Competing Mechanisms in Bacterial Invasion of Human Colon Mucus Probed with Agent-based Modeling.

The gastrointestinal tract is inhabited by a vast community of microorganisms, termed the gut microbiota. Large colonies can pose a health threat but the gastrointestinal mucus system protects epithelial cells from microbiota invasion. The human colon features a bilayer of mucus lining. Due to imbalances in intestinal homeostasis, bacteria may successfully penetrate the inner mucus layer which can lead to severe gut diseases. However, it is hard to tease apart the competing mechanisms that lead to this penetration. To probe the conditions that permit bacteria penetration into the inner mucus layer, we develop an agent-based model consisting of bacteria and an inner mucus layer subject to a constant flux of nutrient fields feeding the bacteria. We find that there are three important variables that determine bacterial invasion: the bacterial reproduction rate, the contact energy between bacteria and mucus, and the rate of bacteria degrading the mucus. Under healthy conditions, all bacteria are naturally eliminated by the constant removal of mucus. In diseased states, imbalances between the rates of bacterial degradation and mucus secretion lead to bacterial invasion at certain junctures. We conduct uncertainty quantification and sensitivity analysis to compare the relative impact between these parameters. The contact energy has the strongest influence on bacterial penetration which, in combination with bacterial degradation rate and growth rate, greatly accelerates bacterial invasion of the human gut mucus lining. Our findings will serve as predictive indicators for the etiology of intestinal diseases and highlight important considerations when developing gut therapeutics.

A Pseudo-Surfactant Chemical Permeation Enhancer to Treat Otitis Media via Sustained Transtympanic Delivery of Antibiotics.

Chemical permeation enhancers (CPEs) represent a prevalent and safe strategy to enable noninvasive drug delivery across skin-like biological barriers such as the tympanic membrane (TM). While most existing CPEs interact strongly with the lipid bilayers in the stratum corneum to create defects as diffusion paths, their interactions with the delivery system, such as polymers forming a hydrogel, can compromise gelation, formulation stability, and drug diffusion. To overcome this challenge, differing interactions between CPEs and the hydrogel system are explored, especially those with sodium dodecyl sulfate (SDS), an ionic surfactant and a common CPE, and those with methyl laurate (ML), a nonionic counterpart with a similar length alkyl chain. Notably, the use of ML effectively decouples permeation enhancement from gelation, enabling sustained delivery across TMs to treat acute otitis media (AOM), which is not possible with the use of SDS. Ciprofloxacin and ML are shown to form a pseudo-surfactant that significantly boosts transtympanic permeation. The middle ear ciprofloxacin concentration is increased by 70-fold in vivo in a chinchilla AOM model, yielding superior efficacy and biocompatibility than the previous highest-performing formulation. Beyond improved efficacy and biocompatibility, this single-CPE formulation significantly accelerates its progression toward clinical deployment.

Coarse-grained modeling and dynamics tracking of nanoparticles diffusion in human gut mucus.

The gastrointestinal (GI) tract's mucus layer serves as a critical barrier and a mediator in drug nanoparticle delivery. The mucus layer's diverse molecular structures and spatial complexity complicates the mechanistic study of the diffusion dynamics of particulate materials. In response, we developed a bi-component coarse-grained mucus model, specifically tailored for the colorectal cancer environment, that contained the two most abundant glycoproteins in GI mucus: Muc2 and Muc5AC. This model demonstrated the effects of molecular composition and concentration on mucus pore size, a key determinant in the permeability of nanoparticles. Using this computational model, we investigated the diffusion rate of polyethylene glycol (PEG) coated nanoparticles, a widely used muco-penetrating nanoparticle. We validated our model with experimentally characterized mucus pore sizes and the diffusional coefficients of PEG-coated nanoparticles in the mucus collected from cultured human colorectal goblet cells. Machine learning fingerprints were then employed to provide a mechanistic understanding of nanoparticle diffusional behavior. We found that larger nanoparticles tended to be trapped in mucus over longer durations but exhibited more ballistic diffusion over shorter time spans. Through these discoveries, our model provides a promising platform to study pharmacokinetics in the GI mucus layer.

Elucidating Interfacial Dynamics of Ti-Al Systems Using Molecular Dynamics Simulation and Markov State Modeling.

