We study the transport phenomena of colloidal particles embedded within a moving array of obstacles that mimics a dynamic, time-varying porous material. While colloidal transport in an array of stationary obstacles ("passive" porous media) has been well studied, we lack the fundamental understanding of colloidal diffusion in a nonequilibrium porous environment. We combine Taylor dispersion theory, Brownian dynamics simulations, and optical tweezer experiments to study the transport of tracer colloidal particles in an oscillating lattice of obstacles. We discover that the dispersion of tracer particles is a non-monotonic function of oscillation frequency and exhibits a maximum that exceeds the Stokes-Einstein-Sutherland diffusivity in the absence of obstacles. By solving the Smoluchowski equation using a generalized dispersion framework, we demonstrate that the enhanced transport of the tracers depends critically on both the direct interparticle interactions with the obstacles and the fluid-mediated, hydrodynamic interactions generated by the moving obstacles.

Ocular inflammation is commonly associated with eye disease or injury. Effective and sustained ocular delivery of therapeutics remains a challenge due to the eye physiology and structural barriers. Herein, we engineered a photocrosslinkable adhesive patch (GelPatch) incorporated with micelles (MCs) loaded with Loteprednol etabonate (LE) for delivery and sustained release of drug. The engineered drug loaded adhesive hydrogel, with controlled physical properties, provided a matrix with high adhesion to the ocular surfaces. The incorporation of MCs within the GelPatch enabled solubilization of LE and its sustained release within 15 days. studies showed that MC loaded GelPatch supported cell viability and growth. In addition, subcutaneous implantation of the MC loaded GelPatch in rats confirmed its biocompatibility and stability within 28 days. This non-invasive, adhesive, and biocompatible drug eluting patch can be used as a matrix for the delivery and sustained release of hydrophobic drugs.

The baroreflex is a multi-input, multi-output control physiological system that regulates blood pressure by modulating nerve activity between the brainstem and the heart. Existing computational models of the baroreflex do not explictly incorporate the intrinsic cardiac nervous system (ICN), which mediates central control of the heart function. We developed a computational model of closed-loop cardiovascular control by integrating a network representation of the ICN within central control reflex circuits. We examined central and local contributions to the control of heart rate, ventricular functions, and respiratory sinus arrhythmia (RSA). Our simulations match the experimentally observed relationship between RSA and lung tidal volume. Our simulations predicted the relative contributions of the sensory and the motor neuron pathways to the experimentally observed changes in the heart rate. Our closed-loop cardiovascular control model is primed for evaluating bioelectronic interventions to treat heart failure and renormalize cardiovascular physiology.

The pharmaceutical manufacturing sector needs to rapidly evolve to absorb the next wave of disruptive industrial innovations - Industry 4.0. This involves incorporating technologies like artificial intelligence, smart factories and 3D printing to automate, miniaturize and personalize the production processes. The goal of this study is to build a formulation and process design (FPD) framework for a pharmaceutical 3D printing technique called drop-on-demand (DoD) printing. FPD can automate the determination of formulation properties and printing conditions (input conditions) for DoD operation that can guarantee production of drug products with desired functional attributes. This study proposes to build the FPD framework in two parts: the first part involves building a machine learning model to simulate the forward problem - predicting DoD operation based on input conditions and the second part seeks to solve and experimentally validate the inverse problem - predicting input conditions that can yield desired DoD operation.

Fluidic oscillators (FOs) are used in a variety of applications, including process control and process intensification. Despite the simple design and operation of FOs, the fluid dynamics of FOs exhibit rich complexities. The inherently unstable flow, jet oscillations, and resulting vortices influence mixing and other transport processes. In this work, we computationally investigated the fluid dynamics of a new design of a planar FO with backflow limbs. The design comprised of two symmetric backflow limbs leading to bistable flow. The unsteady flow dynamics, internal recirculation, jet oscillations, secondary flow vortices were computationally studied over a range of inlet Reynolds numbers (2400-12,000). The nature and frequency of the jet oscillations were quantified. The computed jet oscillation frequency was compared with the experimentally measured (using imaging techniques) jet oscillation frequency. The flow model was then used to quantitatively understand mixing, heat transfer, and residence time distribution. The approach and the results presented in this work will provide a basis for designing FO's with desired flow and transport characteristics for various engineering applications.

