Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Occupancy”

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.

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

At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings

In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL) proved to be effective in optimizing the management of integrated energy systems in buildings, reducing energy costs and improving indoor comfort conditions when compared to traditional reactive controllers. However, the scalability and implementation of DRL controllers are still limited since they require a considerable amount of time before converging to a near-optimal solution. This issue is currently addressed in literature through the offline pre-training of the DRL agent. However this solution results in two main critical issues: (1) the need to develop a building surrogate model to perform the training task, and (2) the need to perform a fine-tuning process over several training episodes to obtain a near-optimal control policy. In this context, this paper introduces an Online Transfer Learning (OTL) strategy that exploits two knowledge-sharing techniques, weight-initialization and imitation learning, to transfer a DRL control policy from a source office building to various target buildings in a simulation environment coupling EnergyPlus and Python. A DRL controller based on discrete Soft Actor–Critic (SAC) is trained on the source building to manage the operation of a cooling system consisting of a chiller and a thermal storage. Several target buildings are defined to benchmark the performance of the OTL strategy with that of a Rule-Based Controller (RBC) and two DRL-based control strategies, deployed in offline and online fashion. The strategy adopted for OTL emulates the real world implementation with a simulation process by implementing the transferred DRL agent for a single episode in the target buildings. Target buildings have the same geometrical features and are served by the same energy system as the source building, but differ in terms of weather conditions, electricity price schedules, occupancy patterns, and building envelope efficiency levels. The results show that the OTL strategy can reduce the cumulated sum of temperature violations on average by 50% and 80% respectively when compared to RBC and online DRL while enhancing the energy system operation with electricity cost savings ranging between 20% and 40%. Furthermore, the OTL agent performs slightly worse than the offline DRL controller but it does not require any modeling effort and can be implemented directly on target buildings emulating a real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Household energy resilience in extreme weather events: An investigation of energy service importance, HVAC usage behaviors, and willingness to pay

Household energy resilience, particularly maintaining essential energy services within an acceptable and affordable level, is critical during extreme weather events (e.g., winter storms, heat waves) with power shortages or outages. However, the research on the importance and acceptable compromise levels of energy services, HVAC usage behavior changes, and willingness to pay (WTP) for energy services during disasters is limited. Therefore, this study investigates the importance and compromise of household energy services, HVAC usage behaviors, and WTP, as three key dimensions of household energy resilience, in both normal days and disaster scenarios through surveys (n=485). First, 12 common residential end-uses are grouped into high, mid, and low-priority services using hierarchical clustering, in which high-priority services (perceived as important and un-compromisable) include food cooking and storage (refrigerator and freezer) and thermal comfort (space heating and cooling), mid-priority services involve water heating and lighting, while low-priority services are mostly related to entertainment and housework (e.g., TV, laundry). Also, HVAC use patterns demonstrate that occupants become more energy conservative during disasters, e.g., reducing durations of running HVAC and adjusting temperature setpoints to save energy. In terms of energy cost, approximately 60% of respondents are willing to pay more to maintain energy services during disasters, although only 13% are prepared to pay over double the normal energy prices. The regression models further reveal that household energy resilience varies across different sociodemographic groups (e.g., age, income, family size) and is impacted by disaster experience and beliefs in clean energy and climate. In conclusion, these research findings provide important perspectives to understand household energy resilience and inform measures for disaster adaptation of households in extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom

Energy-efficient ventilation control plays an important role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate representations of indoor airflow, their high computational cost limits their use in real-time building control. In this work, we present a neural operator learning framework that combines the physical accuracy of CFD with the computational efficiency of machine learning to enable building ventilation control with the high-fidelity fluid dynamics models. Our method jointly optimizes the airflow supply rates and vent angles to reduce energy use and adhere to air quality constraints. We train an ensemble of neural operator transformer models to learn the mapping from building control actions to airflow fields using high-resolution CFD data. This learned neural operator is then embedded in an optimization-based control framework for building ventilation control. Experimental results show that our approach achieves significant energy savings compared to maximum airflow rate control, rule-based control, as well as data-driven control methods using spatially averaged CO 2 prediction and deep learning–based reduced-order models, while consistently maintaining safe indoor air quality. These results highlight the practicality and scalability of our method in maintaining energy efficiency and indoor air quality in real-world buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

A transfer learning approach to energy-efficient control of small and medium-sized commercial buildings

Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.