Due to their remarkable mechanical and chemical properties, Ti-Al-based materials are attracting considerable interest in numerous fields of engineering, such as automotive, aerospace, and defense. With their low density, high strength, and resistance to corrosion and oxidation, these intermetallic alloys and metal-compound composites have found diverse applications. However, additive manufacturing and heat treatment of Ti-Al alloys frequently lead to brittleness and severe formation of defects. The present study delves into the interfacial dynamics of these Ti-Al systems, particularly focusing on the behavior of Ti and Al atoms in the presence of TiAl3 grain boundaries under experimental heat treatment conditions. Using a combination of molecular dynamics and Markov state modeling, we scrutinize the kinetic processes involved in the formation of TiAl3. The molecular dynamics simulation indicates that at the early stage of heat treatment, the predominating process is the diffusion of Al atoms toward the Ti surface through the TiAl3 grain boundaries. Markov state modeling identifies three distinct dynamic states of Al atoms within the Ti/Al mixture that forms during the process, each exhibiting a unique spatial distribution. Using transition time scales as a qualitative measure of the rapidness of the dynamics, it is observed that the Al dynamics is significantly less rapid near the Ti surface compared to the Al surface. Put together, the results offer a comprehensive understanding of the interfacial dynamics and reveal a three-stage diffusion mechanism. The process initiates with the premelting of Al, proceeds with the prevalent diffusion of Al atoms toward the Ti surface, and eventually ceases as the Ti concentration within the mixture progressively increases. The insights gained from this study could contribute significantly to the control and optimization of manufacturing processes for these high-performing Ti-Al-based materials.

Controlling biofilm transport with porous metamaterials designed with Bayesian learning.

Biofilm growth and transport in confined systems frequently occur in natural and engineered systems. Designing customizable engineered porous materials for controllable biofilm transportation properties could significantly improve the rapid utilization of biofilms as engineered living materials for applications in pollution alleviation, material self-healing, energy production, and many more. We combine Bayesian optimization (BO) and individual-based modeling to conduct design optimizations for maximizing different porous materials' (PM) biofilm transportation capability. We first characterize the acquisition function in BO for designing 2-dimensional porous membranes. We use the expected improvement acquisition function for designing lattice metamaterials (LM) and 3-dimensional porous media (3DPM). We find that BO is 92.89% more efficient than the uniform grid search method for LM and 223.04% more efficient for 3DPM. For all three types of structures, the selected characterization simulation tests are in good agreement with the design spaces approximated with Gaussian process regression. All the extracted optimal designs exhibit better biofilm growth and transportability than unconfined space without substrates. Our comparison study shows that PM stimulates biofilm growth by taking up volumetric space and pushing biofilms' upward growth, as evidenced by a 20% increase in bacteria cell numbers in unconfined space compared to porous materials, and 128% more bacteria cells in the target growth region for PM-induced biofilm growth compared with unconfined growth. Our work provides deeper insights into the design of substrates to tune biofilm growth, analyzing the optimization process and characterizing the design space, and understanding biophysical mechanisms governing the growth of biofilms.

Design and Characterization of Model Systems that Promote and Disrupt Transparency of Vertebrate Crystallins In Vitro.

Positioned within the eye, the lens supports vision by transmitting and focusing light onto the retina. As an adaptive glassy material, the lens is constituted primarily by densely-packed, polydisperse crystallin proteins that organize to resist aggregation and crystallization at high volume fractions, yet the details of how crystallins coordinate with one another to template and maintain this transparent microstructure remain unclear. The role of individual crystallin subtypes (α, ß, and γ) and paired subtype compositions, including how they experience and resist crowding-induced turbidity in solution, is explored using combinations of spectrophotometry, hard-sphere simulations, and surface pressure measurements. After assaying crystallin combinations, ß-crystallins emerged as a principal component in all mixtures that enabled dense fluid-like packing and short-range order necessary for transparency. These findings helped inform the design of lens-like hydrogel systems, which are used to monitor and manipulate the loss of transparency under different crowding conditions. When taken together, the findings illustrate the design and characterization of adaptive materials made from lens proteins that can be used to better understand mechanisms regulating transparency.

Fundamental mechanistic insights into the catalytic reactions of Li─S redox by Co single-atom electrocatalysts via operando methods.

