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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Harmonizing model organism data in the Alliance of Genome Resources

The Alliance of Genome Resources (the Alliance) is a combined effort of 7 knowledgebase projects: Saccharomyces Genome Database, WormBase, FlyBase, Mouse Genome Database, the Zebrafish Information Network, Rat Genome Database, and the Gene Ontology Resource. The Alliance seeks to provide several benefits: better service to the various communities served by these projects; a harmonized view of data for all biomedical researchers, bioinformaticians, clinicians, and students; and a more sustainable infrastructure. The Alliance has harmonized cross-organism data to provide useful comparative views of gene function, gene expression, and human disease relevance. The basis of the comparative views is shared calls of orthology relationships and the use of common ontologies. The key types of data are alleles and variants, gene function based on gene ontology annotations, phenotypes, association to human disease, gene expression, protein–protein and genetic interactions, and participation in pathways. The information is presented on uniform gene pages that allow facile summarization of information about each gene in each of the 7 organisms covered (budding yeast, roundworm Caenorhabditis elegans, fruit fly, house mouse, zebrafish, brown rat, and human). The harmonized knowledge is freely available on the alliancegenome.org portal, as downloadable files, and by APIs. We expect other existing and emerging knowledge bases to join in the effort to provide the union of useful data and features that each knowledge base currently provides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Why Regional and Long-Haul Trucks are Primed for Electrification Now

Zero emission freight trucks are needed to both improve public health and reduce global greenhouse gas emissions but at the same time are generally believed to be uneconomical. However, recent dramatic declines in battery prices and improvement in their energy density have created opportunities for battery-electric trucking today that were seldom anticipated just a few years ago. At the current global average battery pack price of $135 per kilowatt-hour (kWh) (realizable when procured at scale), a Class 8 electric truck with 375-mile range and operated 300 miles per day when compared to a diesel truck offers about 13% lower total cost of ownership (TCO) per mile, about 3-year payback and net present savings of about US $200,000 over a 15-year lifetime. This is achieved with only a 3% reduction in payload capacity. Even this small penalty can be reversed cost-effectively through light-weighting, in any case, only matters for a small fraction of trucks which regularly utilize their maximum payload. Electric trucks appear poised to also meet the performance demands for a large share of regional and long-haul trucking today. The estimated average distance traveled between 30- minute driver breaks is 150 miles and 190 miles for regional-haul and long-haul trucks respectively in the US. Thirty minutes of charging using 500 kW or mega-Watt scale fastchargers would add sufficient range without impairing operations and economics of freight movement. However, as with almost any clean technology, higher upfront capital costs of both vehicles and charging infrastructure are major barriers when electric trucking is in its infancy. Without strong policy support, coordinated investments in both vehicle manufacturing and fuel infrastructure will not be forthcoming on the scale needed to harness the true potential of battery electric trucks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes

Abstract. We present MPAS-Seaice, a sea-ice model which uses the Model for Prediction Across Scales (MPAS) framework and spherical centroidal Voronoi tessellation (SCVT) unstructured meshes. As well as SCVT meshes, MPAS-Seaice can run on the traditional quadrilateral grids used by sea-ice models such as CICE. The MPAS-Seaice velocity solver uses the elastic–viscous–plastic (EVP) rheology and the variational discretization of the internal stress divergence operator used by CICE, but adapted for the polygonal cells of MPAS meshes, or alternatively an integral (“finite-volume”) formulation of the stress divergence operator. An incremental remapping advection scheme is used for mass and tracer transport. We validate these formulations with idealized test cases, both planar and on the sphere. The variational scheme displays lower errors than the finite-volume formulation for the strain rate operator but higher errors for the stress divergence operator. The variational stress divergence operator displays increased errors around the pentagonal cells of a quasi-uniform mesh, which is ameliorated with an alternate formulation for the operator. MPAS-Seaice shares the sophisticated column physics and biogeochemistry of CICE and when used with quadrilateral meshes can reproduce the results of CICE. We have used global simulations with realistic forcing to validate MPAS-Seaice against similar simulations with CICE and against observations. We find very similar results compared to CICE, with differences explained by minor differences in implementation such as with interpolation between the primary and dual meshes at coastlines. We have assessed the computational performance of the model, which, because it is unstructured, runs with 70 % of the throughput of CICE for a comparison quadrilateral simulation. The SCVT meshes used by MPAS-Seaice allow removal of equatorial model cells and flexibility in domain decomposition, improving model performance. MPAS-Seaice is the current sea-ice component of the Energy Exascale Earth System Model (E3SM).

