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At least 541 records · Page 30

Some spectral plasma diagnostics for prominences and structures in the middle chromosphere

The present investigation is concerned with the statistical equilibrium of the low-lying levels of Na, Sr(+), and Ba(+) under conditions appropriate to structures just above the solar surface. The solar and atomic data required for this objective are largely available with an adequate precision. However, the metastable (2)D term photoionization cross sections had to be calculated. In the calculations a variant of the scaled Thomas-Fermy method suggested by Kahler (1971) was used. The Na and Sr(+) resonance lines are readily measurable in ordinary prominences. The Ba(+) are weak. It is shown that the ratio of Na to Sr(+) resonance-line integrated intensities provides a useful and sensitive electron-density diagnostic for prominences, yielding values in the neighborhood of 10 to the 11th per cu cm. The statistical equilibrium solutions are applied to an analysis of data from the flash spectrum at eclipse.

Landman, D. A.↗

The Acetylene Bridge in Intramolecular Singlet Fission: A Boon or A Nuisance?

Various analogues of the alkylsilylacetylene group are frequently used as auxiliary groups to enhance the solubility and stability of the acene dimer core, widely used as platforms to investigate intramolecular singlet fission (iSF) mechanisms. However, while in the 2,2’-linked dimers they are primarily auxiliary groups, these are essential fragments of the bridging units in 6,6’/5,5’-linked dimers, the two preferred choices for dimerization. The starkly different iSF dynamics observed in the two variants raise the question of what role the acetylene bridges play. Here, we systematically designed a set of (oligo-)para-phenylene bridged 2,2’-linked pentacene dimers with an additional acetylene fragment in the bridging unit to mimic the structure of 6,6’-linked dimers. Contrasting the results with previously reported analogous 2,2’-linked and 6,6’-linked pentacene dimers reveals that the acetylene bridges contribute to significant conformational freedom. This effect provides a mechanism to promote spin evolution within the triplet pair to achieve free triplets but also offers new parasitic pathways for triplet-pair recombination, revealing that this structural motif can be both a boon and a nuisance. Additionally, our analysis reveals that these bridges directly modify the electronic states, highlighting significant pitfalls of the standard chromophore-bridge-chromophore framework used to design and interpret photophysics of iSF materials.

14 SOLAR ENERGY↗

An engineered lactate oxidase based electrochemical sensor for continuous detection of biomarker lactic acid in human sweat and serum

Lactate levels in humans reveal intensity and duration of exertion and provide a critical readout for the severity of life-threatening illnesses such as pediatric sepsis. Using the lactate oxidase enzyme (Lox) from Aerococcus viridians, we demonstrated its functionality for lactate electrochemical sensing in physiological fluids in a lab setting. The structure and dynamics of LOx were validated by crystallography, X-ray scattering, and hydroxyl radical protein footprinting. This provided a validated protein template for understanding and designing an enzyme-based electrochemical sensing elements. Using this template, LOx enzyme variants were generated and compared. Comparison of the variants demonstrates that one exhibits effective lactate sensing at significantly reduced operating voltages. Additionally, we demonstrate that the four hexahistidine-tags on each enzyme tetramer are sufficient for immobilization to create a durable, functional sensor, with no need for a covalent attachment, enabling self-immobilization and eliminating the need for additional immobilization steps. The functionality of the LOx enzyme variants was verified at physiological lactate concentrations in both human serum (0–4 mM) and artificial sweat (0–100 mM) using 3-electrode setups for analysis of the three variants in parallel. Accuracy of measurement in both artificial sweat and human serum were high. Employing a microfluidic flow cell, we successfully monitored varying lactate levels in physiological fluids continuously over a 2h period. Overall, this optimized LOx enzyme, which self-immobilizes onto gold sensing electrodes, facilitates efficient and reliable lactate detection and continuous monitoring at reduced operating voltages suitable for further development towards commercial use.

