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Designed to be the world's most comprehensive, open, and collaborative energy information network, Open Energy Information (OpenEI - openei.org) supplies essential energy data to decision makers and supports a global energy transformation. The platform, sponsored by the U.S. Department of Energy (DOE) and developed by the National Renewable Energy Laboratory (NREL), is intended for globalcontribution and collaboration.
Today, due to great technological advancements, it is possible to study everything at the same time. This ability has given birth to “totality” studies in the fields of genomics, transcriptomics, proteomics, and metabolomics. In turn, the combined study of all these global analyses gave birth to the field of systems biology. Another “totality” field brought to life with new emerging technologies is structural genomics, an effort to determine the three-dimensional structure of every protein encoded in a genome. The Seattle Structural Genomics Center for Infectious Disease (SSGCID) is a specialized structural genomics effort composed of academic (University of Washington), government (Pacific Northwest National Laboratory), not-for-profit (Seattle BioMed), and commercial (Emerald BioStructures) institutions that is funded by the National Institute of Allergy and Infectious Diseases (Federal Contract: HHSN272200700057C and HHSN27220120025C) to apply genome-scale approaches in solving protein structures from biodefense organisms, as well as those causing emerging and re-emerging disease. In five years over 540 structures have been deposited into the Protein Data Bank (PDB) by SSGICD. About one third of all SSGCID structures contain bound ligands, many of which are metabolites or metabolite analogues present in the cell. These proteins structures are the blueprints for the structure-based design of the next generation of drugs against bacterial pathogens and other infectious diseases. Many of the selected SSGCID targets are annotated enzymes from known metabolomic pathways essential to cellular vitality since selectively “knocking-out” one of the enzymes in an important pathway with a drug may be fatal to the organism. One reason metabolomic pathways are important is because of the small molecules, or metabolites, produced at various steps in these pathways and identified by metabolomic studies. Unlike genomics, transcriptomics, and proteomics that may be influenced by epigenetic, post-transcriptional, and post-translational modifications, respectively, the metabolites present in the cell at any one time represent downstream biochemical endproducts, and therefore, metabolite profiles may be most closely associated with a phenotype and provide valuable information for infectious disease research. Metabolomic data would be even more useful if it could be linked to the vast amount of structural genomics data. Towards this goal SSGCID has created an automated website (http://apps.sbri.org/SSGCIDTargetStatus/Pathway) that assigns selected SSGCID target proteins to MetaCyc pathways (http://metacyc.org/). Details of this website will be provided here. The SSGCID-Pathway website represents a first big step towards linking metabolites and metabolic pathways to structural genomic data with the goal of accelerating the discovery of new agents to battle infectious diseases.
Frenchman Flat basin on the Nevada National Security Site (NNSS) contains Corrective Action Unit (CAU) 98, which is comprised of ten underground nuclear test locations. Environmental management of these test locations is part of the Underground Test Area (UGTA) Activity conducted by the U.S. Department of Energy (DOE) under the Federal Facility Agreement and Consent Order (FFACO) (1996, as amended) with the U.S. Department of Defense (DOD) and the State of Nevada. A Corrective Action Decision Document (CADD)/Corrective Action Plan (CAP) has been approved for CAU 98 (DOE, 2011). The CADD/CAP reports on the Corrective Action Investigation that was conducted for the CAU, which included characterization and modeling. It also presents the recommended corrective actions to address the objective of protecting human health and the environment. The recommended corrective action alternative is “Closure in Place with Modeling, Monitoring, and Institutional Controls.” The role of monitoring is to verify that Contaminants of Concern (COCs) have not exceeded the Safe Drinking Water Act (SDWA) limits (Code of Federal Regulations, 2014) at the regulatory boundary, to ensure that institutional controls are adequate, and to monitor for changed conditions that could affect the closure conditions. The long-term closure monitoring program will be planned and implemented as part of the Closure Report stage after activities specified in the CADD/CAP are complete. Groundwater at the NNSS has been monitored for decades through a variety of programs. Current activities were