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At least 1,009 records · Page 56

Uniting Surface Properties With Hydrodynamic Roughness in Shallow Overland Flow Models

Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's n). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation-based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely-used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted values between 0.48 and 0.54, depending on the roughness scheme used. Litter cover was the best predictor of the roughness coefficient, followed by soil cover and average canopy gap size. The results suggest that selection of an optimal roughness scheme based on surface properties alone remains difficult, but that once a scheme is selected, roughness coefficients can be estimated from surface properties.

54 ENVIRONMENTAL SCIENCES↗

Structure and mechanism of biosynthesis of Streptococcus mutans cell wall polysaccharide

Streptococcus mutans, the causative agent of human dental caries, expresses a cell wall attached Serotype c-specific Carbohydrate (SCC) that is critical for cell viability. SCC consists of a polyrhamnose backbone of →3)α-Rha(1 → 2)α-Rha(1→ repeats with glucose (Glc) side-chains and glycerol phosphate (GroP) decorations. This study reveals that SCC has one predominant and two more minor Glc modifications. The predominant Glc modification, α-Glc, attached to position 2 of 3-rhamnose, is installed by SccN and SccM glycosyltransferases and is the site of the GroP addition. The minor Glc modifications are β-Glc linked to position 4 of 3-rhamnose installed by SccP and SccQ glycosyltransferases, and α-Glc attached to position 4 of 2-rhamnose installed by SccN working in tandem with an unknown enzyme. Both the major and the minor β-Glc modifications control bacterial morphology, but only the GroP and major Glc modifications are critical for biofilm formation.

59 BASIC BIOLOGICAL SCIENCES↗

Best practices for in-situ and operando techniques within electrocatalytic systems

In-situ and operando techniques in heterogeneous electrocatalysis are a powerful tool used to elucidate reaction mechanisms. Ultimately, they are key in determining concrete links between a catalyst’s physical/electronic structure and its activity en route to designing next-generation systems. To this end, the exact execution and interpretation of these lines of experiments is critical as this determines the strength of conclusions that can be drawn and what uncertainties remain. Instead of focusing on how techniques were used to understand systems, as is the case with most reviews on the topic, this work instead initiates a nuanced discussion of 1) how to best carry out each technique and 2) initiate a nuanced analysis of which level of insights can be drawn from the set of in-situ or operando experiments/controls carried out. We focus on several commonly used techniques, including vibrational (IR, Raman) spectroscopy, X-ray absorption spectroscopy and electrochemical mass spectrometry. In addition to this, we include sections of reactor design and the link with theoretical modelling that are applicable across all techniques. While we focus on heterogeneous electrocatalysis, we make links when appropriate to the areas of photo- and thermo-catalytic systems. We highlight common pitfalls in the field, how to avoid them, and what sets of complementary experiments may be used to strengthen the analysis. We end with an overview of what gaps remain in in-situ and operando techniques and what innovations must be made to overcome them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deciphering coulombic loss in lithium-ion batteries and beyond

Lithium-ion batteries are pivotal for modern energy storage, yet accurately predicting their lifespan remains a critical challenge. While descriptors like coulombic efficiency are widely used to assess battery longevity, the unclear physical origins of coulombic losses cause semi-quantitative correlation with capacity, complicating battery development. Here, we combine high-precision leakage current and open-circuit-voltage measurements with charge conservation principles to explore microscopic charge consumptions at electrode-electrolyte interfaces across diverse chemistries. We demonstrate that coulombic loss arises from a synergy between local charge neutrality and global charge compensation, reconciling its quantitative correlation to capacity. Contrary to conventional assumptions equating coulombic loss with irreversible capacity loss, this framework resolves systematic overestimations and paradoxical phenomena in existing chemistries. Our findings establish physics-informed criteria for accelerated lifespan evaluation and guide rational design of long-life lithium-ion batteries and beyond.

