Results for “SPECIFICITY” — Page 16

NASA NTRS2022

Specific Power and Efficiency Projections of Electric Machines and Circuit Protection Exploration for Aircraft Applications

The purpose of this paper is to generate specific power and efficiency projections through the year 2050 for electric machines for aircraft applications. A general literature review was performed to identify the types of electric machines that are commonly used and which types have the biggest potential for future aircraft applications due to their high specific power and efficiency. A database with historical data was built to include parameters such as weight [kg], rated power [kW], specific power [kW/kg], RPM, efficiency, year, motor cooling type, application type and motor type to allow for trend identification and accurate projections. Once the data was gathered, multiple curve fits on the historical data were generated and extrapolated to produce the projections for specific power according to conservative, nominal and aggressive projection scenarios. A different process was followed for the efficiency projections due to the scattered nature of the data. A state of the art (SoA) value for efficiency was identified through literature review and was used to create the conservative, nominal and aggressive projections for the time frames of 2030, 2040, and 2050. The efficiency and the specific power projections of EMs for 2050 are 0.989 and 50kW/kg respectively. This paper will also be examining circuit protection as it is an additional component of electric powertrains.

electric machines↗

NASA NTRSDate not supplied

GeoAI advances in specific landform mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation. References: Arundel, Samantha T., Wenwen Li, and Sizhe Wang. 2020. “GeoNat v1.0: A Dataset for Natural Feature Mapping with Artificial Intelligence and Supervised Learning.” Transactions in GIS 24 (3): 556–72. https://doi.org/10.1111/tgis.12633. Arundel, Samantha T, and Gaurav Sinha. 2018. “Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms BT - Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017).” In Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), Lecture Notes in Geoinformation and Cartography, edited by Paolo Fogliaroni, Andrea Ballatore, and Eliseo Clementini, 9–14. Cham: Springer International Publishing. Arundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. 2023. “Historical Maps Inform Landform Cognition in Machine Learning.” Abstracts of the ICA 6 (August): 1–2. https://doi.org/10.5194/ica-abs-6-10-2023. Evans, Ian S. 2012. “Geomorphometry and Landform Mapping: What Is a Landform?” Geomorphology 137 (1): 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029.

machine learning↗

NASA NTRSDate not supplied

GeoAI Advances in Specific Landform Mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation.

machine learning↗

DOE OSTI2016

Storing files in a parallel computing system based on user or application specification

Techniques are provided for storing files in a parallel computing system based on a user-specification. A plurality of files generated by a distributed application in a parallel computing system are stored by obtaining a specification from the distributed application indicating how the plurality of files should be stored; and storing one or more of the plurality of files in one or more storage nodes of a multi-tier storage system based on the specification. The plurality of files comprise a plurality of complete files and/or a plurality of sub-files. The specification can optionally be processed by a daemon executing on one or more nodes in a multi-tier storage system. The specification indicates how the plurality of files should be stored, for example, identifying one or more storage nodes where the plurality of files should be stored.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

The Site-Specific Advisory Board Experience - A Members Perspective - 19069

The input of stakeholders and in particular the local community, in decisions related to environmental cleanup is critical to the success of the Department of Energy (DOE) Environmental Management (EM) mission. DOE EM engages stakeholders in a variety of ways and the Site-Specific Advisory Boards (SSABs) represent one avenue. SSABs are federally appointed citizens' panels that provide independent and unbiased advice and recommendations to the DOE EM. The Oak Ridge Site Specific Advisory Board (ORSSAB) is the citizens' panel that provides advice and recommendations to the DOE Oak Ridge Office of EM (OREM). The Board considers specific issues on a Work Plan that is developed each fiscal year through a collaborative effort. Issues are introduced through presentations by DOE OREM personnel at monthly Board meetings and further explored through field trips to specific sites (if appropriate) and subcommittee meetings. Issue groups comprised of ORSSAB members are formed and these personnel take on the task of developing a recommendation (if warranted) on the issue. The recommendation follows an approval process and when (if) approved by the Board is submitted to DOE OREM. Although the development of recommendations is the primary mission of the ORSSAB, the Chair and Vice Chair also participate in Chairs Meetings, held twice a year and comprised of the Chair and Vice Chair of each of the eight DOE EM SSAB's across the country. Additional recommendations pertinent to all the sites are developed through these collaborations. Once endorsed by the member Boards, these recommendations are submitted to DOE EM headquarters. Participation in the Chair's meetings and other engagement opportunities allow Board members to become well educated in DOE EMs mission so that recommendations can be as relevant, meaningful and specific as possible. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

