Instabilities and self-organization in spatiotemporal epidemic dynamics driven by nonlinearity and noise.

Theoretical analysis of epidemic dynamics has attracted significant attention in the aftermath of the COVID-19 pandemic. In this article, we study dynamic instabilities in a spatiotemporal compartmental epidemic model represented by a stochastic system of coupled partial differential equations (SPDE). Saturation effects in infection spread-anchored in physical considerations-lead to strong nonlinearities in the SPDE. Our goal is to study the onset of dynamic, Turing-type instabilities, and the concomitant emergence of steady-state patterns under the interplay between three critical model parameters-the saturation parameter, the noise intensity, and the transmission rate. Employing a second-order perturbation analysis to investigate stability, we uncover both diffusion-driven and noise-induced instabilities and corresponding self-organized distinct patterns of infection spread in the steady state. We also analyze the effects of the saturation parameter and the transmission rate on the instabilities and the pattern formation. In summary, our results indicate that the nuanced interplay between the three parameters considered has a profound effect on the emergence of dynamical instabilities and therefore on pattern formation in the steady state. Moreover, due to the central role played by the Turing phenomenon in pattern formation in a variety of biological dynamic systems, the results are expected to have broader significance beyond epidemic dynamics.

Differential modulation of cellular phenotype and drug sensitivity by extracellular matrix proteins in primary and metastatic pancreatic cancer cells.

Pancreatic ductal adenocarcinoma (PDAC) is reported to be the third highest cause of cancer-related deaths in the United States. PDAC is known for its high proportion of stroma, which accounts for 90% of the tumor mass. The stroma is made up of extracellular matrix (ECM) and nonmalignant cells such as inflammatory cells, cancer-associated fibroblasts, and lymphatic and blood vessels. Here, we decoupled the effects of the ECM on PDAC cell lines by culturing cells on surfaces coated with different ECM proteins. Our data show that the primary tumor-derived cell lines have different morphology depending on the ECM proteins on which they are cultured, while metastatic lesion-derived PDAC lines' morphology does not change with respect to the different ECM proteins. Similarly, ECM proteins modulate the proliferation rate and the gemcitabine sensitivity of the primary tumor PDAC cell lines, but not the metastatic PDAC lines. Lastly, transcriptomics analysis of the primary tumor PDAC cells cultured on different ECM proteins reveals the regulation of various pathways, such as cell cycle, cell-adhesion molecules, and focal adhesion, including the regulation of several integrin genes that are essential for ECM recognition.

Memory in aging colloidal gels with time-varying attraction.

We report a combined rheology, x-ray photon correlation spectroscopy, and modeling study of gel formation and aging in suspensions of nanocolloidal spheres with volume fractions of 0.20 and 0.43 and with a short-range attraction whose strength is tuned by changing temperature. Following a quench from high temperature, where the colloids are essentially hard spheres, to a temperature below the gel point, the suspensions form gels that undergo aging characterized by a steadily increasing elastic shear modulus and slowing, increasingly constrained microscopic dynamics. The aging proceeds at a faster rate for stronger attraction strength. When the attraction strength is suddenly lowered during aging, the gel properties evolve non-monotonically in a manner resembling the Kovacs effect in glasses, in which the modulus decreases and the microscopic dynamics become less constrained for a period before more conventional aging resumes. Eventually, the properties of the gel following the decrease in attraction strength converge to those of a gel that has undergone aging at the lower attraction strength throughout. The time scale of this convergence increases as a power law with the age at which the attraction strength is decreased and decreases exponentially with the magnitude of the change in attraction. A model for gel aging in which particles attach and detach from the gel at rates that depend on their contact number reproduces these trends and reveals that the non-monotonic behavior results from the dispersion in the rates that the populations of particles with different contact number adjust to the new attraction strength.

Rheological characterization of cell-laden alginate-gelatin hydrogels for 3D biofabrication.

