SEARCH · Engineering Papers

Results for “PrO”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2024

In vitro selection and analysis of SARS-CoV-2 nirmatrelvir resistance mutations contributing to clinical virus resistance surveillance

To facilitate the detection and management of potential clinical antiviral resistance, in vitro selection of drug-resistant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) against the virus M pro inhibitor nirmatrelvir (Paxlovid active component) was conducted. Six M pro mutation patterns containing T304I alone or in combination with T21I, L50F, T135I, S144A, or A173V emerged, with A173V+T304I and T21I+S144A+T304I mutations showing >20-fold resistance each. Biochemical analyses indicated inhibition constant shifts aligned to antiviral results, with S144A and A173V each markedly reducing nirmatrelvir inhibition and M pro activity. SARS-CoV-2 surveillance revealed that in vitro resistance–associated mutations from our studies and those reported in the literature were rarely detected in the Global Initiative on Sharing All Influenza Data database. In the Paxlovid Evaluation of Protease Inhibition for COVID-19 in High-Risk Patients trial, E166V was the only emergent resistance mutation, observed in three Paxlovid-treated patients, none of whom experienced COVID-19–related hospitalization or death.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive.As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Materials Data on PrCuSO by Materials Project

(PrO)CuS is Parent of FeAs superconductors structured and crystallizes in the tetragonal P4/nmm space group. The structure is two-dimensional and consists of one CuS sheet oriented in the (0, 0, 1) direction and one PrO sheet oriented in the (0, 0, 1) direction. In the CuS sheet, Cu1+ is bonded to four equivalent S2- atoms to form a mixture of edge and corner-sharing CuS4 tetrahedra. All Cu–S bond lengths are 2.42 Å. S2- is bonded in a 4-coordinate geometry to four equivalent Cu1+ atoms. In the PrO sheet, Pr3+ is bonded in a 4-coordinate geometry to four equivalent O2- atoms. All Pr–O bond lengths are 2.35 Å. O2- is bonded to four equivalent Pr3+ atoms to form a mixture of edge and corner-sharing OPr4 tetrahedra.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Statistical Properties of Rainfall in Tasmania (SPORT) Field Campaign Report

The objective of this project is to complement the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility second ARM Mobile Facility (AMF2) deployment at kennaook-Cape Grim (CAPE-k) with a micro-rain radar (MRR-PRO) mounted on top of one of the ARM containers. This was done to locate the MRR-PRO close to the ARM cloud radars (Ka-band ARM Zenith Radar [KAZR] and Marine W-band ARM Cloud Radar [MWACR]). This will allow for a continuous calibration check of the ARM cloud radars against the MRR-PRO and Parsivel-2 disdrometers. Scientifically, it will add one radar frequency to the analysis of vertical profiles of cloud and precipitation properties (K-band).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Polyunsaturated Fatty Acids Mend Macrophage Transcriptome, Glycome, and Phenotype in the Patients with Neurodegenerative Diseases, Including Alzheimer’s Disease

Macrophages of healthy subjects have a pro-resolution phenotype, upload amyloid-β (Aβ) into endosomes, and degrade Aβ, whereas macrophages of patients with Alzheimer’s disease (AD) generally have a pro-inflammatory phenotype and lack energy for brain clearance of Aβ. To clarify the pathogenesis of sporadic AD and therapeutic effects of polyunsaturated fatty acids (PUFA) with vitamins B and D and antioxidants on monocyte/macrophage (MM) migration in the AD brain, MM transcripts in energy and Aβ degradation, MM glycome, and macrophage clearance of Aβ. We followed for 31.3 months (mean) ten PUFA-supplemented neurodegenerative patients: 3 with subjective cognitive impairment (SCI), 2 with mild cognitive impairment (MCI), 3 MCI/vascular cognitive impairment, 2 with dementia with Lewy bodies, and 7 non-supplemented caregivers. We examined: monocyte migration in the brain and a blood-brain barrier model by immunochemistry and electron microscopy; macrophage transcriptome by RNAseq; macrophage glycome by N-glycan profiling and LTQ-Orbitrap mass spectrometry; and macrophage phenotype and phagocytosis by immunofluorescence. MM invade Aβ plaques, upload but do not degrade Aβ, and release Aβ into vessels, which develop cerebrovascular amyloid angiopathy (CAA); PUFA upregulate energy and Aβ degradation enzyme transcripts in macrophages; PUFA enhance sialylated N-glycans in macrophages; PUFA reduce oxidative stress and increase pro-resolution MM phenotype, mitochondrial membrane potential, and Aβ phagocytosis (p < 0.001). Macrophages of SCI, MCI, and AD patients have interrelated defects in the transcriptome, glycome, Aβ phagocytosis, and Aβ degradation. PUFA mend macrophage transcriptome, enrich glycome, enhance Aβ clearance, and benefit the cognition of early-stage AD patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Structures of HIV-1 Neutralizing Antibody 10E8 Delineate the Mechanistic Basis of Its Multi-Peak Behavior on Size-Exclusion Chromatography