SPC-70486 Rev 0 Stirling Engine Prototype Performance Specification

Idaho National Laboratory (INL) is developing a small microreactor to produce electrical power utilizing a small nuclear core and Stirling engines under the Microreactor Application Research Validation and Evaluation (MARVEL) program. The purpose of this performance specification is to define requirements to build and test the Stirling Engine prototype, including interfacing with Kinnetech in the development/test of the engines. This specification includes prototyping components only and are not for use in the reactor. Prototype testing is a preliminary test to be conducted with conceptual equipment from which a final design will be developed. The results of the testing defined herein will not be used as a qualification test. The Stirling Engines have an engine controller module (QEC). Currently, the QEC doesn’t have a means to stop the engine. An analog controlled engine braking system must be developed and tested with the engine prototype. Any conflict between this specification and any supplementary specifications in the procurement documents requires written clarification from the Contractor prior to proceeding with any work. Any deviation from the procurement documents requires approval by the Contractor with the change request process.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2021

Specific absorbed fractions for a revised series of the UF/NCI pediatric reference phantoms: internal photon sources

Assessment of radiation absorbed dose to internal organs of the body from the intake of radionuclides, or in the medical setting through the injection of radiopharmaceuticals, is generally performed based upon reference biokinetic models or patient imaging data, respectively. Biokinetic models estimate the time course of activity localized to source organs. The time-integration of these organ activity profiles are then scaled by the radionuclide S-value, which defines the absorbed dose to a target tissue per nuclear transformation in various source tissues. S-values are computed using established nuclear decay information (particle energies and yields), and a parameter termed the specific absorbed fraction (SAF). The SAF is the ratio of the absorbed fraction—fraction of particle energy emitted in the source tissue that is deposited in the target tissue—and the target organ mass. While values of the SAF may be computed using patient-specific or individual-specific anatomic models, they have been more widely available through the use of computational reference phantoms. In this study, we report on an extensive series of photon SAFs computed in a revised series of the University of Florida and the National Cancer Institute pediatric reference phantoms which have been modified to conform to the specifications embodied in the ICRP reference adult phantoms of Publication 110 (e.g. organs modeled, organ ID numbers, blood contribution to elemental compositions). Following phantom anatomical revisions, photon radiation transport simulations were performed using MCNPX v2.7 in each of the ten phantoms of the series—male and female newborn, 1 year old, 5 year old, 10 year old, and 15 year old—for 60 different tissues serving as source and/or target regions. A total of 25 photon energies were considered from 10 keV to 10 MeV along a logarithm energy grid. Detailed analyses were conducted of the relative statistical errors in the Monte Carlo target tissue energy deposition tallies at low photon energies and over all energies for source–target combinations at large intra-organ separation distances. Based on these analyses, various data smoothing algorithms were employed, including multi-point weighted data smoothing, and log–log interpolation at low energies (1 keV and 5 keV) using limiting SAF values based upon target organ mass to bound the interpolation interval. The final dataset is provided in a series of ten electronic supplemental files in MS Excel format. Finally, the results of this study were further used as the basis for assessing the radiative component of internal electron source SAFs as described in our companion paper (Schwarz et al 2021) for this same pediatric phantom series.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2021

Specific absorbed fractions for a revised series of the UF/NCI pediatric reference phantoms: internal electron sources

