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At least 145 records · Page 8

Prognostics and Life Beyond 60 for Nuclear Power Plants

Safe, secure, reliable and sustainable energy supply is vital for advanced and industrialized life styles. To meet growing energy demand there is interest in longer term operation (LTO) for the existing nuclear power plant fleet and enhancing capabilities in new build. There is increasing use of condition based maintenance (CBM) for active components and periodic in service inspection (ISI) for passive systems: there is growing interest in deploying on-line monitoring. Opportunities exist to move beyond monitoring and diagnosis based on pattern recognition and anomaly detection to and prognostics with the ability to provide an estimate of remaining useful life (RUL). The adoption of digital I&C systems provides a framework within which added functionality including on-line monitoring can be deployed, and used to maintain and even potentially enhance safety, while at the same time improving planning and reducing both operations and maintenance costs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The artificial retina processor for track reconstruction at the LHC crossing rate

We present results of an R&D study for a specialized processor capable of precisely reconstructing, in pixel detectors, hundreds of charged-particle tracks from high-energy collisions at 40 MHz rate. We apply a highly parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature, and describe in detail an efficient hardware implementation in high-speed, high-bandwidth FPGA devices. This is the first detailed demonstration of reconstruction of offline-quality tracks at 40 MHz and makes the device suitable for processing Large Hadron Collider events at the full crossing frequency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Partial homogeneity based high-resolution nuclear magnetic resonance spectra under inhomogeneous magnetic fields

In nuclear magnetic resonance (NMR) technique, it is of great necessity and importance to obtain high-resolution spectra, especially under inhomogeneous magnetic fields. In this study, a method based on partial homogeneity is proposed for retrieving high-resolution one-dimensional NMR spectra under inhomogeneous fields. Signals from series of small voxels, which characterize high resolution due to small sizes, are recorded simultaneously. Then, an inhomogeneity correction algorithm is developed based on pattern recognition to correct the influence brought by field inhomogeneity automatically, thus yielding high-resolution information. Experiments on chemical solutions and fish spawn were carried out to demonstrate the performance of the proposed method. The proposed method serves as a single radiofrequency pulse high-resolution NMR spectroscopy under inhomogeneous fields and may provide an alternative of obtaining high-resolution spectra of in vivo living systems or chemical-reaction systems, where performances of conventional techniques are usually degenerated by field inhomogeneity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Both RIG-I and MDA5 detect alphavirus replication in concentration-dependent mode

Alphaviruses are a family of positive-strand RNA viruses that circulate on all continents between mosquito vectors and vertebrate hosts. Despite a significant public health threat, their biology is not sufficiently investigated, and the mechanisms of alphavirus replication and virus–host interaction are insufficiently understood. In this study, we have applied a variety of experimental systems to further understand the mechanism by which infected cells detect replicating alphaviruses. Our new data strongly suggest that activation of the antiviral response by alphavirus-infected cells is determined by the integrity of viral genes encoding proteins with nuclear functions, and by the presence of two cellular pattern recognition receptors (PRRs), RIG-I and MDA5. No type I IFN response is induced in their absence. The presence of either of these PRRs is sufficient for detecting virus replication. However, type I IFN activation in response to pathogenic alphaviruses depends on the basal levels of RIG-I or MDA5. - Highlights: • Both RIG-I and MDA5 detect alphavirus replication. • Alphavirus-induced transcriptional shutoff affects type I IFN induction. • Sensing of alphavirus replication by RIG-I and MDA5 depends on their concentrations. • High basal level of RIG-I and MDA5 allows IFN induction by pathogenic alphaviruses. • This dependence determines the discrepancy between the in vivo and in vitro data.