recently consolidated in an NNSS Integrated Sampling Plan (DOE, 2014). Although monitoring directed by the plan is not intended to meet the FFACO long-term monitoring requirements for a CAU (which will be defined in the Closure Report), the objective to ensure public health protection is similar. It is expected that data collected in accordance with the plan will support the transition to long-term monitoring at each CAU. The sampling plan is designed to ensure that monitoring activities occur in compliance with the UGTA Quality Assurance Plan (DOE, 2012). The sampling plan should be referenced for Quality Assurance (QA) elements and procedures governing sampling activities. The NNSS Integrated Sampling Plan specifies the groundwater monitoring that will occur in CAU 98 until the long-term monitoring program is approved in the Closure Report. The plan specifies the wells that must be monitored and categorizes them by their sampling objective with the associated analytical requirements and frequency. Possible sample collection methods and required standard operating procedures are also presented. The intent of this handbook is to augment the NNSS Integrated Sampling Plan by providing well-specific details for the sampling professional implementing the Sampling Plan in CAU 98, Frenchman Flat. This handbook includes each CAU 98 well designated for sampling in the NNSS Integrated Sampling Plan. The following information is provided in the individual well sections: 1. The purpose of sampling. 2. A physical description of the well. 3. The chemical characteristics of the formation water. 4. Recommended protocols for purging and sampling. The well-specific information has been gathered from numerous historical and current sources cited in each section, but two particularly valuable resources merit special mention. These are the USGS NNSS website (http://nevada.usgs.gov/doe_nv/ntsarea5.cfm) and the UGTA Field Operations website (https://ugta.nv.doe.gov/sites/Field%20Operations/default.aspx). 2 Land surface elevation and measuring point for water level measurements in Frenchman Flat were a focus during CAU investigations (see Appendix B, Attachment 1 in Navarro-Intera, 2014). Both websites listed above provide information on the accepted datum for each well. A summary is found on the home page for the well on the USGS website. Additional information is available through a link in the “Available Data” section to an “MP diagram” with a photo annotated with the datum information. On the UGTA Field Operations well page, the same information is in the “Wellhead Diagram” link. Well RNM-2s does not have an annotated photo at this time. All of the CAU 98 monitoring wells are located within Area 5 of Frenchman Flat, with the exception of ER-11-2 in Area 11 (Figure 1). The wells are clustered in two areas: the northern area (Figure 2) and the central area (Figure 3). Each well is discussed below in geographic order from north to south as follows: ER-11-2, ER-5-3 shallow piezometer, ER-5-3-2, ER-5-5, RNM-1, RNM-2s, and UE-5n.
Phycobilisomes (PBSs) are the major photosynthetic light-harvesting complexes in cyanobacteria and red algae. PBS, a multisubunit protein complex, has two major interfaces that comprise intrinsically disordered regions (IDRs): rod–core and core-membrane. IDRs do not form regular, three-dimensional structures on their own. Their presence in the photosynthetic pigment–protein complexes portends their structural and functional importance. A recent model suggests that PB-loop, an IDR located on the PBS subunit ApcE and C-terminal extension (CTE) of the PBS subunit ApcG, forms a structural protrusion on the PBS core-membrane side, facing the thylakoid membrane. Here, the structural synergy between the rod–core region and the core-membrane region was investigated using quantitative mass spectrometry (MS). The AlphaFold-predicted CpcG-CTE structure was first modeled onto the PBS rod–core region, guided and justified by the isotopically encoded structural MS data. Quantitative cross-linking MS analysis revealed that the structural proximity of the PB-loop in ApcE and ApcG-CTE is significantly disturbed in the absence of six PBS rods, which are attached to PBS via CpcG-CTE, indicative of drastic conformational changes and decreased structural integrity. Furthermore, these results suggest that CpcG-rod attachment on the PBS rod–core side is essentially required for the PBS core-membrane structural assembly. The hypothesized long-range synergy between the rod–core interface (where the orange carotenoid protein also functions) and the terminal energy emitter of PBS must have important regulatory roles in PBS core assembly, light-harvesting, and excitation energy transmission. These data also lend strategies that genetic truncation of the light-harvesting antennas aimed for improved photosynthetic productivity must rely on an in-depth understanding of their global structural integrity.