Assessment of radiation absorbed dose to internal organs of the body from the intake of radionuclides, or in the medical setting through the injection of radiopharmaceuticals, is generally performed based upon reference biokinetic models or patient imaging data, respectively. Biokinetic models estimate the time course of activity localized to source organs. The time-integration of these organ activity profiles are then scaled by the radionuclide S-value, which defines the absorbed dose to a target tissue per nuclear transformation in various source tissues. S-values are computed using established nuclear decay information (particle energies and yields), and a parameter termed the specific absorbed fraction (SAF). The SAF is the ratio of the absorbed fraction—fraction of particle energy emitted in the source tissue that is deposited in the target tissue—and the target organ mass. While values of the SAF may be computed using patient-specific or individual-specific anatomic models, they have been more widely available through the use of computational reference phantoms. In this study, we report on an extensive series of photon SAFs computed in a revised series of the University of Florida and the National Cancer Institute pediatric reference phantoms which have been modified to conform to the specifications embodied in the ICRP reference adult phantoms of Publication 110 (e.g. organs modeled, organ ID numbers, blood contribution to elemental compositions). Following phantom anatomical revisions, photon radiation transport simulations were performed using MCNPX v2.7 in each of the ten phantoms of the series—male and female newborn, 1 year old, 5 year old, 10 year old, and 15 year old—for 60 different tissues serving as source and/or target regions. A total of 25 photon energies were considered from 10 keV to 10 MeV along a logarithm energy grid. Detailed analyses were conducted of the relative statistical errors in the Monte Carlo target tissue energy deposition tallies at low photon energies and over all energies for source–target combinations at large intra-organ separation distances. Based on these analyses, various data smoothing algorithms were employed, including multi-point weighted data smoothing, and log–log interpolation at low energies (1 keV and 5 keV) using limiting SAF values based upon target organ mass to bound the interpolation interval. The final dataset is provided in a series of ten electronic supplemental files in MS Excel format. Finally, the results of this study were further used as the basis for assessing the radiative component of internal electron source SAFs as described in our companion paper (Schwarz et al 2021) for this same pediatric phantom series.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Impact of anharmonicity on the vibrational entropy and specific heat of UO 2

The impact of anharmonicity on the vibrational entropy and heat capacity of UO 2 has been discovered from 10 to 1200 K using inelastic neutron-scattering measurements of the phonon density of states (PDOS). Small changes in the PDOS are observed from 10 to 295 K, with more noticeable changes appearing in the 750- and 1200-K data. The specific heat determined from the PDOS measurements is in agreement with macroscopic specific heat measurements, and the overall impact of nondilation anharmonicity on the specific heat has been shown to be less than 2%. An analysis of the phonon measurements shows that the softening of acoustic phonons with temperature is consistent with the quasiharmonic approximation. The optical phonons deviate from the quasiharmonic prediction, with the low-energy optical phonons between approximately 20 and 50 meV softening more than expected, while the higher-energy optical phonons between approximately 50 and 80 meV have no appreciable softening over the temperature range measured. The observation of a small anharmonic specific heat contribution has been demonstrated to be the result of relatively large energy-dependent anharmonic effects which have opposite sign, leading to a total contribution near zero.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Spatial Study 2021: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, pH, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides two-hour time series hydrological and water chemistry sensor data, manual chamber open channel respiration data, handheld sensor water chemistry data, river substrate grain size photos, general environmental context photos, and field metadata (including qualitative information on instream and river corridor characteristics) collected during the same two-week period at 47 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Grain size photos can be used to improve estimates of channel substrate D50 data. Related sample-based water chemistry data are published separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898914.This dataset is comprised of four main folders, one containing three sensor-specific subfolders and the others containing photographs. The SFA_SpatialStudy_2021_SensorData main data folder includes file-level metadata (FLMD), data dictionary (dd), installation methods, field metadata, Ultrameter water chemistry data, field data collection protocols, international generic sample number (IGSN) mapping file, and a readme file. The “Sensor_Manual_Specifications” subfolder contains pdf files from the manufacturer of each sensor with details on the sensor specifications. Each sensor subfolder (BarotrollAtm, MantaRiver, and MinidotManualChamber) contains a sensor data subfolder for timeseries data and a subfolder for plots and summary statistics. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL pressure and temperature data. The MantaRiver Data subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and pH data. The MinidotManualChamber Data subfolder contains PME MiniDOT Logger dissolved oxygen (mg/L and percent saturation) and temperature data. The folder SFA_SpatialStudy_2021_EnvironmentalContextPhotos contains environmental context photographs and videos. The folders SFA_SpatialStudy_2021_SedimentQuadratPhotos_Part1 and SFA_SpatialStudy_2021_SedimentQuadratPhotos_Part2 contain sediment quadrat photographs. All files are .csv, .pdf, .R, .jpg, .jpeg, .mp4, or .mov. This data package was originally published September 2022. It was updated January 2023 (modified files) and June 2024 (new and modified files). See the change history in data package readme for more details.We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2012

