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SARS-CoV-2 spike protein is an essential component of numerous protein-based vaccines for COVID-19. The receptor-binding domain of this spike protein is a promising antigen with ease of expression in microbial hosts and scalability at comparatively low production costs. This study describes the production, purification, and characterization of RBD of SARS-CoV-2 protein, which is currently in clinical trials, from a commercialization perspective. The protein was expressed in Pichia pastoris in a large-scale bioreactor of 1200 L capacity. Protein capture and purification are conducted through mixed-mode chromatography followed by hydrophobic interaction chromatography. This two-step purification process produced RBD with an overall productivity of ~21 mg/L at >99% purity. The protein’s primary, secondary, and tertiary structures were also verified using LCMS-based peptide mapping, circular dichroism, and fluorescence spectroscopy, respectively. The glycoprotein was further characterized for quality attributes such as glycosylation, molecular weight, purity, di-sulfide bonding, etc. Through structural analysis, it was confirmed that the product maintained a consistent quality across different batches during the large-scale production process. The binding capacity of RBD of spike protein was also assessed using human angiotensin-converting enzyme 2 receptor. A low binding constant range of KD values, ranging between 3.63 × 10−8 to 6.67 × 10−8, demonstrated a high affinity for the ACE2 receptor, revealing this protein as a promising candidate to prevent the entry of COVID-19 virus.

Chitooligosaccharides (COS) are depolymerized chains produced from the natural polymer chitosan and has been determined to exhibit improved biological activities, high solubility in neutral to slightly alkaline pH, because of the lower molecular weight (MW). This makes COS more attractive in biomedical applications. However, earlier studies focused on depolymerization techniques that were either cumbersome or expensive. Here, a convenient two-stage, green synthesis approach was developed and optimized, where gamma irradiation and oxidative degradation with H2O2 were used to depolymerize chitosan to produce COS for biomedical applications. The gamma radiation dose level, H2O2 degradation reaction’s temperature, time and H2O2 concentration were varied to obtain the mildest combination of reaction conditions. The most optimum set of conditions (15 kGy, 25oC, overnight reaction with 2% H2O2) yielded COS that was soluble in physiological pH range (7–8.5). The COS had a MW of 12.8 ± 1.6 kDa (which was a 95% reduction in MW), a 62.3% degree of deacetylation, and a crystallinity index of 33%. A photopolymerized hydrogel using this COS cross-linked with polyethylene glycol diacrylate (PEGDA) and carboxymethyl cellulose (CMC) was also developed. The hydrogel exhibited high swelling ratio (6.44–10.24), a porous morphology, a compression modulus of 4.5 ± 2.7 kPa (similar to soft tissues), and more than 95% biocompatibility with mammalian cells. This newly developed COS hydrogel involves a simple and green approach for the production of COS and shows promise as a scaffold for artificial soft tissue.

MIT Mobility Systems Center consortium

Aluminum-salt vaccine adjuvants (alum) are commercially available as micron-sized particles with varying chemical composition and crystallinity. There are reports of enhanced adjuvanticity when the alum’s particle size is reduced to the nanometer range. Previously, we demonstrated that a recombinant receptor-binding domain (RBD)-based COVID-19 vaccine candidate (RBD-J; RBD-L452K-F490W) formulated with aluminum hydroxide (Alhydrogel®; AH) and CpG 1018™ (CpG) adjuvants induced potent neutralizing antibody responses in mice yet displayed instability during storage. In this work, we evaluated whether sonication of AH to the nanometer size range (nanoAH) could further enhance immunogenicity or improve storage stability of the above formulation. The addition of CpG to nanoAH (at mouse doses), however, caused re-agglomeration of nanoAH. AH-CpG interactions were evaluated by Langmuir binding isotherms and zeta potential measurements, and stabilized nanoAH + CpG formulations of RBD-J were then designed by (1) optimizing CpG:Aluminum dose ratios or (2) adding a small-molecule polyanion (phytic acid, PA). Compared with the micron-sized AH + CpG formulation, the two stabilized nanoAH + CpG formulations of RBD-J demonstrated no enhancement in SARS-CoV-2 pseudovirus neutralizing titers in mice, but the PA-containing nanoAH + CpG formulation showed improved RBD-J storage stability trends (at 4, 25, and 37 °C). The formulation protocols presented herein can be employed to evaluate the potential benefits of the nanoAH + CpG adjuvant combination with other vaccine antigens in different animal models.

