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At least 19 records

Composite media for non-oxidative ethane dehydrogenation, and related ethane activation systems and method of processing an ethane-containing stream

A composite media for non-oxidative C 2 H 6 dehydrogenation comprises an aluminosilicate zeolite matrix, and an EDH catalyst on one or more of an external surface of the aluminosilicate zeolite matrix and internal surfaces within pores of the aluminosilicate zeolite matrix. The EDH catalyst comprises one or more of Fe, Zn, Pt, Ga, alloys thereof, and oxides thereof. A C 2 H 6 activation system, and a method of processing a C 2 H 6 -containing stream are also described.

Wang, Lucun↗

Multi-organ media compositions and methods of their use

Disclosed herein are media for culture of cells, tissues, and/or organs. The media formulations disclosed herein can be used to support growth, viability, and/or function of one or more than one cell type, tissue, or organ. In some embodiments, one or more cell types, tissues, organ devices, and/or organs are contacted with a disclosed culture medium under conditions sufficient to support growth, viability, and/or function of the cell types, tissues, and/or organs. The disclosed media can be used in methods of culturing multiple cell types, and in some examples, is used in a platform device including one or more organ devices, for example, by circulating the medium through the one or more organ devices in the platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying Growth of Three Common Bacterium on Phytic Acid: Investigating Effects of Media Composition

Microbes can produce a plethora of metabolites and enzymes that allow mobilization of various elements and nutrients in the soil, including phosphorus. Phosphorus is essential to plant growth; however, only a limited amount of it is in a bio-accessible inorganic form that can be utilized by most plants. Microbes can produce enzymes called phosphatase, which break down phytic acid (organic phosphorus) into bioavailable inorganic phosphate. My work aimed to understand how inorganic phosphate, phytic acid, and calcium in media affect the growth of Bacillus subtilis168 (B. subtilis), Escherichia coli K12 BW25113 (E. coli), Pseudomonas putida KT2440 (P. putida), and a strain of Pseudomonas putida AG5577_MS238 engineered to produce a phytase. Eight media were made to test how these components affect growth, and an additional two to understand the effects of multiple carbon sources versus one. It was observed that P. putida’s growth increased in the presence of phytic acid and was strongly driven by nitrate availability. Furthermore, it was able to initiate faster growth when multiple carbon sources were available rather than just one. E. coli’s growth seemed to be limited when inorganic phosphate was unavailable and little to no growth occurred when phytic acid, calcium, and inorganic phosphate were absent. B. subtilis was unable to substantially grow within 28 hrs in any of the mediums tested. The results of this research aid in understanding the growth responses of P. putida, E. coli, and B. subtilis on less accessible and bioavailable forms of phosphorus.

Black, Grace S.↗

Using Complex Probability Amplitudes to Simulate Solute Transport in Composite Porous Media

Probability amplitudes are fundamental to quantum mechanics and offer robust descriptions of complicated systems, which have allowed physicists to explain behaviors inaccessible to classical physics. This article ponders how some of the same conceptual underpinnings of the mathematics used for modeling quantum systems might be applied to subsurface water resources problems and speculates how these tools could facilitate applications on quantum computers. A probability amplitude-based model for describing advective-dispersive transport in porous media using linear operators is investigated. The proposed complex valued model decomposes spreading into two “sub-continuum partial dispersion” coefficients, and this recovers classical spreading when the sum of these coefficients is the Fickian dispersion coefficient. However, the probability amplitudes have a manyto-one relationship to a probability distribution, so it embeds a level of heterogeneity into seemingly equivalent functions. Two propagators with different sub-continuum coefficients may have the same macroscopic behavior when either is considered in isolation, but when they act on the other the system’s behavior changes. Additionally, differences in the amplitudes cause a reduction in spreading as velocity correlations are disrupted, despite both propagators having identical dispersion coefficients, and this cannot be achieved using classical methods without changing the dispersion coefficient. The main point is that these amplitude-based models offer a way to embed information about the system into the propagators, instead of just “averaging it out” when making an upscaled model.