60 APPLIED LIFE SCIENCES↗

Staphylococcal enterotoxin C2 stimulated the maturation of bone marrow derived dendritic cells via TLR-NFκB signaling pathway

Highlights: • SEC2 stimulate the maturation of BMDCs. • SEC2 induce the production of pro-inflammation cytokines in BMDCs. • SEC2 activate NF-κB signaling pathway in BMDCs. As a kind of superantigen, staphylococcal enterotoxin C2 (SEC2) is well known as a powerful immunomodulator. However, most previous studies about SEC2 focus on its T cell activating characters. But the direct effect of SEC2 on antigen-presenting cells (APCs) which are important for the T cell activation is not clearly. In this study, we investigated the effect of SEC2 on murine bone marrow-derived dendritic cells (BMDCs) which are known as the specialized professional APCs. Contrary to its effects on T cells, SEC2 could not induce proliferation or cytotoxicity to BMDCs even in high concentrations. While SEC2 could promote the mature of BMDCs with increased expression of co-stimulatory molecules on cell membrane such as CD80, CD86, and MHC II. The production of pro-inflammatory cytokines such as TNF-α, IFN-γ and IL-6 were also increased in BMDCs treated with SEC2. We also found that SEC2 enhanced the genes expression of pattern recognition receptors including toll-like receptors 2 (TLR2) and TLR4 in BMDCs, and up-regulated the key signal molecule MyD88 in both mRNA and protein levels. In addition, SEC2 also caused IκBα degradating and NFκB p65 translocating from the cytoplasm to the nucleus in BMDCs. The siRNAs for both TLR2 and TLR4, as well as NFκB specific inhibitor BAY 11–7085 could inhibit the co-stimulatory molecules expression and pro-inflammatory cytokines releasing induced by SEC2. Moreover, TLR2/4 specific siRNAs inhibited p65 and MyD88 upregulation induced by SEC2. In summary, all our results indicated that SEC2 could stimulate BMDCs maturation through TLR-NFκB signaling pathways.

60 APPLIED LIFE SCIENCES↗

Application of Noise Cancelling and Damage Detection Algorithms in NDE of Concrete Bridge Decks Using Impact Signals

Delamination is a commonly observed distress in concrete bridge decks. Among all the delamination detection methods, acoustic methods have the advantages of being fast and inexpensive. In traditional acoustic inspection methods, the inspector drags a chain along or hammers on the bridge deck and detects delamination from the 'hollowness' of the sounds. The signals are often contaminated by ambient traffic noise and the detection of delamination is highly subjective. This paper describes the performance of an impact-bases acoustic NDE method where the traffic noise was filtered by employing a noise cancelling algorithm and where subjectivity was eliminated by introducing feature extraction and pattern recognition algorithms. Different algorithms were compared and the best one was selected in each category. The comparison showed that the modified independent component analysis (ICA) algorithm was most effective in cancelling the traffic noise and features consisting of mel-frequency cepstral coefficients (MFCCs) had the best performance in terms of repeatability and separabillty. The condition of the bridge deck was then detected by a radial basis function (RBF) neural network. The performance of the system was evaluated using both experimental and field data. The results show that the selected algorithms increase the noise robustness of acoustic methods and perform satisfactorily if the training data is representative.

42 ENGINEERING↗

Charged particle track reconstruction with SπRIT Time Projection Chamber

In this work, we present a software framework, SπRITROOT, which is capable of track reconstruction and analysis of heavy-ion collision events recorded with the SRIT time projection chamber. The track-fitting toolkit GENFIT and the vertex reconstruction toolkit RAVE are applied to a box-type detector system. A pattern recognition algorithm which performs helix track finding and handles overlapping pulses is described. The performance of the software is investigated using experimental data obtained at the Radioactive Isotope Beam Facility (RIBF) at RIKEN. This work focuses on data from 132 Sn + 124 Sn collision events with beam energy of 270 AMeV. Particle identification is established using < dE/dx >and magnetic rigidity, with pions, hydrogen isotopes, and helium isotopes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A historical survey of algorithms and hardware architectures for neural-inspired and neuromorphic computing applications