We study the accuracy and convergence properties of the chemically significant eigenvalues method as proposed by Georgievskii et al. [J. Phys. Chem. A 117, 12146-12154 (2013)] and its close relative, dominant subspace truncation, for reduction of the energy-grained master equation. We formally derive the connection between both reduction techniques and provide hard error bounds for the accuracy of the latter which confirm the empirically excellent accuracy and convergence properties but also unveil practically relevant cases in which both methods are bound to fall short. We propose the use of balanced truncation as an effective alternative in these cases., Department of Energy (DOE)

Nitrogen-doped carbon nanodots (CNDs) were synthesized and utilized as sensing probes to detect different anions and metallic ions within aqueous solutions. The pristine CNDs were developed through a one-pot hydrothermal synthesis. o-Phenylenediamine was used as the precursor. A similar hydrothermal synthesis technique in the presence of polyethylene glycol (PEG) was adopted to form the PEG-coated CND clusters (CND-100k). Through photoluminescence (PL) quenching, both CND and PEG-coated CND suspensions display ultra-high sensitivity and selectivity towards HSO4− anions (Stern–Volmer quenching constant (KSV) value: 0.021 ppm−1 for CND and 0.062 ppm−1 for CND-100k) with an ultra-low detection limit (LOD value: 0.57 ppm for the CND and 0.19 ppm for CND-100k) in the liquid phase. The quenching mechanism of N-doped CNDs towards HSO4− ions involves forming the bidentate as well as the monodentate hydrogen bonding with the sulfate anionic moieties. The detection mechanism of metallic ions analyzed through the Stern–Volmer formulation reveals that the CND suspension is well suited for the detection of Fe3+ (KSV value: 0.043 ppm−1) and Fe2+ (KSV value: 0.0191 ppm−1) ions, whereas Hg2+ (KSV value: 0.078 ppm−1) sensing can be precisely performed by the PEG-coated CND clusters. Accordingly, the CND suspensions developed in this work can be employed as high-performance PL probes for detecting various anions and metallic ions in the liquid phase.

Anticipating qualitative changes in the rheological response of complex fluids (e.g., a gelation or vitrification transition) is an important capability for processing operations that utilize such materials in real-world environments. One class of complex fluids that exhibits distinct rheological states are soft glassy materials such as colloidal gels and clay dispersions, which can be well characterized by the soft glassy rheology (SGR) model. We first solve the model equations for the time-dependent, weakly nonlinear response of the SGR model. With this analytical solution, we show that the weak nonlinearities measured via medium amplitude parallel superposition (MAPS) rheology can be used to anticipate the rheological aging transitions in the linear response of soft glassy materials. This is a rheological version of a technique called structural health monitoring used widely in civil and aerospace engineering. We design and train artificial neural networks (ANNs) that are capable of quickly inferring the parameters of the SGR model from the results of sequential MAPS experiments. The combination of these data-rich experiments and machine learning tools to provide a surrogate for computationally expensive viscoelastic constitutive equations allows for rapid experimental characterization of the rheological state of soft glassy materials. We apply this technique to an aging dispersion of Laponite® clay particles approaching the gel point and demonstrate that a trained ANN can provide real-time detection of transitions in the nonlinear response well in advance of incipient changes in the linear viscoelastic response of the system.

Using an untargeted stable isotope-assisted metabolomics approach, we identify erythronate as a metabolite that accumulates in several human cancer cell lines. Erythronate has been reported to be a detoxification product derived from off-target glycolytic metabolism. We use chemical inhibitors and genetic silencing to define the pentose phosphate pathway intermediate erythrose 4-phosphate (E4P) as the starting substrate for erythronate production. However, following enzyme assay-coupled protein fractionation and subsequent proteomics analysis, we identify aldehyde dehydrogenase 1A1 (ALDH1A1) as the predominant contributor to erythrose oxidation to erythronate in cell extracts. Through modulating ALDH1A1 expression in cancer cell lines, we provide additional support. We hence describe a possible alternative route to erythronate production involving the dephosphorylation of E4P to form erythrose, followed by its oxidation by ALDH1A1. Finally, we measure increased erythronate concentrations in tumors relative to adjacent normal tissues from lung cancer patients. These findings suggest the accumulation of erythronate to be an example of metabolic reprogramming in cancer cells, raising the possibility that elevated levels of erythronate may serve as a biomarker of certain types of cancer.

A sulfide-based solid electrolyte is an enticing non-organic solid-state electrolyte developed under ambient conditions. Na3SbS4, a profoundly enduring substance capable of withstanding exceedingly elevated temperatures and pressures, emerges as a focal point. Within this investigation, we employ dual distinct techniques to fabricate Na3SbS4, encompassing ball milling and the combination of ball milling with sintering procedures. A remarkable ionic conductivity of 3.1 × 10−4 S/cm at room temperature (RT), coupled with a meager activation energy of 0.21 eV, is achieved through a bifurcated process, which is attributed to the presence of tetragonal Na3SbS4 (t-NSS). Furthermore, we delve into the electrochemical performance and cyclic longevity of the Na2/3Fe1/2Mn1/2O2|t-NSS|Na system within ambient environs. It reveals 160 mAh/g initial charge and 106 mAh/g discharge capacities at 0.01 A/g current density. Furthermore, a cycle life test conducted at 0.01 A/g over 30 cycles demonstrates stable and reliable performance. The capacity retention further highlights its enduring energy storage capabilities. This study underscores the sustainable potential of Na3SbS4 as a solid-state electrolyte for advanced energy storage systems.