60 APPLIED LIFE SCIENCES↗

Analysis of orientation-dependent deformation mechanisms in additively manufactured Zr using in-situ micromechanical testing: Twinning and orientation gradient

Here, orientation-dependent plasticity in zirconium (Zr)-alloy, which is produced through ultrasonic additive manufacturing (UAM) with subsequent hot-isostatic pressing (HIP), was analyzed by recording electron backscattered diffraction (EBSD) data during in-situ micromechanical testing. Three (0001) plane orientations of a hexagonal close-packed (HCP) structure were analyzed parallel to (1) the rolling direction [X||tensile direction (TD)], (2) the build direction [Z], and (3) the transverse direction [Y]. The analysis revealed that the grains with ~<0001>||TD show twin-dominant plasticity with three variants from {10 $\overline{1}$ 2}<$\overline{1}$ 011>; minor slipping with ($10\overline{1}$ 1)[$\overline{2}$ 113], and ($11\overline{2}$ 2)[$\overline{1} \overline{1}$ 23] pyramidal slip has also been observed. However, grains with orientation ~<0001>⊥TD are mainly sensitive to dislocations assisted plasticity-leading to orientation gradients formation. Furthermore, the neck formation was identified as originating from higher populated micro-crack locations and their association with localized plasticity at defect points in the UAM material. These results demonstrate that minimization of impurities to enable grain growth across prior foil interfaces makes HIP an effective methodology for producing Zr plate, with deformation characteristics expected for conventionally manufactured Zr.

36 MATERIALS SCIENCE↗

Automation of Active Space Selection for Multireference Methods via Machine Learning on Chemical Bond Dissociation

Predicting and understanding the chemical bond is one of the major challenges of computational quantum chemistry. Kohn–Sham density functional theory (KS-DFT) is the most common method, but approximate density functionals may not be able to describe systems where multiple electronic configurations are equally important. Multiconfigurational wave functions, on the other hand, can provide a detailed understanding of the electronic structures and chemical bonds of such systems. In the complete active space self-consistent field (CASSCF) method, one performs a full configuration interaction calculation in an active space consisting of active electrons and active orbitals. However, CASSCF and its variants require the selection of these active spaces. This choice is not black box; it requires significant experience and testing by the user, and thus active space methods are not considered particularly user-friendly and are employed only by a minority of quantum chemists. Our goal is to popularize these methods by making it easier to make good active space choices. Here, we present a machine learning protocol that performs an automated selection of active spaces for chemical bond dissociation calculations of main group diatomic molecules. The protocol shows high prediction performance for a given target system as long as a properly correlated system is chosen for training. Good active spaces are correctly predicted with a considerably better success rate than random guess (larger than 80% precision for most systems studied). Our automated machine learning protocol shows that a “black-box” mode is possible for facilitating and accelerating the large-scale calculations on multireference systems where single-reference methods such as KS-DFT cannot be applied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Using Machine Learning to Improve Thermostability of MHETase

Protein engineering is a field which utilizes proteins as tools, which has many useful applications in medicine, industry, biofuels and more.1 One such protein is MHETase, which is a protein that plays an important function in the degradation of polyethylene terephthalate (PET) plastics, which are commonly used in water and soda bottles.2 However, these proteins are adapted to work in specific conditions, and may not satisfy the desired properties that a new application would desire, or could be improved. For instance, a more thermostable MHETase would be more effective in the plastic degradation conditions.3 To make these desired changes, the primary structure of the protein is mutated, but there are many possible mutations and positions to mutate to make with the 20 canonical amino acids. Therefore, to narrow down the possibilities and to make the process of finding a thermostable MHETase variant, we used sequence design tools that are grounded in machine learning to find mutations that would improve thermostability of MHETase.4 In particular, we used the tools Protein MPNN and Fireprot to design a more thermostable MHETase enzyme. We then compiled these mutations into a library and grew these proteins using bacteria colonies, and measured their effectiveness using a fluorescent protein marker. Thermostable proteins and their marker would fold correctly and fluorescence would be seen, but if neither folded correctly then there would be no marker detected. We grew these proteins in bacteria and then intend to use these methods to evaluate their thermostability.