58 GEOSCIENCES↗
DOE OSTI2020

A Comprehensive Approach to Measure the Efficiency of Freight Transport: Freight Mobility Energy Productivity (F-MEP) Metric

Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement is critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting is gaining pace in the recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregated in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance of freight systems. Addressing this research need, this paper presents the 'Freight Mobility Energy Productivity' metric to quantify freight performance of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, which shows intuitive results in quantifying freight performance. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight efficiency as a result of vehicle powertrain technology improvement. Results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the efficiency of existing as well as future freight trends and technologies.

25 ENERGY STORAGE↗
DOE OSTI2023

Chapter 9: Human Behavior Dynamics in Sustainability

Human behavior dynamics and actions play a direct and significant role in shaping pathways toward sustainability, resulting in many sustainability challenges. A social dilemma arose when a hypothetical Colorado rural town closed down most of its medicine take-back stations as a result of reduced tax revenue. The current discourse discusses a scenario in which an individual "plays" against everyone else concerning whether to drive to the take-back station to dispose of unused medication (i.e., cooperating) or to flush it or throw it in the landfill (i.e., defecting). Using the structure of the pay-off matrix, this study analyzed unwanted medication disposal from a social dilemma perspective to provide insight into an individual's motivations to cooperate or defect and techniques for encouraging cooperation. The pay-off matrix encompasses four scenarios, namely, win-win when everyone cooperates, you're the sucker when only the individual cooperates, free rider when only the individual defects, and the tragedy of the commons when everyone defects. Reasons for an individual to cooperate include sharing the high moral value with everyone else, valuing social conformity, and taking great pride in doing the right thing, even when cooperating is costly. On the other hand, the individual who defects believes that cooperating will likely make little difference. The individual is selfish or insufficiently motivated by altruism and feels that the bad action will not get caught. When everyone defects, it likely results from participants not wanting to be a "sucker" and a lack of accountability (e.g., no punishment) associated with bad behavior. One solution to the free-rider problem is to appeal to the free rider's altruism. It is important to convince the individual that doing things for the benefit of others can also benefit themselves. Furthermore, a way to fix the social dilemma is to make the defectors pay for their actions that cause the negative externality (i.e., town water contaminated with pharmaceutical chemicals from unwanted medications). The higher the financial incentive for cooperative behavior, the lower the defecting propensity. By including punishment (e.g., discipline and penalty), people tend to defect less often, and highly cooperative outcomes emerge.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A Framework for Multisector Scenarios of Outcomes for Well-Being and Resilience

Shared community scenarios of societal and environmental system changes have underpinned a broad range of research and assessment studies over the past several decades. These scenarios have largely aimed to address specific questions within broad issue areas like climate change or biodiversity and generally provided information on the drivers of change. The consequences of those drivers, such as impacts on society and policy responses, have tended to be left to the research community to investigate, using scenarios of drivers as inputs to their studies, producing projections of a disparate set of relevant output metrics. While this approach has had many benefits, it has fallen short of producing a robust, comparable literature describing outcomes across studies in common metrics. We argue that new scenarios are needed that extend current approaches to be organized around common outcome metrics for the well-being and resilience of society and ecosystems. We propose an approach that would focus on agreed upon outcomes for well-being and resilience as well as critical drivers of change, cut across issues and scales in multiple sectors, and draw on new systematic methods of scenario generation and discovery to highlight scenarios that are most critical in understanding societal risks and responding to them. Research derived from this outcome-based scenario development approach would facilitate improved assessment of risks of and responses to a range of stressors and the multi-sector interactions they generate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Implementation of quantum key distribution and quantum clock synchronization via time bin encoding