Predicting Gibbs free energy of solution is key to understanding solvent effects on thermodynamics and reaction rates for kinetic modelling. Accurately computing solution free energies requires enumeration and evaluation of relevant solute conformers in solution. However, even after generation of relevant conformers, determining their free energy of solution requires an expensive workflow consisting of several ab initio computational chemistry calculations. To help address this challenge, we generate a large dataset of solution free energies for nearly 44000 solutes with almost 9 million conformers calculated in 41 different solvents using density functional theory and COSMO-RS and quantify the impact of solute conformers on the solution free energy. We then train a message passing neural network to predict the relative solution free energies of a set of solute conformers, enabling identification of a small subset of thermodynamically relevant conformers. The model offers substantial computational time savings with predictions usually substantially within 1 kcal/mol of the free energy of solution calculated using computational chemical methods., Machine Learning for Pharmaceutical Discovery and Synthesis Consortium

This prospective is a forward-looking outlook for researchers investigating electrochemical carbon capture utilizing molecular redox-active organic materials, with the following objectives: (1) identifying the essential components of an electrochemical carbon capture system, (2) introducing design principles for the system utilizing redox-active organic materials, encompassing their physicochemical properties and other critical factors, (3) presenting representative examples, and (4) promoting further experimental and theoretical studies on the application of redox-active organic materials for electrochemical carbon capture. Graphical abstract

AbstractExceeding the energy density of lithium−carbon monofluoride (Li−CFx), today's leading Li primary battery, requires an increase in fluorine content (x) that determines the theoretical capacity available from C−F bond reduction. However, high F‐content carbon materials face challenges such as poor electronic conductivity, low reduction potentials (<1.3 V versus Li/Li+), and/or low C−F bond utilization. This study investigates molecular structural design principles for a new class of high F‐content fluoroalkyl‐aromatic catholytes that address these challenges. A polarizable conjugated system—an aromatic ring with an alkene linker—functions as electron acceptor and redox initiator, enabling a cascade defluorination of an adjacent perfluoroalkyl chain (RF = −CnF2n+1). The synthesized molecules successfully overcome premature deactivation observed in previously studied catholytes and achieve close‐to‐full defluorination (up to 15/17 available F), yielding high gravimetric capacities of 748 mAh g−1fluoroalkyl‐aromatic and energies of 1785 Wh kg−1fluoroalkyl‐aromatic. The voltage compatibility between fluoroalkyl‐aromatics and CFx enables design of hybrid cells containing C−F redox activity in both solid and liquid phases, with a projected enhancement of Li–CFx gravimetric energy by 35% based on weight of electrodes+electrolyte. With further improvement of cathode architecture, these “liquid CFx” analogues are strong candidates for exceeding the energy limitations of today's primary chemistries.

Machine Learning for Pharmaceutical Discovery and Synthesis Consortium, efense Advanced Research Projects Agency - Accelerated Molecular Discover

Semicrystalline polymers are lightweight, multiphase materials that exhibit attractive shock dissipation characteristics and have potential applications as protective armor for people and equipment. For shocks of 10 GPa or less, we analyzed various mechanisms for the storage and dissipation of shock wave energy in a realistic, united atom (UA) model of semicrystalline polyethylene. Systems characterized by different levels of crystallinity were simulated using equilibrium molecular dynamics with a Hugoniostat to ensure that the resulting states conform to the Rankine–Hugoniot conditions. To determine the role of structural rearrangements, order parameters and configuration time series were collected during the course of the shock simulations. We conclude that the major mechanisms responsible for the storage and dissipation of shock energy in semicrystalline polyethylene are those associated with plastic deformation and melting of the crystalline domain. For this UA model, plastic deformation occurs primarily through fine crystallographic slip and the formation of kink bands, whose long period decreases with increasing shock pressure.

In this study, we utilized nano-sized Co3O4 and reduced graphene oxides (rGOs) as composite anode materials for Li-ion batteries. The Co3O4/C composite anode was derived from ZIF67 (Zeolitic Imidazolate Framework-67) and was wrapped in rGOs through precipitation. X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) were used to identify the crystal structure, phase purity, and surface morphology of the composite. The composition-optimized Co3O4/rGO/C composite anode exhibited a reversible capacity of 1326 mAh/g in the first cycle, which was higher than that of the Co3O4/C composite anode with a capacity of 900 mAh/g at a current density of 200 mA/g. Moreover, after 80 cycles, Co3O4/rGO/C maintained a capacity of 1251 mAh/g at the same current density, which was also higher than the bare Co3O4/C composite (595 mAh/g). Additionally, the Co3O4/rGO/C composite exhibited a good capacity retention of 98% after 90 cycles, indicating its excellent cycling stability and high capacity. Therefore, the Co3O4/rGO/C electrode has great potential as a promising anode material for Li-ion batteries.

Vehicle-to-grid (V2G) allows electric vehicles to provide power and services to the grid. At scale, V2G can bolster renewable energy growth and eliminate storage and displace firm generators traditionally used to balance wind and solar intermittency.