Biofabrication of tissue models that closely mimic the tumor microenvironment is necessary for high-throughput anticancer therapeutics. Extrusion-based bioprinting of heterogeneous cell-laden hydrogels has shown promise in advancing rapid artificial tissue development. A major bottleneck limiting the rapid production of physiologically relevant tissue models is the current limitation in effectively printing large populations of cells. However, by significantly increasing hydrogel cell-seeding densities, the time required to produce tissues could be effectively reduced. Here, we explore the effects of increasing cell seeding densities on the viscoelastic properties, printability, and cell viability of two different alginate-gelatin hydrogel compositions. Rheological analysis of hydrogels of varying cell seeding densities reveals an inverse relationship between cell concentration and zero-shear viscosity. We also observe that as cell seeding densities increases, the storage moduli decrease, thus lowering the required printing pressures for gel extrusion. We also observe that increasing cell concentration can negatively impact the structural properties of the extruded material by increasing post-print line spreading. We find that hydrogels composed of higher molecular weight alginates and the highest cell-seeding densities (107 cells/mL) yield higher cell viability (>80%) and structural uniformity after printing. The optimized printing parameters determined for the alginate-gelatin bioinks explored may aid in the future rapid fabrication of functional tissue models for therapeutic screening.

Non-Pharmaceutical Interventions as Controls to mitigate the spread of epidemics: An analysis using a spatiotemporal PDE model and COVID-19 data.

We investigate the spatiotemporal dynamics and control of an epidemic using a partial differential equation (PDE) based Susceptible-Latent-Infected-Recovered (SLIR) model. We first validate the model using empirical COVID-19 data corresponding to a period of 45 days from the state of Ohio, United States. Upon optimizing the model parameters in the learning phase of the analysis using actual infection data from a period of the first 30 days, we then find that the model output closely tracks the actual data for the next 15 days. Next, we introduce a control input into the model to represent the Non-Pharmaceutical Intervention of social distancing. Implementing the control using two distinct schemes, we find that in both cases the control input is able to significantly mitigate the infection spread. In addition to opening a novel pathway towards the characterization, analysis and implementation of Non-Pharmaceutical Interventions across multiple geographical scales using Control frameworks, our results highlight the importance of first-principles based PDE models in understanding the spatiotemporal dynamics of epidemics triggered by novel pathogens.

Halogen Etch of Ti3AlC2 MAX Phase for MXene Fabrication.

The versatile property suite of two-dimensional MXenes is driving interest in various applications, including energy storage, electromagnetic shielding, and conductive coatings. Conventionally, MXenes are synthesized by a wet-chemical etching of the parent MAX-phase in HF-containing media. The acute toxicity of HF hinders scale-up, and competing surface hydrolysis challenges control of surface composition and grafting methods. Herein, we present an efficient, room-temperature etching method that utilizes halogens (Br2, I2, ICl, IBr) in anhydrous media to synthesize MXenes from Ti3AlC2. A radical-mediated process depends strongly on the molar ratio of the halogen to MAX phase, absolute concentration of the halogen, the solvent, and temperature. This etching method provides opportunities for controlled surface chemistries to modulate MXene properties.

20†µs-resolved high-throughput X-ray photon correlation spectroscopy on a 500k pixel detector enabled by data-management workflow.

The performance of the new 52 kHz frame rate Rigaku XSPA-500k detector was characterized on beamline 8-ID-I at the Advanced Photon Source at Argonne for X-ray photon correlation spectroscopy (XPCS) applications. Due to the large data flow produced by this detector (0.2 PB of data per 24 h of continuous operation), a workflow system was deployed that uses the Advanced Photon Source data-management (DM) system and high-performance software to rapidly reduce area-detector data to multi-tau and two-time correlation functions in near real time, providing human-in-the-loop feedback to experimenters. The utility and performance of the workflow system are demonstrated via its application to a variety of small-angle XPCS measurements acquired from different detectors in different XPCS measurement modalities. The XSPA-500k detector, the software and the DM workflow system allow for the efficient acquisition and reduction of up to ∼109 area-detector data frames per day, facilitating the application of XPCS to measuring samples with weak scattering and fast dynamics.