In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.
In recent years, network bandwidth requirements have scaled multiple folds, pushing the need for the development of data exchange mechanisms at 100 Gb/s and beyond. High performance computing, climate modeling, large-scale storage, and collaborative scientific research are examples of applications that can greatly benefit by leveraging high bandwidth capabilities of the order of 100 Gb/s. Such requirements and advances in IEEE Ethernet standards, Optical Transport Unit4 (OTU4), and host-system interconnects demand a network infrastructure supporting throughput rates of the order of 100 Gb/s with a single wavelength. To address such a demand Acadia Optronics in collaboration with the University of New Mexico, proposed and developed a end-system Network Interface Controller (NIC) for the 100Gbps WANs. Acadia’s 100G NIC employs an FPGA based system with a high-performance processor interconnect (PCIe 3.0) and a high capacity optical transmission link (CXP) to provide data transmission at the rate of 100 Gbps.
The Colorado School of Mines (CSM) was awarded a grant by the National Energy Technology Laboratory (NETL), Department of Energy (DOE) to conduct a research project en- titled GIS- and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development in October of 2008. The ultimate goal of this research project is to develop a water resource geo-spatial infrastructure that serves as “baseline data” for creating solutions on water resource management and for supporting decisions making on oil shale resource development. The project came to the end on September 30, 2012. This final project report will report the key findings from the project activity, major accomplishments, and expected impacts of the research. At meantime, the gamma version (also known as Version 4.0) of the geodatabase as well as other various deliverables stored on digital storage media will be send to the program manager at NETL, DOE via express mail. The key findings from the project activity include the quantitative spatial and temporal distribution of the water resource throughout the Piceance Basin, water consumption with respect to oil shale production, and data gaps identified. Major accomplishments of this project include the creation of a relational geodatabase, automated data processing scripts (Matlab) for database link with surface water and geological model, ArcGIS Model for hydrogeologic data processing for groundwater model input, a 3D geological model, surface water/groundwater models, energy resource development systems model, as well as a web-based geo-spatial infrastructure for data exploration, visualization and dissemination. This research will have broad impacts of the devel- opment of the oil shale resources in the US. The geodatabase provides a “baseline” data for fur- ther study of the oil shale development and identification of further data collection needs. The 3D geological model provides better understanding through data interpolation and visualization techniques of the Piceance Basin structure spatial distribution of the oil shale resources. The sur- face water/groundwater models quantify the water shortage and better understanding the spatial distribution of the available water resources. The energy resource development systems model reveals the phase shift of water usage and the oil shale production, which will facilitate better planning for oil shale development. Detailed descriptions about the key findings from the project activity, major accomplishments, and expected impacts of the research will be given in the sec- tion of “ACCOMPLISHMENTS, RESULTS, AND DISCUSSION” of this report.
The ecological importance of viruses is now widely recognized, yet our limited knowledge of viral sequence space and virus–host interactions precludes accurate prediction of their roles and impacts. In this study, we mined publicly available bacterial and archaeal genomic data sets to identify 12,498 high-confidence viral genomes linked to their microbial hosts. These data augment public data sets 10-fold, provide first viral sequences for 13 new bacterial phyla including ecologically abundant phyla, and help taxonomically identify 7–38% of ‘unknown’ sequence space in viromes. Genome- and network-based classification was largely consistent with accepted viral taxonomy and suggested that (i) 264 new viral genera were identified (doubling known genera) and (ii) cross-taxon genomic recombination is limited. Further analyses provided empirical data on extrachromosomal prophages and coinfection prevalences, as well as evaluation of in silico virus–host linkage predictions. Together these findings illustrate the value of mining viral signal from microbial genomes.
