Synergistic Effects of 3D ECM and Chemogradients on Neurite Outgrowth and Guidance: A Simple Modeling and Microfluidic Framework

During nervous system development, numerous cues within the extracellular matrix microenvironment (ECM) guide the growing neurites along specific pathways to reach their intended targets. Neurite motility is controlled by extracellular signal sensing through the growth cone at the neurite tip, including chemoattractive and repulsive cues. However, it is difficult to regenerate and restore neurite tracts, lost or degraded due to an injury or disease, in the adult central nervous system. Thus, it is important to evaluate the dynamic interplay between ECM and the concentration gradients of these cues, which would elicit robust neuritogenesis. Such information is critical in understanding the processes involved in developmental biology, and in developing high-fidelity neurite regenerative strategies post-injury, and in drug discovery and targeted therapeutics for neurodegenerative conditions. Here, we quantitatively investigated this relationship using a combination of mathematical modeling and in vitro experiments, and determined the synergistic role of guidance cues and ECM on neurite outgrowth and turning. Using a biomimetic microfluidic system, we have shown that cortical neurite outgrowth and turning under chemogradients (IGF-1 or BDNF) within 3D scaffolds is highly regulated by the source concentration of the guidance cue and the physical characteristics of the scaffold. A mechanistic-driven partial differential equation model of neurite outgrowth has been proposed, which could also be used prospectively as a predictive tool. The parameters for the chemotaxis term in the model are determined from the experimental data using our microfluidic assay. Resulting model simulations demonstrate how neurite outgrowth was critically influenced by the experimental variables, which was further supported by experimental data on cell-surface-receptor expressions. The model results are in excellent agreement with the experimental findings. This integrated approach represents a framework for further elucidation of biological mechanisms underlying neuronal responses of specialized cell types, during various stages of development, and under healthy or diseased conditions

Mixing Optimization in Grooved Serpentine Microchannels

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Computational fluid dynamics modeling at Reynolds numbers ranging from 10 to 100 was used to characterize the performance of a new type of micromixer employing a serpentine channel with a grooved surface. The new topology exploits the overlap between the typical Dean flows present in curved channels due to the centrifugal forces experienced by the fluids, and the helical flows induced by slanted groove-ridge patterns with respect to the direction of the flow. The resulting flows are complex, with multiple vortices and saddle points, leading to enhanced mixing across the section of the channel. The optimization of the mixers with respect to the inner radius of curvature (Rin) of the serpentine channel identifies the designs in which the mixing index quality is both high (M \u3e 0.95) and independent of the Reynolds number across all the values investigated

Synthesis and Secretome Release by Human Bone Marrow Mesenchymal Stem Cell Spheroids within Three-dimensional Collagen Hydrogels: Integrating Experiments and Modelling

Myocardial infarction results in loss of cardiac cell types, inflammation, extracellular matrix (ECM) degradation, and fibrotic scar. Transplantation of bone marrow-derived mesenchymal stem cells (BM-MSCs) is being explored as they could differentiate into cardiomyocyte-like cells, integrate into host tissue, and enhance resident cell activity. The ability of these cells to restore lost ECM, remodel the inflammatory scar tissue, and repair the injured myocardium remains unexplored. We here elucidated the synthesis and deposition of ECM (e.g., elastin, sulfated glycosaminoglycans, hyaluronan, collagen type III, laminin, fibrillin, lysyl oxidase, and nitric oxide synthases), matrix metalloproteinases (MMPs) and their inhibitors (TIMPs), and other secretome (cytokines, chemokines, and growth factors) in adult human BM-MSC spheroid cultures within three-dimensional collagen gels. The roles of species-specific type I collagen and 5-azacytadine were assessed over a 28-day period. Results revealed that human collagen (but not rat-derived) suppressed MSC proliferation and survival, and MSCs synthesized and released a variety of ECM proteins and secretome over the 28 days. Matrix deposition is at least an order of magnitude lower than their release levels at every time point, most possibly due to elevated MMP levels and interleukins with a concomitant decrease in TIMPs. Matrix synthesis over the 28-day period was fitted to a competitive inhibition form of Michaelis-Menten kinetics, and the production and decay rates of ECM, MMPs, and TIMPs, along with the kinetic model parameters quantified. Such an integrated experimental and modelling approach would help elucidate the critical roles of various parameters (e.g., cell encapsulation and delivery vehicles) in stem cell-based transplantation therapies