In view of largely available renewable electricity as a green future resource, here we report the electrification of a Rh/AlO washcoated SiSiC foam for methane steam reforming (MSR). We show that, thanks to the suitable bulk resistivity of the SiSiC foam, its direct Joule heating up to relevant temperatures is feasible; the interconnected geometry greatly reduces heat and mass transfer limitations, which results in a highly active and energy efficient system for low-carbon H production. The foam-based electrified MSR (eMSR) system showed almost full methane conversion above 700°C and methane conversions approaching equilibrium were obtained in a range of conditions. Energy efficiency as high as 61% and specific power consumption as low as 2.0 kWh/ were measured at 650°C, at gas hourly space velocity (GHSV) of 150,000 cm/h/g. When driven by renewable electricity, the proposed reactor configuration promises a high potential to address the decarbonization challenge in the near-term future.

Aggregation of otherwise soluble proteins into amyloid structures is a hallmark of many disorders, such as Alzheimer's and Parkinson's disease. There is an increasing evidence that the small aggregations, instead of ordered fibrillar aggregates, are the main structures causing toxicity. However, the studies on the small aggregation phase are limited due to the variety of structures and the complexity of the physiological environment. Here, we showed an engineered co-assembling oppositely charged amyloid-like peptide pair ([II]) as a simple tool to establish methodologies to study the mechanism and kinetics of aggregation and relate its aggregation to toxicity. The toxicity mechanism of [II] is through cell membrane damage and stress, shown with YAP and eIF2α, as in the amyloid protein-initiated diseases. Albumin is demonstrated as an extrinsic and physiologically relevant molecule in controlling the aggregation lag time and toxicity of [II]. This study represents a molecular engineering strategy to create simplistic molecular tools for establishing methodologies to study the aggregation process and kinetics of amyloid-like proteins in various conditions. Understanding the nature of protein aggregation kinetics and linking them to their biological functions through engineered peptides paves the way for future designs and drug development applications.

Bone health is determined by factors including bone metabolism or remodeling. Wnt-10b alters osteoblastogenesis through pre-osteoblast proliferation and differentiation and osteoblast apoptosis rate, which collectively lead to the increase of bone density. To model this, we adapted a previously published model of bone remodeling. The resulting model for the bone compartment includes differential equations for active osteoclasts, pre-osteoblasts, osteoblasts, osteocytes, and the amount of bone present at the remodeling site. Our alterations to the original model consist of extending it past a single remodeling cycle and implementing a direct relationship to Wnt-10b. Four new parameters were estimated and validated using normalized data from mice. The model connects Wnt-10b to bone metabolism and predicts the change in trabecular bone volume caused by a change in Wnt-10b input. We find that this model predicts the expected increase in pre-osteoblasts and osteoblasts while also pointing to a decrease in osteoclasts when Wnt-10b is increased.

Penicillenols belong to the family of tetramic acids with anticancer and antibacterial activities. Here, we report the discovery of the biosynthetic gene cluster ( for penicillenol A and E in ATCC9849 by genome mining. We discover the cluster based on the results of gene deletions in and gene cluster heterologous expression in . We also propose the assembly line of the PKS module in PncA with the reduction by PncB provides a highly reduce polyketide chain to be further linked with an L-threonine molecule and released from PncA to produce penicillenol E. Further formation of penicillenol A requires the -methylation of tetramic acid group by PncC. Our work deepens the understanding of the biosynthetic logic for -methylated tetramic acids and contributes to the discovery of new penicillenols by genome mining.

Modern thermodynamic models incorporate the concept of association (hydrogen bonding) and they can describe very satisfactorily many properties of water containing mixtures. They have not been successful in representing water's anomalous properties and this work provides a possible explanation. We have analyzed and interpreted recent experimental data, molecular simulation results, and two-state theory approaches and compared against the predictions from thermodynamic models. We show that the dominance of the tetrahedral structure implemented in modern thermodynamic models may be the reason for their failure for describing water systems. While this study does not prove the two-state theories for water, it indicates that a high level of tetrahedral structure of water is not in agreement with water's anomalous properties when used in thermodynamic models.

Additive manufacturing affords precise control over geometries with high degrees of complexity and pre-defined structure. Lattices are one class of additive-only structures which have great potential in directing transport phenomena because they are highly ordered, scalable, and modular. However, a comprehensive description of how these structures scale and interact in heterogeneous systems is still undetermined. To advance this aim, we designed cubic and Kelvin lattices at two sub-5 mm length scales and compared published correlations to the experimental pressure gradient in pipes ranging from 12-52 mm diameter. We further investigated all combinations of the four lattices to evaluate segmented combinatorial behavior. The results suggest that a single correlation can describe pressure behavior for different lattice geometries and scales. Furthermore, combining lattice systems in series has a complex effect that is sensitive to part geometry. Together, these developments support the promise for tailored, modular lattice systems at laboratory scales and beyond.

