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1.  Pre-Diabetes Augments Neuropeptide Y1- and α1-Receptor Control of Basal Hindlimb Vascular Tone in Young ZDF Rats 
PLoS ONE  2012;7(10):e46659.
Peripheral vascular disease in pre-diabetes may involve altered sympathetically-mediated vascular control. Thus, we investigated if pre-diabetes modifies baseline sympathetic Y1-receptor (Y1R) and α1-receptor (α1R) control of hindlimb blood flow (Qfem) and vascular conductance (VC).
Qfem and VC were measured in pre-diabetic ZDF rats (PD) and lean controls (CTRL) under infusion of BIBP3226 (Y1R antagonist), prazosin (α1R antagonist) and BIBP3226+prazosin. Neuropeptide Y (NPY) concentration and Y1R and α1R expression were determined from hindlimb skeletal muscle samples.
Baseline Qfem and VC were similar between groups. Independent infusions of BIBP3226 and prazosin led to increases in Qfem and VC in CTRL and PD, where responses were greater in PD (p<0.05). The percent change in VC following both drugs was also greater in PD compared to CTRL (p<0.05). As well, Qfem and VC responses to combined blockade (BIBP3226+prazosin) were greater in PD compared to CTRL (p<0.05). Interestingly, an absence of synergistic effects was observed within groups, as the sum of the VC responses to independent drug infusions was similar to responses following combined blockade. Finally, white and red vastus skeletal muscle NPY concentration, Y1R expression and α1R expression were greater in PD compared to CTRL.
For the first time, we report heightened baseline Y1R and α1R sympathetic control of Qfem and VC in pre-diabetic ZDF rats. In support, our data suggest that augmented sympathetic ligand and receptor expression in pre-diabetes may contribute to vascular dysregulation.
PMCID: PMC3465334  PMID: 23071607
2.  An automated cell-counting algorithm for fluorescently-stained cells in migration assays 
A cell-counting algorithm, developed in Matlab®, was created to efficiently count migrated fluorescently-stained cells on membranes from migration assays. At each concentration of cells used (10,000, and 100,000 cells), images were acquired at 2.5 ×, 5 ×, and 10 × objective magnifications. Automated cell counts strongly correlated to manual counts (r2 = 0.99, P < 0.0001 for a total of 47 images), with no difference in the measurements between methods under all conditions. We conclude that our automated method is accurate, more efficient, and void of variability and potential observer bias normally associated with manual counting.
PMCID: PMC3214125  PMID: 22011343
automated cell counting; threshold; migration assays; manual cell counting

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