Analysis of epidemic spread dynamics using a PDE model and COVID-19 data from Hamilton County OH USA.

We study the spatiotemporal dynamics of an epidemic spread using a compartmentalized PDE model. The model is validated using COVID-19 data from Hamilton County, Ohio, USA. The model parameters are estimated using a month of recorded data and then used to forecast the infection spread over the next ten days. The model is able to accurately estimate the key dynamic characteristics of COVID-19 spread in the county. Additionally, a stability analysis indicates that the model is robust to disturbances and perturbations which, for instance, could be used to represent the effects of super spreader events. We also use the modeling framework to analyse and discuss the impact of Non-pharmaceutical interventions (NPIs) for mitigation of infection. Our results suggest that such models can yield useful short and medium term predictive characterization of an epidemic spread in a restricted geographical region and also help formulate effective NPIs for mitigation. The results also signify the importance of further research into the accurate analytical representation of specific NPIs and hence their dampening effects on an infection spread.

Absorbent-Adsorbates: Large Amphiphilic Janus Microgels as Droplet Stabilizers.

Microgel particles are cross-linked polymer networks that absorb certain liquids causing network expansion. The type of swelling fluid and extent of volume change depends on the polymer-liquid interaction and the network's cross-link density. These colloidal gels can be used to stabilize emulsion drops by adsorbing to the interface of two immiscible fluids. However, to enhance the adsorption abilities of these predominantly hydrophilic gel particles, some degree of hydrophobicity is needed. An amphiphilic Janus microgel with spatially distinct lipophilic and hydrophilic sides is desired. Here, we report the fabrication of poly(ethylene glycol) diacrylate/poly(propylene glycol) diacrylate Janus microgels (JM) using microfluidic drop making. The flow streams of the two separate and immiscible monomer solutions are brought into contact and intersected by a third immiscible fluid in a flow-focusing junction to form Janus droplets. The individual droplets are cross-linked via UV irradiation to form monodispersed microgel particles with opposing hydrophilic and hydrophobic 3D-networked polymer matrices. By combining two chemically different polymer gel networks, an amphiphilic emulsion stabilizer is formed that adsorbs to the oil-water interface while its faces absorb their respective water or hydrocarbon solvents. The resulting water-in-oil emulsions are stabilized and destabilized via a thermal-responsive hydrogel. Stimuli-responsive droplets are demonstrated by adding a short-chain oligo ethylene glycol acrylate molecule to the hydrogel formulation on the Janus microgel particle. Droplets stabilized by these particles experience a sudden increase in droplet diameter around 60 °C. This work with absorbent particles may prove useful for applications in bio catalysis, fuel production, and oil transportation.

Reducing variation in hospital mortality for alcohol-related liver disease in North West England.

BACKGROUND: Variations in emergency care quality for alcohol-related liver disease (ARLD) have been highlighted. AIM: To determine whether introduction of a regional quality improvement (QI) programme was associated with a reduction in potentially avoidable inpatient mortality. METHOD: Retrospective observational cohort study using hospital administrative data spanning a 1-year period before (2014/2015) and 3 years after a QI initiative at seven acute hospitals in North West England. The intervention included serial audit of a bundle of process metrics. An algorithm was developed to identify index ("first") emergency admissions for ARLD (n = 3887). We created a standardised mortality ratio (SMR) to compare relative mortality and regression models to examine risk-adjusted odds of death. RESULTS: In 2014/2015, three of seven hospitals had an SMR above the upper control limit ("outliers"). Adjusted odds of death for patients admitted to outlier hospitals was higher than non-outliers (OR 2.13, 95% CI 1.32-3.44, P = 0.002). Following the QI programme there was a step-wise reduction in outliers (none in 2017/2018). Odds of death was 67% lower in 2017/2018 compared to 2014/2015 at original outlier hospitals, but unchanged at other hospitals. Process audit performance of outliers was worse than non-outliers at baseline, but improved after intervention. CONCLUSIONS: There was a reduction in unexplained variation in hospital mortality following the QI intervention. This challenges the pessimism that is prevalent for achieving better outcomes for patients with ARLD. Notwithstanding the limitations of an uncontrolled observational study, these data provide hope that co-ordinated efforts to drive adoption of evidence-based practice can save lives.