Antibody 10E8 is capable of effectively neutralizing HIV through its recognition of the membrane-proximal external region (MPER), and a suitably optimized version of 10E8 might have utility in HIV therapy and prophylaxis. However, 10E8 displays a three-peak profile on size-exclusion chromatography (SEC), complicating its manufacture. Here we show cis-trans conformational isomerization of the Tyr-Pro-Pro (YPP) motif in the heavy chain 3rd complementarity-determining region (CDR H3) of antibody 10E8 to be the mechanistic basis of its multipeak behavior. We observed 10E8 to undergo slow conformational isomerization and delineate a mechanistic explanation for effective comodifiers that were able to resolve its SEC heterogeneity and to allow an evaluation of the critical quality attribute of aggregation. We determined crystal structures of single and double alanine mutants of a key di-proline motif and of a light chain variant, revealing alternative conformations of the CDR H3. We also replicated both multi-peak and delayed SEC behavior with MPER-antibodies 4E10 and VRC42, by introducing a Tyr-Pro (YP) motif into their CDR H3s. Our results show how a conformationally dynamic CDR H3 can provide the requisite structural plasticity needed for a highly hydrophobic paratope to recognize its membrane-proximal epitope.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

DEM, DSM, and Cleaned LiDAR Point Cloud Data from the NGEE Arctic UAS Campaigns at the Teller 27 Field Site from 2017 and 2018, Seward Peninsula, Alaska

A Digital Elevation Model (DEM) and Digital Surface Model (DSM) were derived from airborne Light Detection and Ranging (LiDAR) data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) quadcopter and hexacopter platforms operated by Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) scientists from the EES-14 group at LANL. These data were collected in August 2017 and July 2018 at the NGEE Arctic field site near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway between Nome, Alaska and Teller, Alaska. A Vulcan Raven X8 Airframe (Mitcheldean, Gloucestershire, UK), DJI Matrice 600 Pro Airframe (Shenzhen, China), and Routescene UAV LiDARSystem (Edinburgh, Scotland, UK) were used to collect LiDAR data. Following pre-processing in Routescene LidarViewer Pro software, the LiDAR point clouds were cleaned and processed using CloudCompare software to separate ground and off-ground points. A high resolution DEM and DSM were then created using ArcGIS Pro software. This data package contains fully cleaned point clouds of ground and off-ground points (.las), a 25 cm DEM (.tif), and a 25 cm DSM (.tif) for the Teller 27 field site. Ancillary aircraft data, flight mission parameters, weather conditions, and raw lidar data and imagery can be found in the L0 datasets for these campaigns: NGA299 (2017) and NGA297 (2018). Minimally processed point clouds and auxiliary files can be found in the L1 dataset: NGA304 (2017 and 2018).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

Simulation of linear mechanical systems

A dynamics and controls analyst is typically presented with a structural dynamics model and must perform various input/output tests and design control laws. The required time/frequency simulations need to be done many times as models change and control designs evolve. This paper examines some simple ways that open and closed loop frequency and time domain simulations can be done using the special structure of the system equations usually available. Routines were developed to run under Pro-Matlab in a mixture of the Pro-Matlab interpreter and FORTRAN (using the .mex facility). These routines are often orders of magnitude faster than trying the typical 'brute force' approach of using built-in Pro-Matlab routines such as bode. This makes the analyst's job easier since not only does an individual run take less time, but much larger models can be attacked, often allowing the whole model reduction step to be eliminated.