Lithium-sulfur batteries represent an attractive option for energy storage applications. A deeper understanding of the multistep lithium-sulfur reactions and the electrocatalytic mechanisms are required to develop advanced, high-performance batteries. We have systematically investigated the lithium-sulfur redox processes catalyzed by a cobalt single-atom electrocatalyst (Co-SAs/NC) via operando confocal Raman microscopy and x-ray absorption spectroscopy (XAS). The real-time observations, based on potentiostatic measurements, indicate that Co-SAs/NC efficiently accelerates the lithium-sulfur reduction/oxidation reactions, which display zero-order kinetics. Under galvanostatic discharge conditions, the typical stepwise mechanism of long-chain and intermediate-chain polysulfides is transformed to a concurrent pathway under electrocatalysis. In addition, operando cobalt K-edge XAS studies elucidate the potential-dependent evolution of cobalt's oxidation state and the formation of cobalt-sulfur bonds. Our work provides fundamental insights into the mechanisms of catalyzed lithium-sulfur reactions via operando methods, enabling a deeper understanding of electrocatalysis and interfacial dynamics in electrical energy storage systems.

Biomass carbon mining to develop nature-inspired materials for a circular economy.

A transition from a linear to a circular economy is the only alternative to reduce current pressures in natural resources. Our society must redefine our material sources, rethink our supply chains, improve our waste management, and redesign materials and products. Valorizing extensively available biomass wastes, as new carbon mines, and developing biobased materials that mimic nature's efficiency and wasteless procedures are the most promising avenues to achieve technical solutions for the global challenges ahead. Advances in materials processing, and characterization, as well as the rise of artificial intelligence, and machine learning, are supporting this transition to a new materials' mining. Location, cultural, and social aspects are also factors to consider. This perspective discusses new alternatives for carbon mining in biomass wastes, the valorization of biomass using available processing techniques, and the implementation of computational modeling, artificial intelligence, and machine learning to accelerate material's development and process engineering.

Deformation Rate-Adaptive Conducting Polymers and Composites.

Materials are more easily damaged during accidents that involve rapid deformation. Here, a design strategy is described for electronic materials comprised of conducting polymers that defies this orthodox property, making their extensibility and toughness dynamically adaptive to deformation rates. This counterintuitive property is achieved through a morphology of interconnected nanoscopic core-shell micelles, where the chemical interactions are stronger within the shells than the cores. As a result, the interlinked shells retain material integrity under strain, while the rate of dissociation of the cores controls the extent of micelle elongation, which is a process that adapts to deformation rates. A prototype based on polyaniline shows a 7.5-fold increase in ultimate elongation and a 163-fold increase in toughness when deformed at increasing rates from 2.5 to 10 000% min-1 . This concept can be generalized to other conducting polymers and highly conductive composites to create "self-protective" soft electronic materials with enhanced durability under dynamic movement or deformation.

Computational Design of Antimicrobial Active Surfaces via Automated Bayesian Optimization.

Biofilms pose significant problems for engineers in diverse fields, such as marine science, bioenergy, and biomedicine, where effective biofilm control is a long-term goal. The adhesion and surface mechanics of biofilms play crucial roles in generating and removing biofilm. Designing customized nanosurfaces with different surface topologies can alter the adhesive properties to remove biofilms more easily and greatly improve long-term biofilm control. To rapidly design such topologies, we employ individual-based modeling and Bayesian optimization to automate the design process and generate different active surfaces for effective biofilm removal. Our framework successfully generated optimized functional nanosurfaces for improved biofilm removal through applied shear and vibration. Densely distributed short pillar topography is the optimal geometry to prevent biofilm formation. Under fluidic shearing, the optimal topography is to sparsely distribute tall, slim, pillar-like structures. When subjected to either vertical or lateral vibrations, thick trapezoidal cones are found to be optimal. Optimizing the vibrational loading indicates a small vibration magnitude with relatively low frequencies is more efficient in removing biofilm. Our results provide insights into various engineering fields that require surface-mediated biofilm control. Our framework can also be applied to more general materials design and optimization.

Design and Production of Customizable and Highly Aligned Fibrillar Collagen Scaffolds.

The ability to fabricate anisotropic collagenous materials rapidly and reproducibly has remained elusive despite decades of research. Balancing the natural propensity of monomeric collagen (COL) to spontaneously polymerize in vitro with the mild processing conditions needed to maintain its native substructure upon polymerization introduces challenges that are not easily amenable with off-the-shelf instrumentation. To overcome these challenges, we have designed a platform that simultaneously aligns type I COL fibrils under mild shear flow and builds up the material through layer-by-layer assembly. We explored the mechanisms propagating fibril alignment, targeting experimental variables such as shear rate, viscosity, and time. Coarse-grained molecular dynamics simulations were also employed to help understand how initial reaction conditions including chain length, indicative of initial polymerization, and chain density, indicative of concentration, in the reaction environment impact fibril growth and alignment. When taken together, the mechanistic insights gleaned from these studies inspired the design, iteration, fabrication, and then customization of the fibrous collagenous materials, illustrating a platform material that can be readily adapted to future tissue engineering applications.

