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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian mixture models

This study evaluates the effect of complete nationwide lockdown in 2020 on residential electricity demand across 13 Indian cities and the role of digitalisation using a public smart meter dataset. We undertake a data-driven approach to explore the energy impacts of work-from-home norms across five dwelling typologies. Our methodology includes climate correction, dimensionality reduction and machine learning-based clustering using Gaussian Mixture Models of daily load curves. Results show that during the lockdown, maximum daily peak demand increased by 150-200% as compared to 2018 and 2019 levels for one room-units (RM1), one bedroom-units (BR1) and two bedroom-units (BR2) which are typical for low- and middle-income families. While the upper-middle- and higher-income dwelling units (i.e., three (3BR) and more-than-three bedroom-units (M3BR)) saw night-time demand rise by almost 44% in 2020, as compared to 2018 and 2019 levels. Our results also showed that new peak demand emerged for the lockdown period for RM1, BR1 and BR2 dwelling typologies. We found that the lack of supporting socioeconomic and climatic data can restrict a comprehensive analysis of demand shocks using similar public datasets, which informed policy implications for India's digitalisation. We further emphasised improving the data quality and reliability for effective data-centric policymaking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Physics-guided machine learning for improved accuracy of the National Solar Radiation Database

The National Solar Radiation Database (NSRDB) provides high-resolution spatiotemporal solar irradiance data for the entire globe. The NSRDB uses a two-step Physical Solar Model (PSM) to compute the effects of clouds and other atmospheric variables on the solar radiation reaching the surface of the Earth. Physical and optical cloud properties are fundamental inputs to the PSM and are derived from the National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellites. This paper describes recent improvements to the NSRDB driven by physics-guided machine learning methods for cloud property retrieval. The impacts of these new methods on the NSRDB irradiance data are validated using an extensive set of ground measurement sites, showing significant improvement for all sites. We report on average, the mean absolute percentage error for global horizontal irradiance and direct normal irradiance show reductions of 2.16 and 3.95 percentage points respectively for all daylight conditions, 5.92 and 17.39 percentage points respectively for cloudy conditions, and 9.00 and 22.59 percentage points respectively for gap-filled cloudy conditions. These new methods will help improve the quality and accuracy of the irradiance and cloud data in the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2025

Validation of the DESI DR2 measurements of baryon acoustic oscillations from galaxies and quasars

The Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) galaxy and quasar clustering data represents a significant expansion of data from Data Release 1 (DR1), providing improved statistical precision in baryon acoustic oscillation (BAO) constraints across multiple tracers, including bright galaxies, luminous red galaxies, emission line galaxies, and quasars. In this paper, we validate the BAO analysis of DR2. We present the results of robustness tests on the blinded DR2 data and, after unblinding, consistency checks on the unblinded DR2 data. All results are compared with those obtained from a suite of mock catalogs that replicate the selection and clustering properties of the DR2 sample. We confirm the consistency of DR2 BAO measurements with DR1 while achieving a reduction in statistical uncertainties due to the increased survey volume and completeness. The combined BAO precision, including both statistical and systematic errors, improves from ∼0.52% in DR1 to 0.30% in DR2—a factor of 1.7 gain. We assess the impact of analysis choices, including different data vectors (correlation function vs power spectrum), modeling approaches and systematics treatments, and an assumption of the Gaussian likelihood, finding that our BAO constraints are stable across these variations and assumptions with a few minor refinements to the baseline setup of the DR1 BAO analysis. We summarize a series of pre-unblinding tests that confirmed the readiness of our analysis pipeline, the final systematic errors, and the DR2 BAO analysis baseline. The successful completion of these tests led to the unblinding of the DR2 BAO measurements, ultimately leading to the DESI DR2 cosmological analysis, with their implications for the expansion history of the Universe and the nature of dark energy presented in the DESI key paper (companion paper).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Fertilizer management for global ammonia emission reduction

Crop production is a large source of atmospheric ammonia (NH 3 ), which poses risks to air quality, human health and ecosystems. However, estimating global NH 3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy. In this report we develop a machine learning model for generating crop-specific and spatially explicit NH 3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH 3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr -1 , lower than previous estimates that did not fully consider fertilizer management practices. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3 emissions by about 38% (1.6 ± 0.4 Tg N yr -1 ) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH3 emissions reductions of 47% (44–56%) for rice, 27% (24–28%) for maize and 26% (20–28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH3 emissions could increase by 4.0 ± 2.7% under SSP1–2.6 and 5.5 ± 5.7% under SSP5–8.5 by 2030–2060. However, targeted fertilizer management has the potential to mitigate these increases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Updates to the Regional Seismic Travel Time (RSTT) Model: 1. Tomography

