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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Health and air pollutant emission impacts of net zero CO2 by 2050 scenarios from the energy modeling forum 37 study

Carbon dioxide and non-greenhouse gas air pollutants are emitted from many of the same sources. Decarbonization actions thus typically yield air pollutant emission reductions, resulting in significant air quality benefits. Although several studies have highlighted this connection, including in the context of net zero carbon emission targets, substantial uncertainty remains regarding how alternative technological pathways to this goal will affect the spatial distribution and magnitude of air pollutants. Comprehensive multi-model and multi-scenario analyzes are needed to explore the relative impacts of alternative pathways. Here, our study begins to address this gap by leveraging the results from the recent Energy Modeling Forum 37 inter-model comparison exercise on U.S. decarbonization pathways. Comparing the results of the six teams who submitted air pollutant emissions suggests that strategies that target net zero U.S. carbon emissions would yield significant reductions in many air pollutants, and that this finding is generally robust across pathways. However, some energy sources, such as biomass and fossil fuels with carbon capture, will emit air pollutants and can potentially influence the magnitude, spatial distribution, and even sign of localized air pollutant emission changes. In the second part of this analysis, a simplified air quality and health impacts screening model is used to evaluate the air quality impacts in 2035 of sectoral emission changes from the three models that provided sectoral detail. Relative to a reference scenario, a net zero pathway is estimated to reduce fine particulate matter concentrations across the contiguous U.S., with health benefits from reduced mortality ranging from $\$$65 billion to $\$$250 billion in 2035 alone (2023$\$$s). These benefits would be expected to grow over time as the net zero trajectory becomes more stringent. Both the magnitude of potential benefits and the substantial variation of the projections across models underscore the need for an EMF-like inter-model comparison exercise focused on air quality.

Air pollutants↗
DOE OSTI2023

Structure-guided design of direct-acting antivirals that exploit the gem-dimethyl effect and potently inhibit 3CL proteases of severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) and middle east respiratory syndrome coronavirus (MERS-CoV)

The high morbidity and mortality associated with SARS-CoV-2 infection, the etiological agent of COVID-19, has had a major impact on global public health. Significant progress has been made in the development of an array of vaccines and biologics, however, the emergence of SARS-CoV-2 variants and breakthrough infections are an ongoing major concern. Furthermore, there is an existing paucity of small-molecule host and virus-directed therapeutics and prophylactics that can be used to counter the spread of SARS-CoV-2, and any emerging and re-emerging coronaviruses. Here, we describe herein our efforts to address this urgent need by focusing on the structure-guided design of potent broad-spectrum inhibitors of SARS-CoV-2 3C-like protease (3CL pro or Main protease), an enzyme essential for viral replication. The inhibitors exploit the directional effects associated with the presence of a gem-dimethyl group that allow the inhibitors to optimally interact with the S4 subsite of the enzyme. Several compounds were found to potently inhibit SARS-CoV-2 and MERS-CoV 3CL proteases in biochemical and cell-based assays. Specifically, the EC50 values of aldehyde 1c and its corresponding bisulfite adduct 1d against SARS-CoV-2 were found to be 12 and 10 nM, respectively, and their CC50 values were >50 μM. Furthermore, deuteration of these compounds yielded compounds 2c/2d with EC50 values 11 and 12 nM, respectively. Replacement of the aldehyde warhead with a nitrile (CN) or an α-ketoamide warhead or its corresponding bisulfite adduct yielded compounds 1g, 1e and 1f with EC50 values 60, 50 and 70 nM, respectively. High-resolution cocrystal structures have identified the structural determinants associated with the binding of the inhibitors to the active site of the enzyme and, furthermore, have illuminated the mechanism of action of the inhibitors. Overall, the high Safety Index (SI) (SI=CC50/EC50) displayed by these compounds suggests that they are well-suited to conducting further preclinical studies.