Current Insights on the Diverse Structures and Functions in Bacterial Collagen-like Proteins.

The dearth of knowledge on the diverse structures and functions in bacterial collagen-like proteins is in stark contrast to the deep grasp of structures and functions in mammalian collagen, the ubiquitous triple-helical scleroprotein that plays a central role in tissue architecture, extracellular matrix organization, and signal transduction. To fill and highlight existing gaps due to the general paucity of data on bacterial CLPs, we comprehensively reviewed the latest insight into their functional and structural diversity from multiple perspectives of biology, computational simulations, and materials engineering. The origins and discovery of bacterial CLPs were explored. Their genetic distribution and molecular architecture were analyzed, and their structural and functional diversity in various bacterial genera was examined. The principal roles of computational techniques in understanding bacterial CLPs' structural stability, mechanical properties, and biological functions were also considered. This review serves to drive further interest and development of bacterial CLPs, not only for addressing fundamental biological problems in collagen but also for engineering novel biomaterials. Hence, both biology and materials communities will greatly benefit from intensified research into the diverse structures and functions in bacterial collagen-like proteins.

Molecular Design and Preparation of Protein-Based Soft Ionic Conductors with Tunable Properties.

Protein-based soft ionic conductors have attracted considerable research interest in recent years with great potential in applications at the human-machine interfaces. However, a fundamental mechanistic understanding of the ionic conductivity of silk-based ionic conductors is still unclear. Here, we first developed an environmental-friendly and scalable method to fabricate silk-based soft ionic conductors using silk proteins and calcium chloride. The mechanistic understanding of the ion transport and molecular interactions between calcium ions and silk proteins at variable water contents was investigated in-depth by combining experimental and simulation approaches. The results show that calcium ions primarily interact with amide groups in proteins at a low water content. The ionic conductivity is low since the calcium ions are confined around silk proteins within 2.0-2.6 Å. As water content increases, the calcium ions are hydrated with the formation of water shells, leading to the increased distance between calcium ions and silk proteins (3.3-6.0 Å). As a result, the motion of the calcium ions increased to achieve a higher ionic conductivity. By optimizing the ratio of the silk proteins, calcium ions, and water, silk-based soft ionic conductors with good stretchability and self-healing properties can be obtained. Such protein-based soft ionic conductors can be further used to fabricate smart devices such as electrochromic devices.

Probing the alignment-dependent mechanical behaviors and time-evolutional aligning process of collagen scaffolds.

Efficiently manipulating and reproducing collagen (COL) alignment in vitro remains challenging because many of the fundamental mechanisms underlying and guiding the alignment process are not known. We reconcile experiments and coarse-grained molecular dynamics simulations to investigate the mechanical behaviors of a growing COL scaffold and assay how changes in fiber alignment and various cross-linking densities impact their alignment dynamics under shear flow. We find higher cross-link densities and alignment levels significantly enhance the apparent tensile/shear moduli and strength of a bulk COL system, suggesting potential measures to facilitate the design of stronger COL based materials. Since fibril alignment plays a key factor in scaffold mechanics, we next investigate the molecular mechanism behind fibril alignment with Couette flow by computationally investigating the effects of COL's structural properties such as chain lengths, number of chains, tethering conditions, and initial COL conformations on the COL's final alignment level. Our computations suggest that longer chain lengths, more chains, greater amounts of tethering, and initial anisotropic COL conformations benefit the final alignment, but the effect of chain lengths may be more dominant over other factors. These results provide important parameters for consideration in manufacturing COL-based scaffolds where alignment and cross-linking are necessary for regulating performance.

Thermo- and ion-responsive silk-elastin-like proteins and their multiscale mechanisms.