In the Earth's atmosphere, reactive organic carbon undergoes oxidation via a highly complex, multigeneration process, with implications for air quality and climate. Decades of experimental and theoretical studies, primarily on the reactions of hydrocarbons, have led to a canonical understanding of how gas-phase oxidation of organic compounds takes place. Recent research has brought to light a number of examples where the presence of certain functional groups opens up reaction pathways for key radical intermediates, including alkyl radicals, alkoxy radicals, and peroxy radicals, that are substantially different from traditional oxidation mechanisms. These discoveries highlight the need for methods that systematically explore the chemistry of complex, functionalized molecules without being prohibitively expensive. In this work, automated reaction network generation is used as a screening tool for new pathways in atmospheric oxidation chemistry. The reaction mechanism generator (RMG) is used to generate reaction networks for the OH-initiated oxidation of 200 mono- and bifunctionally substituted n-pentanes. The resulting networks are then filtered to highlight the reactions of key radical intermediates that are fast enough to compete with traditional atmospheric removal processes as well as "uncanonical" processes which differ from traditionally accepted oxidation mechanisms. Several recently reported, uncanonical atmospheric mechanisms appear in the RMG dataset. These "proof of concept" results provide confidence in this approach as a tool in the search for overlooked atmospheric oxidation chemistry. Several previously unreported reaction types are also encountered in the dataset. The most potentially atmospherically important of these is a radical-carbonyl ring-closure reaction that produces a highly functionalized cyclic alkoxy radical. This pathway is proposed as a promising target for further study via experiments and more detailed theoretical calculations. The app

The field of predictive chemistry relates to the development of models able to describe how molecules interact and react. It encompasses the long-standing task of computer-aided retrosynthesis, but is far more reaching and ambitious in its goals. In this review, we summarize several areas where predictive chemistry models hold the potential to accelerate the deployment, development, and discovery of organic reactions and advance synthetic chemistry.

In multiobjective particle swarm optimization (MOPSO), the global-best particle is randomly selected for each population particle from a nondominated solution set. However, this Roulette wheel-based global particle selection is ineffective for convergence and diversity when the problem has numerous decision variables or a large number of global-best candidates. Thus, this study proposes the cluster-based MOPSO (CMOPSO). In CMOPSO, the similarities between particles are considered when selecting the global-best particle. The cluster for each particle is determined based on the Euclidean distance in the decision or objective space. The proposed approach is demonstrated by applying an operating condition optimization problem to the hydrogen production process. The target process is a representative chemical plant with a large search space and strong nonlinearity. Furthermore, the performance of CMOPSO is assessed by comparing it with that of MOPSO. The results indicate that CMOPSO considered in the decision space exhibits superior performance in terms of convergence and diversity.

Virtual high-throughput screening (VHTS) and machine learning (ML) with density functional theory (DFT) suffer from inaccuracies from the underlying density functional approximation (DFA). Many of these inaccuracies can be traced to the lack of derivative discontinuity that leads to a curvature in the energy with electron addition or removal. Over a dataset of nearly one thousand transition metal complexes typical of VHTS applications, we computed and analyzed the average curvature (i.e., deviation from piecewise linearity) for 23 density functional approximations spanning multiple rungs of “Jacob's ladder”. While we observe the expected dependence of the curvatures on Hartree-Fock exchange, we note limited correlation of curvature values between different rungs of “Jacob's ladder”. We train ML models (i.e., artificial neural networks or ANNs) to predict the curvature and the associated frontier orbital energies for each of these 23 functionals and then interpret differences in curvature among the different DFAs through analysis of the ML models. Notably, we observe spin to play a much more important role in determining the curvature of range-separated and double hybrids in comparison to semi-local functionals, explaining why curvature values are weakly correlated between these and other families of functionals. Over a space of 187.2k hypothetical compounds, we use our ANNs to pinpoint DFAs for which representative transition metal complexes have near-zero curvature with low uncertainty, demonstrating an approach to accelerate screening of complexes with targeted optical gaps.

Two-dimensional van der Waals materials exhibit particularly strong excitonic effects, which causes them to be an exceptionally interesting platform for the investigation of exciton physics. A notable example is the two-dimensional Ruddlesden–Popper perovskites, where quantum and dielectric confinement together with soft, polar, and low symmetry lattice create a unique background for electron and hole interaction. Here, with the use of polarization-resolved optical spectroscopy, we have demonstrated that the simultaneous presence of tightly bound excitons, together with strong exciton–phonon coupling, allows for observing the exciton fine structure splitting of the phonon-assisted transitions of two-dimensional perovskite (PEA)PbI, where PEA stands for phenylethylammonium. We demonstrate that the phonon-assisted sidebands characteristic for (PEA)PbI are split and linearly polarized, mimicking the characteristics of the corresponding zero-phonon lines. Interestingly, the splitting of differently polarized phonon-assisted transitions can be different from that of the zero-phonon lines. We attribute this effect to the selective coupling of linearly polarized exciton states to non-degenerate phonon modes of different symmetries resulting from the low symmetry of (PEA)

Nanotechnology-enabled sensors or nanosensors are emerging as promising new tools for various in-vivo life science applications such as biosensing, components of delivery systems, and probes for spatial bioimaging. However, as with a wide range of synthetic biomaterials, tissue responses have been observed depending on cell types and various nanocomponent properties. The tissue response is critical for determining the acute and long term health of the organism and the functional lifetime of the material in-vivo. While nanomaterial properties can contribute significantly to the tissue response, it may be possible to circumvent adverse reactions by formulation of the encapsulation vehicle. In this study, five formulations of poly (ethylene glycol) diacrylate (PEGDA) hydrogel-encapsulated fluorescent nanosensors were implanted into SKH-1E mice, and the inflammatory responses were tracked in order to determine the favorable design rules for hydrogel encapsulation and minimization of such responses. Hydrogels with higher crosslinking density were found to allow faster resolution of acute inflammation. Five different immunocompromised mice lines were utilized for comparison across different inflammatory cell populations and responses. Degradation products of the gels were also characterized. Finally, the importance of the tissue response in determining functional lifetime was demonstrated by measuring the time-dependent nanosensor deactivation following implantation into animal models.