We propose a network architecture with a separate quantum dataplane and a conventional control plane: (a) Quantum Data Plane: The Quantum Data plane consists of links of dark fibers connecting quantum switches and repeaters, which in turn, connect to quantum computers, memory and sensors. Since the current reach is limited to local areas, it will begin as a collection of site networks at laboratories, (b) Conventional Control Plane: The Control plane provides management access to quantum devices for configuration and provisioning via control nodes with firewall and encryption capabilities. Continuous Test and Transition Infrastructure: We propose an infrastructure with a control plane connecting multiple sites via encrypted tunnels over conventional networks consisting of the following: (a) Site Quantum Networks: Individual site networks supported by their fiber plants connect laboratories that house and connect to their quantum devices for testing and interoperability.(b) Site Control Planes: Sites are connected over individual control planes with control hosts with Software Defined Networking capabilities, which can be peered with other networks via ESnet.(c) Progressive Expansion: Initially, sites will develop individual data planes with their specific quantum devices and fiber connections, and mechanisms to interface with conventional networks. They progressively expand and interconnect, under a wide-area ecosystem of peered control planes for device testing, interoperability development and roll off into production environments.
We present measurements of broad emission lines and virial estimates of supermassive black hole masses (M BH ) for a large sample of ultrahard X-ray-selected active galactic nuclei (AGNs) as part of the second data release of the BAT AGN Spectroscopic Survey (BASS/DR2). Our catalog includes M BH estimates for a total of 689 AGNs, determined from the Hα, Hβ, Mg II λ2798, and/or C IV λ1549 broad emission lines. The core sample includes a total of 512 AGNs drawn from the 70 month Swift/BAT all-sky catalog. We also provide measurements for 177 additional AGNs that are drawn from deeper Swift/BAT survey data. We study the links between M BH estimates and line-of-sight obscuration measured from X-ray spectral analysis. We find that broad Hα emission lines in obscured AGNs ($\mathrm{log}({N}_{{\rm{H}}}/{\mathrm{cm}}^{-2})\gt 22.0$) are on average a factor of ${8.0}_{-2.4}^{+4.1}$ weaker relative to ultrahard X-ray emission and about ${35}_{-12}^{\,+7}$% narrower than those in unobscured sources (i.e., $\mathrm{log}({N}_{{\rm{H}}}/{\mathrm{cm}}^{-2})\lt 21.5$). This indicates that the innermost part of the broad-line region is preferentially absorbed. Consequently, current single-epoch M BH prescriptions result in severely underestimated (>1 dex) masses for Type 1.9 sources (AGNs with broad Hα but no broad Hβ) and/or sources with $\mathrm{log}({N}_{{\rm{H}}}/{\mathrm{cm}}^{-2})\gtrsim 22.0$. We provide simple multiplicative corrections for the observed luminosity and width of the broad Hα component (L[bHα] and FWHM[bHα]) in such sources to account for this effect and to (partially) remedy M BH estimates for Type 1.9 objects. As a key ingredient of BASS/DR2, our work provides the community with the data needed to further study powerful AGNs in the low-redshift universe.
This submission includes detailed Bills of Materials for the NREL-designed and -built Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC), as well as the reverse osmosis assembly and submersible pump that are used in the HERO WEC. The WEC file is specific to the components and sub-components that are included on the in-water buoy portion of the WEC. The RO file is specific to the components and sub-components that are included on the reverse osmosis module that is used for both the hydraulic and electric configuration. The submersible pumps file is specific to the components and sub-components that are included on the submersible pump module that is used feed the reverse osmosis module when the HERO WEC is in the electric configuration. In addition to this submission, an additional submission available for the WEC model itself, including the power electronics enclosure, and reverse osmosis assembly that is needed to supply water in the electric submission. A link is provided below. More details on this project including data, CAD drawings, etc. can be found in the HERO-WEC main page link below. This data set has been developed by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.
T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has a variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.