59 BASIC BIOLOGICAL SCIENCES↗

Using Machine Learning to Improve Thermostability of MHETase

Protein engineering is a field which utilizes proteins as tools, which has many useful applications in medicine, industry, biofuels and more. One such protein is MHETase, which is a protein that plays an important function in the degradation of polyethylene terephthalate (PET) plastics, which are commonly used in water and soda bottles.2 However, these proteins are adapted to work in specific conditions, and may not satisfy the desired properties that a new application would desire, or could be improved. For instance, a more thermostable MHETase would be more effective in the plastic degradation conditions.3 To make these desired changes, the primary structure of the protein is mutated, but there are many possible mutations and positions to mutate to make with the 20 canonical amino acids. Therefore, to narrow down the possibilities and to make the process of finding a thermostable MHETase variant, we used sequence design tools that are grounded in machine learning to find mutations that would improve thermostability of MHETase.4 In particular, we used the tools Protein MPNN and FireProt to design a more thermostable MHETase enzyme. We then compiled these mutations into a library and grew these proteins using bacteria colonies, and measured their effectiveness using a fluorescent protein marker. Thermostable proteins and their marker would fold correctly and fluorescence would be seen, but if neither folded correctly then there would be no marker detected. We grew these proteins in bacteria and then intend to use these methods to evaluate their thermostability.

59 BASIC BIOLOGICAL SCIENCES↗

Control of cell cycle by metabolites of prostaglandin D2 through a non-cAMP mediated mechanism

The dehydration products of PGD2, 9-deoxy-9 prostaglandin D2(PGJ2), 9-deoxy-delta 9, delta 12, delta 13 dehydroprostaglandin D2 (delta 12 PGJ2), and PGA2 all contain an unsaturated cyclopentenone structure which is characteristic of prostaglandins which effectively inhibit cell growth. It has been suggested that the action of the inhibitory prostaglandins may be through a cAMP mechanism. In this study, we use S49 wild type (WT) and adenylate cyclase variant (cyc-) cells to show that PGD2 and PGJ2 are not acting via a cyclic AMP mechanism. First, the increase in cyclic AMP in wild type S-49 cells is not proportional to its effects on DNA synthesis. More importantly, when S-49 cyc- cells were exposed to PGJ2, the adenylate cyclase (cyc-) mutant had decreased DNA synthesis with no change in its nominal cAMP content. Short-term (2 hours or less) exposure of the cyc- cells to prostaglandin J2 caused an inhibition of DNA synthesis. PGJ2 caused cytolysis at high concentrations. Long-term exposure (>14 hrs) of the cells to PGJ2, delta 12PGJ2 or delta 12, delta 14PGJ2 caused a cell cycle arrest in G1 demonstrating a cell cycle specific mechanism of action for growth inhibition by naturally occurring biological products independent of cAMP.

NASA Discipline Cell Biology↗

System and method for substance removal

In variants, an air treatment module can include a sorption module defining a sorption cavity, an air intake channel, an air exhaust channel, and a target substance exhaust channel. The air treatment module can include a sorbent encapsulated within a sorbent structure (e.g., microencapsulated carbon sorbent) which can sorb carbon dioxide from air passing through the sorption cavity. The air treatment module can desorb carbon dioxide from the air and store the carbon dioxide in long term storage.

Dess, Peter Colin↗

De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )

The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.