Stimuli responsive Janus microgels with convertible hydrophilicity for controlled emulsion destabilization.

Although the utilization of rigid particles can afford stable emulsions, some applications require eventual emulsion destabilization to release contents captured in the particle-covered droplet. This destabilizing effect is achieved when using stabilizers that respond to controlled changes in environment. Microgels can be synthesized as stimuli responsive polymeric gel networks that adsorb to oil/water interfaces and stabilize emulsions. These particles are commonly hydrogels that swell and collapse in water in response to environmental changes. However, amphiphilic functionality is desired to enhance the adsorption abilities of these hydrogels while maintaining their stimuli responsivity. Microfluidic techniques are used to synthesize Janus microgels with two opposing stimuli responsive hemispheres. The particles have a temperature responsive domain connected to a pH responsive network where each side changes its hydrophilicity in response to a change in temperature or pH, respectively. The Janus microgels are amphiphilic in acidic conditions at 19 °C and alkaline conditions at 40 °C, while the opposite conditions cause a reduction of the amphiphilicity. By stabilizing emulsions with these dual responsive microgels, "smart" droplets that respond to environmental cues are formed. Emulsion droplets remain stable with smaller diameters when aqueous solution conditions favor amphiphilic particles yet, coalesce to larger droplets upon changing pH or temperature. These responsive Janus microgels represent the advancing technology of responsive droplets and demonstrate the applicability of microgels as emulsion stabilizers.

Evolution of structure and dynamics of thermo-reversible nanoparticle gels-A combined XPCS and rheology study.

A combined X-ray photon correlation spectroscopy and rheology study is carried out to capture the evolution of structure, fast particle-scale dynamics, and moduli (elastic and loss) at early times of gel formation near the fluid-gel boundary of a suspension of nanoparticles. The system is comprised of moderately concentrated suspensions of octadecyl silica in decalin (ϕ = 0.2) undergoing thermoreversible gelation. Near the gel boundary, the rate of gel formation is very sensitive to changes in attraction strength. However, we find that at different attraction strengths, the system goes through identical intermediate states of microscopic and macroscopic behavior, even though the absolute time needed to form a gel varies by orders of magnitude. We identify a single dimensionless time parameter, tw/tg, where tw is the wait time following the quench and tg is the rheologically determined gel time, that captures the similarity in gel formation at a range of attraction strengths. Following a temperature quench below the gel boundary, the system is initially fluidlike and forms diffusive clusters (∼8.5 times the particle diameter). After a lag-time, tL, clusters aggregate to form a network like structure which is characterized by the onset of mechanical rigidity and a rapid growth in microscopic relaxation times. At tg, the Baxter parameter obtained from adhesive hard sphere fits of the structure factor attains a constant value corresponding to the theoretical percolation boundary, thus demonstrating that gelation is percolation driven.

Millimeter-Size Pickering Emulsions Stabilized with Janus Microparticles.

The ability to make stable water-in-oil and oil-in-water millimeter-size Pickering emulsions is demonstrated using Janus particles-particles with distinct surface chemistries. The use of a highly cross-linked hydrophobic polymer network and the excellent water-wetting nature of a hydrogel as the hydrophobic and hydrophilic sides, respectively, permit distinct wettability on the Janus particle. Glass capillary microfluidics allows the synthesis of Janus particles with controlled sizes between 128 and 440 µm and control over the hydrophilic-to-hydrophobic domain volume ratio of the particle from 0.36 to 12.77 for a given size. It is shown that the Janus particle size controls the size of the emulsion drops, thus providing the ability to tune the structure and stability of the resulting emulsions. Stability investigations using centrifugation reveal that particles with the smallest size and a balanced hydrophilic-to-hydrophobic volume ratio (Janus ratio) form emulsions with the greatest stability against coalescence. Particles eventually jam at the interface to form nonspherical droplets. This effect is more pronounced as the hydrogel volume is increased. The large Janus particles permit facile visualization of particle-stabilized emulsions, which result in a better understanding of particle stabilization mechanisms of formed emulsions.

