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At least 271 records · Page 15

PD-L1 induces macrophage polarization toward the M2 phenotype via Erk/Akt/mTOR

Highlights: • PD-L1 treatment upregulates CD206 but not CD86 expression. • PD-L1-induced DEGs are related to the immune response, mitochondrial function, and metabolism. • Nivolumab, LY294002, U0126, and rapamycin inhibit the PD-L1-stimulated CD206 expression. • PD-L1 promotes M2 polarization via Erk/Akt/mTOR. PD-L1 (programmed death-ligand 1) is the ligand of PD-1 (programmed cell death protein 1) and regulates inhibitory immune responses. It is well known that PD-L1 suppresses T cell function via binding to PD-1. However, little is known about the role of the PD-1/PD-L1 axis in macrophage polarization. According to previous studies, the function of the PD-1/PD-L1 axis in macrophage polarization is controversial, and the underlying mechanism has not been fully elucidated. Thus, we treated THP-1-derived macrophages with human PD-L1 Fc to determine the role of the PD-1/PD-L1 axis in macrophage polarization. To further explore the mechanism, we performed RNA sequencing and used specific inhibitors to identify the implicated signalling pathways. In this study, we found that PD-L1 induces the upregulation of CD206 expression, which is inhibited by nivolumab, LY294002, U0126, and rapamycin. Evaluation of differentially expressed genes (DEGs) and bioinformatics analysis indicated that PD-L1 also induces the upregulation of the expression of genes that maintain mitochondrial function and mediate metabolic switching. In addition, we did not detect PD-L1-induced CD86 alterations, indicating that PD-L1 treatment has no significant influence on M1 polarization. Taken together, these results suggest that PD-L1 binds to PD-1 and promotes M2 polarization accompanied by mitochondrial function enhancement and metabolic reprogramming via Erk/Akt/mTOR. This study elucidates the role of PD-L1 in macrophage polarization and verifies the underlying mechanisms for the first time. Considering that aberrantly upregulated PD-L1 expression contributes to a wide variety of diseases, targeting PD-L1-mediated macrophage polarization is a prospective therapeutic strategy for both neoplastic and nonneoplastic diseases.

60 APPLIED LIFE SCIENCES↗

Distribution of Bound and Free Water in Anatomical Fractions of Pine Residues and Corn Stover as a Function of Biological Degradation

Biomass quality is influenced by water’s abundance, distribution, and status in relation to other chemical species within the polymer matrix. Water interacts with polymers that make up the cell walls, and these interactions govern the physical and chemical changes that occur during the storage and preprocessing of biomass feedstocks. Time-domain nuclear magnetic resonance (TD-NMR) was employed to explore variations in the physical constraints of water within the lignocellulosic microstructure in distinct anatomical fractions of biomass and as a function of biological degradation. The Carr–Purcell–Meiboom–Gill sequence, when combined with knowledge of the chemical composition and physical structure of pine residues and corn stover anatomical fractions, gives an accurate measurement of the bound and free water. In this work, the impacts of storage and biological degradation were investigated to elucidate changes in the status and distribution of water within distinct plant tissues. We also investigate how degradation during storage affects water interactions in different pine residues (e.g., bark, branch, and needle) and corn stover (e.g., cob, leaf, and stalk) anatomical fractions using transverse relaxation times (T2). As demonstrated herein, TD-NMR provides quantitative data on lignocellulosic biomass–water interactions within anatomical fractions, which can further aid in the investigation of preprocessing effects on feedstock quality. Our findings suggest that biological heating enhances biomass–water interactions at the cellular and macromolecular scale. In addition, analysis of three-dimensional scanning electron microscopy reconstructions indicates that surface roughness wavelengths align with microscale roughness, suggesting that pine forestry residue and corn stover particles have primarily hydrophobic exterior surfaces. Furthermore, this study offers multiscale insights into understanding the microstructure, wettability, and chemical environment that dictate diffusion, enzyme access, and recalcitrance of lignocellulosic biomass.

