Functionally redundant formate dehydrogenases enable formate-dependent growth in Methanococcus maripaludis
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Dirigent isoflavene-forming PsPTS2: 3D structure, stereochemical, and kinetic characterization comparison with pterocarpan-forming PsPTS1 homolog in pea
Pea (legume plant defense) phytoalexin pterocarpans (–)-maackiain and (+)-pisatin have opposite C6a and C11a configurations, but how this occurs biosynthetically is unknown. Herein, pea dirigent-protein (DP) PsPTS2, which generates 7,2'-dihydroxy-4',5'-methylenedioxyisoflav-3-ene (DMDIF), was investigated as regards stereoselectivity towards four possible 7,2'-dihydroxy-4',5'-methylenedioxyisoflavan-4-ol (DMDI) stereoisomers. Each DMDI stereoisomer configuration was determined using NMR spectroscopy, electronic circular dichroism, and molecular orbital analyses. PsPTS2 efficiently converted cis-(3R,4R)-DMDI into DMDIF, this being 20-fold faster than with the trans-(3R,4S)-isomer. The 4R-configured substrate’s near ß-axial OH orientation significantly enhanced its leaving group abilities in creating intermediate A-ring mono-quinone methide (QM), whereas the 4S-isomer’s 4-OH group α-equatorial orientation was a poorer leaving group. Substrate docking simulations also indicated that the 4R-configured ß-axial OH was closest to the Asp catalytic center, whereas the 4S-isomer’s α-equatorial OH was further away. Neither cis-(3S,4S)- nor trans-(3S, 4R)-DMDIs were substrates, even with the former having the same C3/C4 stereochemistry as (+)-pisatin. PsPTS2, assayed with cis-(3R,4R)-7,2'-dihydroxy-4'-methoxyisoflavan-4-ol [cis-(3R,4R)-DMI] and its C3/C4 stereoisomers, gave 2',7-dihydroxy-4'-methoxyisoflav-3-ene (DMIF), with the same substrate stereoselectivity. DP homologs may exist in licorice (Glycyrrhiza pallidiflora) and the tree legume Bolusanthus speciosus, as DMIF is found in both. PsPTS1 preferentially utilized cis-(3R,4R)-DMDI to give (–)-maackiain, this being 2200-fold more efficient than with cis-(3R,4R)-DMI. PsPTS1 also slowly converted trans-(3S,4R)-DMDI into (+)-maackiain, again reflecting the better 4R configured OH leaving group. Pea PsPTS2 and PsPTS1 provisionally provide a facile DP-engendered means to enable differing C6a and C11a configurations in (+)-pisatin and (–)-maackiain. Both DP transformations are considered to occur via DP-engendered generation of an identical mono-QM bound intermediate, which with PsPTS2 either re-aromatizes to give DMDIF or with PsPTS1 undergoes intramolecular cyclization to afford (–)-maackiain. Substrate docking simulations using PsPTS2 (2.5 Å resolution) and PsPTS1 (1.5 Å resolution) plausibly indicate that cis-(3R,4R)-DMDI binds in the anti-configuration in the PsPTS2 active site to afford DMDIF, and the syn-configuration in PsPTS1 to give maackiain.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization
Objective: The growing availability of electronic health records (EHR) data opens opportunities for integrative analysis of multi-institutional EHR to produce generalizable knowledge. A key barrier to such integrative analyses is the lack of semantic interoperability across different institutions due to coding differences. We propose a Multiview Incomplete Knowledge Graph Integration (MIKGI) algorithm to integrate information from multiple sources with partially overlapping EHR concept codes to enable translations between healthcare systems. Methods: The MIKGI algorithm combines knowledge graph information from (i) embeddings trained from the co-occurrence patterns of medical codes within each EHR system and (ii) semantic embeddings of the textual strings of all medical codes obtained from the Self-Aligning Pretrained BERT (SAPBERT) algorithm. Due to the heterogeneity in the coding across healthcare systems, each EHR source provides