Transcutaneous vaccination is one of the successful, affordable, and patient-friendly advanced immunization approaches because of the presence of multiple immune-responsive cell types in the skin. However, in the absence of a preferable facilitator, the skin’s outer layer is a strong impediment to delivering biologically active foreign particles. Lipid-based biocompatible ionic-liquid-mediated nanodrug carriers represent an expedient and distinct strategy to permit transdermal drug delivery; with acceptable surfactants, the performance of drug formulations might be further enhanced. For this purpose, we formulated a lipid-based nanovaccine using a conventional (cationic/anionic/nonionic) surfactant loaded with an antigenic protein and immunomodulator in its core to promote drug delivery by penetrating the skin and boosting drug delivery and immunogenic cell activity. In a follow-up investigation, a freeze–dry emulsification process was used to prepare the nanovaccine, and its transdermal delivery, pharmacokinetic parameters, and ability to activate autoimmune cells in the tumor microenvironment were studied in a tumor-budding C57BL/6N mouse model. These analyses were performed using ELISA, nuclei and HE staining, flow cytometry, and other biological techniques. The immunomodulator-containing nanovaccine significantly (p < 0.001) increased transdermal drug delivery and anticancer immune responses (IgG, IgG1, IgG2, CD8+, CD207+, and CD103+ expression) without causing cellular or biological toxicity. Using a nanovaccination approach, it is possible to create a more targeted and efficient delivery system for cancer antigens, thereby stimulating a stronger immune response compared with conventional aqueous formulations. This might lead to more effective therapeutic and preventative outcomes for patients with cancer.

AbstractActivation of the innate immune STimulator of INterferon Genes (STING) pathway potentiates antitumour immunity, but systemic delivery of STING agonists to tumours is challenging. We conjugated STING-activating cyclic dinucleotides (CDNs) to PEGylated lipids (CDN-PEG-lipids; PEG, polyethylene glycol) via a cleavable linker and incorporated them into lipid nanodiscs (LNDs), which are discoid nanoparticles formed by self-assembly. Compared to state-of-the-art liposomes, intravenously administered LNDs carrying CDN-PEG-lipid (LND-CDNs) exhibited more efficient penetration of tumours, exposing the majority of tumour cells to STING agonist. A single dose of LND-CDNs induced rejection of established tumours, coincident with immune memory against tumour rechallenge. Although CDNs were not directly tumoricidal, LND-CDN uptake by cancer cells correlated with robust T-cell activation by promoting CDN and tumour antigen co-localization in dendritic cells. LNDs thus appear promising as a vehicle for robust delivery of compounds throughout solid tumours, which can be exploited for enhanced immunotherapy.

Department of Energy (DOE)

In this work, we have studied how the vertical illuminance of the human eye position, illuminance of the horizontal work surface, and the brightness of the computer screen in the office space lighting are correlated under an energy-saving environment. This investigation was conducted in a full-scale laboratory that simulates an office space with 20 adults. It was found that when the indoor ambient lighting illuminance changes, the vertical illuminance of the subject’s eye position is affected accordingly, and the two factors are strongly correlated. On the other hand, when the surrounding environment is brighter and the vertical illuminance increases, the illuminance of the horizontal working surface adjusted by the subject during the visual display terminal (VDT) operation is significantly reduced. The horizontal illuminance value can even be lower than the value frequently employed in various countries around the world, since the computer screen brightness will be adjusted accordingly. Therefore, in an energy-saving environment, the illuminance of the horizontal working surface and the brightness of the computer screen adjusted by the users will vary with the ambient lighting. Especially in the current mainstream VDT operating environment and within a certain range of conditions, the interior setting can be lower than the current horizontal illuminance benchmark for additional energy conservation.

Isoprenoids are a large family of natural products with diverse structures, which allow them to play diverse and important roles in the physiology of plants and animals. They also have important commercial uses as pharmaceuticals, flavoring agents, fragrances, and nutritional supplements. Recently, metabolic engineering has been intensively investigated and emerged as the technology of choice for the production of isoprenoids through microbial fermentation. Isoprenoid biosynthesis typically originates in plants from acetyl-coA in central carbon metabolism, however, a recent study reported an alternative pathway, the isopentenol utilization pathway (IUP), that can provide the building blocks of isoprenoid biosynthesis from affordable C5 substrates. In this study, we expressed the IUP in Escherichia coli to efficiently convert isopentenols into geranate, a valuable isoprenoid compound. We first established a geraniol-producing strain in E. coli that uses the IUP. Then, we extended the geraniol synthesis pathway to produce geranate through two oxidation reactions catalyzed by two alcohol/aldehyde dehydrogenases from Castellaniella defragrans. The geranate titer was further increased by optimizing the expression of the two dehydrogenases and also parameters of the fermentation process. The best strain produced 764 mg/L geranate in 24 h from 2 g/L isopentenols (a mixture of isoprenol and prenol). We also investigated if the dehydrogenases could accept other isoprenoid alcohols as substrates.