Quantum key distribution allows for a provably secure transmission of cryptographic keys over an optical channel. Encoded polarization states or time-bin degree of freedom have been used for successful demonstrations. However, photon losses in long fibers, slow single photon detectors, and detector dark counts significantly limit the overall bit rate. Improving key throughput and reducing the overhead of key reconciliation remain as major challenges. Methods which utilize multiple time bins allow for multiple key bits to be encoded in a single photon, thus increasing the fidelity of transmitted keys and decreasing the overhead of key reconciliation in real-world conditions. Previous implementations of these methods required that Alice and Bob share a time reference by sharing a dedicated classical channel used for synchronization. This work presents a technique that allows two parties to exchange time-bin encoded photons without the need for synchronized time references. Our technique uses a framing protocol which allows Alice to encode a time reference along with a key which is determined by Alice before transmission. Security can be achieved by monitoring the visibility of a pair of Franson interferometers, using decoy pulses and measuring the round trip time between Alice and Bob. The bit rate of this technique is limited only by the recovery time of the detector and the speed of the modulation electronics. We experimentally demonstrate a raw bit rate of 5Mb/s over an optical channel with 55dB of loss, which is competitive with current research. We also demonstrate absolute timing synchronization with an accuracy of 20ps.

encryption↗
DOE OSTI2020

Comprehensive Approach to Measure the Mobility Energy Productivity of Freight Transport

Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement are critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting has been gaining pace in recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregate in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance or productivity of freight systems. Addressing the research need, this paper presents the “Freight Mobility Energy Productivity” metric to quantify freight productivity of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, and shows intuitive results in quantifying freight productivity. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight productivity as a result of vehicle electrification. The relative differences in Freight Mobility Energy Productivity scores help identify which zones benefit from the vehicle powertrain technology improvement. The results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the productivity of existing as well as future freight trends and technologies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A Comprehensive Approach to Measure the Mobility Energy Productivity of Freight Transport: Preprint

Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement are critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting is gaining pace in the recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregate in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance or productivity of freight systems. Addressing the research need, this paper presents the “Freight Mobility Energy Productivity” metric to quantify freight productivity of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, which shows intuitive results in quantifying freight productivity. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight productivity as a result of vehicle electrification. The relative differences in Freight Mobility Energy Productivity scores help identify which zones benefit from the vehicle powertrain technology improvement. The results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the productivity of existing as well as future freight trends and technologies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

High Energy Physics Network Requirements Review: Two-Year Update

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide a range of network services tailored to meet the unique requirements of the DOE’s data-intensive science. In July 2023, the Energy Sciences Network (ESnet) and the High Energy Physics program (HEP) of the DOE SC organized an interim ESnet requirements review of HEP-supported activities, to follow up on the work started during the 2020 HEP Network Requirements Review. Preparation for these events included checking back with the key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare updates to their previously submitted case study documents, so that ESnet could update the understanding of any changes to the current, near-term, and long-term status, expectations, and processes that will support the science activities of the program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

GCAM-Demeter-LU

This GCAM-Demeter-LU is made available under the Open Data Commons Attribution License:http://opendatacommons.org/licenses/by/1.0/. The dataset includes the projected global gridded land cover (excluding the Antarctic) for the period of 2015-2100 at 0.05-degree resolution and 5-year time step under fifteen SSP-RCP scenarios driven by five GCMs (i.e., gfdl, hadgem, ipsl, miroc, and noresm), using the Global Change Analysis Model (GCAM) and a geospatial downscaling model (Demeter). The data has been stored in self-describing NetCDF format. The dataset also includes the mean and standard deviation of the results driven by the five GCMs. More specifically, the data in each year includes grid-explicit fraction (in percent) of each of the 32 plant functional types that are widely used in current Earth system models. The NetCDF files are named as “GCAM_Demeter_LU_SSP_RCP_Model_Year.nc”, where “SSP” and “RCP” denote the SSP and RCP scenarios, including 'ssp1_rcp26', 'ssp1_rcp45', 'ssp1_rcp60', 'ssp2_rcp26', 'ssp2_rcp45', 'ssp2_rcp60', 'ssp3_rcp45', 'ssp3_rcp60', 'ssp4_rcp26', 'ssp4_rcp45', 'ssp4_rcp60', 'ssp5_rcp26', 'ssp5_rcp45', 'ssp5_rcp60', and 'ssp5_rcp85'. “Year” denotes the year of the land use data, and “GCM” denotes the source driving forcing data from five global climate models (gfdl, hadgem, ipsl, miroc, and noresm), or the mean (“modelmean”) and the standard deviation (“modelstd”) of the results from the five GCMs.See https://github.com/JGCRI/chen_et_al_2020a for details on how to reproduce this data. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Use Case-Informed Framework for Utility Cloud Migration