ASHRAE guideline 36↗
DOE OSTI2026

Consumer safety-oriented scheduling of rotating power outages during heat waves

Extreme heat events have widespread effects on power systems, reducing available generation capacity, limiting transmission capabilities, and causing unusual demand patterns on the consumer side. As these combined effects expose bulk transmission systems to potential large-scale blackouts, utilities may be required to schedule and apply rotating outages, by temporarily and alternately disconnecting distribution substations to reduce overload. However, utilities lack mechanisms to inform these events, exacerbating the negative effects of heat waves on affected communities. This paper introduces a novel framework for scheduling rotating outages during heat waves while considering impacts on consumers’ safety. Instead of random sequential load shedding, we propose a methodology to rotate power outages considering a metric that quantifies the indoor overheating risk of groups of consumers during a power outage. The overheating risk is derived from a detailed building simulation using CityBES, where the buildings are modeled based on available data—use type, year built, floor area, number of stories, location—while presence of air conditioning and occupancy are calibrated from smart meter data. Based on the metric, an algorithm to schedule the rotating outages is applied to prioritize feeders for disconnection at each hour according to their overheating risk to meet a utility load reduction target. Applied to two substations and seven feeders in the Portland General Electric territory, the results show that this approach effectively leads to the lowest overheating risk during the resulting outage schedules, with an average 10.1% lower overheating compared to uninformed schedules.

Building thermal simulation↗
DOE OSTI2021

Parametric and sensitivity analysis of a PCM-integrated wall for optimal thermal load modulation in lightweight buildings

Load modulation in buildings is becoming increasingly important due to growing disparity in energy demand during peak and off-peak hours. Integrating phase change material (PCM) in building envelopes and using a controlled precooling strategy can provide substantial thermal load modulation; however, it may greatly increase the total energy use. Previous studies have employed PCM in building envelopes primarily for energy savings and, to some extent, peak load shedding and shifting. However, the load modulation capacity of a PCM-integrated envelope has not been well explored in the literature. In this study, we perform an extensive parametric and sensitivity analysis on PCM-integrated lightweight building walls and examine the combinatory effects of various PCM parameters on thermal load modulation and wall-related heat gains in buildings. Using numerical simulations, we investigate eight PCM parameters: PCM location in the wall, transition temperature, thickness, latent heat, transition range, density, specific heat, and thermal conductivity. Here, we evaluate their impact and relative importance to achieve maximum load modulation in buildings without compromising occupants’ thermal comfort or total energy use. The results show that the optimized PCM proposed in this study can completely invert the transient heat gain profile of the wall, providing up to 70% reduction of wall-related heat gain during peak hours without a major increase in the cumulative heat gain.

42 ENGINEERING↗
DOE OSTI2024

Implementation and validation of optimal start control strategy for air conditioners and heat pumps

Commercial buildings are responsible for approximately 20 % of the total energy consumption and greenhouse gas emissions in the United States. Over 85 % of these buildings lack building automation systems, and many are small (<50,000 square feet), underserved, and use rooftop units (RTUs) for heating, ventilation, and air-conditioning needs. Because these buildings lack proper energy management systems, several operational deficiencies lead to excess energy consumption. Studies have shown that managing the RTUs’ heating and cooling set points, schedules, setbacks, and optimal start can result in a 20 % to 25 % reduction in electricity consumption in small commercial buildings. These buildings typically use fixed schedules to start the RTUs 60 to 120 min before occupancy begins, which results in excess energy consumption. This paper presents research that demonstrates and evaluates the performance of four optimal start methods, which utilize data-based modeling as a key element in facilitating adaptive control in response to time-varying inputs while requiring minimal sensor inputs. The evaluation found energy savings in two commercial buildings equipped with RTUs by periodically alternating four different optimal start models during the cooling and heating season. The resulting energy savings are positive for all models and range from 2 to 5 kWh/day/unit. The units on the east side of the building showed higher savings, while interior units showed greater variability in savings due to the differences in capacities and room sizes. Savings were considerably greater during the heating season compared to the cooling season. The performance of all four models on Mondays was poor; models suggested a shorter optimal start time, which resulted in relatively larger errors. Finally, the future work will look at using a different model for the days after weekends and holidays.