The development of technologies to recycle polyethylene (PE) and polypropylene (PP), globally the two most produced polymers, is critical to increase plastic circularity. Here, we show that 5 wt % cobalt supported on ZSM-5 zeolite catalyzes the solvent-free hydrogenolysis of PE and PP into propane with weight-based selectivity in the gas phase over 80 wt % after 20 h at 523 K and 40 bar H2. This catalyst significantly reduces the formation of undesired CH4 (≤5 wt %), a product which is favored when using bulk cobalt oxide or cobalt nanoparticles supported on other carriers (selectivity ≤95 wt %). The superior performance of Co/ZSM-5 is attributed to the stabilization of dispersed oxidic cobalt nanoparticles by the zeolite support, preventing further reduction to metallic species that appear to catalyze CH4 generation. While ZSM-5 is also active for propane formation at 523 K, the presence of Co promotes stability and selectivity. After optimizing the metal loading, it was demonstrated that 10 wt % Co/ZSM-5 can selectively catalyze the hydrogenolysis of low-density PE (LDPE), mixtures of LDPE and PP, as well as postconsumer PE, showcasing the effectiveness of this technology to upcycle realistic plastic waste. Cobalt supported on zeolites FAU, MOR, and BEA were also effective catalysts for C2-C4 hydrocarbon formation and revealed that the framework topology provides a handle to tune gas-phase selectivity.

Quantifying the composition of viral vectors used in vaccine development and gene therapy is critical for assessing their functionality. Adeno-associated virus (AAV) vectors, which are the most widely used viral vectors for in vivo gene therapy, are typically characterized using PCR, ELISA, and analytical ultracentrifugation which require laborious protocols or hours of turnaround time. Emerging methods such as charge-detection mass spectroscopy, static light scattering, and mass photometry offer turnaround times of minutes for measuring AAV mass using optical or charge properties of AAV. Here, we demonstrate an orthogonal method where suspended nanomechanical resonators (SNR) are used to directly measure both AAV mass and aggregation from a few microliters of sample within minutes. We achieve a precision near 10 zeptograms which corresponds to 1% of the genome holding capacity of the AAV capsid. Our results show the potential of our method for providing real-time quality control of viral vectors during biomanufacturing.

Viruslike particles (VLPs) fabricated using wireframe DNA origami are emerging as promising vaccine and gene therapeutic delivery platforms due to their programmable nature that offers independent control over their size and shape, as well as their site-specific functionalization. As materials that biodegrade in the presence of endonucleases, specifically DNase I and II, their utility for the targeting of cells, tissues, and organs depends on their stability in vivo. Here, we explore minor groove binders (MGBs) as specific endonuclease inhibitors to control the degradation half-life of wireframe DNA origami. Bare, unprotected DNA-VLPs composed of two-helix edges were found to be stable in fetal bovine serum under typical cell culture conditions and in human serum for 24 h but degraded within 3 h in mouse serum, suggesting species-specific endonuclease activity. Inhibiting endonucleases by incubating DNA-VLPs with diamidine-class MGBs increased their half-lives in mouse serum by more than 12 h, corroborated by protection against isolated DNase I and II. Our stabilization strategy was compatible with the functionalization of DNA-VLPs with HIV antigens, did not interfere with B-cell signaling activity of DNA-VLPs in vitro, and was nontoxic to B-cell lines. It was further found to be compatible with multiple wireframe DNA origami geometries and edge architectures. MGB protection is complementary to existing methods such as PEGylation and chemical cross-linking, offering a facile protocol to control DNase-mediated degradation rates for in vitro and possibly in vivo therapeutic and vaccine applications.

Composite solid electrolytes (CSEs), composed of sodium superionic conductor (NASICON)-type Li1+xAlxTi2‒x(PO4)3 (LATP), poly (vinylidene fluoride-hexafluoro propylene) (PVDF-HFP), and lithium bis (trifluoromethanesulfonyl)imide (LiTFSI) salt, are designed and fabricated for lithium-metal batteries. The effects of the key design parameters (i.e., LiTFSI/LATP ratio, CSE thickness, and carbon content) on the specific capacity, coulombic efficiency, and cyclic stability were systematically investigated. The optimal CSE configuration, superior specific capacity (~160 mAh g−1), low electrode polarization (~0.12 V), and remarkable cyclic stability (a capacity retention of 86.8%) were achieved during extended cycling (>200 cycles). In addition, with the optimal CSE structure, a high ionic conductivity (~2.83 × 10−4 S cm−1) was demonstrated at an ambient temperature. The CSE configuration demonstrated in this work can be employed for designing highly durable CSEs with enhanced ionic conductivity and significantly reduced interfacial electrolyte/electrode resistance.