Abstract A function of global monitoring of nuclear explosions is the development of Earth models for predicting seismic travel times for more accurate calculation of event locations. Most monitoring agencies rely on fast, distance-dependent one-dimensional (1D) Earth models to calculate seismic event locations quickly and in near real-time. RSTT (Regional Seismic Travel Time) is a seismic velocity model and computer software package that captures the major effects of three-dimensional crust and upper mantle structure on regional seismic travel times, while still allowing for fast prediction speed (milliseconds). We describe updates to the RSTT model using a refined data set of regional phases (i.e., Pn, Pg, Sn, Lg) using the Bayesloc relative relocation algorithm. The tomographic inversion shown here acts to refine the previous RSTT public model ( rstt201404um ) and displays significant features related to areas of global tectonic complexity as well as further reduction in arrival residual values. Validation of the updated RSTT model demonstrates significant reduction in median epicenter mislocation (15.3 km) using all regional phases compared to the iasp91 1D model (22.1 km) as well as to the current station correction approach used at the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (18.9 km).

58 GEOSCIENCES↗
DOE OSTI2020

Opportunities for Using the Industrial Assessment Center Database for Industrial Water Use Analysis

The manufacturing sector accounted for approximately 5–6% of total U.S. water use in 2015. Of that amount, 75–80% is self supplied withdrawal from surface-water and groundwater sources and the remainder is from public water supplies. Although manufacturing facilities commonly locate in water-scarce areas, water scarcity still poses a great risk to the manufacturing sector. Reliable water is necessary for any facility that relies on it for process and comfort cooling, cleaning, employee use, and steam generation. One of these barriers to water efficiency is the lack of reliable data on overall U.S. industrial water use—how it is used and the quantities required for each sector. If a facility cannot be easily compared with a facility of similar size and sector, knowing if it is effectively using water conservation best practices is difficult. One potential source of industrial water use data is the U.S. Department of Energy (DOE)–sponsored Industrial Assessment Centers (IACs). IACs are university-based organizations that provide free audits to small- and medium-sized manufacturing facilities to identify productivity improvement and waste and energy reduction opportunities. The IACs also maintain a database of all the audits conducted, which currently holds more than 19,267 assessments and 145,000 recommendations (as of July 24, 2020). This database also contains energy utility (electricity, natural gas, and other fuels) and water utility data, making it a potential data source for industrial water use. This report attempts to create regression models to predict a small- or medium-sized industrial facility’s annual water use or cost based on its industrial subsector and several possible relevant variables. Using data collected by IAC assessments, models for several industrial subsectors were generated via stepwise regression techniques to determine which variables (annual sales, number of employees, facility/plant area, annual production hours, and a water stress metric) are relevant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Cell-free bioelectrocatalytic platform for carbon dioxide reduction (Final Technical Report)

The University of Minnesota (UMN) EcoSynBio Team aimed to develop a cell-free, enzyme-based platform for the electro- biocatalytic conversion of CO2 into formate as a platform chemical for further upgrading. This type of bio electrocatalytic process delivers a clean product stream without the need for extensive separation from the electrolyte as in electrochemical synthesis and microbial processes. The reduction reaction is catalyzed by metal-dependent formate dehydrogenases (mFDHs) that are capable of efficient electrocatalytic CO2 reduction without the need of costly co-factors. The development of an efficient, scalable electrobiocatalytic process with high total turnover numbers and viable space time yields, however, was not without its challenges. The UM team has developed a protein-based scaffolding system that facilitates enzyme stabilization and attachment to electrodes along with electron transfer. Yet, although FDHs are highly promising enzymes for cell-free, electrobiochemical CO2 reduction, they are also greatly understudied and especially for applications in electrocatalysis. The UM team used the best described mFDH from Clostridium as its benchmark system and spent significant time and effort in attempting to replicate published data and finally, redesigned a recombinant production system for proper metal co-factor incorporation. The UM team has also identified a small set of new enzyme homologs from extreme microorganisms with superior stabilities that have yielded initial structural data for further engineering. In addition, a new bioelectrocatalytic reactor system has been developed that can be 3D printed and used for enzyme attachment to electrodes. In summary the project has generated critical basic information for the further development of this class of enzymes for the electricity driven reduction of CO2 into formate as platform chemical for upgrading into various other chemicals, including fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Where Have All of the Electrons Gone? Understanding the Role of Alternative Electron Flow and O 2 Reduction in Balancing Cellular Redox (Final Technical Report)