Sirlin, S. W.↗

NASA NTRS2005

SQL-RAMS

SQL-RAMS (where "SQL" signifies Structured Query Language and "RAMS" signifies Rocketdyne Automated Management System) is a successor to the legacy version of RAMS a computer program used to manage all work, nonconformance, corrective action, and configuration management on rocket engines and ground support equipment at Stennis Space Center. The legacy version resided in the FileMaker Pro software system and was constructed in modules that could act as stand-alone programs. There was little or no integration among modules. Because of limitations on file-management capabilities in FileMaker Pro, and because of difficulty of integration of FileMaker Pro with other software systems for exchange of data using such industry standards as SQL, the legacy version of RAMS proved to be limited, and working to circumvent its limitations too time-consuming. In contrast, SQL-RAMS is an integrated SQL-server-based program that supports all data-exchange software industry standards. Whereas in the legacy version, it was necessary to access individual modules to gain insight to a particular work-status documents, SQL-RAMS provides access through a single-screen presentation of core modules. In addition, SQL-RAMS enable rapid and efficient filtering of displayed statuses by predefined categories and test numbers. SQL-RAMS is rich in functionality and encompasses significant improvements over the legacy system. It provides users the ability to perform many tasks which in the past required administrator intervention. Additionally many of the design limitations have been corrected allowing for a robust application that is user centric.

Alfaro, Victor O.↗

NASA NTRS2005

SQL-RAMS

SQL-RAMS (where "SQL" signifies Structured Query Language and "RAMS" signifies Rocketdyne Automated Management System) is a successor to the legacy version of RAMS -- a computer program used to manage all work, nonconformance, corrective action, and configuration management on rocket engines and ground support equipment at Stennis Space Center. The legacy version resided in the File-Maker Pro software system and was constructed in modules that could act as standalone programs. There was little or no integration among modules. Because of limitations on file-management capabilities in FileMaker Pro, and because of difficulty of integration of FileMaker Pro with other software systems for exchange of data using such industry standards as SQL, the legacy version of RAMS proved to be limited, and working to circumvent its limitations too time-consuming. In contrast, SQL-RAMS is an integrated SQL-server-based program that supports all data-exchange software industry standards. Whereas in the legacy version, it was necessary to access individual modules to gain insight into a particular workstatus document, SQL-RAMS provides access through a single-screen presentation of core modules. In addition, SQL-RAMS enables rapid and efficient filtering of displayed statuses by predefined categories and test numbers. SQL-RAMS is rich in functionality and encompasses significant improvements over the legacy system. It provides users the ability to perform many tasks, which in the past required administrator intervention. Additionally, many of the design limitations have been corrected, allowing for a robust application that is user centric.

Alfaro, Victor O.↗

DOE OSTI2024

Reduction of Chemokine CXCL9 Expression by Omega-3 Fatty Acids via ADP-Ribosylhydrolase ARH3 in MIN6 Insulin-Producing Cells

Type 1 diabetes (T1D) results from the autoimmune destruction of the insulin-producing β cells of the pancreas. Omega-3 fatty acids protect β cells and reduce the incidence of T1D, but the mechanism is poorly understood. We have shown that omega-3 fatty acids reduce pro-inflammatory cytokine-mediated β-cell apoptosis by upregulating the expression of the ADP-ribosylhydrolase ARH3. Here, we further investigate the β-cell protection mechanism of ARH3 by performing siRNA analysis of its gene Adprhl2 in MIN6 insulin-producing cells, subsequent treatment with a cocktail of the pro-inflammatory cytokines IL-1β + IFN-γ + TNF-α, followed by proteomics analysis. ARH3 regulated proteins from several pathways related to the nucleus (splicing, RNA surveillance, and nucleocytoplasmic transport), mitochondria (metabolic pathways), and endoplasmic reticulum (protein folding). ARH3 also regulated the levels of proteins related to antigen processing and presentation, and the chemokine-signaling pathway. We further studied the role of ARH3 in regulating the chemokine CXCL9. We found that ARH3 reduces the cytokine-induced expression of CXCL9, which is dependent on omega-3 fatty acids. In conclusion, we demonstrate that omega-3 fatty acids regulate CXCL9 expression via ARH3, which may have a role in protecting β cells from immune attack thereby preventing T1D development.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Metabolic engineering of non-pathogenic microorganisms for 2,3-butanediol production