42 ENGINEERING↗
DOE OSTI2023

A critical review of cyber-physical security for building automation systems

Modern Building Automation Systems (BASs), as the brain that enable the smartness of a smart building, often require increased connectivity both among system components as well as with outside entities, such as the cloud, to enable low-cost remote management, optimized automation via outsourced cloud analytics, and increased building-grid integrations. As smart buildings move towards open communication technologies, providing access to BASs through the building's intranet, or even remotely through the Internet, has become a common practice. However, increased connectivity and accessibility come with increased cyber security threats. BASs were historically developed as closed environments with limited cyber-security considerations. As a result, BASs in many buildings are vulnerable to cyber-attacks that may cause adverse consequences, such as occupant discomfort, excessive energy usage, and unexpected equipment downtime. Therefore, there is a strong need to advance the state-of-the-art in cyber-physical security for BASs and provide practical solutions for attack mitigation in buildings. However, an inclusive and systematic review of BAS vulnerabilities, potential cyber-attacks with impact assessment, detection & defense approaches, and cyber resilient control strategies is currently lacking in the literature. This review paper fills the gap by providing a comprehensive up-to-date review of cyber-physical security for BASs at three levels in commercial buildings: management level, automation level, and field level. The general BASs vulnerabilities and protocol-specific vulnerabilities for the four dominant BAS protocols (i.e., BACnet, KNX, LonWorks, and Modbus) are reviewed, followed by a discussion on four attack targets and seven potential attack scenarios. Furthermore, the impact of cyber-attacks on BASs is summarized as signal corruption, signal delaying, and signal blocking. The typical cyber-attack detection and defense approaches are identified at the three levels. Cyber resilient control strategies for BASs under attack are categorized into passive and active resilient control schemes. Open challenges and future opportunities are finally discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Constraining Galaxy-Halo connection using machine learning

We investigate the potential of machine learning (ML) methods to model small-scale galaxy clustering for constraining Halo Occupation Distribution (HOD) parameters. Our analysis reveals that while many ML algorithms report good statistical fits, they often yield likelihood contours that are significantly biased in both mean values and variances relative to the true model parameters. This highlights the importance of careful data processing and algorithm selection in ML applications for galaxy clustering, as even seemingly robust methods can lead to biased results if not applied correctly. ML tools offer a promising approach to exploring the HOD parameter space with significantly reduced computational costs compared to traditional brute-force methods if their robustness is established. Using our ANN-based pipeline, we successfully recreate some standard results from recent literature. Properly restricting the HOD parameter space, transforming the training data, and carefully selecting ML algorithms are essential for achieving unbiased and robust predictions. Among the methods tested, artificial neural networks (ANNs) outperform random forests (RF) and ridge regression in predicting clustering statistics, when the HOD prior space is appropriately restricted. We demonstrate these findings using the projected two-point correlation function (w p (r p )), angular multipoles of the correlation function (ξ ℓ (r)), and the void probability function (VPF) of Luminous Red Galaxies from Dark Energy Spectroscopic Instrument mocks. Our results show that while combining w p (r p ) and VPF improves parameter constraints, adding the multipoles ξ 0 , ξ 2 , and ξ 4 to w p (r p ) does not significantly improve the constraints.

cosmology↗
DOE OSTI2013

Light yield in DarkSide-10: A prototype two-phase argon TPC for dark matter searches

As part of the DarkSide program of direct dark matter searches using liquid argon TPCs, a prototype detector with an active volume containing 10 kg of liquid argon, DarkSide-10, was built and operated underground in the Gran Sasso National Laboratory in Italy. A critically important parameter for such devices is the scintillation light yield, as photon statistics limits the rejection of electron-recoil backgrounds by pulse shape discrimination. We have measured the light yield of DarkSide-10 using the readily-identifiable full-absorption peaks from gamma ray sources combined with single-photoelectron calibrations using low-occupancy laser pulses. For gamma lines of energies in the range 122-1275 keV, we get consistent light yields averaging 8.887+-0.003(stat)+-0.444(sys) p.e./keVee. With additional purification, the light yield measured at 511 keV increased to 9.142+-0.006(stat) p.e./keVee.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Molecular Dynamics Study of the Proposed Proton Transport Pathways in [FeFe]-Hydrogenase