Batteries↗

Reweighting configurations generated by transferable, machine learned models for protein sidechain backmapping

Multiscale modeling requires the linking of models at different levels of detail, with the goal of gaining accelerations from lower fidelity models while recovering fine details from higher resolution models. Communication across resolutions is particularly important in modeling soft matter, where tight couplings exist between molecular-level details and mesoscale structures. While multiscale modeling of biomolecules has become a critical component in exploring their structure and self-assembly, backmapping from coarse-grained to fine-grained, or atomistic, representations presents a challenge, despite recent advances through machine learning. A major hurdle, especially for strategies utilizing machine learning, is that backmappings can only approximately recover the atomistic ensemble of interest. We demonstrate conditions for which backmapped configurations may be reweighted to exactly recover the desired atomistic ensemble. By training separate decoding models for each sidechain type, we develop an algorithm based on normalizing flows and geometric algebra attention to autoregressively propose backmapped configurations for any protein sequence. Critical for reweighting with modern protein force fields, our trained models include all hydrogen atoms in the backmapping and make probabilities associated with atomistic configurations directly accessible. We also demonstrate, however, that reweighting is extremely challenging despite state-of-the-art performance on recently developed metrics and generation of configurations with low energies in atomistic protein force fields. Through detailed analysis of configurational weights, we show that machine-learned backmappings must not only generate configurations with reasonable energies, but also correctly assign relative probabilities under the generative model. These are broadly important considerations in generative modeling of atomistic molecular configurations.

Monroe, Jacob I. [Univ. of Arkansas, Fayetteville,↗

Diacylglycerol enantiomer selectivity of diacylglycerol acyltransferases highlights metabolic specialization in triacylglycerol synthesis across the tree of life

Triacylglycerols are the major energy storage lipids in plants, animals, and microorganisms, and are predominantly produced by acyl-CoA:diacylglycerol (DAG) acyltransferases (DGATs). Two enantiomers of the DAG substrate, sn -1,2 and sn -2,3, can be produced by different biological mechanisms; however, little is known about which species produce each enantiomer, the selectivity of DGAT isoforms for either enantiomer, or whether DGAT enantiomer selectivity varies across organisms. Here, DAG enantiomer selectivity of DGAT1 and DGAT2 was measured from eight seed plants, two mammals, one oleaginous yeast, and one photosynthetic microalga using enantiomer-specific in vitro DGAT assays. Across most plants, DGAT1 favored sn -1,2-DAG, whereas DGAT2 preferentially utilized sn -2,3-DAG. However, there were several exceptions. Mammalian DGAT1, DGAT2, and microbial DGAT1s efficiently used both DAG enantiomers, while microbial DGAT2s had unique selectivity. The selectivity of several DGATs for combined acyl-CoA and DAG enantiomer molecular species were also evaluated for biotechnical applications. Therefore, DGAT DAG enantiomer selectivity is common yet strongly dependent on lineage and isoform and likely shaped in part by species-specific metabolic context of triacylglycerol synthesis, turnover, and remodeling. This work expands our understanding of DGAT function and establishes a foundation for leveraging enantiomer-selective acyltransferases in metabolic engineering of tailored lipid products.

Arabidopsis thaliana↗

Large-Data Omics Approaches in Modern Remediation

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

42 ENGINEERING↗

Quantum efficiency enhancement in simulated nanostructured negative electron affinity GaAs photocathodes

We report nanostructured negative electron affinity GaAs photocathodes for a polarized electron source are studied using finite difference time domain optical simulation. The structures studied are nanosquare columns, truncated nanocones, and truncated nanopyramids. Mie-type resonances in the 700–800 nm waveband, suitable for generation of polarized electrons, are identified. At resonance wavelengths, the nanostructures can absorb up to 99% of the incident light. For nanosquare columns and truncated nanocones, the maximum quantum efficiency (QE) at 780 nm obtained from simulation is 27%, whereas for simulated nanopyramids, the QE is ~21%. The high photocathode quantum efficiency is due to the shift of Mie resonance toward the longer wavelength, leading to increased light absorption. The field profile distribution shows the excitation of dipole and quadrupole modes within the nanostructures at resonant frequencies. This leads to enhanced photoabsorption and photoelectron generation closer to emission surfaces than for a flat photocathode. The enhanced photoabsorption and reduced electron transport distance for the nanostructured photocathode enhance its QE compared to that for the flat surface wafer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An automatic multi-precursor flow-type atomic layer deposition system