An informed understanding of the fundamentals of light-driven electron transfer reactions in photoautotrophic organisms is necessary to enable improved photosynthetic efficiencies for the production of renewable fuels and novel biomaterials. To obtain high photosynthetic yields, light energy must be efficiently coupled to the fixation of CO 2 . Sub-optimal environmental conditions and metabolic routing (caused by blocks in biosynthetic routes) can severely impact the conversion of light energy to biomass and lead to reactive oxygen production, which in turn can cause cellular damage and productivity losses. Hence, plants, algae, and photosynthetic bacteria have evolved a network of alternative outlets to sustain the flow of photosynthetically derived-electrons. Our research was focused on the nature and integration of these outlets. The data obtained in this project will inform efforts to rationally engineer crop plants and algae to improve photosynthetic yields by enhancing electron transfer reactions to CO 2 reduction and targeted biomass accumulation. A major project research thrust was focused on identifying and quantifying the flow of photosynthetic reductant through electron transfer circuits that result in the light-dependent reduction of O 2 . New energy management strategies were identified that are used when normal carbon assimilation pathways are compromised due to nutrient deprivation, and/or by a reduction in starch synthesis/carbon storage, all conditions resulting in highly reduced intracellular redox pools. The green alga Chlamydomonas reinhardtii, and likely many other algae, have multiple O 2 -reducing pathways that play critical roles in maintaining cellular metabolic balance and scavenging electrons that could potentially cause cellular damage, which in some instances leads to reduced photosynthetic yields but increased fitness. We explored the activities of three essential outlets associated with Chlamydomonas reinhardtii photosynthetic electron transport: (1) reduction of O 2 to H 2 O through Flavodiiron proteins (FLVs) and (2) Plastid Terminal Oxidases (PTOX), and (3) the synthesis of starch. Real-time measurements of O 2 exchange demonstrated that FLVs immediately engage during dark to light transitions, allowing electron transport when the CBBC is not fully activated. Under these conditions, we quantified, for the first time, maximal FLV activity and its overall capacity to direct photosynthetic electrons towards O 2 reduction. However, when starch synthesis is compromised, a greater proportion of electrons is directed toward O 2 reduction through the FLVs, while PTOX, which is sensitive to the PQ pool redox state, is activated. This suggests, that starch synthesis has an important role in priming/regulating CBBC and electron transport. We also identified a biological ‘switch’ in the green alga Chlamydomonas reinhardtii that reversibly restricts photosynthetic electron transport (PET) at the cytochrome b 6 f complex when reductant and ATP generated by PET are in excess of the capacity of carbon metabolism to utilize these products; we specifically show a restriction at this switch when sta6 mutant cells, which cannot synthesize starch, are limited for nitrogen (growth inhibition) and subjected to a dark to light transition. This restriction causes diminished electron flow to PSI, which prevents PSI photodamage, and the plastid alternative oxidase (PTOX) becomes fully activated, serving as an electron valve that dissipates excitation energy absorbed by PSII, thereby lessening PSII photoinhibition. Furthermore, illumination of the cells following the dark acclimation gradually diminishes the restriction at the switch. Future engineering of these switches may allow more effective electron transfer to lipid (biofuel) pathways and diminish the number of electrons “wasted” in the reduction of O 2 to water. Lastly, we explored metabolic routing of electrons during algal fermentation and discovered multiple novel pathways that are activated when the preferred anoxic routes are blocked. These provide valuable products (e.g. lactate, glycerol) that can be used in broad portfolio of biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue

In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it. These processes are considered, to start from the aortic inlet to the capillaries and tissue of the breast. Large variations in biophysical properties and flow conditions exist in this system necessitating the use of different flow models for different geometries and flow regimes. In total, we consider four different model types. First, a system of 1D nonlinear hyperbolic partial differential equations (PDEs) is considered to simulate blood flow in larger arteries with highly elastic vessel walls. Second, we assign 1D linearized hyperbolic PDEs to model the smaller arteries with stiffer vessel walls. The third model type consists of ODE systems (0D models). It is used to model the arterioles and peripheral circulation. Finally, homogenized 3D porous media models are considered to simulate flow and transport in capillaries and tissue within the breast volume. Sink terms are used to account for the influence of the venous and lymphatic systems. Combining the four model types, we obtain two different 1D–0D–3D coupled models for simulating blood flow and transport processes: The first model results in a fully coupled 1D–0D–3D model covering the complete path from the aorta to the breast combining a generic arterial network with a patient specific breast network and geometry. The second model is a reduced one based on the separation of the generic and patient specific parts. The information from a calibrated fully coupled model is used as inflow condition for the patient specific sub-model allowing a significant computational cost reduction. Several numerical experiments are conducted to calibrate the generic model parameters and to demonstrate realistic flow simulations compared to existing data on blood flow in the human breast and vascular system. Moreover, we use two different breast vasculature and tissue data sets to illustrate the robustness of our reduced sub-model approach.

multiscale blood flow models↗
DOE OSTI2020

Potential impacts of climate change on wind and solar electricity generation in Texas

Wind and solar energy sources are climate and weather dependent, therefore susceptible to a changing climate. in this paper, we quantify the impacts of climate change on wind and solar electricity generation under high concentrations of greenhouse gases in Texas. We employ mid-twenty-first century climate projections and a high-resolution numerical weather prediction model to generate weather variables in the future and produce wind and solar generation time series. We find that mid-twenty-first century projections based on five global climate models agree on the multiyear average increases across Texas in direct normal irradiance, global horizontal irradiance, surface air temperature, and 100-m wind speed of up to 5%, 4%, 10%, and 1%, respectively. These changes lead to multiyear average relative changes across Texas of -0.6 to + 2.5% and of + 1.3 to + 3.5% in solar and wind capacity factors, respectively, with significant regional, seasonal, and diurnal differences. Areas with low solar resource show an increase in solar capacity factors but reductions in wind capacity factors. Areas with high solar resource show reductions in solar capacity factors. The spatial and temporal differences in our results highlight the importance of using high-resolution data sets to study the potential impacts of climate change on wind and solar power.

14 SOLAR ENERGY↗
DOE OSTI2021

Alteration in micro-mechanical characteristics of wellbore cement fracture surfaces due to fluid exposure

The stiffness of wellbore cement fracture surfaces was measured after exposing to the advective flow of nitrogen, silicone oil, and medium sweet dead crude oil for different exposure periods. The test specimens were extracted from fractured cement cylinders, where the cement fracture surfaces were exposed to the different fluids up to 15 weeks. A nanoindenter with a Berkovich indenter tip was used to measure load-indentation depth data, which was used to extract the elastic modulus (E) and nano-hardness (H) of the cement fracture surfaces. A reduction in the elastic modulus compared with an unexposed specimen were observed in all the specimens. Both elastic modulus and nano-hardness for the specimens exposed to silicone oil were lower than specimens exposed to nitrogen gas and varied with the period of exposure. The elastic modulus and nano-hardness of the specimens exposed to crude oil were the lowest with a significant decrement with the exposure period. The frequency distribution of the nanoindentation measurements shows that the volume-fraction ratio of the two types of cement hydrated nanocomposites for both the unexposed and test specimens is about 70:30%. Phase transformation beneath the indenter is observed for all of the specimens, with more obvious plastic deformation in specimens exposed to crude oil. Analytical measurements (SEM, EDS, FT-IR, and XRD) on exposed cement fracture surfaces reveal different levels of physical and chemical alteration that are consistent with the reduction in stiffness measured by nanoindentation. Furthermore, the study suggests that cement stiffness will decrease due to crude oil exposure, and the fracture will be sensitive to stress and pore pressure with time.