09 BIOMASS FUELS↗

Supernovae and their host galaxies – VII. The diversity of Type Ia supernova progenitors

ABSTRACT We present an analysis of the light curve (LC) decline rates (Δm15) of 407 normal and peculiar supernovae (SNe) Ia and global parameters of their host galaxies. As previously known, there is a significant correlation between the Δm15 of normal SNe Ia and global ages (morphologies, colours, and masses) of their hosts. On average, those normal SNe Ia that are in galaxies from the Red Sequence (early-type, massive, old hosts) have faster declining LCs in comparison with those from the Blue Cloud (late-type, less massive, younger hosts) of the colour–mass diagram. The observed correlations between the Δm15 of normal SNe Ia and hosts’ parameters appear to be due to the superposition of at least two distinct populations of faster and slower declining normal SNe Ia from older and younger stellar components. We show, for the first time, that the Δm15 of 91bg- and 91T-like SNe is independent of host morphology and colour. The distribution of hosts on the colour–mass diagram confirms the known tendency for 91bg-like SNe to occur in globally red/old galaxies, while 91T-like events prefer blue/younger hosts. On average, the youngest global ages of 02cx-like SNe hosts and their positions in the colour–mass diagram hint that these events likely originate from young population, but they differ from 91T-like events in the LC decline rate. Finally, we discuss the possible explosion channels and present our favoured SN Ia models that have the potential to explain the observed SN–host relations.

Hakobyan, A. A.↗

Redefining Resource Adequacy for Modern Power Systems: A Report of the Redefining Resource Adequacy Task Force

Today's rapidly increasing levels of wind, solar, storage, and load flexibility require the industry to rethink reliability planning and resource adequacy methods for modern power systems. Periods with a risk of shortfall often no longer coincide with peak demand - reliability risks are less about peak load and more about the daily setting of the sun, extended cloud cover, wind speeds, cold snaps, and heat waves. In addition, demand is increasingly flexible. Key resources are time-sensitive, as batteries need time to recharge and electricity customers can only be asked to provide demand response for just so long. And reliability failures are often correlated - with one another and with the weather. Two driving factors require the industry to reconsider its analytical approach for resource adequacy: (1) Chronological grid operations: The increasing importance of variable renewable resources (such as wind and solar) and of energy-limited resources (storage and demand response) make it essential to understand the full year of chronological operation of the grid. Specific attention must be paid to hourly, seasonal, and inter-annual resource variability. The sequence of the variability is key, as energy-limited resources such as batteries or demand response require either a preceding period or subsequent period of high production to be useful for grid reliability. (2) Correlated events: Historically, resource adequacy analysis focused on shortfalls caused by random, discrete mechanical failures of large generating units. In contrast, shortfalls today are often caused by multiple, correlated events caused by common weather patterns. Resource adequacy analysis must increasingly shift its focus to these correlated events. The redesign of resource adequacy methods will benefit from a set of guiding principles to better allow for sharing of insights and best practices, interregional resource coordination, and a smoother regulatory process for resource procurement. The objective of this report is to move this redesign forward. It provides an overview of key drivers changing the way resource adequacy needs to be evaluated, identifies shortcomings of conventional approaches, and outlines first principles for practitioners to consider as they adapt their approaches. The central message is: what got us here won't get us there.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding

Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. Here, the standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.