54 ENVIRONMENTAL SCIENCES↗

Multipoint Correlations in Poisson Media

Multipoint correlations in randomly heterogeneous composite media are determined by the probability that a set of points belong to specific phases. They determine a wide range of macroscopic transport properties such as conductivity, dielectric constant, diffusion coefficient, and transmittance. The Poisson model—a random tesselation of space by hyperplanes—provides realistic descriptions of heterogeneous media in, e.g., radiation-transport applications; yet, until now, it has lacked closed-form expressions for its multipoint correlations. We resolve this problem by presenting an exact solution for the multipoint correlations in the Poisson model. By comparing it to Monte Carlo simulations of four-point correlations in three dimensions, we demonstrate the accuracy of our solution. In conclusion, we visualize the multipoint correlations and discuss their features.

Amorphous materials↗

A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions

Modeling of heterogeneous materials and media is a problem of fundamental importance to a wide class of phenomena and systems, ranging from condensed matter physics, soft materials, and composite media to porous media, biological systems, geosystems, ceramic engineering, pharmaceutical science and even in space discoveries. Among the most important materials are granular systems, which have received intense interest from the engineering, physics, and mathematics communities. In this review paper, the recent developments and new advances in experimental, and computational methods on a variety of scales and physics that extend understanding to a wide range of materials and phenomena are reviewed. Experimental advances include computed neutron and nanometer-scale tomography, magnetic resonance imaging, refractive index matching, digital image correlation, acoustic emission analysis, and the most recent 4D techniques. Furthermore, a tremendous shift has occurred from the continuum scale to micro-scale and developing multiscale approaches. As such, various computational methods, including, constitutive modeling, discrete modeling, and multiscale approaches, have been developed. In conclusion, aside from all these evolutions, more complicated modeling called coupled, or multiphysics, systems representing a simultaneous presence of heat, fluid, chemical variation, and mechanical effect are also explored.

36 MATERIALS SCIENCE↗

Smart culture medium optimization for recombinant protein production: Experimental, modeling, and AI/ML-driven strategies

Recombinant protein production (RPP) is central to biotechnology, where recombinant proteins are used as either end products or catalysts in the synthesis of chemicals, fuels, and materials. Among the major cost drivers, culture medium plays a pivotal role in determining protein yield and quality. This review presents a comprehensive perspective on the critical stages of “smart” culture medium optimization: planning, screening, modeling, optimization, and validation. In the planning stage, we examine the nutritional and energetic roles of medium components, including carbon, nitrogen, amino acids, salts, and trace metals, and their impacts on culture parameters such as pH, oxidative state, and osmolality. We highlight the variability in trace metal content due to water sources, culture vessels, and raw materials, which can substantially influence RPP. The screening stage covers Design of Experiments (DoE) approaches, assessing their theoretical basis, implementation, and limitations. For modeling, we describe methods that integrate experimental data to develop predictive models for smart medium formulation. Model-based optimization strategies can then be employed to select optimal media compositions for a given application. The validation stage aims to evaluate model predictions and provide feedback for model training and refinement. Finally, we survey mechanistic and artificial intelligence/machine learning (AI/ML)-driven models as integrated, transformational tools for predictive modeling of bioprocess conditions, nutrient availability, cellular metabolism, and protein quality, with the goal of optimizing culture media to enhance protein yields while reducing costs and environmental impact. We conclude by addressing the challenges of translating laboratory-scale medium optimization to industrial-scale settings and exploring future AI/ML-driven approaches that may overcome current bottlenecks and accelerate medium design for RPP. Overall, this review provides a unified framework for advancing smart medium design in RPP.