The EDX disCO2ver Carbon Transport and Storage Planning and Viability Support Tools are made up of the Carbon Storage Planning Inquiry Tool (CS PlanIT, Justman et al. 2024) and the Carbon Storage Technical Viability Approach Support Tool (CS TVA). Together, these tools support data access to support understanding data availability to support planning efforts for carbon transport and storage. The Carbon Storage Planning Inquiry Tool (CS PlanIT) is an online web mapping application designed to help users explore, query, and evaluate multiple data layers to support and accelerate carbon storage resource and feasibility assessments and planning efforts. CS PlanIT currently contains a range of datasets associated with geologic, technical, and infrastructure factors. The data sets can be filtered geographically for an area of interest to update statistics and charts within the dashboard. The dashboard is divided into different sections called widgets, relating to different steps in the carbon storage planning process. The resources in this submission include a link to PlanIT, as well as a data catalog and link to user documentation. The original citation for the CS PlanIT tool, which has now been integrated into the toolset here, was: - Devin Justman, Scott Pantaleone, Maneesh Sharma, Lucy Romeo, Paige Morkner, CS PlanIT (Carbon Storage Planning Inquiry Tool) , 6/28/2024, https://edx.netl.doe.gov/dataset/cs-planit-carbon-storage-planning-inquiry-tool, DOI: 10.18141/2377953 The Carbon Storage Technical Viability Approach Support (CS TVA) Tool displays spatial data availability for the many components of Geologic Carbon Storage (GCS) technical viability assessment (Creason al 2025). Identifying sites suitable for GCS requires evaluating the intersection of myriad factors, including reservoir conditions, subsurface and surface hazards, infrastructure requirements, and energy community metrics. The technical viability of a site can only be confirmed for instances where all these factors have data available, and where those data support viability. Additional Resources related to the Technical Viability Assessment Tool: - Julia Mulhern, Casey White, Araceli Lara, Neyda Cordero Rodriguez, Zachary Jackson, Jacob Shay, Gabriel Creason, MacKenzie Mark-Moser, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Database, 3/26/2025, https://edx.netl.doe.gov/dataset/edx4ccs-carbon-storage-technical-viability-approach-database , DOI:10.18141/1984655 - Julia Mulhern, MacKenzie Mark-Moser, Gabriel Creason, Casey White, Araceli Lara, Neyda Cordero Rodriguez, Zach Jackson, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Matrix, 3/27/2025, https://edx.netl.doe.gov/dataset/carbon-storage-technical-viability-approach-cs-tva-matrix , DOI: 10.18141/2539979 - Gabriel Creason, Zach Jackson, Neyda Cordero Rodriguez, Julia Mulhern, Casey White, Araceli Lara, MacKenzie Mark-Moser, Paige Morkner, Kelly Rose, Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database, 3/27/2025, https://edx.netl.doe.gov/dataset/carbon-storage-technical-viability-approach-cs-tva-data-availability-results-database, DOI:10.18141/2538557
We present a multi-wavelength data analysis of the extended star-forming region S235 (hereafter E-S235), where two molecular clouds are present. In E-S235, using the {sup 12}CO (1–0) and {sup 13}CO (1–0) line data, a molecular cloud linked with the site “S235main” is traced in a velocity range [−24, −18] km s{sup −1}, while the other one containing the sites S235A, S235B, and S235C (hereafter “S235ABC”) is depicted in a velocity range [−18, −13] km s{sup −1}. In the velocity space, these two clouds are separated by ∼4 km s{sup −1}, and are interconnected by a lower-intensity intermediate velocity emission, tracing a broad bridge feature. In the velocity channel maps, a possible complementary molecular pair at [−21, −20] km s{sup −1} and [−16, −15] km s{sup −1} is also evident. The sites, “S235ABC,” east 1, and south–west, are spatially seen in the interface of two clouds. Together, these observed features are consistent with the predictions of numerical models of the cloud–cloud collision (CCC) process, favoring the onset of the CCC in E-S235 about 0.5 Myr ago. Deep UKIDSS near-infrared photometric analysis of point-like sources reveals significant clustering of young stellar populations toward the sites located at the junction, and the “S235main.” The sites “S235ABC” harbor young compact H ii regions with dynamical ages of ∼0.06–0.22 Myr, and these sites (including south–west and east 1) also contain dust clumps (having M {sub clump} ∼ 40 to 635 M{sub ⊙}). Our observational findings suggest that the star formation activities (including massive stars) appear to be influenced by the CCC mechanism at the junction.
We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.