Viral systems such as wild-type viruses, viral vectors, and virus-like particles are essential components of modern biotechnology and medicine. Despite their importance, the commercial-scale production of viral systems remains highly inefficient for multiple reasons. Computational strategies are a promising avenue for improving process development, optimization, and control, but require a mathematical description of the system. This article reviews mechanistic modeling strategies for the production of viral particles, both at the cellular and bioreactor scales. In many cases, techniques and models from adjacent fields such as epidemiology and wild-type viral infection kinetics can be adapted to construct a suitable process model. These process models can then be employed for various purposes such as in-silico testing of novel process operating strategies and/or advanced process control.

To accelerate the exploration of chemical space, it is necessary to identify the compounds that will provide the most additional information or value. A large-scale analysis of mononuclear octahedral transition metal complexes deposited in an experimental database confirms an under-representation of lower-symmetry complexes. From a set of around 1000 previously studied Fe(II) complexes, we show that the theoretical space of synthetically accessible complexes formed from the relatively small number of unique ligands is significantly (∼816k) larger. For the properties of these complexes, we validate the concept of ligand additivity by inferring heteroleptic properties from a stoichiometric combination of homoleptic complexes. An improved interpolation scheme that incorporates information about cis and trans isomer effects predicts the adiabatic spin-splitting energy to around 2 kcal/mol and the HOMO level to less than 0.2 eV. We demonstrate a multi-stage strategy to discover leads from the 816k Fe(II) complexes within a targeted property region. We carry out a coarse interpolation from homoleptic complexes that we refine over a subspace of ligands based on the likelihood of generating complexes with targeted properties. We validate our approach on nine new binary and ternary complexes predicted to be in a targeted zone of discovery, suggesting opportunities for efficient transition metal complex discovery.

Radiometry, simulations, and photo-polymerization case studies validate a photo-reactor platform with uniform illumination and multiple wavelengths for well plates, in-plane flow reactors, and droplets.

Genotoxicity testing relies on the detection of gene mutations and chromosome damage and has been used in the genetic safety assessment of drugs and chemicals for decades. However, the results of standard genotoxicity tests are often difficult to interpret due to lack of mode of action information. The TGx-DDI transcriptomic biomarker provides mechanistic information on the DNA damage-inducing (DDI) capability of chemicals to aid in the interpretation of positive in vitro genotoxicity data. The CometChip® assay was developed to assess DNA strand breaks in a higher-throughput format. We paired the TGx-DDI biomarker with the CometChip® assay in TK6 cells to evaluate three model agents: nitrofurantoin (NIT), metronidazole (MTZ), and novobiocin (NOV). TGx-DDI was analyzed by two independent labs and technologies (nCounter® and TempO-Seq®). Although these anti-infective drugs are, or have been, used in human and/or veterinary medicine, the standard genotoxicity testing battery showed significant genetic safety findings. Specifically, NIT is a mutagen and causes chromosome damage, and MTZ and NOV cause chromosome damage in conventional in vitro tests. Herein, the TGx-DDI biomarker classified NIT and MTZ as non-DDI at all concentrations tested, suggesting that NIT’s mutagenic activity is bacterial specific and that the observed chromosome damage by MTZ might be a consequence of in vitro test conditions. In contrast, NOV was classified as DDI at the second highest concentration tested, which is in line with the fact that NOV is a bacterial DNA-gyrase inhibitor that also affects topoisomerase II at high concentrations. The lack of DNA damage for NIT and MTZ was confirmed by the CometChip® results, which were negative for all three drugs except at overtly cytotoxic concentrations. This

Conventional gold electrode fabrication is too costly and laborious for implementation in low-resource settings (LRS). We review affordable, simple alternative fabrication methods, highlighting gold leaf electrodes, for LRS applications.

This study examines the movement of a small freely rotating spherical particle in a two-dimensional trajectory through a viscoelastic fluid described by the Giesekus model. The fluid equations of motion in the inertialess limit and the Giesekus constitutive equation are expanded as a power series in the Weissenberg number, for which analytical solutions for velocity and pressure profiles at low order can be determined for the case of a steady-state flow. These steady solutions are then related to Fourier-transformed variables in frequency space through the use of correspondence relationships, allowing the analysis of time-dependent particle trajectories. The relative unsteadiness and nonlinearity of these time-dependent flows are quantified through a Deborah and Weissenberg number, respectively. The impact of changing these dimensionless parameters on the characteristics of the flow is discussed at length. We calculate the predicted rate of rotation of a small particle undergoing an arbitrary two-dimensional translation through a viscoelastic fluid, as well as the predicted correction to the force exerted on the particle arising from the interaction of particle rotation and translation. Finally, we calculate the angular velocity and total force including second-order corrections for particles executing a few specific trajectories that have been studied experimentally, as well as the predicted trajectory for a particle being directed by a known time-dependent forcing protocol.