Designs for two automated atomic layer deposition (ALD) flow reactors are presented, and their capabilities for coating additively manufactured (AM) metal prints are described. One instrument allows the coating of several AM parts in batches, while the other is useful for single part experiments. To demonstrate reactor capabilities, alumina (Al 2 O 3 ) was deposited onto AM 316L stainless steel by dosing with water (H 2 O) vapor and trimethylaluminum (TMA) and purging with nitrogen gas (N 2 ). Both instruments are controlled by custom-programmed LabVIEW software that enables in situ logging of temperature, total pressure, and film thickness using a quartz crystal microbalance. An initial result shows that 150 ALD cycles led to a film thickness of ~55 nm, which was verified with Rutherford backscattering spectroscopy. This indicates that the reactors were indeed depositing single atomic layers of Al 2 O 3 per ALD cycle, as intended.

47 OTHER INSTRUMENTATION↗

Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass

The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. Here, to address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate (A MASS ) and leaf nitrogen (N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of activation temperature on quantum efficiency and lifetime of NEA truncated nanocone array GaAs photocathode

This study investigates the quantum efficiency (QE) and operational lifetime of a negative electron affinity GaAs truncated nanocone array (TNCA) photocathode benchmarked against a conventional flat GaAs photocathode under varying activation temperatures. The TNCA structure demonstrated a QE of up to 13.6% at 590 nm with room temperature (RT) activation—approximately 1.5 times higher than its flat counterpart. This enhancement is due to Mie resonance effects within the nanostructure, as confirmed by finite-difference time-domain simulations. Moreover, the TNCA photocathode exhibits significantly extended charge lifetime, with enhancement factors of ∼6.1 and ∼19.8 under RT and 50 °C activations, respectively. These gains are primarily attributed to increased effective surface area and optimized dipole layer formation at elevated temperatures. In addition, shorter excitation wavelengths further contribute to lifetime improvements. These findings underscore the TNCA GaAs photocathode’s potential as a high QE, long lifetime electron source for many large-scale electron accelerators.

Cs-NF3 activation↗

Development, characterisation, and deployment of the SNO+ liquid scintillator

A liquid scintillator consisting of linear alkylbenzene as the solvent and 2,5-diphenyloxazole as the fluor was developed for the SNO+ experiment. This mixture was chosen as it is compatible with acrylic and has a competitive light yield to pre-existing liquid scintillators while conferring other advantages including longer attenuation lengths, superior safety characteristics, chemical simplicity, ease of handling, and logistical availability. Its properties have been extensively characterized and are presented here. This liquid scintillator is now used in several neutrino physics experiments in addition to SNO+.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions

Wetlands are the single largest natural source of atmospheric methane (CH 4 ), contributing approximately 30% of total surface CH 4 emissions, and they have been identified as the largest source of uncertainty in the global CH 4 budget based on the most recent Global Carbon Project CH 4 report. High uncertainties in the bottom–up estimates of wetland CH 4 emissions pose significant challenges for accurately understanding their spatiotemporal variations, and for the scientific community to monitor wetland CH 4 emissions from space. In fact, there are large disagreements between bottom–up estimates versus top–down estimates inferred from inversion of atmospheric CH 4 concentrations. To address these critical gaps, we review recent development, validation, and applications of bottom–up estimates of global wetland CH 4 emissions, as well as how they are used in top–down inversions. These bottom–up estimates, using (1) empirical biogeochemical modeling (e.g. WetCHARTs: 125–208 TgCH 4 yr -1 ); (2) process-based biogeochemical modeling (e.g. WETCHIMP: 190 ± 39 TgCH 4 yr -1 ); and (3) data-driven machine learning approach (e.g. UpCH4: 146 ± 43 TgCH 4 yr -1 ). Bottom–up estimates are subject to significant uncertainties (~80 Tg CH 4 yr -1 ), and the ranges of different estimates do not overlap, further amplifying the overall uncertainty when combining multiple data products. These substantial uncertainties highlight gaps in our understanding of wetland CH 4 biogeochemistry and wetland inundation dynamics. Major tropical and arctic wetland complexes are regional hotspots of CH 4 emissions. However, the scarcity of satellite data over the tropics and northern high latitudes offer limited information for top–down inversions to improve bottom–up estimates. Recent advances in surface measurements of CH 4 fluxes (e.g. FLUXNET-CH 4 ) across a wide range of ecosystems including bogs, fens, marshes, and forest swamps provide an unprecedented opportunity to improve existing bottom–up estimates of wetland CH 4 estimates. We suggest that continuous long-term surface measurements at representative wetlands, high fidelity wetland mapping, combined with an appropriate modeling framework, will be needed to significantly improve global estimates of wetland CH 4 emissions. There is also a pressing unmet need for fine-resolution and high-precision satellite CH 4 observations directed at wetlands.