The global Feature Extractor (gFEX) is a component of the Phase-I upgrade of the Level-1 Calorimeter (L1Calo) trigger system for the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The gFEX is used to identify patterns of energy associated with the hadronic decays of high momentum Higgs, W and Z bosons, top quarks, and exotic particles in real time at the 40 MHz LHC bunch crossing rate. Three prototypes were implemented and tested from 2014 to 2017. With the lessons learned from the prototypes, the final gFEX production board has been implemented at the end of 2017. The gFEX receives up to 300 fiber optical links from the calorimeter and transmits trigger data on 96 links to the ATLAS Level-1 Topological [1] (L1Topo) trigger at a rate of up to 12.8 Gb/s. There are also 24 electrical links on board for communication between two FPGAs running at speeds of up to 25.6 Gb/s. Here, the hardware functionality and performance of the production board have been evaluated. A data path integration test between the Liquid Argon Digital Processing Blade (LDPB) [2] and the Front End LInk eXchange (FELIX) [3] was performed successfully at CERN in 2018.
Highlights: {yields} OxLDL-induced responses in human gingival epithelial cells were studied. {yields} OxLDL enhanced the production of IL-8, IL-1{beta} and PGE{sub 2} in Ca9-22 cells. {yields} An NF-{kappa}B inhibitor suppressed the expression of COX-2 and mPGES1 induced by oxLDL. {yields} Unlike the case in macrophages, oxLDL did not increase the CD36 level. -- Abstract: Periodontitis is characterized by chronic gingival tissue inflammation, and inflammatory mediators such as IL-8 and prostaglandin E{sub 2} (PGE{sub 2}) are associated with disease progression. Previously we showed that oxidatively modified low-density lipoprotein (oxLDL) was present in gingival crevicular fluid. In this study, the role of oxLDL in the gingival epithelial cell inflammatory response was further investigated using Ca9-22 cells and primary human oral keratinocytes (HOK). Treatment of Ca9-22 cells and HOK with oxLDL induced an up-regulation of IL-8 and the PGE{sub 2}-producing enzymes, cyclooxygenase-2 and microsomal PGE{sub 2} synthase-1. These responses induced by oxLDL were significantly suppressed by a nuclear factor-kappa B (NF-{kappa}B) inhibitor. However, unlike the result in macrophages, oxLDL did not lead to an increase in CD36 expression in these two cells. These results suggest that oxLDL elicits gingival epithelial cell inflammatory responses through an activation of the NF-{kappa}B pathway. These data suggest a mechanistic link between periodontal disease and lipid metabolism-related disorders, including atherosclerosis.
Studies have shown that γ-irradiation induces various biological responses, including oxidative stress and apoptosis, as well as cellular repair and immune system responses. However, most such studies have been performed using traditional two-dimensional cell culture systems, which are limited in their ability to faithfully represent in vivo conditions. A three-dimensional (3D) environment composed of properly interconnected and differentiated cells that allow communication and cooperation among cells via secreted molecules would be expected to more accurately reflect cellular responses. Here, we investigated γ-irradiation–induced changes in the secretome of 3D-cultured keratinocytes. An analysis of keratinocyte secretome profiles following fractionated-dose γ-irradiation revealed changes in genes involved in cell adhesion, angiogenesis, and the immune system. Notably, peroxisome proliferator-activated receptor-α (PPARα) was upregulated in response to fractionated-dose γ-irradiation. This upregulation was associated with an increase in the transcription of known PPARα target genes in secretome, including angiopoietin-like protein 4, dermokine and kallikrein-related peptide 12, which were differentially regulated by fractionated-dose γ-irradiation. Collectively, our data imply a mechanism linking γ-irradiation and secretome changes, and suggest that these changes could play a significant role in the coordinated cellular responses to harmful ionizing radiation, such as those associated with radiation therapy. This extension of our understanding of γ-irradiation-induced secretome changes has the potential to improve radiation therapy strategies. - Highlights: • γ-irradiation induced changes of cell adhesion, angiogenesis, and immune system in secretome of 3D-cultured keratinocytes. • Peroxisome proliferator-activated receptor-α (PPARα) was upregulated in response to fractionated-dose γ-irradiation. • The known PPARα target genes were differentially regulated by fractionated-dose γ-irradiation.