3-Chymotrypsin-like protease (3CLpro)↗
DOE OSTI2025

High-performance windows improve thermal survivability of occupants during cold snaps

Exposure to low indoor air temperature is a major contributor to temperature-related mortality during extreme cold events, especially when power outages disrupt operation of space heating systems. This study explores the impact of high-performance windows on the thermal resilience of residential buildings during extreme cold weather and grid power outages, as well as their long-term benefits through energy efficiency and reduced risk of property damage. Building performance simulations were conducted for reference residential buildings in three construction vintages and two major U.S. cities located in cold climate zones, considering two types of extreme cold events: short and severe, and long and milder. Our research found that even houses compliant with current energy codes struggle to maintain safe indoor temperatures for more than a few hours during power outages, necessitating rapid evacuations. High-performance windows can extend the thermal survivability time by up to 3.8 days within a 7-day cold snap and significantly reduce risk of bursting frozen water pipes, depending on the building’s insulation and infiltration level, cold event severity, and occupant vulnerability. This extended thermal safety time is crucial in scenarios where reduced mobility complicates emergency responses in senior housing. In addition to boosting thermal resilience, upgrading older homes with high-performance windows can reduce heating energy consumption by over 18% and cooling energy by 15%. Our findings highlight the need to incorporate thermal resilience assessments into new designs or major retrofits, including the use of typical and extreme weather scenarios and advanced technologies like high-performance windows.

Krelling, Amanda F↗
DOE OSTI2020

The direct and indirect effects of copper on vector-borne disease dynamics

Metal pollution is a growing concern that affects the health of humans and animals globally. Copper is an essential insect micronutrient required for respiration, pigmentation and oxidative stress protection but can also act as a potentially toxic trace element. While several studies have focused on the negative fitness effects of copper on the aquatic larvae of mosquitoes, the effects of larval copper exposure on adult mosquito fitness (i.e., survival and fecundity) and their ability to transmit parasites (i.e., vector competence) remains unclear. Here, using a well-studied model vector-parasite system, the mosquito Aedes aegypti and parasite Dirofilaria immitis, we show that sublethal copper exposure in larval mosquitoes alters adult female fecundity and vector competence. Specifically, mosquitoes exposed to copper had a hormetic fecundity response and mosquitoes exposed to 600 μg/L of copper had significantly fewer infective parasite larvae than control mosquitoes not exposed to copper. Therefore, exposure of mosquito larvae to copper levels far below EPA-mandated safe drinking water limits (1300 μg/L) can impact vector-borne disease dynamics not only by reducing mosquito abundance (through increased larval mortality), but also by reducing parasite transmission risk. Our results also demonstrated that larval copper is retained through metamorphosis to adulthood in mosquitoes, indicating that these insects could transfer copper from aquatic to terrestrial foodwebs, especially in urban areas where they are abundant. To our knowledge this is the first study to directly link metal exposure with vector competence (i.e., ability to transmit parasites) in any vector-parasite system. Additionally, it also demonstrates unequivocally that mosquitoes can transfer contaminants from aquatic to terrestrial ecosystems. These results have broad implications for public health because they directly linking contaminants and vector-borne disease dynamics, as well as linking mosquitoes and contaminant dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Community vulnerability is the key determinant of diverse energy burdens in the United States

Low-income households generally experience a high energy burden; however, the factors influencing energy burdens are beyond socio-economics. This study explores the relationships between the multidimensionality of community vulnerability factors and energy burden across multiple geospatial levels in the United States. Our study found the distribution of energy burden in 2020 showed a great deal of variety, ranging from a minimum of 2.93 % to a maximum of 30.45 % across 3142 counties. The results of non-spatial and spatial regressions showed that the vulnerability ranks of socioeconomic, household composition and disability, minority and language, household type and transportation, and COVID mortality rate are significant predictors of energy burdens at the national level. However, at the regional level, only socioeconomic, minority and language significantly influence energy burdens. Minority and language negatively impact energy burdens except for the South East-Central region. Additionally, our analyses highlight the need to consider community vulnerability indicators' spatial homogeneity and heterogeneity. At the national level, only the epidemiological factors index is a spatially homogeneous predictor; on the regional and state level, the spatially homogeneous predictors such as socioeconomic status, household composition and disability, and household type and transportation vary by region. Such a region-sensitive relationship between energy burden and the predictors indicates spatial heterogeneity. Here this study suggests policy recommendations through the lens of the multidimensionality of community vulnerability factors. Implementing flexible national energy policies while making particular energy assistance policies for the vulnerable population at the regional or state levels is essential.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Long-term effects of thinning and woody control on longleaf pine plantation development, understory abundance, and tree damage from an ice storm