42 ENGINEERING↗
DOE OSTI2025

No evidence of a reduction in the dipole polarisability at shell closures

Photoabsorption reactions have a long and productive history as probes of the response of nuclei to electromagnetic fields. In recent years, there has been a suggestion that the dipole polarisability may be reduced at shell closures, potentially due to the reduced level density. In the current paper, more recent photoabsorption strengths are reanalysed including nuclei on closed proton shells to search for a similar reduction. The previously reported reduction is not reproduced. We conclude that the previously observed reduction may be due to incomplete evaluations of the photoabsorption due to missing cross section contributions and experimental artefacts. More experimental data are necessary to draw a firm conclusion about whether shell effects persist into high excitation energies, especially data which can obviate any systematic effects and look at relative photoabsorption strengths between nuclei.

Giant dipole response↗
DOE OSTI2025

The Impact of Clean Grid Transition on Wastewater Sector Greenhouse Gas Emissions

This study examines the spatial and temporal impacts of the U.S. clean energy grid transition on related greenhouse gas (GHG) emissions from the wastewater treatment industry. By analyzing data from 17,156 water resource recovery facilities (WRRFs) and state-specific grid decarbonization scenarios, the results project a 60% reduction in Scope 2 emissions by 2050, driven by the national shift to renewable energy. However, regional disparities are prominent, with northeastern and western states achieving the most significant reductions, while the Ohio Valley and Rockies are likely to experience higher emissions due to the reliance on fossil fuels. This study offers the first assessment of clean grid impacts on the WRRFs and highlights the need for targeted, region-specific strategies across different emission scopes. This research provides insights for policymakers and stakeholders in the wastewater sector, emphasizing the critical role of grid decarbonization in achieving GHG reduction goals.

Li, Xiatong↗
DOE OSTI2025

Radical Treatment of Haloacetonitriles in Aqueous Systems: A Kinetic Study

Haloacetonitriles (HANs) are important drinking water disinfection byproducts formed through the chlorination and chloramination of amino acids. Although HAN concentrations in treated water are usually lower than trihalomethanes, they are still of major concern due to their higher cyto- and genotoxicity. HANs undergo chemical transformations by hydrolysis on the hour to week time scales; however, for possible direct water reuse situations, their active removal using advanced oxidation/reduction processes (AO/RPs) may be required. We report here our systematic kinetic study of the four major AO/RP radiolysis species, oxidizing hydroxyl (·OH) and sulfate (SO 4 −· ) radicals and reducing hydrated electron (e aq − ) and hydrogen atoms (H · ) with five HANs (mono-, di-, and trichloroacetonitriles and mono- and dibromoacetonitriles) in water measured using electron pulse radiolysis techniques. At ambient temperatures and pH 1−7, significant reactivity was found for e aq − ( k = (1−5) × 10 10 M −1 s −1 ) and H · atoms ( k = (1 − 40 × 10 7 M −1 s −1 ), but only minimal oxidation by ·OH ( k = (0.6−10) × 10 7 M −1 s −1 ) and SO 4 −· ( k = (0.2−4) × 10 6 M −1 s −1 ) occurred. These data suggest that the large-scale AO/RP treatment of these contaminants will be effective for deaerated reducing systems, where the reductive electron-induced degradation of HANs will occur.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

How Precisely Can Individual Molecules Be Analyzed? A Case Study on Locally Quantifying Forces and Energies Using Scanning Probe Microscopy

Recent advances in scanning probe microscopy methodology have enabled the measurement of tip-sample interactions with picometer accuracy in all three spatial dimensions, thereby providing a detailed site-specific and distance-dependent picture of the related properties. This paper explores the degree of detail and accuracy that can be achieved in locally quantifying probe-molecule interaction forces and energies for adsorbed molecules. Toward this end, cobalt phthalocyanine (CoPc), a promising CO 2 reduction catalyst, was studied on Ag(111) as a model system using low-temperature, ultrahigh vacuum noncontact atomic force microscopy. Data were recorded as a function of distance from the surface, from which detailed three-dimensional maps of the molecule's interaction with the tip for normal and lateral forces as well as the tip-molecule interaction potential were constructed. The data were collected with a CO molecule at the tip apex, which enabled a detailed visualization of the atomic structure. Determination of the tip-substrate interaction as a function of distance allowed isolation of the molecule-tip interactions; when analyzing these in terms of a Lennard-Jones-type potential, the atomically resolved equilibrium interaction energies between the CO tethered to the tip and the CoPc molecule could be recovered. Interaction energies peaked at less than 160 meV, indicating a physisorption interaction. As expected, the interaction was weakest at the aromatic hydrogens around the periphery of the molecule and strongest surrounding the metal center. In conclusion, the interaction, however, did not peak directly above the Co atom but rather in pockets surrounding it.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Elucidating the Role of Halides and Iron during Radiolysis-Driven Oxidative Etching of Gold Nanocrystals Using Liquid Cell Transmission Electron Microscopy and Pulse Radiolysis