59 BASIC BIOLOGICAL SCIENCES↗

Numerical Optimization of Spray-Guided Spark Assistance for Cold Idle Operation in a Heavy-Duty Gasoline Compression Ignition Engine

This article describes the results of a response surface model (RSM)-based numerical optimization campaign for spray-guided spark assistance at cold operations in a heavy-duty gasoline compression ignition (GCI) engine. On the basis of an earlier work on spark-assisted GCI cold combustion, a space-filling design of experiments (DoE) method was first undertaken to investigate a multitude of hardware design variables and engine operating parameters. The main design variables included the number of injector nozzles, fuel split quantities and injection timings, and spark timing. The objective variables were engine combustion efficiency (ŋ c ), maximum pressure rise rate (MPRR), and engine-out nitrogen oxide (NO x ) emissions. A total of 150 design candidates were automatically generated using the Sobol sequence method provided by the commercial software package, CAESES. Then, closed-cycle computational fluid dynamic (CFD) spark-assisted GCI simulations under cold idling operations were performed. The outcomes from the CFD-DoE design campaign were utilized to construct high-fidelity RSMs that allowed for further design optimization of the spark plug- and fuel injector-related design variables, along with fuel injection strategy parameters. A merit function with respect to objective variables was formulated with an appropriate weight assignment on each objective variable. Finally, the best design candidate was identified from the RSM-based optimization process and further validated in the CFD analysis. The best design candidate showed the potential to significantly improve combustion efficiency (ŋ c > 90%) over the baseline at cold idle while satisfying MPRR and NOx emissions constraints (MPRR < 5 bar/CAD and NO x < 4.5 g/kWh).

33 ADVANCED PROPULSION SYSTEMS↗

How Good Is Your Location? Comparing and Understanding the Uncertainties in Location for the 1993 Rock Valley Sequence

Accurate event locations are important for many endeavors in seismology, and understanding the factors that contribute to uncertainties in those locations is complex. In this article, we present a case study that takes an in-depth look at the accuracy and precision possible for locating nine shallow earthquakes in the Rock Valley fault zone in southern Nevada. These events are targeted by the Rock Valley Direct Comparison phase of the Source Physics Experiment, as candidates for the colocation of a chemical explosion with an earthquake hypocenter to directly compare earthquake and explosion sources. For this comparison, it is necessary to determine earthquake hypocenters as accurately as possible so that different source types have nearly identical locations. Our investigations include uncertainty analysis from different sets of phase arrivals, stations, velocity models, and location algorithms. For a common set of phase arrivals and stations, we find that epicentral locations from different combinations of velocity models and algorithms are within 600 m of one another in most cases. Event depths exhibit greater uncertainties, but focusing on the S-P times at the nearest station allows for estimates within approximately 500 m.

58 GEOSCIENCES↗

Hard X-Ray to Radio Multiwavelength SED Analysis of Local U/LIRGs in the GOALS Sample with a Self-consistent AGN Model including a Polar-dust Component

We conduct hard X-ray to radio multiwavelength spectral energy distribution (SED) decomposition for 57 local luminous and ultraluminous infrared galaxies observed with the Nuclear Spectroscopic Telescope Array and/or Swift/Burst Alert Telescope in the GOALS sample. We modify the latest SED-fitting code X-CIGALE by implementing the infrared (IR) CLUMPY model, allowing us to conduct the multiwavelength study with the X-ray torus model XCLUMPY self-consistently. Adopting the torus parameters obtained by the X-ray fitting, we estimate the properties of the host galaxies, active galactic nucleus (AGN) tori, and polar dust. The star formation rates (SFRs) become larger with merger stage and most of them are above the main sequence. The SFRs are correlated with radio luminosity, indicating starburst emission is dominant in the radio band. Although polar-dust extinction is much smaller than torus extinction, the UV-to-IR (mainly IR) polar dust luminosities are ~2 times larger than the torus ones. The polar-dust temperature decreases while the physical size, estimated by the temperature and dust sublimation radius, increases with AGN luminosity from a few tens of parsec (early mergers) to kiloparsec scales (late mergers), where the polar dust likely comes from expanding (i.e., evolving) dusty outflows. A comparison between the SFRs and intrinsic AGN luminosities suggests that starbursts occur first and AGNs arise later, and overall their growth rates follow the simultaneous coevolution local galaxy–SMBH mass relation. We confirm the coexistence of intense starbursts, AGNs, and large-scale outflows in late mergers, supporting a standard AGN feedback scenario.