Cationic carrier peptide enhances cerebrovascular targeting of nanoparticles in Alzheimer's disease brain.

Accumulation of amyloid beta (Aß) peptides in the cerebral vasculature, referred to as cerebral amyloid angiopathy (CAA), is widely observed in Alzheimer's disease (AD) brain and was shown to accelerate cognitive decline. There is no effective method for detecting cerebrovascular amyloid (CVA) and treat CAA. The targeted nanoparticles developed in this study effectively migrated from the blood flow to the vascular endothelium as determined by using quartz crystal microbalance with dissipation monitoring (QCM-D) technology. We also improved the stability, and blood-brain barrier (BBB) transcytosis of targeted nanoparticles by coating them with a cationic BBB penetrating peptide (K16ApoE). The K16ApoE-Targeted nanoparticles demonstrated specific targeting of vasculotropic DutchAß40 peptide accumulated in the cerebral vasculature. Moreover, K16ApoE-Targeted nanoparticles demonstrated significantly greater uptake into brain and provided specific MRI contrast to detect brain amyloid plaques.

Enhanced gel formation in binary mixtures of nanocolloids with short-range attraction.

Colloidal suspensions transform between fluid and disordered solid states as parameters such as the colloid volume fraction and the strength and nature of the colloidal interactions are varied. Seemingly subtle changes in the characteristics of the colloids can markedly alter the mechanical rigidity and flow behavior of these soft composite materials. This sensitivity creates both a scientific challenge and an opportunity for designing suspensions for specific applications. In this paper, we report a novel mechanism of gel formation in mixtures of weakly attractive nanocolloids with modest size ratio. Employing a combination of x-ray photon correlation spectroscopy, rheometry, and molecular dynamics simulations, we find that gels are stable at remarkably weaker attraction in mixtures with size ratio near two than in the corresponding monodisperse suspensions. In contrast with depletion-driven gelation at larger size ratio, gel formation in the mixtures is triggered by microphase demixing of the species into dense regions of immobile smaller colloids surrounded by clusters of mobile larger colloids that is not predicted by mean-field thermodynamic considerations. These results point to a new route for tailoring nanostructured colloidal solids through judicious combination of interparticle interaction and size distribution.

Dielectric Properties for Nanocomposites Comparing Commercial and Synthetic Ni- and Fe3O4-Loaded Polystyrene.

Nanomaterial-loaded thermoplastics are attractive for applications in adaptive printing methods, as the physical properties of the printed materials are dependent on the nanomaterial type and degree of dispersion. This study compares the dispersion and the impact on the dielectric properties of two common nanoparticles, nickel and iron oxide, loaded into polystyrene. Comparisons between commercial and synthetically prepared samples indicate that well-passivated synthetically prepared nanomaterials are dispersed and minimize the impact on the dielectric properties of the host polymer by limiting particle-particle contacts. Commercial samples were observed to phase-segregate, leading to the loss of the low-k performance of polystyrene. The change in the real and imaginary dielectric was systematically studied in two earth abundant nanoparticles at the concentration between 0 and 13 vol % (0-50 wt %). By varying the volume percentage of fillers in the matrix, it is shown that one can increase the magnetic properties of the materials while minimizing unwanted contributions to the dielectric constant and dielectric loss. The well-dispersed nanoparticle systems were successfully modeled through the Looyenga dielectric theory, thus giving one a predictive ability for the dielectric properties. The current experimental work coupled with modeling could facilitate future material choices and guide design rules for printable polymer composite systems.

Dynamic Scaling of Colloidal Gel Formation at Intermediate Concentrations.