Longleaf pine (Pinus palustris) plantations have been established across the southeastern United States as the first step in restoring the declining savanna ecosystem, yet their long-term stability and development to open canopied woodlands may depend on early density and vegetation management treatments. Commercial thinning (CT) was applied in 2012 (year 18) to a long-term study of longleaf pine community restoration at the Savannah River Site near Aiken, SC to increase abundance of herb species. Although precommercial thinning (PCT) and woody vegetation control increased herb species cover during the first five years of the study, measurements from years 17 to 22 indicated a continuing decline in their cover since year 9 despite application of CT in year 18. Herb species richness, however, increased from 21 to 43 species per 100 m2 area during the last six years of the study, likely a result of disturbances associated with CT and an ice storm in year 20. Application of PCT in 1994, when the plantations were 8–11 years old, reduced their susceptibility to stem bending and breakage from the ice storm, which occurred 20 years later in 2014. Measured 5 months before the storm, pine height: dbh ratio (HD) averaged 78 and 90 for trees growing with and without PCT, respectively, and stem breakage (% of trees) from the ice storm increased linearly (r2 = 0.53) with HD. Pine mortality from the combined effects of glaze ice and wind differed with (28%) versus without (45%) PCT, indicating that long-term stability of longleaf pine plantations depends on early density management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Drivers and ecological impacts of a wildfire outbreak in the southern Appalachian Mountains after decades of fire exclusion

During one of the warmest and driest droughts of the last century, the southern Appalachian Mountains experienced a regional outbreak of over a dozen large wildfires in late fall of 2016. We provide a synthesis of long-term forest changes leading up to the 2016 wildfires, examine the climatic setting and patterns of burn severity in relationship to topography, and discuss the ecological and management implications of these and future fires. During the pre- and post-European settlement periods, frequent low- and mixed-severity wildfires interacted with complex topographic gradients and maintained heterogenous landscapes dominated by several species of oak (Quercus spp.), pine (Pinus spp.), and the American chestnut (Castanea dentata). Land-use changes associated with European settlement, loss of the American chestnut, and 20th century fire exclusion resulted in large scale shifts towards mesic, fire-intolerant species (i.e. mesophication). Wildfire activity began increasing in the early 1980s, but most fires in the region are small (<1,000 ha). In Fall of 2016, deciduous tree leaf fall occurred concurrently with a period of anomalously dry and warm weather, creating ideal conditions for fire ignition and spread. Thousands of ignitions across the region strained suppression resources and eight fires grew to greater than 5,000 ha. The 2016 fires were larger and burned more area than in the previous three decades combined. In one unique landscape setting, the Chimney Tops 2 Fire, a synoptic wind event drove extreme fire behavior and burned large, high-severity patches resulting in devastating effects in the wildland urban interface. However, immediate post-fire burn severity mosaics for other fires were composed primarily of low- (73 %) and moderate-severity (21 %) fire effects. High-severity fire comprised only 6 % of the area burned, and occurred mostly on steep upper slopes and ridges on south-facing aspects, reflecting the importance of bottom-up topographic drivers in this region. Although the fires will likely enhance biodiversity by restoring fire-dependent species and creating early seral habitat, invasions of non-native plant species, delayed mortality of mature pines and oaks, and rapid re-sprouting of pyrophyllic shrubs pose significant management challenges. Although similar large fire outbreaks may become more common under future climatic conditions, they are unlikely to reverse the effects of mesophication and significantly alter forest dynamics at broad spatial scales. Furthermore, the 2016 fires exposed the vulnerability of the region to wildfire during acute fall drought and demonstrate the potential ecological effects of future wildfires in mixed pine-hardwood landscapes of the southern Appalachians.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Salinity exposure affects lower-canopy specific leaf area of upland trees in a coastal deciduous forest