79 ASTRONOMY AND ASTROPHYSICS↗

The Delplot kinetic method applied to systems with adsorbates: Hydrodeoxygenation of benzofuran on a bimetallic CoPd phosphide catalyst supported on KUSY

The Delplot method provides a means of analyzing conversion and selectivity data to derive a reaction sequence and has been applied so far to gas-phase or liquid-phase species. This study analyses the applicability of the method for catalytic reactions and considers for the first time adsorbed intermediates. The method is applied to a contact time study of the hydrodeoxygenation (HDO) of benzofuran at 0.5 MPa and 350 °C over a catalyst consisting of bimetallic CoPd phosphide supported on a potassium ion-exchanged ultra-stable Y (KUSY) zeolite. Both simple and detailed reaction networks were derived. The simple networks considered only gas-phase species and were modeled by a first-order sequence of steps, whereas the detailed network took into account adsorbed intermediates and was simulated using a rake mechanism. The networks were compared using F-statistics, which accounted for the differences in the number of fitting parameters. The detailed network gave a better fit to the experimental data because it represented a more realistic description of the transformation. A suggested sequence from the Delplot method was consistent with the simple network but not with the detailed network. The lack of applicability of the Delplot analysis to the network with adsorbates was linked to overly large equilibrium constants, a determination supported by Delplot fitting for a model sequence. Further, this study indicated the inapplicability of the Delplot method in determining reaction sequences that involve adsorbed species with large equilibrium constants for formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autonomous adaptive data acquisition for scanning hyperspectral imaging

Non-invasive and label-free spectral microscopy (spectromicroscopy) techniques can provide quantitative biochemical information complementary to genomic sequencing, transcriptomic profiling, and proteomic analyses. However, spectromicroscopy techniques generate high-dimensional data; acquisition of a single spectral image can range from tens of minutes to hours, depending on the desired spatial resolution and the image size. This substantially limits the timescales of observable transient biological processes. To address this challenge and move spectromicroscopy towards efficient real-time spatiochemical imaging, we developed a grid-less autonomous adaptive sampling method. Our method substantially decreases image acquisition time while increasing sampling density in regions of steeper physico-chemical gradients. When implemented with scanning Fourier Transform infrared spectromicroscopy experiments, this grid-less adaptive sampling approach outperformed standard uniform grid sampling in a two-component chemical model system and in a complex biological sample, Caenorhabditis elegans. We quantitatively and qualitatively assess the efficiency of data acquisition using performance metrics and multivariate infrared spectral analysis, respectively.

47 OTHER INSTRUMENTATION↗

Mesh-Sequenced Realizations for Evaluation of Subgrid-Scale Models for Turbulent Combustion

This paper develops a new approach for analysis of subgrid closures for turbulent combustion as modeled using direct quadrature (finite-rate chemistry) techniques. The approach, termed multiresolution analysis through mesh-sequenced realizations (MRA-MSR), conducts simultaneous, constrained large-eddy simulations on a set of hierarchically coarsened meshes. Furthermore, the availability of underlying fine-mesh (subgrid) data corresponding to coarse-mesh locations allows a clearer assessment of the effects of unresolved fluctuations on apparent reactivity. A key to MRA-MSR is the correlation of eddy structures at coarser mesh levels, which is facilitated by the transfer of filtered fine-mesh velocity information. A seven-mesh MRA-MSR hierarchy using three resolution levels is applied to one of the Sydney bluff-body stabilized methane–hydrogen flames. Analysis of the simultaneously evolved data at different resolution levels reveals several interesting trends. First, at high Damköhler numbers, there is clear evidence of attenuation of apparent reactivity due to the effects of unresolved fluctuations. Secondly, single-point, single-time filtered density functions of a normalized subgrid Damköhler number show a characteristic beta probability density function (PDF) form and display evidence of scale similarity. Interrogation of the MRA-MSR database also shows that the recently-proposed least-squares minimization (LSM) turbulence–chemistry interaction model can account for the observed diminishment in reactivity at high Damköhler numbers but cannot reduce scatter significantly. A new form of the LSM model, which makes use of the normalized subgrid Damköhler number beta PDF distribution, performs slightly better than the original model, illustrating the potential of MRA-MSR both in assessing existing closure concepts and in developing new ones.

