Although simple, the procedure is lengthy and subjective regarding the selection of the intersects. To overcome these limitations, we fitted the viscosity-corrected data to the sum of the two distributions described by equations 6 and 7 (see Materials and Methods for details) to obtain the deconvoluted areas under the Gaussian peaks. The procedure worked well for curves where the two distributions could be clearly distinguished. In cases where the contribution from one of the peaks to the overall signal was minimal (0 to 10%), analysis was more challenging and often resulted in overfitting due to the high number of parameters. We solved this by writing a custom python script that globally fits the Taylorgrams across the whole urea concentration range by parametrizing the monomer peak area using ΔG and m-value from the isodesmic model and sharing the rest of the parameters from equations 6 and 7 (except the area of the asymmetric fibril peak).