2,3-Butanediol (2,3-BDO) is a promising commodity chemical with various industrial applications. While petroleum-based chemical processes currently dominate the industrial production of 2,3-BDO, fermentation-based production of 2,3-BDO pro- vides an attractive alternative to chemical-based processes with regards to economic and environmental sustainability. The achievement of high 2,3-BDO titer, yield, and productivity in microbial fermentation is a prerequisite for the production of 2,3-BDO at large scales. Also, enantiopure production of 2,3-BDO production is desirable because 2,3-BDO stereoisomers have unique physicochemical properties. Pursuant to these goals, many metabolic engineering strategies to improve 2,3-BDO pro- duction from inexpensive sugars by Klebsiella oxytoca, Bacillus species, and Saccharomyces cerevisiae have been developed. Furthermore, this review summarizes the recent advances in metabolic engineering of non-pathogenic microorganisms to enable efficient and enantiopure production of 2,3-BDO.

2,3-BDO stereoisomers↗

DOE OSTI2023

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV- 2 main protease

Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML) approaches followed by experimental validation. Generative deep learning models have been recently developed that can generate thousands of new candidates, but their physiochemical properties are typically not optimized. Using our deep learning models and a scaffold as a starting point, we generated tens of thousands of compounds for SARS-CoV-2 M pro that preserve the core scaffold. Here we utilized and implemented several computational tools such as structural alert and toxicity analysis, high throughput virtual screening, ML-based 3D quantitative structure–activity relationships, multi-parameter optimization, and graph neural networks on libraries of generated candidates to predict biological activity and binding affinity a priori. From these collective computational results, eight promising candidates were identified and tested experimentally using Native Mass Spectrometry (MS) and FRET-based functional assays. Two compounds, with quinazoline-2-thiol and acetylpiperidine core moiety showed IC 50 values in the low micromolar range: 2.95±0.0017 µM and 3.41±0.0015 µM, respectively. The molecular dynamics simulations further highlight that binding of these compounds results in allosteric modulations in the chain B and the interface domains of the M pro . The key fragments from these top hits can be used as input for closed loop lead optimization in the integrated pipeline.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Identification of a Covalent Molecular Inhibitor of Anti-apoptotic BFL-1 by Disulfide Tethering

The BCL-2 family is composed of anti- and pro-apoptotic members that respectively protect or disrupt mitochondrial integrity. Anti-apoptotic overexpression can promote oncogenesis by trapping the BCL-2 homology 3 (BH3) “killer domains” of pro-apoptotic proteins in a surface groove, blocking apoptosis. Groove inhibitors, such as the relatively large BCL-2 drug venetoclax (868 Da), have emerged as cancer therapies. BFL-1 remains an undrugged oncogenic protein and can cause venetoclax resistance. Having identified a unique C55 residue in the BFL-1 groove, we performed a disulfide tethering screen to determine if C55 reactivity could enable smaller molecules to block BFL-1's BH3-binding functionality. We found that a disulfide-bearing N-acetyltryptophan analog (304 Da adduct) effectively targeted BFL-1 C55 and reversed BFL-1-mediated suppression of mitochondrial apoptosis. Structural analyses implicated the conserved leucine-binding pocket of BFL-1 as the interaction site, resulting in conformational remodeling. Thus, therapeutic targeting of BFL-1 may be achievable through the design of small, cysteine-reactive drugs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Comprehensive proteomics analysis of stressed human islets identifies GDF15 as a target for type 1 diabetes intervention