Artificial Intelligence/Machine Learning (AI/ML)↗

Parsed synthesis of pyocyanin via co-culture enables context-dependent intercellular redox communication

Abstract Background Microbial co-cultures and consortia are of interest in cell-based molecular production and even as “smart” therapeutics in that one can take advantage of division of labor and specialization to expand both the range of available functions and mechanisms for control. The development of tools that enable coordination and modulation of consortia will be crucial for future application of multi-population cultures. In particular, these systems would benefit from an expanded toolset that enables orthogonal inter-strain communication. Results We created a co-culture for the synthesis of a redox-active phenazine signaling molecule, pyocyanin (PYO), by dividing its synthesis into the generation of its intermediate, phenazine carboxylic acid (PCA) from the first strain, followed by consumption of PCA and generation of PYO in a second strain. Interestingly, both PCA and PYO can be used to actuate gene expression in cells engineered with the soxRS oxidative stress regulon, although importantly this signaling activity was found to depend on growth media. That is, like other signaling motifs in bacterial systems, the signaling activity is context dependent. We then used this co-culture’s phenazine signals in a tri-culture to modulate gene expression and production of three model products: quorum sensing molecule autoinducer-1 and two fluorescent marker proteins, eGFP and DsRed. We also showed how these redox-based signals could be intermingled with other quorum-sensing (QS) signals which are more commonly used in synthetic biology, to control complex behaviors. To provide control over product synthesis in the tri-cultures, we also showed how a QS-induced growth control module could guide metabolic flux in one population and at the same time guide overall tri-culture function. Specifically, we showed that phenazine signal recognition, enabled through the oxidative stress response regulon soxRS, was dependent on media composition such that signal propagation within our parsed synthetic system could guide different desired outcomes based on the prevailing environment. In doing so, we expanded the range of signaling molecules available for coordination and the modes by which they can be utilized to influence overall function of a multi-population culture. Conclusions Our results show that redox-based signaling can be intermingled with other quorum sensing signaling in ways that enable user-defined control of microbial consortia yielding various outcomes defined by culture medium. Further, we demonstrated the utility of our previously designed growth control module in influencing signal propagation and metabolic activity is unimpeded by orthogonal redox-based signaling. By exploring novel multi-modal strategies for guiding communication and consortia outcome, the concepts introduced here may prove to be useful for coordination of multiple populations within complex microbial systems.

Chun, Kayla↗

Two-step conversion of polyethylene into recombinant proteins using a microbial platform

Background: The increasing prevalence of plastic waste combined with the inefficiencies of mechanical recycling has inspired interest in processes that can convert these waste streams into value-added biomaterials. To date, the microbial conversion of plastic substrates into biomaterials has been predominantly limited to polyhydroxyalkanoates production. Expanding the capabilities of these microbial conversion platforms to include a greater diversity of products generated from plastic waste streams can serve to promote the adoption of these technologies at a larger scale and encourage a more sustainable materials economy. Results: Herein, we report the development of a new strain of Pseudomonas bacteria capable of converting depolymerized polyethylene into high value bespoke recombinant protein products. Using hexadecane, a proxy for depolymerized polyethylene, as a sole carbon nutrient source, we optimized media compositions that facilitate robust biomass growth above 1 × 10 9 cfu/ml, with results suggesting the benefits of lower hydrocarbon concentrations and the use of NH 4 Cl as a nitrogen source. We genomically integrated recombinant genes for green fluorescent protein and spider dragline-inspired silk protein, and we showed their expression in Pseudomonas aeruginosa, reaching titers of approximately 10 mg/L when hexadecane was used as the sole carbon source. Lastly, we demonstrated that chemically depolymerized polyethylene, comprised of a mixture of branched and unbranched alkanes, could be converted into silk protein by Pseudomonas aeruginosa at titers of 11.3 ± 1.1 mg/L. Conclusion: This work demonstrates a microbial platform for the conversion of a both alkanes and plastic-derived substrates to recombinant, protein-based materials. The findings in this work can serve as a basis for future endeavors seeking to upcycle recalcitrant plastic wastes into value-added recombinant proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of Oxalic Acid Consumption and pH on the In Vitro Biological Control of Oxalogenic Phytopathogen Sclerotinia sclerotiorum