Specification and Design of Electrical Flight System Architectures with SysML

Modern space flight systems are required to perform more complex functions than previous generations to support space missions. This demand is driving the trend to deploy more electronics to realize system functionality. The traditional approach for the specification, design, and deployment of electrical system architectures in space flight systems includes the use of informal definitions and descriptions that are often embedded within loosely coupled but highly interdependent design documents. Traditional methods become inefficient to cope with increasing system complexity, evolving requirements, and the ability to meet project budget and time constraints. Thus, there is a need for more rigorous methods to capture the relevant information about the electrical system architecture as the design evolves. In this work, we propose a model-centric approach to support the specification and design of electrical flight system architectures using the System Modeling Language (SysML). In our approach, we develop a domain specific language for specifying electrical system architectures, and we propose a design flow for the specification and design of electrical interfaces. Our approach is applied to a practical flight system.

specifications↗

DOE OSTI2017

Model-based verification of I and C specifications - 184

In the field of nuclear I and C (Instrumentation and Control), the late detection of errors in the specifications and the design of I and C has a strong impact in terms of time and money. The early verification in the V cycle of I and C functions is a key issue to capture inconsistencies and errors before the implementation and on-site tests. EDF, in the framework of the collaborative project CONNEXION, has investigated methods based on simulation to formalize I and C requirements and to evaluate them at the conceptual and basic design phases. Behavioral models of the physic parts of the system and I and C functions, described as functional diagrams, are co-simulated in an integration environment based on the FMI (Functional Mockup Interface) standard. In this specific environment, test scenarios are performed on these models. These scenarios are defined on the basis of a high level model of the studied system that takes into account the states to cover (in normal and degraded situations). Requirements, once formalized, are translated into observers that evaluate their fulfillment during the simulations. Simulation logs are then a tool for the designer to analyze the causes of the possible non-fulfillment of requirements and to fix the corresponding errors in the specifications. The proposed methodology enables to detect errors in the specifications of I and C functions, to generate automatically functional test scenarios taking into account the coverage of the requirements and all the different operational modes of the system. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1994

Initiating Formal Requirements Specifications with Object-Oriented Models

This paper reports results of an investigation into the suitability of object-oriented models as an initial step in developing formal specifications. The requirements for two critical system-level software modules were used as target applications. It was found that creating object-oriented diagrams prior to formally specifying the requirements enhanced the accuracy of the initial formal specifications and reduced the effort required to produce them. However, the formal specifications incorporated some information not found in the object-oriented diagrams, such as higher-level strategy or goals of the software.

requirements specifications↗

DOE OSTI2023

Structural and functional validation of a highly specific Smurf2 inhibitor

Smurf1 and Smurf2 are two closely related member of the HECT (homologous to E6AP carboxy terminus) E3 ubiquitin ligase family and play important roles in the regulation of various cellular processes. Both were initially identified to regulate transforming growth factor‐β and bone morphogenetic protein signaling pathways through regulating Smad protein stability and are now implicated in various pathological processes. Generally, E3 ligases, of which over 800 exist in humans, are ideal targets for inhibition as they determine substrate specificity; however, there are few inhibitors with the ability to precisely target a particular E3 ligase of interest. In this work, we explored a panel of ubiquitin variants (UbVs) that were previously identified to bind Smurf1 or Smurf2. In vitro binding and ubiquitination assays identified a highly specific Smurf2 inhibitor, UbV S2.4, which was able to inhibit ligase activity with high potency in the low nanomolar range. Orthologous cellular assays further demonstrated high specificity of UbV S2.4 toward Smurf2 and no cross‐reactivity toward Smurf1. Structural analysis of UbV S2.4 in complex with Smurf2 revealed its mechanism of inhibition was through targeting the E2 binding site. In summary, we investigated several protein‐based inhibitors of Smurf1 and Smurf2 and identified a highly specific Smurf2 inhibitor that disrupts the E2–E3 protein interaction interface.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Method for Accurate Determination of the Electron Contribution: Specific Heat of Ba 0.59 K 0.41 Fe 2 As 2