Type 1 diabetes results from the progressive loss of beta cells, a process propagated by pro-inflammatory cytokine signaling that disrupts the balance between the expression of pro- and anti-apoptotic proteins. To identify such proteins, we performed comprehensive proteomics of human pancreatic islets treated with interleukin-1ß and interferon-?, leading to the identification of 11,325 proteins, of which 387 were significantly regulated by treatment. We then tested the function of growth/differentiation factor 15 (GDF15), which was repressed by the cytokine treatment. We found that GDF15 translation was blocked during inflammation, while the addition of exogenous GDF15 inhibited interleukin-1ß/interferon-?-induced apoptosis of human islets and a human beta-cell line. Furthermore, administration of GDF15 significantly decreased insulitis in NOD mice. Our approach provides a unique resource for the identification of the human islet proteins regulated by cytokines and was effective in discovering a potential target for type 1 diabetes therapy.

Nakayasu, Ernesto S.↗

DOE OSTI2023

Cecropin P1 antimicrobial peptide modulates differential expression of immune relevant genes in rainbow trout ( Oncorhynchus mykiss ) gill cell line, RTgill-W1

Accumulated evidence indicates that antimicrobial peptides modulate immune activities in fish. In this study, we profiled the differential expression patterns of representative immune relevant genes in an epithelial-like cell line of rainbow trout gill, RTgill-W1, in response to exposure of cecropin P1 antimicrobial peptide. RTgill-W1 cells were treated with synthetic cecropin P1 over time (0, 2, 4 and 24 h) with or without the present of lipopolysaccharide (LPS) or polyinosinic polycytidylic acid (PolyI:C). The relative abundances of each mRNA were measured by real-time quantitative PCR. The dose-response study revealed significant perturbations of mRNA levels of genes related to pro-inflammation, acute phase, surface proteins and transcription factors at 30 μM of cecropin P1. In addition, cecropin P1 altered the differential expression patterns that were induced by LPS or PolyI:C, at different time points in RTgill-W1. Overall, our results indicate that cecropin P1 exhibits pro-inflammation activity, modulate cell-cell interaction and cytokine signal transduction in rainbow trout gill cell, and may suggest a potential application of this peptide as an immune adjuvant for disease control in aquaculture.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Genetic algorithm optimization of a chemical kinetic mechanism for propane at engine relevant conditions

Propane has demonstrated significant potential for reductions in greenhouse gas and pollutant emissions in medium- and heavy-duty engine applications, but further improvements require accurate, compact, and scalable chemical kinetic mechanisms to design the next generation of propane fueled engines, particularly at the boosted operating conditions necessary to meet the power density demand of medium- and heavy-duty applications. In this work, six key chemical reactions were identified in a reduced mechanism with 70 species and 352 reactions through a sensitivity analysis performed at conditions typical of thermodynamic trajectories observed in a high compression ratio, long stroke engine operated on propane from throttled to boosted operating conditions. While the original mechanism was validated against rapid compression machine (RCM) data, it was found to overpredict experimental autoignition tendencies in 2-zone, 0-D SI engine simulations performed in Chemkin Pro. Subsequently, a genetic algorithm approach was used to optimize the six reaction rate parameters within established uncertainty bounds by performing RCM simulations and comparing to two independent sets of literature ignition delay times for propane, thus generating two new kinetic mechanisms. The first optimization achieved a mean absolute percent error (MPE) reduction in 2nd stage ignition delay of 61.4% in seven generations, while the second optimization utilized a newer experimental RCM dataset, and achieved MPE reduction of 56.7% in seven generations, and further marginal improvement to 57.8% reduction in 34 generations. Finally, the two mechanisms were then evaluated again in the 2-zone 0-D SI engine model in Chemkin Pro comparing typical mean and knocking cycle trajectories, and it was found that the second optimized mechanism provided better prediction of knock onset at the representative conditions evaluated in this work, particularly for higher load operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