Biophysical and Biomechanical Properties of Neural Progenitor Cells as Indicators of Developmental Neurotoxicity

Conventional in vitro toxicity studies have focused on identifying IC50 and the underlying mechanisms, but how toxicants influence biophysical and biomechanical changes in human cells, especially during developmental stages, remain understudied. Here, using an atomic force microscope, we characterized changes in biophysical (cell area, actin organization) and biomechanical (Young\u27s modulus, force of adhesion, tether force, membrane tension, tether radius) aspects of human fetal brain-derived neural progenitor cells (NPCs) induced by four classes of widely used toxic compounds, including rotenone, digoxin, N-arachidonoylethanolamide (AEA), and chlorpyrifos, under exposure up to 36 h. The sub-cellular mechanisms (apoptosis, mitochondria membrane potential, DNA damage, glutathione levels) by which these toxicants induced biochemical changes in NPCs were assessed. Results suggest a significant compromise in cell viability with increasing toxicant concentration (p \u3c 0.01), and biophysical and biomechanical characteristics with increasing exposure time (p \u3c 0.01) as well as toxicant concentration (p \u3c 0.01). Impairment of mitochondrial membrane potential appears to be the most sensitive mechanism of neurotoxicity for rotenone, AEA and chlorpyrifos exposure, but compromise in plasma membrane integrity for digoxin exposure. The surviving NPCs remarkably retained stemness (SOX2 expression) even at high toxicant concentrations. A negative linear correlation (R-2 = 0.92) exists between the elastic modulus of surviving cells and the number of living cells in that environment. We propose that even subtle compromise in cell mechanics could serve as a crucial marker of developmental neurotoxicity (mechanotoxicology) and therefore should be included as part of toxicology assessment repertoire to characterize as well as predict developmental outcomes

Sensitivity of Neural Stem Cell Survival, Differentiation and Neurite Outgrowth Within 3D Hydrogels to Environmental Heavy Metals

© 2015 Elsevier Ireland Ltd. We investigated the sensitivity of embryonic murine neural stem cells exposed to 10 pM-10. μM concentrations of three heavy metals (Cd, Hg, Pb), continuously for 14 days within 3D collagen hydrogels. Critical endpoints for neurogenesis such as survival, differentiation and neurite outgrowth were assessed. Results suggest significant compromise in cell viability within the first four days at concentrations ≥10. nM, while lower concentrations induced a more delayed effect. Mercury and lead suppressed neural differentiation at as low as 10 pM concentration within 7 days, while all three metals inhibited neural and glial differentiation by day 14. Neurite outgrowth remained unaffected at lower cadmium or mercury concentrations (≤100. pM), but was completely repressed beyond day 1 at higher concentrations. Higher metal concentrations (≥100. pM) suppressed NSC differentiation to motor or dopaminergic neurons. Cytokines and chemokines released by NSCs, and the sub-cellular mechanisms by which metals induce damage to NSCs have been quantified and correlated to phenotypic data. The observed degree of toxicity in NSC cultures is in the order: lead. \u3e. mercury. \u3e. cadmium. Results point to the use of biomimetic 3D culture models to screen the toxic effects of heavy metals during developmental stages, and investigate their underlying mechanistic pathways

Bioanalytical Method Development and Validation of Memantine in Human Plasma by High Performance Liquid Chromatography with Tandem Mass Spectrometry: Application to Bioequivalence Study

A simple, sensitive, and rapid HPLC-MS/MS method was developed and validated for quantitative estimation of memantine in human plasma. Chromatography was performed on Zorbax SB-C18 (4.6 × 75 mm, 3.5 μm) column. Memantine (ME) and internal standard Memantine-d6(MED6) were extracted by using liquid-liquid extraction and analyzed by LC-ESI-MS/MS using multiple-reaction monitoring (MRM) mode. The assay exhibited a linear dynamic range of 50.00–50000.00 pg/ml for ME in human plasma. This method demonstrated an intra- and interday precision within the range of 2.1–3.7 and 1.4–7.8%, respectively. Further intra- and interday accuracy was within the range of 95.6–99.8 and 95.7–99.1% correspondingly. The mean recovery of ME and MED6 was 86.07 ± 6.87 and 80.31 ± 5.70%, respectively. The described method was successfully employed in bioequivalence study of ME in Indian male healthy human volunteers under fasting conditions