This white paper presents a comprehensive methodology for assessing utilities’ cloud postures and frameworks. It aims to produce a roadmap and strategy for a cloud-enabled grid future, providing guidance for integrators, asset owners, and operators. Instead of offering a yes or no answer for cloud implementation, this framework offers strategic guidance on responsibly preparing for and deploying cloud solutions. This paper delves into cloud-service models pertinent to the electric sector, dissecting the shared responsibility model and elucidating what on-premise infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) entail. A pivotal consideration within the context of the shared responsibility model is the allocation of responsibility for foundational security aspects—a decision that will be informed by a comprehensive risk assessment. The ensuing discussion will present a checklist of certifications necessary for a secure cloud transition, equipping utilities with the knowledge to navigate this digital transformation with confidence and with a strategic roadmap. Furthermore, the paper outlines gaps in understanding the U.S. government’s role in shaping technology development and responsible use. Its purpose is to aid decision-making by offering support for risk-informed solutions that benefit those managing assets and operating in the cloud environment. The primary objective is to enhance the resilience and future readiness of a decarbonized electric grid, with cloud solutions as one viable option. The paper synthesizes information on current and future grid architectures and applications, considering both conservative and progressive energy transitions, along with scalable and distributed computing considerations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Future energy infrastructure, energy platform and energy storage

Today fossil energy dominates energy consumption across the world. There has been an increasing momentum to reduce fossil energy consumption and increase renewable energy utilization to more than 70%. Such high penetrations of distributed renewable resources bring large uncertainty and complexity that cannot be easily handled by the current infrastructure. For the last two decades, telecommunication industry has gone through a similar transition from centralized to distributed systems, and more recently to platform approaches, which become the corner stone of today’s vibrant platform economy. Based on telecommunication history, we believe that a platform-based approach, called the energy platform, is a viable solution for addressing the renewable energy challenges. The energy platform consists of an array of computational algorithms, sensing and control technologies for key industry, energy generators and users to jointly manage and control the complex energy infrastructure. It includes the following key components: (1) the hardware and software to generate, store, control and transmit electricity/data (the energy cloud), (2) the digital platforms and tools for key energy producers, digital, service and communication industry to share the assets, participate in and manage the complex infrastructure, and for customers to participate in energy transactions, (3) the transaction platform for new service and business models. Additionally, the energy platform requires breakthroughs in large scale energy storage and many other areas including efficient power electronics, sensors and controls, new mathematical and computational tools, and deep integration of energy technologies and information sciences to control and stabilize such complex chaotic systems.

25 ENERGY STORAGE↗
DOE OSTI2023

AOI-2, A Novel Access Control Blockchain Paradigm for Cybersecure Sensor Infrastructure in Fossil Power Generation Systems

Fossil power generation systems are increasingly vulnerable to attack from both cybercriminals as well as internal threats. These vulnerabilities demand that emerging technologies such as blockchains be utilized to secure the data involved in the information flows within the Supervisory Control and Data Acquisition (SCADA) systems of the fossil power generation plants. The publicly accessible blockchain protocols, although secure, are visible to everyone. Even private blockchains currently are unable to support different levels of access to different participants, which is a critical requirement for the existing SCADA systems running the power plants. In light of the above, novel blockchain protocols that are specifically adapted to fossil power generation environments need to be developed in order to achieve the goal of cybersecure sensor networks. In this work, we address this question by creating a novel blockchain technology, namely smart private ledger, for cybersecure communication within the fossil power generation systems. A lab-scale sensor network consisting of strain and temperature sensors is constructed to develop the ledger. The technology has hierarchical access control which is compatible with the existing SCADA systems in fossil power plants. The sensor data is used with cryptographic digital signatures and secret sharing protocols within the nodes of the blockchain technology. The research results will lead to cybersecurity for machine-to-machine interactions, infrastructure for secure data logging for sensors, decentralized data storage, and second-layer technologies for high volume machine-to-machine interactions in the power plants. The work aims to largely address the concerns for the security of distributed sensor networks in such systems that can be compromised by insider threats and by cybercriminals. The research has led to the training of the next generation of engineers and scientists in the important areas of sensor engineering and blockchain technology.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Rigor and Reproducibility in Electrocatalysis: Best Practices for Operando Studies