Twenty two years after the opening of the field of high temperature superconductivity by Georg Bednorz and Alex Müller a new addition to this class of materials, namely the iron-pnictides and chalcogenides, perplexes the scientific community. Making use of the accumulated wisdom, a great deal of their physics has been “mapped” in record time using all available measurement techniques. Among these, specific-heat has been proven a powerful and unique technique in the study of physical properties of bulk materials, especially of superconductors. We report here specific-heat measurements on the nearly optimally doped iconic iron-arsenide superconductor Ba 0.59 K 0.41 Fe 2 As 2 . We use a new method, based on direct comparisons of α-model expressions for the electron contribution with the measured total specific heat, to extract the electron contribution. It circumvents the need in the conventional analyses for an independent, necessarily approximate, determination of the lattice contribution, which is subtracted from the total to obtain the electron contribution, and it eliminates the consequent uncertainties in the electron contribution. For Ba 0.59 K 0.41 Fe 2 As 2 the electron density of states is comprised of contributions from two electron bands with superconducting-state energy gaps differing by a factor 3.8, with 77% coming from the band with the larger gap. The vortex-state specific heat suggests nodeless gaps. Comparison of the normal-state density of states with band-structure calculations shows an extraordinarily large effective mass enhancement, for which there is no precedent in simple metals and no theoretical explanation.

Conventional Analysis↗

DOE OSTI2019

Negative specific heat from non-planar interactions and small black holes in AdS/CFT

The gravity side of the gauge/gravity duality predicts the existence of small black holes with negative specific heat. A free theory of strings has a Hagedorn behavior, but it does not lead to negative specific heat. To understand such states one needs to consider a theory of interacting strings. In the dual gauge theory, the string interactions are related to non-planar diagrams. In this paper the simplest gauge matrix model of two free matrices, that has Hagedorn behavior is analyzed in detail. A simple double trace deformation of the Hamiltonian, proportional to square of the free Hamiltonian square with a negative sign that mimics a gravitational attraction is enough to produce states with negative specific heat perturbatively and one can still compute the equation of state relating the entropy and the energy. A more general argument based on non-planar interactions that are random and that grow faster in strength than the energy suggests that states with negative specific heat appear generically.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Biochemical Properties and Catalytic Specificity of a Novel Neutral Serine Peptidase Secreted by Fungus Pyrenochaetopsis sp

The fungal genus Pyrenochaetopsis has received particular attention because of its different lifestyles, such as numerous plant pathogenic, saprophytic, and endophytic species. Its ability to infect plant cells relies heavily upon secreted peptidases. Here, we investigated the biochemical properties and catalytic specificity of a new serine peptidase secreted by the filamentous fungus Pyrenochaetopsis sp. We found that while this neutral serine peptidase displayed optimal activity at a pH of 7.0 and temperature of 45 °C, it tolerated a wide range of pH conditions and temperatures lower than 45 °C. Its peptidase activity was depressed by some metallic ions (such as aluminum, cobalt, and copper (II) chloride) and enhanced by others (such as sodium, lithium, magnesium, potassium, calcium, and manganese). Lastly, the enzyme showed the greatest specificity for non-polar amino acids, particularly leucine and isoleucine, and moderate specificity for basic and neutral polar amino acids. It displayed the least specificity for acidic residues.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Rapid PD-L1 detection in tumors with PET using a highly specific peptide

Molecular imaging can report on the status of the tumor immune microenvironment and guide immunotherapeutic strategies to enhance the efficacy of immune modulation therapies. Imaging agents that can rapidly report on targets of immunomodulatory therapies are few. The programmed death ligand 1 (PD-L1) is an immune checkpoint protein over-expressed in several cancers and contributes to tumor immune suppression. Tumor PD-L1 expression is indicative of tumor response to PD-1 and PD-L1 targeted therapies. Herein, we report a highly specific peptide-based positron emission tomography (PET) imaging agent for PD-L1. We assessed the binding modes of the peptide WL12 to PD-L1 by docking studies, developed a copper-64 labeled WL12 ([{sup 64}Cu]WL12), and performed its evaluation in vitro, and in vivo by PET imaging, biodistribution and blocking studies. Our results show that [{sup 64}Cu]WL12 can be used to detect tumor PD-L1 expression specifically and soon after injection of the radiotracer, to fit within the standard clinical workflow of imaging within 60 min of administration. - Highlights: • A highly specific PD-L1 binding peptide, WL12, was developed as a PET imaging agent. • [{sup 64}Cu]WL12 demonstrates specific binding to PD-L1 in vitro and in vivo. • [{sup 64}Cu]WL12-PET allows PD-L1 detection in cancers within 60 min of administration. • WL12 binding interactions with PD-L1 overlaps with that of PD-1.

60 APPLIED LIFE SCIENCES↗