Sea level rise and increasing storm surges are likely to affect the canopy physiology, ecology, and structure of coastal forests, even well in advance of tree mortality. Laboratory and greenhouse studies have documented that saltwater exposure can trigger changes in leaf-level physiology and morphology, but few in situ studies have examined how tree-specific leaf area (SLA), the ratio of leaf area to mass and a crucial trait and model parameter, is affected by saline soils. We conducted an observational study of SLA in a mid-Atlantic (USA) coastal deciduous forest, taking advantage of a natural gradient in salinity along a tidal creek. Measured SLA of the 239 trees and seven species sampled ranged from Carya glabra (N = 6 trees, mean SLA = 277.9±36.3cm 2 /g) to Fagus grandifolia (N=60, 321.9±62.9cm 2 g); as expected, trees species and canopy position (sun versus shade) significantly affected SLA. For trees (N=100) directly exposed to the tidal creek, salinity was highly significant after accounting for species (P<0.001), with trees in the lower reaches of the creek having lower SLA. Leaf area index (LAI), computed from SLA and litter traps, ranged from 4.8 to 15.8 and was inversely related to salinity exposure; the spatial variability in leaf litter production contributed much more to LAI uncertainty than did SLA variability. These in situ results are correlative but consistent with the hypothesis, based on previous greenhouse studies, that the stress of chronic salinity exposure changes species’ leaf morphology. Our findings are useful for understanding the growing effects of saltwater intrusion into upland forests, as well as parameterizing and testing ecosystem-scale models simulating forest stressors and disturbances at the terrestrial-aquatic interface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Effects of head-starting on multi-year space use and survival of an at-risk tortoise

A major challenge in the recovery of long-lived at-risk taxa like turtles is low juvenile recruitment. Head-starting—the raising of juveniles to larger sizes to improve survival—is one tool that can be used in circumstances where juvenile recruitment is limited. Due to declining populations and difficulty detecting juveniles, however, lack of knowledge of the ecology of juveniles can hinder efforts to develop and evaluate head-starting programs for many turtle species. We sought to inform recovery efforts of Mojave desert tortoises by quantifying multi-year space use and survival of head-started juveniles after release. We radio-tracked tortoises head-started under three different husbandry treatments that varied in rearing duration (from two to over six years) and whether head-starting included an indoor rearing component the first year. We compared postrelease space use and survival as a function of treatment, release size, and time since release. We found that space use, including home range size and site fidelity, varied by husbandry treatment, with smaller and younger tortoises having smaller home ranges and higher site fidelity. Additionally, home range size decreased and site fidelity increased with time since release across treatments. Tortoises with an indoor-rearing component experiencing increased risk of mortality as movement increased compared to tortoises reared solely outdoors. Nevertheless, survival did not differ among treatments or with tortoise age or size. Regardless of husbandry treatment, head-started tortoises exhibited similar space-use and survival overall. Our study provides insight into juvenile tortoise behavior and head-starting as a tool for tortoise conservation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Interplay between liver and blood stages of Plasmodium infection dictates malaria severity via γδ T cells and IL-17-promoted stress erythropoiesis

Plasmodium replicates within the liver prior to reaching the bloodstream and infecting red blood cells. Because clinical manifestations of malaria only arise during the blood stage of infection, a perception exists that liver infection does not impact disease pathology. By developing a murine model where the liver and blood stages of infection are uncoupled, we showed that the integration of signals from both stages dictated mortality outcomes. This dichotomy relied on liver stage-dependent activation of Vγ4 + γδ T cells. Subsequent blood stage parasite loads dictated their cytokine profiles, where low parasite loads preferentially expanded IL-17-producing γδ T cells. IL-17 drove extra-medullary erythropoiesis and concomitant reticulocytosis, which protected mice from lethal experimental cerebral malaria (ECM). Adoptive transfer of erythroid precursors could rescue mice from ECM. Modeling of γδ T cell dynamics suggests that this protective mechanism may be key for the establishment of naturally acquired malaria immunity among frequently exposed individuals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