Towards Enhanced Chlorine Control: Mathematical Modeling for Free Chlorine Kinetics During Fresh-cut Carrot, Cabbage and Lettuce Washing

In this study, we developed a novel produce-specific mechanistic model to predict free chlorine (FC) dynamics during washing of disk-cut carrots, cut cabbage, and cut iceberg lettuce, in 3 L and 50–100 L tanks, and of shredded iceberg lettuce in 3200 L pilot-plant trials. Ranges for two key parameters: β (L mg−1 min−1) the apparent reaction rate constant of FC with produce constituents, and γ, the fraction of the increase of chemical oxygen demand (COD) contributing to the reaction, were determined at the 3 L scale. For disk carrots β∈[0.05,0.09] and γ∈[0.054,0.078], for cut cabbage β∈[0.05,0.10] and γ∈[0.09,0.12], and for cut iceberg lettuce β∈[0.03,0.06] and γ∈[0.07,0.14]. Taking values from these ranges the model was able to consistently predict experimental FC dynamics (decay and replenishment), indicating robustness of the apparent reaction rate constants across scales. Comparing sequential changes in COD with turbidity and total dissolved solids (TDS) relative to produce washing rates, our results also illustrate that turbidity and TDS may not be reliable predictors of FC decay rates across produce types and experimental scales. In concert with future experiments, these models could serve as important tools aimed at validating FC compliance within operational limits as well as guiding large-scale commercial experiments focused on improving chlorine management strategies relevant for industry

Modeling of Free Chlorine Consumption and Escherichia coli O157:H7 Cross-Contamination During Fresh-Cut Produce Wash Cycles

Controlling the free chlorine (FC) availability in wash water during sanitization of fresh produce enhances our ability to reduce microbial levels and prevent cross-contamination. However, maintaining an ideal concentration of FC that could prevent the risk of contamination within the wash system is still a technical challenge in the industry, indicating the need to better understand wash water chemistry dynamics. Using bench-scale experiments and modeling approaches, we developed a comprehensive mathematical model to predict the FC concentration during fresh-cut produce wash processes for different lettuce types (romaine, iceberg, green leaf, and red leaf), carrots, and green cabbage as well as Escherichia coli O157:H7 cross-contamination during fresh-cut iceberg lettuce washing. Fresh-cut produce exudates, as measured by chemical oxygen demand (COD) levels, appear to be the primary source of consumption of FC in wash water, with an apparent reaction rate ranging from 4.74x10-4 to 7.42x10-4 L/mg center dot min for all produce types tested, at stable pH levels (6.5 to 7.0) in the wash water. COD levels increased over time as more produce was washed and the lettuce type impacted the rate of increase in organic load. The model parameters from our experimental data were compared to those obtained from a pilot-plant scale study for lettuce, and similar reaction rate constant (5.38 x 10(-4) L/mg center dot min) was noted, supporting our hypothesis that rise in COD is the main cause of consumption of FC levels in the wash water. We also identified that the bacterial transfer mechanism described by our model is robust relative to experimental scale and pathogen levels in the wash water. Finally, we proposed functions that quantify an upper bound on pathogen levels in the water and on cross-contaminated lettuce, indicating the maximum potential of water-mediated cross-contamination. Our model results could help indicate the limits of FC control to prevent cross-contamination during lettuce washing

Balancing Energy Dissipation in Data Gathering Wireless Sensor Networks Using Ant Colony Optimization

Abstract. Formulation of energy efficient protocols is of utmost importance for wireless sensor networks because of energy constraints of sensor nodes. When a number of nodes is deployed in a field located away from the base station, the nodes undergo unequal energy dissipation while transmitting information to the base station primarily due to two reasons: i) the difference in the distances of nodes from the base station and ii) the variation in inter-nodal distances. The schemes presented here better network lifetime by taking into account these two issues and try to equalize the energy dissipation by the nodes. While constructing the chain we also use Ant Colony Optimization algorithm instead of greedy approach used in PEGASIS. Application of ACO ensures that the chain formed is of shortest possible length and thus further helps enhance network performances by reducing the inter-nodal transmission distances as much as possible. Extensive simulations performed corroborates that the proposed schemes outperform PEGASIS by a significant margin