Possible proton channels in Clostridium pasteurianum [FeFe]-hydrogenase were investigated with molecular dynamics simulations. This study was undertaken to discern proposed channels, compare their properties, evaluate the functional channel, and to provide insight into the features of an active proton channel. Our simulations suggest that protons are not transported through water wires. Instead, a five-residue motif (E282, S319, E279, HOH, C299) was found to be the likely channel, consistent with experimental observations. This channel connects the surface of the enzyme and the di-thiomethylamine bridge of the catalytic H-cluster, permitting the transport of protons. The channel was found to have a persistent hydrogen bonded core (residues E279 to S319), with less persistent hydrogen bonds at the ends of the channel. The hydrogen bond occupancy in this network was found to be sensitive to the protonation state of the residues in the channel, with different protonation states enhancing or stabilizing hydrogen bonding in different regions of the network. Single site mutations to non-hydrogen bonding residues break the hydrogen bonding network at that residue, consistent with experimental observations showing catalyst inactivation. In many cases, these mutations alter the hydrogen bonding in other regions of the channel which may be equally important in catalytic failure. A correlation between the protein dynamics near the proton channel and the redox partner binding regions was also found as a function of protonation state. The likely mechanism of proton movement in [FeFe]-hydrogenases is discussed based on the structural analysis presented here. This work was funded by the DOE Office of Science Early Career Research Program through the Office of Basic Energy Sciences. Computational resources were provided at W. R. Wiley Environmental Molecular Science Laboratory (EMSL), a national scientific user facility sponsored by the Department of Energy’s Office of Biological and Environmental Research located at Pacific Northwest National Laboratory, and a portion of the research was performed using PNNL Institutional Computing at Pacific Northwest National Laboratory. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy.

biomimetics↗
DOE OSTI2012

MgATP-concentration dependence of protection of yeast vacuolar V-ATPase from inactivation by 7-chloro-4-nitrobenzo-2-oxa-1,3-diazole supports a bi-site catalytic mechanism of ATP hydrolysis

Highlights: Black-Right-Pointing-Pointer MgATP protects V-ATPase from inactivation by 7-chloro-4-nitrobenzo-2-oxa-1,3-diazole. Black-Right-Pointing-Pointer V-ATPase activity saturation with MgATP is not sufficient for complete protection. Black-Right-Pointing-Pointer The results support a bi-site catalytic mechanism for V-ATPase. -- Abstract: Catalytic site occupancy of the yeast vacuolar V-ATPase during ATP hydrolysis in the presence of an ATP-regenerating system was probed using sensitivity of the enzyme to inhibition by 7-chloro-4-nitrobenzo-2-oxa-1,3-diazole (NBD-Cl). The results show that, regardless of the presence or absence of the proton-motive force across the vacuolar membrane, saturation of V-ATPase activity at increasing MgATP concentrations is accompanied by only partial protection of the enzyme from inhibition by NBD-Cl. Both in the presence and absence of an uncoupler, complete protection of V-ATPase from inhibition by NBD-Cl requires MgATP concentrations that are significantly higher than those expected from the K{sub m} values for MgATP. The results are inconsistent with a tri-site model and support a bi-site model for a mechanism of ATP hydrolysis by V-ATPase.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Exploring the membrane fusion mechanism through force-induced disassembly of HIV-1 six-helix bundle

Enveloped virus, such as HIV-1, employs membrane fusion mechanism to invade into host cell. HIV-1 gp41 ectodomain uses six-helix bundle configuration to accomplish this process. Using molecular dynamic simulations, we confirmed the stability of this six-helix bundle by showing high occupancy of hydrogen bonds and hydrophobic interactions. Key residues and interactions important for the bundle integration were characterized by force-induced unfolding simulations of six-helix bundle, exhibiting the collapse order of these groups of interactions. Moreover, our results in some way concerted with a previous theory that the formation of coiled-coil choose a route which involved cooperative interactions between the N-terminal and C-terminal helix. -- Highlights: •Unfolding of HIV-1 gp41 six-helix bundle is studied by molecular dynamics simulations. •Specific interactions responsible for the stability of HIV-1 envelope post-fusion conformation were identified. •The gp41 six-helix bundle transition inducing membrane fusion might be a cooperative process of the three subunits.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Co-crystal structures of PTK6: With Dasatinib at 2.24 Å, with novel imidazo[1,2-a]pyrazin-8-amine derivative inhibitor at 1.70 Å resolution