59 BASIC BIOLOGICAL SCIENCES↗

On the Importance of Chemical Precision in Organic Electronics: Fullerene Intercalation in Perfectly Alternating Conjugated Polymers

Abstract The true structure of alternating conjugated polymers—the state‐of‐the‐art materials for many organic electronics—often deviates from the idealized picture. Homocoupling defects are in fact inherent to the widely used cross‐coupling polymerization methods. Nevertheless, many polymers still perform excellently in the envisaged applications, which raises the question if one should really care about these imperfections. This article looks at the relevance of chemical precision (and lack thereof) in conjugated polymers covering the entire spectrum from the molecular scale, to the micro and mesostructure, up to the device level. The different types of polymerization errors for the alkoxylated variant of the benchmark (semi)crystalline polymer poly[2,5‐bis(3‐tetradecylthiophen‐2‐yl)thieno[3,2‐ b ]thiophene (PBTTT) are identified, visualized, and quantified and a general strategy to avoid homocoupling is introduced. Through a combination of experiments and supported by simulations, it is shown that these coupling defects hinder fullerene intercalation and limit device performance as compared to the homocoupling‐free analog. This clearly demonstrates that structural defects do matter and should be generally avoided, in particular when the geometrical regularity of the polymer is essential. These insights likely go beyond the specific PBTTT derivatives studied here and are of general relevance for the wider organic electronics field.

36 MATERIALS SCIENCE↗

Understanding the role of negative charge in the scaffold of an artificial enzyme for CO 2 hydrogenation on catalysis

Here, we have approached the construction of an artificial enzyme by employing a robust protein scaffold, lactococcal multidrug resistance regulator, LmrR, providing a structured secondary and outer coordination spheres around a molecular rhodium complex, [Rh I (P Et2 N gly P Et2 ) 2 ] - . Previously, we demonstrated a 2–3 fold increase in activity for one Rh-LmrR construct by introducing positive charge in the secondary coordination sphere. In this study, a series of variants was made through site-directed mutagenesis where the negative charge is located in the secondary sphere or outer coordination sphere, with additional variants made with increasingly negative charge in the outer coordination sphere while keeping a positive charge in the secondary sphere. Placing a negative charge in the secondary or outer coordination sphere demonstrates decreased activity by a factor of two compared to the wild-type Rh-LmrR. Interestingly, addition of positive charge in the secondary sphere, with the negatively charged outer coordination sphere restores activity. Vibrational and NMR spectroscopy suggest minimal changes to the electronic density at the rhodium center, regardless of inclusion of a negative or positive charge in the secondary sphere, suggesting another mechanism is impacting catalytic activity, explored in the discussion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Making Macroscopic Assemblies of Aligned Carbon Nanotubes

A method of aligning and assembling single-wall carbon nanotubes (SWNTs) to fabricate macroscopic structures has been invented. The method entails suspending SWNTs in a fluid, orienting the SWNTs by use of a magnetic and/or electric field, and then removing the aligned SWNTs from suspension in such a way as to assemble them while maintaining the alignment. SWNTs are essentially tubular extensions of fullerene molecules. It is desirable to assemble aligned SWNTs into macroscopic structures because the common alignment of the SWNTs in such a structure makes it possible to exploit, on a macroscopic scale, the unique mechanical, chemical, and electrical properties that individual oriented SWNTs exhibit at the molecular level. Because of their small size and high electrical conductivity, carbon nanotubes, and especially SWNTs, are useful for making electrical connectors in integrated circuits. Carbon nanotubes can be used as antennas at optical frequencies, and as probes in scanning tunneling microscopes, atomic-force microscopes, and the like. Carbon nanotubes can be used with or instead of carbon black in tires. Carbon nanotubes are useful as supports for catalysts. Ropes of SWNTs are metallic and, as such, are potentially useful in some applications in which electrical conductors are needed - for example, they could be used as additives in formulating electrically conductive paints. Finally, macroscopic assemblies of aligned SWNTs can serve as templates for the growth of more and larger structures of the same type. The great variety of tubular fullerene molecules and of the structures that could be formed by assembling them in various ways precludes a complete description of the present method within the limits of this article. It must suffice to present a typical example of the use of one of many possible variants of the method to form a membrane comprising SWNTs aligned substantially parallel to each other in the membrane plane. The apparatus used in this variant of the method (see figure) includes a reservoir containing SWNTs dispersed in a suspending agent (for example, dimethylformamide) and a reservoir containing a suitable solvent (for example, water mixed with a surfactant). By use of either pressurized gas supplied from upstream or suction from downstream, the suspension of SWNTs and the solvent are forced to mix and flow into a tank. A filter inside the tank contains pores small enough to prevent the passage of most SWNTs, but large enough to allow the passage of molecules of the solvent and suspending agent. The filter is oriented perpendicular to the flow path. A magnetic field parallel to the plane of the filter is applied. The success of the method is based on the tendency of SWNTs to become aligned with their longitudinal axes parallel to an applied magnetic field. The alignment energy of an SWNT increases with the length of the SWNT and the magnetic-field strength. In order to obtain an acceptably small degree of statistical deviation of SWNTs of a given length from alignment with a magnetic field, one must make the field strong enough so that the thermal energy associated with rotation of an SWNT away from alignment is less than the alignment energy.