partial coverage of the available codes. MIKGI synthesizes the incomplete knowledge graphs derived from these multi-source embeddings by minimizing a spherical loss function that combines the pairwise directional similarities of embeddings computed from all available sources. MIKGI outputs harmonized semantic embedding vectors for all EHR codes, which improves the quality of the embeddings and enables direct assessment of both similarity and relatedness between any pair of codes from multiple healthcare systems. Results: With EHR co-occurrence data from Veteran Affairs (VA) healthcare and Mass General Brigham (MGB), MIKGI algorithm produces high quality embeddings for a variety of downstream tasks including detecting known similar or related entity pairs and mapping VA local codes to the relevant EHR codes used at MGB. Based on the cosine similarity of the MIKGI trained embeddings, the AUC was 0.918 for detecting similar entity pairs and 0.809 for detecting related pairs. For cross-institutional medical code mapping, the top 1 and top 5 accuracy were 91.0% and 97.5% when mapping medication codes at VA to RxNorm medication codes at MGB; 59.1% and 75.8% when mapping VA local laboratory codes to LOINC hierarchy. When trained with 500 labels, the lab code mapping attained top 1 and 5 accuracy at 77.7% and 87.9%. MIKGI also attained best performance in selecting VA local lab codes for desired laboratory tests and COVID-19 related features for COVID EHR studies. Compared to existing methods, MIKGI attained the most robust performance with accuracy the highest or near the highest across all tasks. Conclusions: The proposed MIKGI algorithm can effectively integrate incomplete summary data from biomedical text and EHR data to generate harmonized embeddings for EHR codes for knowledge graph modeling and cross-institutional translation of EHR codes.
Zhou, Doudou↗
ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis
Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.
Electronic health records↗
DOME: Directional medical embedding vectors from Electronic Health Records
Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.
60 APPLIED LIFE SCIENCES↗
Charging of radioactive and environmental airborne particles
The charging of various airborne particles was investigated using single-particle levitation and charge-balance equations. Though radioactive decay and triboelectrification can induce charging, it is typically assumed that the aerosols in a radioactive plume will not carry significant charge at steady state since atmospheric particles can have their charge neutralized through the capture of adjacent counter-ions (i.e., diffusion charging). Here to assess this assumption, we directly measured the surface charge and charge density of various triboelectrically charged aerosols including radioactive uranium oxide (<1 μm), urban dust, Arizona desert dust, hydrophilic and hydrophobic silica nanoparticles, and graphene oxide powders using an electric field-assisted particle levitator in air. Of these particles, uranium oxide aerosols exhibited the highest surface charge density. Charge balance equations were employed to predict the average charge gained from radioactive decay as a function of time and to evaluate the effects of diffusion charging on triboelectrically charged radioactive and non-radioactive particles in the atmosphere. Simulation results show that particles, initially charged through triboelectrification, can be quickly discharged by diffusion charging in the absence of radioactive decay. Nevertheless, simulation results also indicate that particles can be strongly charged when they carry radionuclides. These experimental and simulation results suggest that radioactive decay can induce strong particle charging that may potentially affect atmospheric transport of airborne radionuclides.