From Tg O/GABA-AT, GABA, and T-263 Mutant to Conception of Toxoplasma

Toxoplasma gondii causes morbidity, mortality, and disseminates widely via cat sexual stages. Here, we find T. gondii ornithine aminotransferase (OAT) is conserved across phyla. We solve TgO/GABA-AT structures with bound inactivators at 1.55 Å and identify an inactivator selective for TgO/GABA-AT over human OAT and GABA-AT. However, abrogating TgO/GABA-AT genetically does not diminish replication, virulence, cyst-formation, or eliminate cat’s oocyst shedding. Increased sporozoite/merozoite TgO/GABA-AT expression led to our study of a mutagenized clone with oocyst formation blocked, arresting after forming male and female gametes, with “Rosetta stone”-like mutations in genes expressed in merozoites. Mutations are similar to those in organisms from plants to mammals, causing defects in conception and zygote formation, affecting merozoite capacitation, pH/ionicity/sodium-GABA concentrations, drawing attention to cyclic AMP/PKA, and genes enhancing energy or substrate formation in TgO/GABA-AT-related-pathways. These candidates potentially influence merozoite’s capacity to make gametes that fuse to become zygotes, thereby contaminating environments and causing disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Unsupervised probabilistic models for sequential Electronic Health Records

We develop an unsupervised probabilistic model for heterogeneous Electronic Health Record (EHR) data. Utilizing a mixture model formulation, our approach directly models sequences of arbitrary length, such as medications and laboratory results. This allows for subgrouping and incorporation of the dynamics underlying heterogeneous data types. The model consists of a layered set of latent variables that encode underlying structure in the data. These variables represent subject subgroups at the top layer, and unobserved states for sequences in the second layer. We train this model on episodic data from subjects receiving medical care in the Kaiser Permanente Northern California integrated healthcare delivery system. The resulting properties of the trained model generate novel insight from these complex and multifaceted data. In addition, we show how the model can be used to analyze sequences that contribute to assessment of mortality likelihood.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

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↗
DOE OSTI2025

Substituent size versus metal binding of inhibitors with variants of influenza endonuclease

The influenza virus causes a significant burden of illness each year. Although vaccination is the most effective method to prevent seasonal influenza infection, viral escape mechanisms make vaccine composition difficult to predict. Antivirals are crucial for decreasing rates of morbidity and mortality from influenza viral infection. The newest anti-influenza drugs target the RNA-dependent RNA polymerase acidic N-terminal (PA N ) endonuclease, a critical component of influenza viral replication machinery. This study examines the structure of inhibitors of PAN that utilize a hydroxypyridinone-based metal-binding pharmacophore (MBP). Specifically, this report explores how the size of substituent groups impacts the binding conformation and affinity of a series of compounds against both wild-type (WT) and resistance mutant strains, I38T and E23K. Co-crystal structures revealed that the distance between compounds and enzyme residue 38 was conserved to maintain strong interactions, resulting in deviations from ideal coordination geometries at the active site metal centers. This suggests the interactions with residue 38 with each compound is important and can impact inhibitor potency as a consequence of distortions in the metal binding geometry of the compounds.

Endonuclease↗
DOE OSTI2022

Computational studies of hydraulic stressors for biological performance assessment in a hydropower plant with Kaplan turbine

We report Hydropower is currently one of the preeminent sources of renewable energy in the United States and globally. Hydropower plants also have detrimental impacts on the environment and ecology, including direct impacts to anadromous fish populations. The computational fluid dynamics (CFD) – based Biological Performance Assessment (BioPA) toolset is used for biological evaluations of fish passage through hydropower plants. The hydraulic environment of a hydropower plant was evaluated using CFD coupled with discrete element method (DEM) simulations. The predicted flow field and particle collision rate were validated against the experimental data in a water flume that has an idealized hydroturbine distributor geometry. Flow simulations were conducted to evaluate the hydraulic stressors, such as nadir pressure, fluid shear, runner collision, in a physical scale in a hydropower plant with Kaplan turbine which are responsible for injury and mortality of fish in a downstream migration. The cumulative exposure probability for the nadir pressure and collision with turbine runner was found to decrease with increased discharge rate. The lowest discharge rate shows the higher value of cumulative shear exposure probability. The maximum value of collision velocity increases with increased discharge rate. We offer the conclusions that will help in understanding various hydraulic stressors for biological assessment for environmentally sustainable hydroturbine passage.