Smalley, Richard E.↗

Republished: Colossal density-driven resistance response in the negative charge transfer insulator MnS 2

The Mn chalcogenides show a remarkable variation in structural and physical properties with density. In MnS 2 we observe a pronounced difference with the effects of varying hydrostaticity with pressure inducing a structural transition at 300 K. Within the pyrite phase, a colossal electrical resistance drop of 10 8 Ohms is observed by 12 GPa of nonhydrostatic compression at 300 K. DFT simulations reveal the metallization to be unexpectedly driven by previously unoccupied S$^{2-}_2$ σ$^*_{3p}$ antibonding states crossing the Fermi level. This is a seldom seen variant of the charge transfer insulator to metal transition for negative charge transfer insulators which have anions with an unsaturated valence. Finally, by 36 GPa of nonhydrostatic compression, the single presence of the low-spin insulating arsenopyrite (P2 1 /c) phase is confirmed, and the bulk metallicity is broken with the system returning to an insulative electronic state.

36 MATERIALS SCIENCE↗

Stereochemically‐Controlled Fluorinated Copolymers for Selectively Permeable Barrier Applications

Selective oxygen permeability coupled with low water vapor transmission is essential for biomedical and packaging applications requiring controlled oxygen flux under humid conditions. However, most high‐performance barrier polymers depend on perfluoroalkyl substances (PFAS), whose persistence and regulatory restrictions limit their long‐term applicability. We designed a series of stereocontrolled thiol‐yne‐based polyesters, including both fluorinated and non‐fluorinated variants, for selective oxygen permeability with considerable water barrier performance. Tailoring polymer crystallinity and morphology tuned both oxygen transport and mechanical properties. Fluorinated polymers demonstrated enhanced hydrophobicity and water resistance while maintaining oxygen diffusivity within a range relevant to oxygen‐sensing applications. Structure–property relationships were elucidated through small‐ and wide‐angle X‐ray scattering, revealing semi‐crystalline domains influenced by fluorine content and dithiol chain length. Barrier performance was rigorously evaluated via water vapor transmission rate and dynamic vapor sorption, showing reduced water uptake with increasing dithiol monomer length and crystallinity. In conclusion, this work introduces a PFAS‐free alternative to conventional barrier materials and establishes a tunable materials platform with potential relevance for biomedical devices and packaging systems requiring controlled oxygen permeability.