The phytopathogenic fungus Sclerotinia sclerotiorum has a wide host range and causes significant economic losses in crops worldwide. This pathogen uses oxalic acid as a virulence factor; for this reason, the degradation of this organic acid by oxalotrophic bacteria has been proposed as a biological control approach. However, previous studies on the potential role of oxalotrophy in biocontrol did not investigate the differential effect of oxalic acid consumption and the subsequent pH alkalinisation on fungal growth. In this study, confrontation experiments on different media using a wild-type (WT) strain of S. sclerotiorum and an oxalate-deficient mutant (strain Δoah) with the soil oxalotrophic bacteria Cupriavidus necator and Cupriavidus oxalaticus showed the combined effect of media composition on oxalic acid production, pH, and fungal growth control. Oxalotrophic bacteria were able to control S. sclerotiorum only in the medium in which oxalic acid was produced. However, the deficient Δoah mutant was also controlled, indicating that the consumption of oxalic acid is not the sole mechanism of biocontrol. WT S. sclerotiorum acidified the medium when inoculated alone, while for both fungi, the pH of the medium changed from neutral to alkaline in the presence of bacteria. Therefore, medium alkalinisation independent of oxalotrophy contributes to fungal growth control.

Estoppey, Aislinn (ORCID:0000000347410835)↗

Multi-stage preconditioners for thermal–compositional–reactive flow in porous media

We present a family of multi-stage preconditioners for coupled thermal-compositional-reactive reservoir simulation problems. The most common preconditioner used in industrial practice, the Constrained Pressure Residual (CPR) method, was designed for isothermal models and does not offer a specific strategy for the energy equation. For thermal simulations, inadequate treatment of the temperature unknown can cause severe conver-gence degradation. When strong thermal diffusion is present, the energy equation exhibits significant elliptic behavior that cannot be accurately corrected by CPR's second stage. In this work, we use Schur-complement decompositions to extract a temperature subsystem and apply an Algebraic MultiGrid (AMG) approximation as an additional preconditioning stage to improve the treatment of the energy equation. We present results for several two-dimensional hot air injection problems using an extra heavy oil, including challenging reactive In-Situ Combustion (ISC) cases. We show improved performance and robustness across different thermal regimes, from advection dominated (high Péclet number) to diffusion dominated (low Péclet number). The number of linear iterations is reduced by 40–85% compared to standard CPR for both homogeneous and heterogeneous media, and the new methods exhibit almost no sensitivity to the thermal regime.

42 ENGINEERING↗

Integration of Biorelevant Pediatric Dissolution Methodology into PBPK Modeling to Predict In Vivo Performance and Bioequivalence of Generic Drugs in Pediatric Populations: a Carbamazepine Case Study

This study investigated the impact of gastro-intestinal fluid volume and bile salt (BS) concentration on the dissolution of carbamazepine (CBZ) immediate release (IR) 100 mg tablets and to integrate these in vitro biorelevant dissolution profiles into physiologically based pharmacokinetic modelling (PBPK) in pediatric and adult populations to determine the biopredictive dissolution profile. Dissolution profiles of CBZ IR tablets (100 mg) were generated in 50–900 mL biorelevant adult fasted state simulated gastric and intestinal fluid (Ad-FaSSGF and Ad-FaSSIF), also in three alternative compositions of biorelevant pediatric FaSSGF and FaSSIF medias at 200 mL. This study found that CBZ dissolution was poorly sensitive to changes in the composition of the biorelevant media, where dissimilar dissolution (F2 = 46.2) was only observed when the BS concentration was changed from 3000 to 89 μM (Ad-FaSSIF vs Ped-FaSSIF 50% 14 BS). PBPK modeling demonstrated the most predictive dissolution volume and media composition to forecast the PK was 500 mL of Ad-FaSSGF/Ad-FaSSIF media for adults and 200 mL Ped-FaSSGF/FaSSIF media for pediatrics. A virtual bioequivalence simulation was conducted by using Ad-FaSSGF and/or Ad-FaSSIF 500 mL or Ped-FaSSGF and/or Ped-FaSSIF 200 mL dissolution data for CBZ 100 mg (reference and generic test) IR product. The CBZ PBPK models showed bioequivalence of the product. This study demonstrates that the integration of biorelevant dissolution data can predict the PK profile of a poorly soluble drug in both populations. Further work using more pediatric drug products is needed to verify biorelevant dissolution data to predict the in vivo performance in pediatrics.