54 ENVIRONMENTAL SCIENCES↗
Simulation of radioactive plume transport in the atmosphere including dynamics of particle aggregation and breakup
Accurate prediction of the atmospheric transport of debris particles relies heavily on our knowledge of the size distribution of the particles within a debris cloud. Assuming a fixed particle size during simulations is not always viable since the size distribution of the debris can change during transport. Various microphysical processes, such as aggregation and breakup, influence debris particles and dictate any changes to the size distribution. To track those changes that can occur, a population balance model can be adopted and instituted within a model framework. Nonetheless, many of the models that simulate the transport of radioactive debris following a device-driven fission incident have historically neglected to consider these processes. As such, this work describes our effort to develop a modeling framework capable of simulating the transport and deposition of a radioactive plume generated from a fission incident with a dynamic population balance including particle aggregation and breakup. Herein the impact of aggregation and breakup, individually and collectively, on the particle size distribution is explored using the developed framework. When simulating aggregation, for example, six mechanisms, including Brownian coagulation, the convective enhancement to Brownian coagulation, van der Waals-viscous force correction for Brownian coagulation, gravitational collection, turbulent inertial motion, and turbulent shear, are considered. Brownian coagulation and its corrections have, as one would expect, a large impact on relatively small aggregates. Aggregates with a diameter that is less than or equal to 1.0 μm, for instance, comprise 50.6 vol % of all aggregates in the absence of aggregation and 31.2 vol % when Brownian coagulation and its corrections are considered. Gravitational collection and, to a much lesser extent, turbulent shear and turbulent inertial motion are, conversely, of great importance to relatively large aggregates (i.e., diameter greater than 3.0 μm). Additionally, the individual effects of atmospheric and particle parameters, such as wind speed and particle density, are examined. Of the parameters examined, turbulent energy dissipation and aggregate fractal dimension (i.e., aggregate shape with lower values representing more irregular particles) were of substantial importance since both terms directly impact aggregate stability and, by extension, the breakup rate. Large-scale transport and deposition simulations in a dry atmosphere are also presented and discussed as a proof of concept.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Cantor-derived medium-entropy alloys: bridging the gap between traditional metallic and high-entropy alloys
The year 2004 marked the beginning of a new era in the design of metallic materials, as the concept of multiple principal component alloys, commonly known as High-Entropy Alloys (HEAs), was proposed by Cantor and Yeh. The unexpected single-phase microstructure, instead of the expected brittle intermetallic compounds, was attributed to the large entropy of mixing and immediately caught the attention of the scientific community. Today, HEAs are considered important advanced materials and a broad range of alloys using nominally the same design principle have been investigated. Despite that, the CrMnFeCoNi (Cantor) alloy stands out as the most successful HEA due to its outstanding mechanical properties and microstructure. In this scenario, variants of the Cantor alloy, named medium-entropy alloys (MEAs), are gaining significant interest as they display a better industrial potential than both HEAs and traditional alloys. These variants of the Cantor alloy with only three or four main elements result in 15 possible combinations. The microstructure of these alloys is discussed in terms of advanced characterization as well as thermodynamic parameters and computational simulation. Their phase stability is addressed over a wide range of temperatures and strain rates. The mechanical properties, especially the fracture toughness, of the CrFeCoNi and CrCoNi alloys have been reported to be even superior to those of the Cantor alloy and most modern engineering alloys. This is associated with the formation of a continuous sequence of strengthening mechanisms, including hierarchical twin networks, which serve to prolong the strain hardening. The present article reviews and critically assesses, for the first time, recent advances in these Cantor-derived MEAs.
36 MATERIALS SCIENCE↗
Printable, emissivity-adaptive and albedo-optimized covering for year-round energy saving
Radiative cooling uses high-emissivity materials to passively cool the surface of outdoor objects, such as building roofs on hot days. The issue of overcooling with this technology on cold days can be addressed by structures with thermal emissivity that is adaptive to temperature. Despite recent advances in temperature-adaptive structures, great challenges remain in their fabrication feasibility and unoptimized solar heating that may override the radiative cooling benefit. Here, in this work, we develop a printable, emissivity-adaptive and albedo-optimized covering (PEAC) based on recyclable materials with roll-to-roll fabrication. A PEAC automatically switches its sky-window emissivity from 0.25 to 0.85 when the surface temperature exceeds a pre-set transition temperature, delivering an albedo optimized for maximal year-round energy saving or thermal comfort in a given climate.
36 MATERIALS SCIENCE↗
High-emissivity, thermally robust emitters for high power density thermophotovoltaics
Thermal radiative energy transport is essential for high-temperature energy harvesting technologies, including thermophotovoltaics (TPVs) and grid-scale thermal energy storage. However, the inherently low emissivity of conventional high-temperature materials constrains radiative energy transfer, thereby limiting system performance and technoeconomic viability. Here, in this study, we demonstrate ultrafast femtosecond laser-material interactions to transform diverse materials into near-blackbody surfaces with broadband spectral emissivity above 0.96. This enhancement arises from hierarchically engineered light-trapping microstructures enriched with nanoscale features, effectively decoupling surface optical properties from bulk thermomechanical properties. These laser-blackened surfaces (LaBS) exhibit exceptional thermal stability, retaining high emissivity for over 100 h at temperatures exceeding 1,000°C, even in oxidizing environments. When applied as TPV thermal emitters, Ta LaBS double electrical power output from 2.19 to 4.10 W cm −2 at 2,200°C while sustaining TPV conversion efficiencies above 30%. This versatile, largely material-independent technique offers a scalable and economically viable pathway to enhance emissivity for advanced thermal energy applications.