Human Protein tyrosine kinase 6 (PTK6)(EC:2.7.10.2), also known as the breast tumor kinase (BRK), is an intracellular non-receptor Src-related tyrosine kinase expressed five-fold or more in human breast tumors and breast cancer cell lines but its expression being low or completely absent from normal mammary gland. There is a recent interest in targeting PTK6-positive breast cancer by developing small molecule inhibitor against PTK6. Novel imidazo[1,2-a]pyrazin-8-amines (IPA) derivative compounds and FDA approved drug, Dasatinib are reported to inhibit PTK6 kinase activity with IC{sub 50} in nM range. To understand binding mode of these compounds and key interactions that drive the potency against PTK6, one of the IPA compounds and Dasatinib were chosen to study through X-ray crystallography. The recombinant PTK6 kinase domain was purified and co-crystallized at room temperature by the sitting-drop vapor diffusion method, collected X-ray diffraction data at in-house and resolved co-crystal structure of PTK6-KD with Dasatinib at 2.24 Å and with IPA compound at 1.70 Å resolution. Both these structures are in DFG-in & αC-helix-out conformation with unambiguous electron density for Dasatinib or IPA compound bound at the ATP-binding pocket. Relative difference in potency between Dasatinib and IPA compound is delineated through the additional interactions derived from the occupation of additional pocket by Dasatinib at gatekeeper area. Refined crystallographic coordinates for the kinase domain of PTK6 in complex with IPA compound and Dasatinib have been submitted to Protein Data Bank under the accession number (5DA3) and (5H2U) respectively. - Highlights: • We report first co-crystal structures of human PTK6 with potent inhibitors bound at the ATP binding pocket. • Relative difference in potency between FDA approved drug, Dasatinib and an inhibitor is delineated at the molecular level. • These co-crystal structures of PTK6-KD are in DFG-in and αC-helix-out conformation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Evidence for presynaptically silent synapses in the immature hippocampus

Silent synapses show NMDA receptor (NMDAR)-mediated synaptic responses, but not AMPAR-mediated synaptic responses. A prevailing hypothesis states that silent synapses contain NMDARs, but not AMPARs. However, alternative presynaptic hypotheses, according to which AMPARs are present at silent synapses, have been proposed; silent synapses show slow glutamate release via a fusion pore, and glutamate spillover from the neighboring synaptic terminals. Consistent with these presynaptic hypotheses, the peak glutamate concentrations at silent synapses have been estimated to be ≪170 μM, much lower than those seen at functional synapses. Glutamate transients predicted based on the two presynaptic mechanisms have been shown to activate only high-affinity NMDARs, but not low-affinity AMPARs. Interestingly, a previous study has developed a new approach to distinguish between the two presynaptic mechanisms using dextran, an inert macromolecule that reduces the diffusivity of released glutamate: postsynaptic responses through the fusion pore mechanism, but not through the spillover mechanism, are potentiated by reduced glutamate diffusivity. Therefore, we reasoned that if the fusion pore mechanism underlies silent synapses, dextran application would reveal AMPAR-mediated synaptic responses at silent synapses. In the present study, we recorded AMPAR-mediated synaptic responses at the CA3-CA1 synapses in neonatal rats in the presence of blockers for NMDARs and GABAARs. Bath application of dextran revealed synaptic responses at silent synapses. GYKI53655, a selective AMPAR-antagonist, completely inhibited the unsilenced synaptic responses, indicating that the unsilenced synaptic responses are mediated by AMPARs. The dextran-mediated reduction in glutamate diffusivity would also lead to the activation of metabotropic glutamate receptors (mGluRs), which might induce unsilencing via the activation of unknown intracellular signaling. Hence, we determined whether mGluR-blockers alter the dextran-induced unsilencing. However, dextran application continued to produce significant synaptic unsilencing in the presence of a cocktail of the blockers for all subtypes of mGluRs. Our findings provide evidence that slowed glutamate diffusion produces synaptic unsilencing by enhancing the peak glutamate occupancy of pre-existing AMPARs, supporting the fusion pore mechanism of silent synapses. - Highlights: • Slowed glutamate diffusion by dextran reveals synaptic responses at silent synapses. • Unsilenced synaptic responses are mediated by AMPA receptors. • Dextran-induced unsilencing is independent of metabotropic glutamate receptors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

TCF7L1 recruits CtBP and HDAC1 to repress DICKKOPF4 gene expression in human colorectal cancer cells