42 ENGINEERING↗

Characterization of Heparin’s Conformational Ensemble by Molecular Dynamics Simulations and Nuclear Magnetic Resonance Spectroscopy

Heparin is a highly charged, polysulfated polysaccharide and serves as an anticoagulant. Heparin binds to multiple proteins throughout the body, suggesting a large range of potential therapeutic applications. Although its function has been characterized in multiple physiological contexts, heparin’s solution conformational dynamics and structure–function relationships are not fully understood. Molecular dynamics (MD) simulations facilitate the analysis of a molecule’s underlying conformational ensemble, which then provides important information necessary for understanding structure–function relationships. However, for MD simulations to afford meaningful results, they must both provide adequate sampling and accurately represent the energy properties of a molecule. The aim of this study is to compare heparin’s conformational ensemble using two well-developed force fields for carbohydrates, known as GLYCAM06 and CHARMM36, using replica exchange molecular dynamics (REMD) simulations, and to validate these results with NMR experiments. In this work, the anticoagulant sequence, an ultra-low-molecular-weight heparin, known as Arixtra (fondaparinux, sodium), was simulated with both parameter sets. The results suggest that GLYCAM06 matches experimental nuclear magnetic resonance three-bond J-coupling values measured for Arixtra better than CHARMM36. In addition, NOESY and ROESY experiments suggest that Arixtra is very flexible in the sub-millisecond time scale and does not adopt a unique structure at 25 C. Moreover, GLYCAM06 affords a much more dynamic conformational ensemble for Arixtra than CHARMM36.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combined analysis of microbial metagenomic and metatranscriptomic sequencing data to assess in situ physiological conditions in the premature infant gut

Microbes alter their transcriptomic profiles in response to the environment. The physiological conditions experienced by a microbial community can thus be inferred using meta-transcriptomic sequencing by comparing transcription levels of specifically chosen genes. However, this analysis requires accurate reference genomes to identify the specific genes from which RNA reads originate. In addition, such an analysis should avoid biases in transcript counts related to differences in organism abundance. In this study we describe an approach to address these difficulties. Sample-specific meta-genomic assembled genomes (MAGs) were used as reference genomes to accurately identify the origin of RNA reads, and transcript ratios of genes with opposite transcription responses were compared to eliminate biases related to differences in organismal abundance, an approach hereafter named the “diametric ratio” method. We used this approach to probe the environmental conditions experienced by Escherichia spp. in the gut of 4 premature infants, 2 of whom developed necrotizing enterocolitis (NEC), a severe inflammatory intestinal disease. We analyzed twenty fecal samples taken from four premature infants (4–6 time points from each infant), and found significantly higher diametric ratios of genes associated with low oxygen levels in samples of infants later diagnosed with NEC than in samples without NEC. We also show this method can be used for examining other physiological conditions, such as exposure to nitric oxide and osmotic pressure. These study results should be treated with caution, due to the presence of confounding factors that might also distinguish between NEC and control infants. Nevertheless, together with benchmarking analyses, we show here that the diametric ratio approach can be applied for evaluating the physiological conditions experienced by microbes in situ. Results from similar studies can be further applied for designing diagnostic methods to detect NEC in its early developmental stages.