54 ENVIRONMENTAL SCIENCES↗

Volatiles from the necrophagous fly Cochliomyia macellaria (Diptera: Calliphoridae) as indicators of Salmonella exposure

Blow flies (Diptera: Calliphoridae) are crucial in forensic investigations due to their association with both living and dead humans and other animals. Additionally, their interactions with various resources and potential as vectors of pathogens of humans and other animals, thus, make them potential tools for biosurveillance. This study investigated the potential of monitoring volatile organic compounds (VOCs) emitted by blow flies exposed to Salmonella as a method for pathogen surveillance. Adult blow flies ( Cochliomyia macellaria ) were exposed, or not, to Salmonella enterica . Following exposure, VOCs released by the blow flies were collected and analyzed using gas chromatography-mass spectrometry (GC-MS). Results indicate a treatment by time interaction (P < 0.01). Indicator species analysis identified a single compound significantly associated with S. enterica exposure (P = 0.02), Nonane, 2,2,4,4,6,8,8-heptamethyl, potentially indicating an immune system response. Given a compound indicating exposure was detected, future research should determine if more replicates could detect more differences after Salmonella ingestion. This research highlights the potential of blow flies as biosurveillance tools and the potential value of volatiles for assessing their exposure to pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

On alert for Ebola: public health risk assessment of travellers from Uganda to the USA during the 2022 outbreak

Abstract Background On 20 September 2022, the Ugandan Ministry of Health declared an outbreak of Ebola disease caused by Sudan ebolavirus. Methods From 6 October 2022 to 10 January 2023, Centers for Disease Control and Prevention (CDC) staff conducted public health assessments at five US ports of entry for travellers identified as having been in Uganda in the past 21 days. CDC also recommended that state, local and territorial health departments (‘health departments’) conduct post-arrival monitoring of these travellers. CDC provided traveller contact information, daily to 58 health departments, and collected health department data regarding monitoring outcomes. Results Among 11 583 travellers screened, 132 (1%) required additional assessment due to potential exposures or symptoms of concern. Fifty-three (91%) health departments reported receiving traveller data from CDC for 10 114 (87%) travellers, of whom 8499 (84%) were contacted for monitoring, 1547 (15%) could not be contacted and 68 (1%) had no reported outcomes. No travellers with high-risk exposures or Ebola disease were identified. Conclusion Entry risk assessment and post-arrival monitoring of travellers are resource-intensive activities that had low demonstrated yield during this and previous outbreaks. The efficiency of future responses could be improved by incorporating an assessment of risk of importation of disease, accounting for individual travellers’ potential for exposure, and expanded use of methods that reduce burden to federal agencies, health departments, and travellers.

General & Internal Medicine↗

Towards rational control of seed oil composition: dissecting cellular organization and flux control of lipid metabolism

Plant lipids represent a fascinating field of scientific study, in part due to a stark dichotomy in the limited fatty acid (FA) composition of cellular membrane lipids vs the huge diversity of FAs that can accumulate in triacylglycerols (TAGs), the main component of seed storage oils. With few exceptions, the strict chemical, structural, and biophysical roles imposed on membrane lipids since the dawn of life have constrained their FA composition to predominantly lengths of 16–18 carbons and containing 0–3 methylene-interrupted carbon-carbon double bonds in cis-configuration. However, over 450 “unusual” FA structures can be found in seed oils of different plants, and we are just beginning to understand the metabolic mechanisms required to produce and maintain this dichotomy. Here we review the current state of plant lipid research, specifically addressing the knowledge gaps in membrane and storage lipid synthesis from 3 angles: pathway fluxes including newly discovered TAG remodeling, key acyltransferase substrate selectivities, and the possible roles of “metabolons.”

