Determination of Evans blue as a blood–brain barrier integrity tracer in plasma and brain tissue by UHPLC/UV method

<p>Blood–brain barrier changes are an integral part of many neurodegenerative diseases. Evans blue is an intravital dye that binds to albumin and can therefore be used to monitor extravasation of this plasma protein across blood–brain barrier in animal models of neurodegeneration. To monitor extravasation of albumin across blood–brain barrier, we developed and validated an ultrahigh-performance liquid chromatography method for the analysis of Evans blue in rat plasma and brain samples. Analyte was separated on ACQUITY UPLC BEH C18 column (2.1 mm × 50 mm) using a 5-min gradient run and detected by a UV detector. The limits of quantification (LOQ) were 10 µg/mL in plasma and 0.5 µg/g in brain samples. The limits of detection (LOD) were 1 µg/mL in plasma and 0.015 µg/g in brain samples. The method showed excellent linearity with regression coefficients higher than 0.99. The accuracy was within the range of 91–105%. The inter-day precision was in the range of 1.3–8%. The benefits of using UPLC are selectivity, short analysis period, and thus, a very good sample throughput. Using this method, we analyzed albumin extravasation across blood–brain barrier in transgenic rat model for tauopathy SHR-72 and age-matched control animals.</p

Symmetry index of the different conditions.

<p>The bars on the top indicate the significant differences between the four groups. The three interventions are more symmetric than the neutral condition, but no intervention is more symmetric than another intervention.</p

Separation of subjects.

<p>A: Distance matrix between subjects. The grey values indicate the distance between subjects. The red squares indicate the 11 comparisons that were not significantly classified. For the 4 subjects indicated by the green squares (two subjects are combined in every square) the projection on the discriminant was calculated and plotted in the graph B. B: Trials of the same subject were indicated by subject specific colour of the outer circle. The colours of the 4 subjects were green (10), red (14), magenta (4) and blue (15). The trials of the same condition were colour coded in the inner circle. The colour for the condition is given in the legend.</p

Subject specific classification of different conditions.

<p>The classification rate within each subject is mentioned for the three comparisons: Neutral to centric, neutral to DPS and neutral to Max. Significant classification rates are highlighted in bold.</p><p>Subject specific classification of different conditions.</p

Subject specific differences of the movement pattern between the conditions.

<p>A: Main contributions to the discriminant between different conditions and subjects. B: One example: Discriminant (blue line) between neutral and centric for subject 4, the highest contributions to the classification of the two conditions are indicated by the grey area. C: Movement pattern of the neutral (black) and centric (cyan) condition.</p

Cluster analysis.

<p>All trials of all conditions were subjected to a cluster analysis. The colour code for the three different categories is plotted in the legend. A: Distance matrix between each trial. Trials are plotted in the x and y direction. The colour of the image gives the distance between two trials. The contribution of the trials to subject, condition or side is colour coded in the legend underneath the image. B: Dendogram to visualize the similar characteristics of different trials. The trials on the x-axis are organized depending on the distance between them. The distance on the y axis is a measure for the number of steps required to combine sets of trials. C Loading rate of subjects (C1), conditions (C2), and subject, condition and side (C3). The rate is a value between 0 and 1 depending if no trial is loaded in a cluster or all trials are loaded in the same cluster.</p

Reduction of CCI-induced pathological tau expression in hippocampus and cortex by mHW.

<p>The CCI-induced increase in AT8 and Alz50 immunoreactivity is attenuated by treatment with hydrogen water. Representative images of immunostaining in brains from sham (A, D, G, H), CCI (B, E, I, J), and CCI+mHW treated (C, F, K, L) animals. Low power representative images depict AT8 (A–C) and Alz50 (D–F) immunoreactivity. G–L, high power images of the cortical region designated by arrows, immunostained for AT8 (G,I,K) and Alz50 (H, J, L). Scale bars: 500 µm, A–F; 50 µm, G–L.</p

Reduction of CCI-induced pathological tau by mHW in frontal cortex.

<p>CCI induced increases in AT8 and Alz50 immunoreactivity extend to the frontal cortex and are attenuated by treatment with hydrogen water. Low power representative images demonstrate increased AT8 immunoreactivity in the frontal cortex of CCI (B) compared to sham treated (A) mice. C–F, high power images of the cortical region shown in B (arrow) demonstrate AT8 (C,D) and Alz50 (E,F) immunoreactivity in CCI (C,E) and HW treated (D,F) mice. Scale bars: 500 µm, A,B; 50 µm, D–F.</p

Effects of CCI and mHW on Cyclophillin A, APP, and Amyloid Beta Peptide Levels.

<p>The upper left panel shows that protein levels of APP were decreased 7 days after CCI and that mHW did not protect from CCI. Amyloid beta peptide_1–40 (upper right panel) was increased on day 7 and amyloid beta peptide_1–42 (lower right panel) was decreased 24 h after CCI, but mHW did not alter these effects of CCI. CypA was decreased 7 days after CCI and this decrease was enhanced by mHW (lower left panel).</p

Changes in Brain Expression with CCI and mHW: Cellular Component.

<p>Categories listed consisted of a minimum of 6 genes, had at least 3 genes that were changed, and a Z-score of ≥2.0.</p><p>Changes in Brain Expression with CCI and mHW: Cellular Component.</p