59 BASIC BIOLOGICAL SCIENCES↗

Phylodynamics of SARS-CoV-2 Lineages B.1.1.7, B.1.1.529 and B.1.617.2 in Nigeria Suggests Divergent Evolutionary Trajectories

Background: The early months of the COVID-19 pandemic were characterized by high transmission rates and mortality, compounded by the emergence of multiple SARS-CoV-2 lineages, including Variants of Concern (VOCs). This study investigates the phylodynamic and spatio-temporal trends of VOCs during the peak of the pandemic in Nigeria. Methods: Whole-genome sequencing (WGS) data from three major VOCs circulating in Nigeria, B.1.1.7 (Alpha), B.1.617.2 (Delta), and B.1.1.529 (Omicron), were analyzed using tools such as Nextclade, R Studio v 4.2.3, and BEAST X v 10.5.0. The spatial distribution, evolutionary history, viral ancestral introductions, and geographic dispersal patterns were characterized. Results: Three major lineages following WHO nomenclature were identified: Alpha, Delta, and Omicron. The Delta variant exhibited the widest geographic spread, detected in 14 states, while the Alpha variant was the least distributed, identified in only eight states but present across most epidemiological weeks studied. Evolutionary rates varied slightly, with Alpha exhibiting the slowest rate (2.66 × 10 −4 substitutions/site/year). Viral population analyses showed distinct patterns: Omicron sustained elevated population growth over time, while Delta declined after initial expansion. The earliest Times to Most Recent Common Ancestor (TMRCA) were consistent with the earliest outbreaks of SARS-CoV-2 globally. Geographic transmission analysis indicated a predominant coastal-to-inland spread for all variants, with Omicron showing the most diffuse dispersal, highlighting commercial routes as significant drivers of viral diffusion. Conclusion: The SARS-CoV-2 epidemic in Nigeria was characterized by multiple variant introductions and a dominant coastal-to-inland spread, emphasizing that despite lockdown measures, commercial trade routes played a critical role in viral dissemination. These findings provide insights into pandemic control strategies and future outbreak preparedness.

Nigeria↗

Comparative and pangenomic analysis of the genus Streptomyces

Abstract Streptomycetes are highly metabolically gifted bacteria with the abilities to produce bioproducts that have profound economic and societal importance. These bioproducts are produced by metabolic pathways including those for the biosynthesis of secondary metabolites and catabolism of plant biomass constituents. Advancements in genome sequencing technologies have revealed a wealth of untapped metabolic potential from Streptomyces genomes. Here, we report the largest Streptomyces pangenome generated by using 205 complete genomes. Metabolic potentials of the pangenome and individual genomes were analyzed, revealing degrees of conservation of individual metabolic pathways and strains potentially suitable for metabolic engineering. Of them, Streptomyces bingchenggensis was identified as a potent degrader of plant biomass. Polyketide, non-ribosomal peptide, and gamma-butyrolactone biosynthetic enzymes are primarily strain specific while ectoine and some terpene biosynthetic pathways are highly conserved. A large number of transcription factors associated with secondary metabolism are strain-specific while those controlling basic biological processes are highly conserved. Although the majority of genes involved in morphological development are highly conserved, there are strain-specific varieties which may contribute to fine tuning the timing of cellular differentiation. Overall, these results provide insights into the metabolic potential, regulation and physiology of streptomycetes, which will facilitate further exploitation of these important bacteria.

59 BASIC BIOLOGICAL SCIENCES↗

Enter the AHU (36th Chamber of ASHRAE): A Multi-site Field Study of ASHRAE G36

Despite being recognized as the best practice for advanced building controls, ASHRAE Guideline 36 (G36) has seen slow adoption in retrofit cases. Decisionmakers lack credible field evidence to justify the time and person-power investment. Most prior analyses have relied on software simulations, which overlook implementation challenges and fail to persuade owners to move from models to real-world deployment. This paper presents a multi-site field study of G36 performance, drawing on measured results from 17 projects across diverse building types and climate zones. The analysis disaggregates outcomes by the most widely adopted air handling unit (AHU) based G36 strategies, including trim-and-respond approaches to supply air temperature (SAT) and duct static pressure (DSP) reset, and economizer controls. Results for controls re programming implementations are encouraging, with HVAC savings ranging from 2% - 49%, with a median of 18%. The range aligns with simulation study findings showing 1% - 46% savings through these three strategies. These findings show that even without capital investment in control infrastructure upgrades, existing building owners are reaping significant benefits from updating HVAC sequences of operation to industry best-practice solutions. The results give practitioners and decisionmakers a reference point on what to expect, which strategies deliver, and how field performance may compare to simulation.