The breakdown of the ventricular zone (VZ) with the presence of blood in cerebrospinal fluid (CSF) has been shown to increase shunt catheter obstruction in the treatment of hydrocephalus, but the mechanisms by which this occurs are generally unknown. Using a custom-built incubation chamber, we immunofluorescently assayed cell attachment and morphology on shunt catheters with and without blood after 14 days. Samples exposed to blood showed significantly increased cell attachment (average total cell count 392.0±317.1 versus control of 94.7±44.5, <0.0001). Analysis of the glial fibrillary acidic protein (GFAP) expression showed similar trends (854.4±450.7 versus control of 174.3±116.5, <0.0001). An model was developed to represent the exposure of astrocytes to blood following an increase in BBB permeability. Exposure of astrocytes to blood increases the number of cells and their spread on the shunt.

Otitis Media (OM) is the most common reason for U.S. children to receive prescribed oral antibiotics, leading to potential to cause antibiotic resistance. To minimize oral antibiotic usage, we developed polyvinylpyrrolidone-coated silver nanoparticles (AgNPs-PVP), which completely eradicated common OM pathogens, i.e., and non-typeable (NTHi) at 1.04μg/mL and 2.13μg/mL. The greater antimicrobial efficacy against was a result of the HO-producing ability of and the known synergistic interactions between HO and AgNPs. To enable the sustained local delivery of AgNPs-PVP (e.g., via injection through perforated tympanic membranes), a hydrogel formulation of 18%(w/v)P407 was developed. Reverse thermal gelation of the AgNPs-PVP-P407 hydrogel could gel rapidly upon entering the warm auditory bullae and thereby sustained release of antimicrobials. This hydrogel-based local delivery system completely eradicated OM pathogens in vitro without cytotoxicity, and thus represents a promising strategy for treating bacterial OM without relying on conventional antibiotics.

Bacterial biofilms are associated with chronic infectious diseases and are highly resistant to conventional antibiotics. Antimicrobial bacteriocins are alternatives to conventional antibiotics and are characterized by unique cell-killing mechanisms, including pore formation on cell membranes, nuclease activity, and cell wall synthesis inhibition. Here, we used cell-free protein synthesis to rapidly evaluate the anti-biofilm activities of colicins E1, E2, and E3. We found that E2 (with DNase activity) most effectively killed target biofilm cells (., the K361 strain) while leaving non-targeted biofilms intact. We then engineered probiotic microorganisms with genetic circuits to controllably synthesize and secrete colicin E2, which successfully inhibited biofilms and killed pre-formed indicator biofilms. Our findings suggest that colicins rapidly and selectively kill target biofilm cells in multispecies biofilms and demonstrate the potential of using microorganisms engineered to produce antimicrobial colicin proteins as live therapeutic strategies to treat biofilm-associated infections.

Antiviral monoclonal antibody (mAb) discovery enables the development of antibody-based antiviral therapeutics. Traditional antiviral mAb discovery relies on affinity between antibody and a viral antigen to discover potent neutralizing antibodies, but these approaches are inefficient because many high affinity mAbs have no neutralizing activity. We sought to determine whether screening for anti-SARS-CoV-2 mAbs at reduced pH could provide more efficient neutralizing antibody discovery. We mined the antibody response of a convalescent COVID-19 patient at both physiological pH (7.4) and reduced pH (4.5), revealing that SARS-CoV-2 neutralizing antibodies were preferentially enriched in pH 4.5 yeast display sorts. Structural analysis revealed that a potent new antibody called LP5 targets the SARS-CoV-2 N-terminal domain supersite via a unique binding recognition mode. Our data combine with evidence from prior studies to support antibody screening at pH 4.5 to accelerate antiviral neutralizing antibody discovery.

Emulsion electrospinning provides a tunable system for the development of porous scaffolds for controlled, localized drug delivery in tissue engineering applications. This study aimed to elucidate the role of model drug interactions with emulsion chemistry on loading and release rates from fibers with controlled fiber diameter and fiber volume fraction. Nile Red and Rhodamine B were used as model drugs and encapsulation efficiency and release rates were determined from poly(caprolactone) (PCL) electrospun fibers spun either with no surfactant (Span 80), surfactant, or water-in-oil emulsions. Drug loading efficiency and release rates were modulated by both surfactant and aqueous internal phase in the emulsions as a function of drug molecule hydrophobicity. Overall, these results demonstrate the role of intermolecular interactions and drug phase solubility on the release from emulsion electrospun fibers and highlight the need to independently control these parameters when designing fibers for use as tunable drug delivery systems.