59 BASIC BIOLOGICAL SCIENCES↗

Complete replacement of Arabidopsis oil-producing enzymes with heterologous diacylglycerol acyltransferases

Acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) and phospholipid:diacylglycerol acyltransferase 1 (PDAT1) share responsibility for triacylglycerol (TAG) biosynthesis, and their selectivities control TAG fatty acid (FA) compositions. For rational metabolic engineering of seed oils, replacing endogenous TAG biosynthesis with exogenous enzymes containing different substrate FA selectivities is desirable; however, the dgat1-1/pdat1-2 double mutant is pollen lethal. Here, we evaluated the ability of 3 DGAT1s, from phylogenetically diverse plants with distinct TAG assembly processes, to completely replace endogenous TAG biosynthesis in Arabidopsis ( Arabidopsis thaliana ). We transformed dgat1-1 mutant plants with expression constructs for DGAT1 s from Camelina sativa , Physaria fendleri , and castor ( Ricinus communis ). Transgene expression was properly “contextualized” by using a previously determined minimum necessary expression unit containing the promoter/5′ UTR and first intron of native AtDGAT1 ; both of these DNA elements are essential for pollen expression. Next, we crossed homozygous lines with a DGAT1/DGAT1/PDAT1/pdat1-2 parent. C. sativa and P. fendleri DGAT1s restored the FA compositions and transcriptional differences of dgat1-1 to near wild-type and rescued the dgat1-1/pdat1-2 pollen lethality. R. communis DGAT1 was active in dgat1-1 seeds but produced unique oil profiles and alterations in the expression of lipid metabolic genes; it also failed to rescue dgat1-1/pdat1-2 lethality. This study confirms that the promoter and first intron of AtDGAT1 can modulate the expression of foreign DGAT1 genes to fit the correct spatiotemporal profile necessary for completely replacing endogenous TAG biosynthesis. Furthermore, it demonstrates an additional layer of unexpected enzyme incompatibility between oilseed lineages, which may complicate bioengineering approaches that seek to replace essential genes with orthologs.

McGuire, Sean T. [Washington State Univ., Pullman,↗

PII interactions with the acetyl-CoA carboxylase subunits BADC and BCCP co-regulate lipid and nitrogen metabolism in Arabidopsis

In plants, the initiation of fatty acid synthesis is catalyzed by acetyl-CoA carboxylase (ACCase), which produces malonyl-CoA. The heteromeric form of ACCase (htACCase) is a holoenzyme consisting of biotin carboxylase and carboxyltransferase sub-complexes, both of which are subject to extensive regulation. Biotin carboxylase activity is controlled in part by the presence of the catalytic biotin carboxyl carrier proteins (BCCP1/2) and/or the non-catalytic, non-biotinylated, biotin/lipoyl attachment domain-containing proteins (BADC1/2/3) that associate with backbone biotin carboxylase (BC) protein. However, the mechanisms regulating BADC and BCCP interactions with BC and, consequently, ACCase activity in planta , remain unclear. Here, we demonstrate that the Arabidopsis ( Arabidopsis thaliana ) regulatory protein PII modulates htACCase activity through independent interactions with BADC and BCCP proteins in a selective manner. Analysis of badc1 badc2 and badc1 badc3 mutant lines and the respective pii triple mutants revealed that changes in seed oil and protein accumulation of badc double mutants are PII/nitrogen dependent. Absolute quantification of htACCase subunits and PII in developing seeds suggests that Arabidopsis exerts tight regulation over individual protein stoichiometry to balance oil and protein accumulation. The effects on vegetative and seed development indicate that PII and BADC proteins have distinct yet overlapping roles in regulating plant metabolism.

Garneau, Matthew G. [Washington State Univ., Pullm↗