Deshpande, Reva↗

Cradle-to-Grave Lifecycle Analysis of U.S. Light-Duty Vehicle-Fuel Pathways: A Greenhouse Gas Emissions and Economic Assessment of Current (2020) and Future (2030-2035) Technologies

This study provides a comprehensive life cycle analysis (LCA), or cradle-to-grave (C2G) analysis, of the cost and greenhouse gas (GHG) emissions of a variety of vehicle-fuel pathways, the levelized cost of driving (LCD) and cost of avoided GHG emissions. The C2G analysis assesses light duty midsize sedans and small sport utility vehicles (SUVs) across a variety of vehicle-fuel technology pathways, including conventional internal combustion engine vehicles (ICEVs), flexible hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), battery electric vehicles (BEVs) with varying vehicle ranges, and fuel cell electric vehicles (FCEVs). Coming at a timely manner, given the marked increase, since 2016, in climate aspirations announced by governmental institutions and private firms both in the US and across the globe, this analysis builds on a previous comprehensive life cycle analysis, updating that study’s 2016 assumptions and methods (Elgowainy et al. 2016). These updates incorporate technological advances and changes in energy supply sources that have emerged during the intervening period. Utilizing these updated assumptions and methods, alongside more recent data, the present report accounts for a broader range of vehicle technologies and considers both current (2020) and expected future (2030-2035) conditions. Reflecting increased research interest in synthetic liquid fuels produced using renewable low-carbon electricity and CO 2 sources, electro-fuels (a.k.a. e-fuels) were added to the potential future fuel technologies that are evaluated. This study takes a “pathway” approach rather than a “scenario” approach; hence distinct, technically feasible, routes or sequences of processes starting with one or more feedstocks and ending with an intermediate or a final product are examined, not necessarily constrained by practical feedstock, economic, policy, and market considerations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Chromosome-level assembly and analysis of Camelina neglecta : a novel diploid model for Camelina biotechnology research

Camelina neglecta is a new diploid Brassicaceae species, which has great research value because of its close relationship with the hexaploid oilseed crop Camelina sativa. Here, we report a chromosome-level assembly of C. neglecta with a total length of 210 Mb. By adopting PacBio sequencing and Hi-C technology, the C. neglecta genome was assembled into 6 chromosomes with scaffold N50 of 29.62 Mb. C. neglecta has undergone the whole-genome triplication (γ) shared among eudicots and two whole-genome duplications (α and β) shared by crucifers, but it has not undergone a specific whole-genome duplication event. By synteny analysis between C. neglecta and C. sativa, we successfully used the method of calculating Ks to distinguish the three subgenomes of C. sativa and determined that C. neglecta was closest to the first subgenome (SG1) of C. sativa. Further, transcriptomic analysis revealed the key genes associated with seed oil biosynthesis and its transcriptional regulation, including SAD, FAD2, FAD3, FAE1, ABI3, WRI1 and FUS3 displaying high expression levels in C. neglecta seeds. The high representability of C. neglecta as a model species for Camelina-based biotechnology research has been demonstrated for the first time. In particular, floral Agrobacterium tumefaciens infiltration-based transformation of C. neglecta, leading to overexpression of CvLPAT2, CpDGAT1 and CvFatB1 transgenes, was demonstrated for medium-chain fatty acid accumulation in C. neglecta seed oil. This study provides an important genomic resource and establishes C. neglecta as a new model for oilseed biotechnology research.

60 APPLIED LIFE SCIENCES↗