Graphene liquid cell transmission electron microscopy (TEM) has enabled the observation of a variety of nanoscale transformations. Yet understanding the chemistry of the liquid cell solution and its impact on the observed transformations remains an important step toward translating insights from liquid cell TEM to benchtop chemistry. Gold nanocrystal etching can be used as a model system to probe the reactivity of the solution. FeCl 3 has been widely used to promote gold oxidation in bulk and liquid cell TEM studies, but the roles of the halide and iron species have not been fully elucidated. In this work, we observed the etching trajectories of gold nanocrystals in different iron halide solutions. We observed an increase in gold nanocrystal etch rate going from Cl - - to Br - - to I - -containing solutions. Furthermore, this is consistent with a mechanism in which the dominant role of halides is as complexation agents for oxidized gold species. Additionally, the mechanism through which FeCl 3 induces etching in liquid cell TEM remains unclear. Ground-state bleaching of the Fe(III) absorption band observed through pulse radiolysis indicates that iron may react with Cl 2 · - radicals to form an oxidized transient species under irradiation. Complete active space self-consistent field (CASSCF) calculations indicate that the FeCl 3 complex is oxidized to an Fe species with an OH radical ligand. Together our data indicate that an oxidized Fe species may be the active oxidant, while halides modulate the etch rate by tuning the reduction potential of gold nanocrystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Elimination of human rabies in Goa, India through an integrated One Health approach

Dog-mediated rabies kills tens of thousands of people each year in India, representing one third of the estimated global rabies burden. Whilst the World Health Organization (WHO), World Organization for Animal Health (OIE) and the Food and Agriculture Organization of the United Nations (FAO) have set a target for global dog-mediated human rabies elimination by 2030, examples of large-scale dog vaccination programs demonstrating elimination remain limited in Africa and Asia. We describe the development of a data-driven rabies elimination program from 2013 to 2019 in Goa State, India, culminating in human rabies elimination and a 92% reduction in monthly canine rabies cases. Smartphone technology enabled systematic spatial direction of remote teams to vaccinate over 95,000 dogs at 70% vaccination coverage, and rabies education teams to reach 150,000 children annually. An estimated 2249 disability-adjusted life years (DALYs) were averted over the program period at 526 USD per DALY, making the intervention ‘very cost-effective’ by WHO definitions. This One Health program demonstrates that human rabies elimination is achievable at the state level in India.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Ligand dependent interaction between PC-TP and PPARδ mitigates diet-induced hepatic steatosis in male mice

Phosphatidylcholine transfer protein (PC-TP; synonym StarD2) is a soluble lipid-binding protein that transports phosphatidylcholine (PC) between cellular membranes. To better understand the protective metabolic effects associated with hepatic PC-TP, we generated a hepatocyte-specific PC-TP knockdown (L-Pctp -/- ) in male mice, which gains less weight and accumulates less liver fat compared to wild-type mice when challenged with a high-fat diet. Hepatic deletion of PC-TP also reduced adipose tissue mass and decreases levels of triglycerides and phospholipids in skeletal muscle, liver and plasma. Gene expression analysis suggest that the observed metabolic changes are related to transcriptional activity of peroxisome proliferative activating receptor (PPAR) family members. An in-cell protein complementation screen between lipid transfer proteins and PPARs uncovered a direct interaction between PC-TP and PPARδ that was not observed for other PPARs. We confirmed the PC-TP– PPARδ interaction in Huh7 hepatocytes, where it was found to repress PPARδ-mediated transactivation. Mutations of PC-TP residues implicated in PC binding and transfer reduce the PC-TP-PPARδ interaction and relieve PC-TP-mediated PPARδ repression. Reduction of exogenously supplied methionine and choline reduces the interaction while serum starvation enhances the interaction in cultured hepatocytes. Together our data points to a ligand sensitive PC-TP– PPARδ interaction that suppresses PPAR activity.

59 BASIC BIOLOGICAL SCIENCES↗