We have examined the formation and dissolution of gels composed of intermediate volume-fraction nanoparticles with temperature-dependent short-range attractions using small-angle x-ray scattering, x-ray photon correlation spectroscopy, and rheology to obtain nanoscale and macroscale sensitivity to structure and dynamics. Gel formation after temperature quenches to the vicinity of the rheologically determined gel temperature, T_{gel}, was characterized via the slowdown of dynamics and changes in microstructure observed in the intensity autocorrelation functions and structure factor, respectively, as a function of quench depth (ΔT=T_{quench}-T_{gel}), wave vector, and formation time t_{f}. We find the wave-vector-dependent dynamics, microstructure, and rheology at a particular ΔT and t_{f} map to those at other ΔTs and t_{f}s via an effective scaling temperature, T_{s}. A single T_{s} applies to a broad range of ΔT and t_{f} but does depend on the particle size. The rate of formation implied by the scaling is a far stronger function of ΔT than expected from the attraction strength between colloids. We interpret this strong temperature dependence in terms of cooperative bonding required to form stable gels via energetically favored, local structures.

Phosphorescent Molecular Butterflies with Controlled Potential-Energy Surfaces and Their Application as Luminescent Viscosity Sensor.

We report precise manipulation of the potential-energy surfaces (PESs) of a series of butterfly-like pyrazolate-bridged platinum binuclear complexes, by synthetic control of the electronic structure of the cyclometallating ligand and the steric bulkiness of the pyrazolate bridging ligand. Color tuning of dual emission from blue/red, to green/red and red/deep red were achieved for these phosphorescent molecular butterflies, which have two well-controlled energy minima on the PESs. The environmentally dependent photoluminescence of these molecular butterflies enabled their application as self-referenced luminescent viscosity sensor.

Stability of Polymer Grafted Nanoparticle Monolayers: Impact of Architecture and Polymer-Substrate Interactions on Dewetting.

The stability of polymer thin films is crucial to a broad range of technologies, including sensors, energy storage, filtration, and lithography. Recently, the demonstration of rapid deposition on solid substrates of ordered monolayers of polymer grafted nanoparticles (PGN) has increased potential for inks to additively manufacture such components. Herein, enhanced stability against dewetting of these self-assembled PGN films (gold nanoparticle functionalized with polystyrene (AuNP-PS)) is discussed in context to linear polystyrene (PS) analogues using high throughput surface gradients: surface energy (20-45 mN/m) and temperature (90-160 °C). PGNs exhibit a lower surface (γp) and interfacial (γsp) energy relative to linear polymers, which results in increased thermal and energetic stability by 10-25 °C and 5-15 mN/m, respectively. This enhanced wetting-dewetting transition is qualitatively consistent with the behavior of star macromolecules and depends on the architecture of the polymer canopy. Increased film stability through canopy architecture expands the manufacturability of thin film hybrids and refines postprocessing conditions to maximize local PGN order.

Stochastic non-linear oscillator models of EEG: the Alzheimer's disease case.

In this article, the Electroencephalography (EEG) signal of the human brain is modeled as the output of stochastic non-linear coupled oscillator networks. It is shown that EEG signals recorded under different brain states in healthy as well as Alzheimer's disease (AD) patients may be understood as distinct, statistically significant realizations of the model. EEG signals recorded during resting eyes-open (EO) and eyes-closed (EC) resting conditions in a pilot study with AD patients and age-matched healthy control subjects (CTL) are employed. An optimization scheme is then utilized to match the output of the stochastic Duffing-van der Pol double oscillator network with EEG signals recorded during each condition for AD and CTL subjects by selecting the model physical parameters and noise intensity. The selected signal characteristics are power spectral densities in major brain frequency bands Shannon and sample entropies. These measures allow matching of linear time varying frequency content as well as non-linear signal information content and complexity. The main finding of the work is that statistically significant unique models represent the EC and EO conditions for both CTL and AD subjects. However, it is also shown that the inclusion of sample entropy in the optimization process, to match the complexity of the EEG signal, enhances the stochastic non-linear oscillator model performance.