Chlorosulfonic acid and oleum are ideal solvents for enabling the transformation of disordered carbon nanotubes (CNTs) into precise and highly functional morphologies. Currently, processing these solvents using extrusion techniques presents complications due to chemical compatibility, which constrain equipment and substrate material options. Here, we present a novel acid solvent system based on methanesulfonic or p-toluenesulfonic acids with low corrosivity, which form true solutions of CNTs at concentrations as high as 10 g/liter (≈0.7 volume %). The versatility of this solvent system is demonstrated by drop-in application to conventional manufacturing processes such as slot die coating, solution spinning continuous fibers, and 3D printing aerogels. Through continuous slot coating, we achieve state-of-the-art optoelectronic performance (83.6 %T and 14 ohm/sq) at industrially relevant production speeds. This work establishes practical and efficient means for scalable processing of CNT into advanced materials with properties suitable for a wide range of applications.

Transition state search is key in chemistry for elucidating reaction mechanisms and exploring reaction networks. The search for accurate 3D transition state structures, however, requires numerous computationally intensive quantum chemistry calculations due to the complexity of potential energy surfaces. Here we developed an object-aware SE(3) equivariant diffusion model that satisfies all physical symmetries and constraints for generating sets of structures—reactant, transition state and product—in an elementary reaction. Provided reactant and product, this model generates a transition state structure in seconds instead of hours, which is typically required when performing quantum-chemistry-based optimizations. The generated transition state structures achieve a median of 0.08 Å root mean square deviation compared to the true transition state. With a confidence scoring model for uncertainty quantification, we approach an accuracy required for reaction barrier estimation (2.6 kcal mol–1) by only performing quantum chemistry-based optimizations on 14% of the most challenging reactions. We envision usefulness for our approach in constructing large reaction networks with unknown mechanisms.

Inadequate clearance of protein-bound uremic toxins (PBUTs) during dialysis is associated with morbidities in chronic kidney disease patients. The development of high-permeance membranes made from materials such as graphene raises the question whether they could enable the design of dialyzers with improved PBUT clearance. Here, we develop device-level and multi-compartment (body) system-level models that account for PBUT-albumin binding (specifically indoxyl sulfate and p-cresyl sulfate) and diffusive and convective transport of toxins to investigate how the overall membrane permeance (or area) and system parameters including flow rates and ultrafiltration affect PBUT clearance in hemodialysis. Our simulation results indicate that, in contrast to urea clearance, PBUT clearance in current dialyzers is mass-transfer limited: Assuming that the membrane resistance is dominant, raising PBUT permeance from 3 × 10−6 to 10−5 m s−1 (or equivalently, 3.3 × increase in membrane area from ~ 2 to ~ 6 m2) increases PBUT removal by 48% (from 22 to 33%, i.e., ~ 0.15 to ~ 0.22 g per session), whereas increasing dialysate flow rates or adding adsorptive species have no substantial impact on PBUT removal unless permeance is above ~ 10−5 m s−1. Our results guide the future development of membranes, dialyzers, and operational parameters that could enhance PBUT clearance and improve patient outcomes.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1980., Includes bibliographical references., by Ifiyenia Kececioglu.

Hydrogen-free reductive catalytic fractionation (RCF) is a promising method to extract and depolymerize lignin from native biomass without the use of external hydrogen gas. Here, we show that Pt/C and Pd/C achieve comparable monomer yields regardless of hydrogen pressure, whereas Ru/C and Ni/C show lower yields under H2-free conditions. Ru/C and Ni/C primarily perform hydrodeoxygenation regardless of the hydrogen pressure, but Pt/C and Pd/C demonstrated the ability to form both ethyl products from dehydrogenation and propanol products through hydrogenation depending on the presence of external H2. Adding water to the solvent increased HDO selectivity to propyl products for both Pt/C and Pd/C. Monomer yields from poplar RCF showed similar trends in yield and selectivity to reactions with the model compound coniferyl alcohol, suggesting that H2-free RCF performance is dictated by the stabilization rate of reactive monomer intermediates.

Flame-retardant chemicals are frequently used within consumer products and can even be employed as a treatment on the surface of different types of materials (e.g., wood, steel, and textiles) to prevent fire or limit the rapid spread of flames. Functionalized graphene oxide (FGO) nanosheets are a promising construction coating nanomaterial that can be blended with sodium metasilicate and gypsum to reduce the flammability of construction buildings. In this work, we designed and fabricated novel and halogen-free FGO sheets using the modified Hummers method; and subsequently functionalized them by pentaerythritol through a chemical impregnation process before dispersing them within the construction coating. Scanning electron microscopic images confirm that the FGO-filled coating was uniformly dispersed on the surface of wooden substrates. We identified that the FGO content is a critical factor affecting the fire retardancy. Thermogravimetric analysis of the FGO coating revealed that higher char residue can be obtained at 700 °C. Based on the differential scanning calorimetry, the exothermic peak contained a temperature delay in the presence of FGO sheets, primarily due to the formation of a thermal barrier. Such a significant improvement in the flame retardancy confirms that the FGO nanosheets are superior nanomaterials to be employed as a flame-retardant construction coating nanomaterial for improving thermal management within buildings.