laser-blackened surfaces↗
Aeroelastic oscillations of a pitching flexible wing with structural geometric nonlinearities: Theory and numerical simulation
In this paper, we focus on the derivation of an analytical model of the aeroelastic dynamics of an elastically mounted flexible wing. This equations of motion obtained serve to help understand the behaviour of the aeroelastic wind tunnel setup in question, which consists of a rectangular wing with a uniform NACA 0012 airfoil profile, whose base is free to rotate rigidly about a longitudinal axis. Of particular interest are the structural geometric nonlinearities primarily introduced by the coupling between the rigid body pitch degree-of-freedom and the continuous system. A coupled system of partial differential equations (PDEs) coupled with an ordinary differential equation (ODE) describing axial-bending-bending-torsion-pitch motion is derived using Hamilton's principle. A finite dimensional approximation of the system of coupled differential equations is obtained using the Galerkin method, leading to a system of coupled nonlinear ODEs. Subsequently, these nonlinear ODEs are solved numerically using Houbolt's method. The results that are obtained are verified by comparison with the results obtained by direct integration of the equations of motion using a finite difference scheme. Adopting a linear unsteady aerodynamic model, it is observed that the system undergoes coalescence flutter due to coupling between the rigid body pitch rotation dominated mode and the first flapwise bending dominated mode. Finally, the behaviour of the limit cycle oscillations is primarily influenced by the structural geometric nonlinear terms in the coupled system of PDEs and ODE.
42 ENGINEERING↗
Nonnegative matrix factorization-based blind source separation for full-field and high-resolution modal identification from video
Not Available
Silva, Moisés (ORCID:0000000178973978)↗
Carbapenem resistant Enterobacteriaceae from port areas in São Paulo State (Brazil): Isolation and molecular characterization
Not Available
Andrade, Vanessa Costa↗
Scalable phononic metamaterials: Tunable bandgap design and multi-scale experimental validation
Phononic metamaterials offer unprecedented control over wave propagation, making them essential for applications such as vibration isolation, waveguiding, and acoustic filtering. However, achieving scalable and precisely tunable bandgap properties across different length scales remains challenging. This study presents a user-friendly design framework for phononic metamaterials, enabling ultra-wide bandgap tunability (B/ω c ratios up to 172 %) across multiple frequency ranges and scales. Using finite element simulations of a Yablonovite-inspired unit cell, we establish a comprehensive parametric design space that illustrates how geometric parameters, such as sphere size and beam diameter, controls bandgap width and frequency. The scalability and robustness of the framework are validated through experimental testing on additively manufactured structures at both macro (10 mm) and micro (80 µm) scales, fabricated using Stereolithography and Two-Photon Polymerization. Transmission loss measurements, conducted with piezoelectric transducers and laser vibrometry, closely match simulations in the kHz and MHz frequency ranges, confirming the reliability and consistency of the bandgap behavior across scales. This work bridges theory and experiments at multiple scales, offering a practical methodology for the rapid design of phononic metamaterials and expanding their potential for diverse applications across a broad range of frequencies.
36 MATERIALS SCIENCE↗
On the effect of elemental partitioning to secondary phases after solution and aging heat treatments in a Co-Ni-based superalloy
Here, this paper presents the phase stability and elemental partitioning in a Co-40Ni-10Al-7.5W-10Cr-3Nb-0.06B-0.6C (at.%) superalloy (referred to as 3Nb) after a two-step heat treatment. The resulting microstructure consisted of γ, γ', MC carbides and µ-Co 7 W 6 phase decorating the regions near and at the grain boundaries. Nb preferentially partitioned to the γ'-phase and other elements such as Ni, Cr and W were responsible for the μ-phase formation.
36 MATERIALS SCIENCE↗