60 APPLIED LIFE SCIENCES↗

Au x Pd (300‐ x ) Alloy Nanoparticles for the Oxygen Reduction Reaction in Alkaline Media

Abstract Au x Pd (300‐ x ) nanoalloys were prepared using a dendrimer‐templating method and their electrocatalytic efficiencies towards the oxygen reduction reaction (ORR) were analyzed in alkaline media. The composition‐dependent PdO x reduction potentials of the Au x Pd (300‐ x ) nanoalloys were correlated to the oxygen‐binding (O‐binding) energy of the catalysts. Multiple PdO x reduction peaks were present for the Au 150 Pd 150 and Au 50 Pd 250 catalysts. These peaks were assigned to the alloyed and bulk‐like Pd active sites on the alloyed surface. The results described here are significant because modulation of the O‐binding energies improved the ORR activity on the nanoalloys. Specifically, a linear trend in O‐binding energies of Au x Pd (300‐ x ) dendrimers (DENs) as a function of Pd composition resulted in a volcano‐shaped trend in ORR activity. The optimal O‐binding energy of Au 50 Pd 250 resulted in an approximate 89 mV shift in PdO x reduction relative to Pd 300 and a shift of approximately 76 mV in ORR peak potential.

Trindell, Jamie A.↗

Metaproteomics reveals insights into microbial structure, interactions, and dynamic regulation in defined communities as they respond to environmental disturbance

Abstract Background Microbe-microbe interactions between members of the plant rhizosphere are important but remain poorly understood. A more comprehensive understanding of the molecular mechanisms used by microbes to cooperate, compete, and persist has been challenging because of the complexity of natural ecosystems and the limited control over environmental factors. One strategy to address this challenge relies on studying complexity in a progressive manner, by first building a detailed understanding of relatively simple subsets of the community and then achieving high predictive power through combining different building blocks (e.g., hosts, community members) for different environments. Herein, we coupled this reductionist approach with high-resolution mass spectrometry-based metaproteomics to study molecular mechanisms driving community assembly, adaptation, and functionality for a defined community of ten taxonomically diverse bacterial members of Populus deltoides rhizosphere co-cultured either in a complex or defined medium. Results Metaproteomics showed this defined community assembled into distinct microbiomes based on growth media that eventually exhibit composition and functional stability over time. The community grown in two different media showed variation in composition, yet both were dominated by only a few microbial strains. Proteome-wide interrogation provided detailed insights into the functional behavior of each dominant member as they adjust to changing community compositions and environments. The emergence and persistence of select microbes in these communities were driven by specialization in strategies including motility, antibiotic production, altered metabolism, and dormancy. Protein-level interrogation identified post-translational modifications that provided additional insights into regulatory mechanisms influencing microbial adaptation in the changing environments. Conclusions This study provides high-resolution proteome-level insights into our understanding of microbe-microbe interactions and highlights specialized biological processes carried out by specific members of assembled microbiomes to compete and persist in changing environmental conditions. Emergent properties observed in these lower complexity communities can then be re-evaluated as more complex systems are studied and, when a particular property becomes less relevant, higher-order interactions can be identified.