13 HYDRO ENERGY↗
DOE OSTI2025

Velocity- and pressure-based metrics for estimating strike injuries during fish passage through hydro turbines

Hydropower is a crucial source of clean and reliable energy worldwide, and its importance will continue to grow. To enhance the environmental sustainability of hydropower development and operations, it is essential to predict the strike injury rates of fish passing through turbines accurately and cost-effectively. However, conventional experiments involving a large number of live fish are still commonly conducted in practice, and previous attempts mainly focused on the dose-response relationships at an individual level or relative comparisons of biological characterization between different conditions. Thus, this study proposes two novel strike metrics based on velocity and pressure (M V and M P ) measured by the cutting-edge Sensor Fish (SF) technology, designed to quantify the biological effects of strikes and collisions between fish and rigid hydraulic structures. SF measurements and 48-hour survival rates of live fish from a study conducted at the Ice Harbor Dam on the Snake River were used to establish thresholds for the two proposed metrics. These metrics and thresholds were then applied to three additional SF studies conducted at hydropower facilities featuring Kaplan turbines within the Columbia River basin. Results from the application of the strike metrics indicate that the estimated survival rates derived from both metrics agree well with previously reported live fish survival rates. Furthermore, the study identified specific passage regions with elevated risks of fish mortality due to strikes and collisions. Overall, the proposed strike metrics present a reliable and cost-effective approach to reducing reliance on live fish and lowering costs in fish passage studies.

Biological characterization↗
DOE OSTI2022

A phenology- and trend-based approach for accurate mapping of sea-level driven coastal forest retreat

The rapid replacement of upland forest by encroaching marshland is a striking manifestation of global sea-level rise (SLR). Timely and high-resolution information on the location and extent of transition forest (the ecotone between upland forest and marsh where tree mortality due to seawater intrusion begins) is fundamental to understanding the processes and patterns of SLR-driven landscape reorganization. Despite its significance, accurate characterization of salt-impacted transition forest remains challenging due to the complexity of coastal environments, scarcity of ground-truth data, and the lack of effective mapping algorithms. Here we use the full archive of Landsat images between 1984 and 2021 to investigate the spectral, temporal, and phenological characteristics of transition forest, and develop a robust framework for monitoring coastal vegetation shifts in the mid-Atlantic U.S., a global SLR hotspot. Here, we found that transition forest exhibits strong negative NDVI trends and a deviation of land surface phenology from marsh and upland forest that distinguishes itself from surrounding vegetation. By integrating temporal trends and land surface phenology, our results demonstrate superior discrimination between marsh and coastal forests to existing map products (e.g. NOAA Coastal Change Analysis Program, National Land Cover Database) that allows a reliable identification of the coastal treeline. We applied the approach to map regional land cover in 1985, 2000 and 2020 (overall classification accuracy >92%) and found that the area of coastal forest decreased by 22.0% from 1985 to 2020, the majority of which transitioned to marshland (92.3%, 5.3 × 10 3 ha). Based upon fine-scale patterns of coastal transgression, we created a practical workflow for spatially explicit quantification of forest retreat rates. Concurrent with rising sea level, coastal forests migrated upslope from 0.63 (± 0.27) m above sea level in 1985 to 0.78 (± 0.32) m above sea level in 2020, and horizontal forest retreat rates accelerated from 3.1 (range of 0–36) m yr -1 during 1985–2000 to 4.7 (0–55) m yr -1 during 2001–2020. As SLR continues to accelerate, our study may serve as a scalable solution for consistent tracking of coastal landscape evolution that is urgently needed for sustainable forest and wetland management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Protein data bank: From two epidemics to the global pandemic to mRNA vaccines and Paxlovid

Structural biologists and the open-access Protein Data Bank (PDB) played decisive roles in combating the COVID-19 pandemic. Global biostructure data were turned into global knowledge, allowing scientists and engineers to understand the inner workings of coronaviruses and develop effective countermeasures. Two mRNA vaccines, initially designed with guidance from PDB structures of the SARS-CoV-1 and MERS-CoV spike proteins, prevented infections entirely or reduced the likelihood of morbidity and mortality for more than five billion individual recipients worldwide. Structure-guided drug discovery by Pfizer, Inc (facilitated by PDB structures), initiated in the 2000s in response to SARS-CoV-1 and resumed in 2020, yielded nirmatrelvir (the active ingredient of Paxlovid) -- a potent, orally-bioavailable inhibitor of the SARS-CoV-2 main protease. You've got to love the Protein Data Bank!

Burley, Stephen K.↗