Improving Recovery of Diatoms Bio-Silica Using Chemical Treatment with VAUS TM.

High-temperature baking is a typical method to remove organic matter from diatoms, but it's not suitable for bio-silica because of the high crystallinity. This study provides a method using the VAUS™ to remove organic matter from diatoms more quickly and biocompatibly. Organic matter was removed by using VAUS™, while NaOCl was utilized to remove the organic matter from the silicate frustule. The optimal frequency for organic matter removal was investigated to domestically produced M. nummuloides . The removal efficiency of TOC/TN was calculated and analyzed. The C and Si elements were analyzed in EDS, while visual confirmation of organic matter removal was analyzed by using XRD. TOC RE% at a frequency of 35kHz exhibited the highest value, indicating a statistically significant difference. XRD analysis demonstrated that the organic matter was almost removed using NaOCl compared to the high-temperature baked M. nummuloides. In the EDS analysis, there were significant differences in the C and Si elements with respect to frequency. This is very similar to the values from the positive control group, high temperature baked M. nummuloides . This new procedure of applying periodic negative pressure to NaOCl pre-treatment is considered to be an effective method of chemically removing organic matter from diatoms.

Effect of Circadian Rhythm Modulated Blood Flow on Nanoparticle based Targeted Drug Delivery in Virtual In Vivo Arterial Geometries.

Delivery of drug using nanocarriers tethered with vasculature-targeting epitopes aims to maximize the therapeutic efficacy of the drug while minimizing the drug side effects. Circadian rhythm which is governed by the central nervous system has implications for targeted drug delivery due to sleep-wake cycle changes in blood flow dynamics. This paper presents an advanced fluid dynamics modeling method that is based on viscous incompressible shear-rate fluid (blood) coupled with an advection-diffusion equation to simulate the formation of drug concentration gradients in the blood stream and buildup of concentration at the targeted site. The method is equipped with an experimentally calibrated nanoparticle-endothelial cell adhesion model that employs Robin boundary conditions to describe nanoparticle retention based on probability of adhesion, a friction model accounting for surface roughness of endothelial cell layer, and a dispersion model based on Taylor-Aris expression for effective diffusion in the boundary layer. The computational model is first experimentally validated and then tested on engineered bifurcating arterial systems where impedance boundary conditions are applied at the outflow to account for the downstream resistance at each outlet. It is then applied to a virtual geometric model of an in vivo arterial tree developed through MRI-based image processing techniques. These simulations highlight the potential of the computational model for drug transport, adhesion, and retention at multiple sites in virtual in vivo models. The model provides a virtual platform for exploring circadian rhythm modulated blood flow for targeted drug delivery while minimizing the in vivo experimentation.

Modeling of spatiotemporal dynamics of ligand-coated particle flow in targeted drug delivery processes.

Nanoparticles tethered with vasculature-binding epitopes have been used to deliver the drug into injured or diseased tissues via the bloodstream. However, the extent that blood flow dynamics affects nanoparticle retention at the target site after adhesion needs to be better understood. This knowledge gap potentially underlies significantly different therapeutic efficacies between animal models and humans. An experimentally validated mathematical model that accurately simulates the effects of blood flow on nanoparticle adhesion and retention, thus circumventing the limitations of conventional trial-and-error-based drug design in animal models, is lacking. This paper addresses this technical bottleneck and presents an integrated mathematical method that derives heavily from a unique combination of a mechanics-based dispersion model for nanoparticle transport and diffusion in the boundary layers, an asperity model to account for surface roughness of endothelium, and an experimentally calibrated stochastic nanoparticle-cell adhesion model to describe nanoparticle adhesion and subsequent retention at the target site under external flow. PLGA-b-HA nanoparticles tethered with VHSPNKK peptides that specifically bind to vascular cell adhesion molecules on the inflamed vascular wall were investigated. The computational model revealed that larger particles perform better in adhesion and retention at the endothelium for the particle sizes suitable for drug delivery applications and within physiologically relevant shear rates. The computational model corresponded closely to the in vitro experiments which demonstrates the impact that model-based simulations can have on optimizing nanocarriers in vascular microenvironments, thereby substantially reducing in vivo experimentation as well as the development costs.

Delivery-mediated exosomal therapeutics in ischemia-reperfusion injury: advances, mechanisms, and future directions.

Ischemia-reperfusion injury (IRI) poses significant challenges across various organ systems, including the heart, brain, and kidneys. Exosomes have shown great potentials and applications in mitigating IRI-induced cell and tissue damage through modulating inflammatory responses, enhancing angiogenesis, and promoting tissue repair. Despite these advances, a more systematic understanding of exosomes from different sources and their biotransport is critical for optimizing therapeutic efficacy and accelerating the clinical adoption of exosomes for IRI therapies. Therefore, this review article overviews the administration routes of exosomes from different sources, such as mesenchymal stem cells and other somatic cells, in the context of IRI treatment. Furthermore, this article covers how the delivered exosomes modulate molecular pathways of recipient cells, aiding in the prevention of cell death and the promotions of regeneration in IRI models. In the end, this article discusses the ongoing research efforts and propose future research directions of exosome-based therapies.