59 BASIC BIOLOGICAL SCIENCES↗

Fully‐Printed Ion Sensor Arrays for Measuring Agricultural Nitrogen and Potassium Concentrations Using Nernstian and AI Models

Abstract The chemical composition of growing media is a key factor for plant growth, impacting agricultural yield and sustainability. However, there is a lack of affordable chemical sensors for ubiquitous nutrient ion monitoring in agricultural applications. This work investigates using fully printed ion‐sensor arrays to measure the concentrations of nitrate, ammonium, and potassium in mixed‐electrolyte media. Ion sensor arrays composed of nitrate, ammonium, and potassium ion‐selective electrodes and a printed silver‐silver chloride (Ag/AgCl) reference electrode are fabricated and characterized in aqueous solutions in a range of concentrations that encompass what is typical for agricultural growing media (0.01 m m –1 m ). The sensors are also tested in mixed‐electrolyte solutions of NaNO 3 , NH 4 Cl, and KCl of varying concentrations, and the recorded potentials are input into Nernstian and artificial neural network models to compare the prediction accuracy of the models against ground truth. The artificial neural network models demonstrated higher accuracy over the Nernstian model, and the model using only ion‐sensor inputs is 7.5% more accurate than the Nernstian model under the same conditions. By enabling more precise and efficient fertilizer application, these sensor arrays coupled to computational models can help increase crop yields, optimize resource use, and reduce environmental impact.

Goodrich, Payton [University of California Berkele↗

Disulfonamide Ligands as f-Element Extractants from Alkaline High-Level Waste

Almost 100 million gallons of high level waste (HLW) has been generated from defense reprocessing programs to support nuclear weapons production. HLW is currently stored at the Hanford and Savannah River Sites (SRS) [1]. It contains radioactive components, such as {sup 137}Cs, {sup 99}Tc and {sup 90}Sr, as well as large amounts of non-radioactive species, including solvated cations and insoluble metal hydroxides. HLW has high concentration of soluble hydroxides ([OH{sup -}] = 2 M at SRS [2]), complexing inorganic anions ([NO{sub 3}{sup -}] ∼ 0.65 - 3.7 M at SRS [2]) and a high ionic strength. Even though the majority of actinide component in alkaline HLW is precipitated, studies of An(III) and Ln(III) complexation in highly alkaline solutions in the presence of high nitrate concentrations have showed that soluble nitrate complexes can be formed [3]. The current treatment of HLW at SRS currently consists of two processes: The Actinide Removal Process (ARP) and the Next-Generation Caustic-Side Solvent Extraction process (NG-CSSX). Strontium and actinides are removed by sorption on monosodium titanate through the Actinide Removal Process (ARP) commonly referred to as the alpha-strike step [4]. Then, cesium is selectively extracted from the alkaline media via the Caustic-Side Solvent Extraction (CSSX) process [5]. The CSSX solvent consists of a calix[4]arene-crown-6 extractant dissolved in an inert hydrocarbon matrix containing i) a solvent modifier (alkylphenoxy alcohol) which increases extractant solubility and prevents third phase formation, and ii) a suppressor (trioctylamine or guanidine) - that mitigates surfactant effects. The CSSX process removes {sup 137}Cs selectively and rapidly, yet the post- CSSX aqueous stream may still contain high amounts of An, thus requiring a second ARP treatment (referred to as 'alpha-finishing') for some tanks. Despite the success of the ARP process in removing Sr and An, it often represents the kinetic bottleneck of integrated processing, as it is slower than solvent extraction. Understanding the complexation of actinides by organic ligands that are compatible with the CSSX process could eventually lead to a combined caustic-side Cs/Sr/actinide extraction process with better economics due to a reduced amount of monosodium titanate and/or a shorter required contact time with titanate during ARP. This would ensure a low-activity waste (LAW) stream with no actinides without additional ARP processing post-CSSX. Disulfonamides were studied for extraction of Sm(III) from alkaline aqueous media of pH 10-14 into dichloromethane. Up to 82% of Sm(III) was extracted from solutions of pH 12.5 -13.5 and up to 84% from solutions of pH 10.5 - 11.5. These results show some resemblance with Am extraction results by calixarene ligands previously reported [10]. Kinetic studies demonstrated that even 5 min is enough to complete stripping, whereas extraction is time-limiting process and requires up to 20 h for efficient removal of Sm(III) from alkaline aqueous media. Determination of composition of complexes in solution after extraction by the equilibrium shift method showed a 1:1 Sm(III):dsa-2 complexation ratio for the extracted species.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