36 MATERIALS SCIENCE↗

Involvement of the Streptococcus mutans PgfE and GalE 4-epimerases in protein glycosylation, carbon metabolism, and cell division

Streptococcus mutans is a key pathogen associated with dental caries and is often implicated in infective endocarditis. This organism forms robust biofilms on tooth surfaces and can use collagen-binding proteins (CBPs) to efficiently colonize collagenous substrates, including dentin and heart valves. One of the best characterized CBPs of S. mutans is Cnm, which contributes to adhesion and invasion of oral epithelial and heart endothelial cells. These virulence properties were subsequently linked to post-translational modification (PTM) of the Cnm threonine-rich repeat region by the Pgf glycosylation machinery, which consists of 4 enzymes: PgfS, PgfM1, PgfE, and PgfM2. Inactivation of the S. mutans pgf genes leads to decreased collagen binding, reduced invasion of human coronary artery endothelial cells, and attenuated virulence in the Galleria mellonella invertebrate model. The present study aimed to better understand Cnm glycosylation and characterize the predicted 4-epimerase, PgfE. Using a truncated Cnm variant containing only 2 threonine-rich repeats, mass spectrometric analysis revealed extensive glycosylation with HexNAc2. Compositional analysis, complemented with lectin blotting, identified the HexNAc2 moieties as GlcNAc and GalNAc. Comparison of PgfE with the other S. mutans 4-epimerase GalE through structural modeling, nuclear magnetic resonance, and capillary electrophoresis demonstrated that GalE is a UDP-Glc-4-epimerase, while PgfE is a GlcNAc-4-epimerase. While PgfE exclusively participates in protein O-glycosylation, we found that GalE affects galactose metabolism and cell division. Furthermore, this study further emphasizes the importance of O-linked protein glycosylation and carbohydrate metabolism in S. mutans and identifies the PTM modifications of the key CBP, Cnm.

4-epimerases↗

Comparative Assessment of U-Net-Based Deep Learning Models for Segmenting Microfractures and Pore Spaces in Digital Rocks

Segmentation of high-resolution X-ray microcomputed tomography (µCT) images is crucial in digital rock physics (DRP), affecting the characterization and analysis of microscale phenomena in the porous media. The complexity of geological structures and nonideal scanning conditions pose significant challenges to conventional image segmentation approaches. Motivated by the recent increasing popularity of deep learning (DL) techniques in image processing, this work undertakes a comparative study of DL models, specifically U-Net and its variants, for segmenting multiple targets with distinguished features in digital rocks, including discrete fracture networks (DFNs), pore spaces, and solid rock. Particularly, DFNs have a smaller volumetric fraction over others, bringing in a substantial challenge of imbalanced segmentation. The primary focus is to evaluate the architecture and feature enhancement strategies of various DL models, including U-Net, attention U-Net, residual U-Net, U-Net++, and residual U-Net++. The models were designed as 2.5D, utilizing a central 2D image and its two adjacent upper and lower 2D images as input to provide a pseudo-3D context. In addition, because the ground truth of segmentation was unknown for real-world digital rocks, we created a benchmark data set following the inverse operations of segmentation. The data synthesis started from the label images (i.e., solid rock, pore spaces, and DFNs), followed by simulating partial volume blurring, adding random background noise, and introducing ring artifacts to mimic real raw X-ray µCT images. The data set, which included various rock types (i.e., sandstone and artificial data), scanning resolution, and magnitudes of noise and artifacts, was divided into training and testing data sets with a 90% and 10% ratio, respectively. Moreover, in addition to the conventional pixel-wise evaluation metrics, the physics-based metric of the lattice-Boltzmann method (LBM) simulated permeability provided more comprehensive assessments. The results demonstrated that the residual connections, nested architectures, and redesigned skip connections contribute to the model performance and give the residual U-Net++ the highest accuracy. The improvements were mainly on the boundaries and small targets, especially the DFNs, which dominate the interconnectivity and therefore affect the permeability greatly. This study also rigorously evaluated the efficiency and generalization of each model, demonstrating that the sophisticated architectures achieved excellent practicability and maintained robust performance on completely unseen data, ensuring their suitability for diverse and challenging DRP applications.

58 GEOSCIENCES↗