Neuronal innervation regulates the secretion of neurotrophic myokines and exosomes from skeletal muscle.

Myokines and exosomes, originating from skeletal muscle, are shown to play a significant role in maintaining brain homeostasis. While exercise has been reported to promote muscle secretion, little is known about the effects of neuronal innervation and activity on the yield and molecular composition of biologically active molecules from muscle. As neuromuscular diseases and disabilities associated with denervation impact muscle metabolism, we hypothesize that neuronal innervation and firing may play a pivotal role in regulating secretion activities of skeletal muscles. We examined this hypothesis using an engineered neuromuscular tissue model consisting of skeletal muscles innervated by motor neurons. The innervated muscles displayed elevated expression of mRNAs encoding neurotrophic myokines, such as interleukin-6, brain-derived neurotrophic factor, and FDNC5, as well as the mRNA of peroxisome-proliferator-activated receptor γ coactivator 1α, a key regulator of muscle metabolism. Upon glutamate stimulation, the innervated muscles secreted higher levels of irisin and exosomes containing more diverse neurotrophic microRNAs than neuron-free muscles. Consequently, biological factors secreted by innervated muscles enhanced branching, axonal transport, and, ultimately, spontaneous network activities of primary hippocampal neurons in vitro. Overall, these results reveal the importance of neuronal innervation in modulating muscle-derived factors that promote neuronal function and suggest that the engineered neuromuscular tissue model holds significant promise as a platform for producing neurotrophic molecules.

Graphene Hybrid Tough Hydrogels with Nanostructures for Tissue Regeneration.

Over the past few decades, hydrogels have attracted considerable attention as promising biomedical materials. However, conventional hydrogels require improved mechanical properties, such as brittleness, which significantly limits their widespread use. Recently, hydrogels with remarkably improved toughness have been developed; however, their low biocompatibility must be addressed. In this study, we developed a tough graphene hybrid hydrogel with nanostructures. The resultant hydrogel exhibited remarkable mechanical properties while representing an aligned nanostructure that resembled the extracellular matrix of soft tissue. Owing to the synergistic effect of the topographical properties, and the enhanced biochemical properties, the graphene hybrid hydrogel had excellent stretchability, resilience, toughness, and biocompatibility. Furthermore, the hydrogel displayed outstanding tissue regeneration capabilities (e.g., skin and tendons). Overall, the proposed graphene hybrid tough hydrogel may provide significant insights into the application of tough hydrogels in tissue regeneration.

Biofilm removal effect of diatom complex on 3D printed denture base resin.

For patients who have difficulty in mechanical cleaning of dental appliances, a denture cleaner that can remove biofilm with dense extracellular polymeric substances is needed. The purpose of this study is to evaluate the efficacy of diatom complex with active micro-locomotion for removing biofilms from 3D printed dentures. The diatom complex, which is made by doping MnO2 nanosheets on diatom biosilica, is mixed with H2O2 to generate fine air bubbles continuously. Denture base resin specimens were 3D printed in a roof shape, and Pseudomonas aeruginosa (107 CFU/mL) was cultured on those for biofilm formation. Cleaning solutions of phosphate-buffered saline (negative control, NC), 3% H2O2 with peracetic acid (positive control, PC), denture cleanser tablet (DCT), 3% H2O2 with 2 mg/mL diatom complex M (Melosira, DM), 3% H2O2 with 2 mg/mL diatom complex A (Aulacoseira, DA), and DCT with 2 mg/mL DM were prepared and applied. To assess the efficacy of biofilm removal quantitatively, absorbance after cleaning was measured. To evaluate the stability of long-term use, surface roughness, ΔE, surface micro-hardness, and flexural strength of the 3D printed dentures were measured before and after cleaning. Cytotoxicity was evaluated using Cell Counting Kit-8. All statistical analyses were conducted using SPSS for Windows with one-way ANOVA, followed by Scheffe's test as a post hoc (p < 0.05). The group treated with 3% H2O2 with DA demonstrated the lowest absorbance value, followed by the groups treated with 3% H2O2 with DM, PC, DCT, DCT + DM, and finally NC. As a result of Scheffe's test to evaluate the significance of difference between the mean values of each group, statistically significant differences were shown in all groups based on the NC group. The DA and DM groups showed the largest mean difference though there was no significant difference between the two groups. Regarding the evaluation of physical and mechanical properties of the denture base resin, no statistically significant differences were observed before and after cleaning. In the cytotoxicity test, the relative cell count was over 70%, reflecting an absence of cytotoxicity. The diatom complex utilizing active micro-locomotion has effective biofilm removal ability and has a minimal effect in physical and mechanical properties of the substrate with no cytotoxicity.