Engineering Smooth Muscle to Understand Extracellular Matrix Remodeling and Vascular Disease.

The vascular smooth muscle is vital for regulating blood pressure and maintaining cardiovascular health, and the resident smooth muscle cells (SMCs) in blood vessel walls rely on specific mechanical and biochemical signals to carry out these functions. Any slight change in their surrounding environment causes swift changes in their phenotype and secretory profile, leading to changes in the structure and functionality of vessel walls that cause pathological conditions. To adequately treat vascular diseases, it is essential to understand how SMCs crosstalk with their surrounding extracellular matrix (ECM). Here, we summarize in vivo and traditional in vitro studies of pathological vessel wall remodeling due to the SMC phenotype and, conversely, the SMC behavior in response to key ECM properties. We then analyze how three-dimensional tissue engineering approaches provide opportunities to model SMCs' response to specific stimuli in the human body. Additionally, we review how applying biomechanical forces and biochemical stimulation, such as pulsatile fluid flow and secreted factors from other cell types, allows us to study disease mechanisms. Overall, we propose that in vitro tissue engineering of human vascular smooth muscle can facilitate a better understanding of relevant cardiovascular diseases using high throughput experiments, thus potentially leading to therapeutics or treatments to be tested in the future.

Selective hydrogen bonding controls temperature response of layer-by-layer upper critical solution temperature micellar assemblies.

This work establishes a correlation between the selectivity of hydrogen-bonding interactions and the functionality of micelle-containing layer-by-layer (LbL) assemblies. Specifically, we explore LbL films formed by assembly of poly(methacrylic acid) (PMAA) and upper critical solution temperature block copolymer micelles (UCSTMs) composed of poly(acrylamide-co-acrylonitrile) P(AAm-co-AN) cores and polyvinylpyrrolidone (PVP) coronae. UCSTMs had a hydrated diameter of ∼380 nm with a transition temperature between 45 and 50 °C, regardless of solution pH. Importantly, micelles were able to hydrogen-bond with PMAA, with the critical interaction pH being temperature dependent. To better understand the thermodynamic nature of these interactions, in depth studies using isothermal titration calorimetry (ITC) were conducted. ITC reveals opposite signs of enthalpies for binding of PMAA with micellar coronae vs. with the cores. Moreover, ITC indicates that pH directs the interactions of PMAA with micelles, selectively enabling binding with the micellar corona at pH 4 or with both the corona and the core at pH 3. We then explore UCSTM/PMAA LbL assemblies and show that the two distinct modes of PMAA interaction with the micelles (i.e. whether or not PMAA binds with the core) had significant effects on the film composition, structure, and functionality. Consistent with PMAA hydrogen bonding with the P(AAm-co-AN) micellar cores, a significantly higher fraction of PMAA was found within the films assembled at pH 3 compared to pH 4 by both spectroscopic ellipsometry and neutron reflectometry. Selective interaction of PMAA with PVP coronae of the assembled micelles, achieved by the emergence of partial ionization of PMAA at pH 4 was critical for preserving film functionality demonstrated as temperature-controlled swelling and release of a model small molecule, pyrene. The work done here can be applied to a multitude of assembled polymer systems in order to predict suppression/retention of their stimuli-responsive behavior.

A rapid and convenient screening method for detection of restricted monensin, decoquinate, and lasalocid in animal feed by applying SERS and chemometrics.

The surface-enhanced activities of size- and shape-controlled gold nanoparticles (AuNPs) with superior chemical stability were investigated to explore a possible development of a simple and non-destructive spectroscopic method to help the regulatory agency's analytical services for rapid detection and characterization of selected antimicrobials in animal feeds. Feed samples spiked at different concentration ranges of antimicrobials were evaluated using AuNPs as a surface-enhanced Raman spectroscopy (SERS) agent. The collected SERS spectra were mathematically preprocessed for further analysis. The classification models obtained 100% predictive accuracy with zero or little misclassification. The first two canonical variables (p = 0.001) could explain >95% of the variability in preprocessed spectral data. Most chemometric models for predicting MON, DEC, and LAS concentrations showed a high predictive accuracy (r2 > 0.90), lower predictive error (<20 mg/kg), and satisfactory regression quality (slope close to 1.0). The statistical results showed no statistically significant difference between the reference and SERS predicted values (p > 0.05). The findings and implications from the study indicate that SERS would be a powerful and efficient technique possessing a great potential serving as an excellent monitoring and screening tool for antimicrobial contaminated samples in the on-site analysis.