The T-cell factor/Lymphoid enhancer factor (TCF/LEF; hereafter TCF) family of transcription factors are critical regulators of colorectal cancer (CRC) cell growth. Of the four TCF family members, TCF7L1 functions predominantly as a repressor of gene expression. Few studies have addressed the role of TCF7L1 in CRC and only a handful of target genes regulated by this repressor are known. By silencing TCF7L1 expression in HCT116 cells, we show that it promotes cell proliferation and tumorigenesis in vivo by driving cell cycle progression. Microarray analysis of transcripts differentially expressed in control and TCF7L1-silenced CRC cells identified genes that control cell cycle kinetics and cancer pathways. Among these, expression of the Wnt antagonist DICKKOPF4 (DKK4) was upregulated when TCF7L1 levels were reduced. We found that TCF7L1 recruits the C-terminal binding protein (CtBP) and histone deacetylase 1 (HDAC1) to the DKK4 promoter to repress DKK4 gene expression. In the absence of TCF7L1, TCF7L2 and β-catenin occupancy at the DKK4 promoter is stimulated and DKK4 expression is increased. These findings uncover a critical role for TCF7L1 in repressing DKK4 gene expression to promote the oncogenic potential of CRCs. - Highlights: • TCF7L1 promotes colorectal cancer cell proliferation and tumorigenesis. • DICKKOPF4 is directly regulated by TCF7L1. • TCF7L1 recruits CtBP and HDAC1 to repress DKK4 gene expression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

SETDB1-mediated FosB regulation via ERK2 is associated with an increase in cell invasiveness during anticancer drug treatment of A549 human lung cancer cells

Highlights: • SETDB1 directly regulates FosB expression during doxorubicin treatment. • PD98059 restores the expression of SETDB1 and FosB by doxorubicin treatment. • SETDB1-mediated FosB regulation through ERK2 is responsible for cell survival. • Ectopic FosB expression increases transforming and migration activity. • ERK2-SETDB1-FosB pathway has an anti-therapeutic regulatory mechanism during anticancer drug treatment. We have determined a functional link to the inverse expression of SETDB1 and FosB following anticancer drug treatment. Doxorubicin treatment caused decreased SETDB1 expression and FosB overexpression both at the mRNA and protein levels. The decreased HMTase activity of SETDB1 coincided with altered occupancy across the promoter region of the FosB gene. SETDB1 overexpression decreased the luciferase reporter activity containing the FosB promoter region, but siSETDB1 increased the luciferase reporter activity, suggesting that SETDB1 directly and negatively regulated FosB expression. In addition, MEK inhibitor (PD98059) blocked the SETDB1 regulation of the FosB promoter activity via ERK2 activation during doxorubicin treatment. A microscopic analysis reveals that FosB expression was observed in living cells in spite of doxorubicin treatment. Ectopic FosB/ΔFosB expression increased the number of colonies and the migration of A549 cells compared to that in control. These results suggest that the ERK2-SETDB1-FosB signaling pathway might have an anti-therapeutic regulatory mechanism that increases the transformation and migration activity of cancer cells during anticancer drug treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Keratin 13 gene is epigenetically suppressed during transforming growth factor-β1-induced epithelial-mesenchymal transition in a human keratinocyte cell line

Highlights: • TGF-β1 induced mesenchymal-like morphology in HaCaT cells. • TGF-β1-induced EMT partially controlled the gene expression of EMT markers. • KRT13 was identified as a TGF-β1-responsive epithelial marker in HaCaT cells. • Chromatin state of the KRT13 promoter was epigenetically regulated during EMT. Epithelial-mesenchymal transition (EMT) is a biological event in which epithelial cells lose their polarity and cell–cell adhesions and concomitantly acquire mesenchymal traits, and is thought to play an important role in pathological processes such as wound healing and cancer progression. In this study, we evaluated transforming growth factor (TGF)-β1-treated human keratinocyte HaCaT cells as an in vitro model of EMT. HaCaT cells were changed into an elongated fibroblast-like morphology, which is indicative of EMT in response to TGF-β1. Phalloidin staining demonstrated the formation of actin stress fibers in TGF-β1-treated cells. Quantitative RT-PCR analysis revealed that TGF-β1 increased the mRNA levels of EMT transcription factors (SNAI2, TWIST1, and ZEB1) and mesenchymal markers (CDH2, VIM, and FN1), while it decreased the transcripts of epithelial phenotypic genes (CLDN1, OCLN, KRT5, KRT15, KRT13, and TGM1). Furthermore, we found that KRT13 was drastically suppressed through the reduction of RNA polymerase II occupancy of its promoter, which was accompanied by a decrease in active histone marks (H3K4me3 and H3K27ac) and an increase in a repressive mark (H3K27me3) during EMT. These findings indicate that the TGF-β1-induced EMT program regulates a subset of epithelial and mesenchymal marker genes, and that KRT13 is transcriptionally suppressed through the modulation of the chromatin state at the KRT13 promoter in HaCaT cells.

60 APPLIED LIFE SCIENCES↗