Silk-elastin-like protein (SELP) is an excellent biocompatible and biodegradable material for hydrogels with tunable properties that can respond to multiple external stimuli. By integrating fully atomistic, replica exchange molecular dynamics simulations with detailed experiments, we predict and measure structural responses to changes in temperature and ion concentration of a novel SELP sequence, as well as a diazonium-coupled version. A single SELP molecule shrinks at high temperatures, whereas diazonium coupling decreases this thermo-responsiveness. Diazonium coupling weakens electrostatic interactions, leading to an insignificant ionic response in the single chain, while also decreasing gelation rates by reducing the number of exposed dityrosine crosslink sites and their solvent-accessible surface areas. With further data from our coarse-grained crosslinked SELP model and our experiments, we find that three effects are critical for SELP cluster's physical response to external stimuli: (1) the structural transition of SELPs at high temperature, (2) the geometry restraints in hydrogel networks, and (3) the electrostatic interactions between molecules. This molecular understanding of the thermal and ion response in single molecules of SELPs and their crosslinked networks may further improve and help innovate SELP's stimuli-responsive properties, creating significant opportunities for applications in biomedical devices and other engineering applications.

Engineering Natural and Recombinant Silks for Sustainable Biodevices.

Silk fibroin (SF) is a structural protein derived from natural silkworm silks. Materials fabricated based on SF usually inherit extraordinary physical and biological properties, including high mechanical strength, toughness, optical transparency, tailorable biodegradability, and biocompatibility. Therefore, SF has attracted interest in the development of sustainable biodevices, especially for emergent bio-electronic technologies. To expand the function of current silk devices, the SF characteristic sequence has been used to synthesize recombinant silk proteins that benefit from SF and other functional peptides, such as stimuli-responsive elastin peptides. In addition to genetic engineering methods, innovated chemistry modification approaches and improved material processing techniques have also been developed for fabricating advanced silk materials with tailored chemical features and nanostructures. Herein, this review summarizes various methods to synthesize functional silk-based materials from different perspectives. This review also highlights the recent advances in the applications of natural and recombinant silks in tissue regeneration, soft robotics, and biosensors, using B. mori SF and silk-elastin-like proteins (SELPs) as examples.

The Impact of Foaming Effect on the Physical and Mechanical Properties of Foam Glasses with Molecular-Level Insights.

Foaming effect strongly impacts the physical and mechanical properties of foam glass materials, but an understanding of its mechanism especially at the molecular level is still limited. In this study, the foaming effects of dextrin, a mixture of dextrin and carbon, and different carbon allotropes are investigated with respect to surface morphology as well as physical and mechanical properties, in which 1 wt.% carbon black is identified as an optimal choice for a well-balanced material property. More importantly, the different foaming effects are elucidated by all-atomistic molecular dynamics simulations with molecular-level insights into the structure-property relationships. The results show that smaller pores and more uniform pore structure benefit the mechanical properties of the foam glass samples. The foam glass samples show excellent chemical and thermal stability with 1 wt.% carbon as the foaming agent. Furthermore, the foaming effects of CaSO4 and Na2HPO4 are investigated, which both create more uniform pore structures. This work may inspire more systematic approaches to control foaming effect for customized engineering needs by establishing molecular-level structure-property-process relationships, thereby, leading to efficient production of foam glass materials with desired foaming effects.

Hybridly double-crosslinked carbon nanotube networks with combined strength and toughness via cooperative energy dissipation.

Although chemical crosslinking has been extensively explored to enhance the mechanical properties of network-type materials for structural and energy (electrochemical, thermal, etc.) applications, loading-induced energy dissipations usually occur through a single channel that either leads to network brittleness or low strength/stiffness. In this work, we apply coarse-grained molecular dynamics simulations to explore the potential of hybridly double-crosslinked carbon nanotube (CNT) networks as a light weight functional material with combined strength and toughness. While increasing the crosslinking density or strong crosslink composition may, in general, enhance the strength and toughness, further increasing the two parameters would surprisingly lead to deteriorated strength and toughness. We find that double-crosslinked networks can nicely achieve cooperative energy dissipation with minimal structural damage. In particular, the weak crosslinks serve as "sacrificial bonds" to dissipate elastic energies from external loading, while the strong crosslinks act as "structure holders" and break at a much later stage during the tensile test. Therefore, the combination of more than one type of crosslinking with hybrid potential energy landscapes and breaking time scales can prevent premature simultaneous breaking of multiple strong crosslinks. By deploying intermediate amounts of weak and strong crosslinks, we observe an outstanding density-normalized strength of 227-2130 kPa m3 kg-1 as compared to many structural materials and advanced nanocomposites. The crosslinking strategies developed here would pave new avenues for the rational design of functional network materials beyond CNTs, such as hydrogels, nanofibers, and nanocomposites.