Operando measurements have rapidly expanded the scope of electrocatalysis by enabling direct observation of catalytic interfaces under working conditions and by linking structural, compositional, and spectroscopic observables to activity and selectivity. However, the growth of operando methods has outpaced the adoption of broadly shared experimental standards, creating persistent challenges in reproducibility, interpretation, and comparison across laboratories and platforms. This perspective synthesizes discussions from the 2025 National Science Foundation Workshop on Rigor and Reproducibility in Electrocatalysis and outlines a practical framework for the rigorous use of operando measurements in electrocatalysis. We highlight three recurring needs: careful implementation of complex methods to avoid overinterpretation; recognition that (subtle) differences in reactor architecture, hydrodynamics, and electrical boundary conditions can alter apparent kinetics and selectivity; and transparent reporting standards that enable meaningful cross-comparison without constraining measurement-specific cell innovation. Focusing on widely used techniques (including X-ray and vibrational spectroscopies, mass spectrometry, and electron microscopy), we discuss technique-specific pitfalls, cross-validation strategies, and recurring platform-agnostic considerations such as mass transport, current distribution, temporal-resolution mismatches, and catalyst evolution. This Perspective aims to strengthen the mechanistic inference and improve the reproducibility, comparability, and predictive value of operando electrocatalysis research.

X-ray absorption spectroscopy↗
DOE OSTI2025

Understanding and design of interstitial oxygen conductors

Highly efficient oxygen-active materials that react with, absorb, and transport oxygen is essential for fuel cells, electrolyzers and related applications. While vacancy-mediated oxygen-ion conductors have long been the focus of research, they are limited by high migration barriers at intermediate temperatures (400–600 °C), which hinder their practical applications. In contrast, interstitial oxygen conductors exhibit significantly lower migration barriers enabling higher ionic conductivity at lower temperatures. This review systematically examines both well-established and recently identified families of interstitial oxygen-ion conductors, focusing on how their unique structural motifs such as corner-sharing polyhedral frameworks, isolated polyhedral, and cage-like architectures, facilitate low migration barriers through interstitial and/or interstitialcy diffusion mechanisms. A central discussion of this review focuses on the evolution of design strategies, from targeted donor doping, element screening, to physical-intuition descriptor material screening and machine learning approach, which leverage computational tools to explore vast chemical spaces in search for new interstitial conductors. The success of these strategies demonstrates that a significant, largely unexplored space remains for discovering high-performing interstitial oxygen conductors. Crucial features enabling high-performance interstitial oxygen diffusion include the availability of electrons for oxygen reduction and sufficient structural flexibility with accessible volume for interstitial accommodation and migration. This review concludes with a forward-looking perspective, proposing a knowledge-driven methodology that integrates current understanding with data-centric approaches to identify promising interstitial oxygen conductors outside traditional search paradigms. These approaches are expected to significantly accelerate the development of high-performance interstitial oxygen conductors for a variety of oxygen-active applications, ultimately paving the way for more efficient and sustainable energy technologies.

Interstitial oxygen conductors↗
DOE OSTI2023

Sarcocystis cruzi (Hasselmann, 1923) Wenyon, 1926: redescription, molecular characterization and deposition of life cycle stages specimens in the Smithsonian Museum

Currently, 7 named Sarcocystis species infect cattle: Sarcocystis hirsuta, S. cruzi, S. hominis, S. bovifelis, S. heydorni, S. bovini and S. rommeli; other, unnamed species also infect cattle. Of these parasites of cattle, a complete life cycle description is known only for S. cruzi, the most pathogenic species in cattle. The life cycle of S. cruzi was completed experimentally in 1982, before related parasite species were structurally characterized, and before the advent of molecular diagnostics; to our knowledge, no archived frozen tissues from the cattle employed in the original descriptions remain for DNA characterization. Here, we isolated DNA from a paraffin-embedded kidney of a calf experimentally infected with S. cruzi in 1980; we then sequenced portions of 18S rRNA, 28S rRNA, COX1 and Acetyl CoA genes and verified that each shares 99–100% similarity to other available isolates attributed to S. cruzi from naturally infected cattle. We also reevaluated histological sections of tissues of calves experimentally infected with S. cruzi in the original description, exploiting improvements in photographic technology to render clearer morphological detail. Finally, we reviewed all available studies of the life cycle of S. cruzi, noting that S. cruzi was transmitted between bison (Bison bison) and cattle (Bos taurus) and that the strain of parasite derived from bison appeared more pathogenic than the cattle strain. Based on these newfound molecular, morphological and physiological data, we thereby redescribed S. cruzi and deposited reference material in the Smithsonian Museum for posterity.

59 BASIC BIOLOGICAL SCIENCES↗