Translation of nanotherapeutics from preclinical research to clinical application is difficult due to the complex and dynamic interaction space between the nanotherapeutic and the brain environment. To improve translation, increased insight into nanoformulation-brain interactions in preclinical research is necessary. We developed a nanoformulation-brain database and wrote queries to connect the complex physical, chemical, and biological features of neurotherapeutics based on experimental data. We queried the database to select nanoformulations based on specific physical characteristics that enable effective penetration within the brain, including size, polydispersity index, and zeta potential. Additionally, we demonstrate the ability to query the database to return select nanoformulation characteristics, including nanoformulation methodology or methodological variables such as surfactant, polymer, drug loading, and sonication times. Finally, we show the capacity of our database to produce correlations relating nanoparticle formulation parameters to biological outcomes, including nanotherapeutic impact on cell viability in cultured brain slices.

Optimal tip sonication settings, namely tip position, input power, and pulse durations, are necessary for temperature sensitive procedures like preparation of viable cell extract. In this paper, the optimum tip immersion depth (20-30% height below the liquid surface) is estimated which ensures maximum mixing thereby enhancing thermal dissipation of local cavitation hotspots. A finite element (FE) heat transfer model is presented, validated experimentally with (R > 97%) and used to observe the effect of temperature rise on cell extract performance of BL21 DE3 star strain and estimate the temperature threshold. Relative yields in the top 10% are observed for solution temperatures maintained below 32°C; this reduces below 50% relative yield at temperatures above 47°C. A generalized workflow for direct simulation using the COMSOL code as well as master plots for estimation of sonication parameters (power input and pulse settings) is also presented.

SARS-CoV-2, a novel coronavirus spreading worldwide, was declared a pandemic by the World Health Organization 3 months after the outbreak. Termed as COVID-19, airborne or surface transmission occurs as droplets/aerosols and seems to be reduced by social distancing and wearing mask. Demographic and geo-temporal factors like population density, temperature, healthcare system efficiency index and lockdown stringency index also influence the COVID-19 epidemiological curve. In the present study, an attempt is made to relate these factors with curve characteristics (mean and variance) using the classical residence time distribution analysis. An analogy is drawn between the continuous stirred tank reactor and infection in a given country. The 435 days dataset for 15 countries, where the first wave of epidemic is almost ending, have been considered in this study. Using method of moments technique, dispersion coefficient has been calculated. Regression analysis has been conducted to relate parameters with the curve characteristics.

Continuous manufacturing and closed-loop quality control are emerging technologies that are pivotal for next-generation pharmaceutical modernization. We develop a process control framework for a continuous carousel for integrated filtration-drying of crystallization slurries. The proposed control system includes model-based monitoring and control routines, such as state estimation and real-time optimization, implemented in a hierarchical, three-layer quality-by-control (QbC) framework. We implement the control system in ContCarSim, a publicly available carousel simulator. We benchmark the proposed control system against simpler methods, comprising a reduced subset of the elements of the overall control system, and against open-loop operation (the current standard in pharmaceutical manufacturing). The proposed control system demonstrates superior performance in terms of higher consistency in product quality and increased productivity, proving the benefits of closed-loop control and of model-based techniques in pharmaceutical manufacturing. This study represents a step forward toward end-to-end continuous pharmaceutical processing, and in the evolution of quality-by-design toward quality-by-control.

Increased interest in the pharmaceutical industry to transition from batch to continuouos manufacturing motivates the use of digital frameworks that allow systematic comparison of candidate process configurations. This paper evaluates the technical and economic feasibility of different end-to-end optimal process configurations, . batch, hybrid and continuous, for small-scale manufacturing of an active pharmaceutical ingredient. Production were analyzed for those configurations containing continuous equipment, where significant start-up effects are expected given the relatively short campaign times considered. Hybrid operating mode was found to be the most attractive process configuration at intermediate and large annual production targets, which stems from combining continuous reactors and semi-batch vaporization equipment. Continuous operation was found to be more costly, due to long stabilization times of continuous crystallization, and thermodynamic limitations of flash vaporization. Our work reveals the benefits of systematic digital evaluation of process configurations that operate under feasible conditions and compliant product quality attributes.