In this study, biological neural networks continue to inspire new developments in algorithms and microelectronic hardware to solve challenging data processing and classification problems. Here in this research, we survey the history of neural-inspired and neuromorphic computing in order to examine the complex and intertwined trajectories of the mathematical theory and hardware developed in this field. Early research focused on adapting existing hardware to emulate the pattern recognition capabilities of living organisms. Contributions from psychologists, mathematicians, engineers, neuroscientists, and other professions were crucial to maturing the field from narrowly-tailored demonstrations to more generalizable systems capable of addressing difficult problem classes such as object detection and speech recognition. Algorithms that leverage fundamental principles found in neuroscience such as hierarchical structure, temporal integration, and robustness to error have been developed, and some of these approaches are achieving world-leading performance on particular data classification tasks. Additionally, novel microelectronic hardware is being developed to perform logic and to serve as memory in neuromorphic computing systems with optimized system integration and improved energy efficiency. Key to such advancements was the incorporation of new discoveries in neuroscience research, the transition away from strict structural replication and towards the functional replication of neural systems, and the use of mathematical theory frameworks to guide algorithm and hardware developments.

97 MATHEMATICS AND COMPUTING↗

Bacterial cGAS-like enzymes synthesize diverse nucleotide signals

Cyclic dinucleotides (CDNs) have central roles in bacterial homeostasis and virulence by acting as nucleotide second messengers. Bacterial CDNs also elicit immune responses during infection when they are detected by pattern-recognition receptors in animal cells. Here we perform a systematic biochemical screen for bacterial signalling nucleotides and discover a large family of cGAS/DncV-like nucleotidyltransferases (CD-NTases) that use both purine and pyrimidine nucleotides to synthesize a diverse range of CDNs. Here, a series of crystal structures establish CD-NTases as a structurally conserved family and reveal key contacts in the enzyme active-site lid that direct purine or pyrimidine selection. CD-NTase products are not restricted to CDNs and also include an unexpected class of cyclic trinucleotide compounds. Biochemical and cellular analyses of CD-NTase signalling nucleotides demonstrate that these cyclic di- and trinucleotides activate distinct host receptors and thus may modulate the interaction of both pathogens and commensal microbiota with their animal and plant hosts.

59 BASIC BIOLOGICAL SCIENCES↗

The Center for Momentum Transport and Flow Organization in Plasmas - Final Scientific Report

Overview of University of Colorado Efforts: The University of Colorado group has focused on two primary fronts during the grant period: development of a variety of multi-point diagnostic and/or imaging analysis techniques, and momentum-transport related experiments on a variety of devices (NSTX at PPPL, CSDX at UCSD, LAPD at UCLA, DIII-D at GA). Experimental work has taken advantage of several diagnostic instruments, including fast-framing cameras for imaging of electron density fluctuations (either directly or using injected gas puffs), ECEI for imaging of electron temperature fluctuations, and multi-tipped Langmuir and magnetic probes for corroborating measurements of Reynolds and Maxwell stresses. Mode Characterization in CSDX: We have performed a series of experiments at the CSDX linear device at UCSD, in collaboration with Center PI G. Tynan's group. The experiments included a detailed study of velocity estimation techniques, including direct comparisons between Langmuir probes and image-based velocimetry from fast-framing camera data. We used the camera data in a second set of studies to identify the spatial and spectral structure of coherent modes, which illuminates wave behavior to a level of detail previously unavailable, and enables direct comparison of dispersion curves to theoretical estimates. In another CSDX study, similar techniques were used to demonstrate a controlled transition from nonlinearly coupled discrete eigenmodes to fully developed broadband turbulence. The axial magnetic field was varied from 40-240 mT, which drove the transition. At low magnetic fields, the plasma is dominated by drift waves. As the magnetic field is increased, a strong potential gradient at the edge introduces an ExB shear-driven instability. At the transition, another mode with signatures of a rotation-induced Rayleigh–Taylor instability appears at the central plasma region. Concurrently, large axial velocities were found in the plasma core. For larger magnetic fields, all of the instabilities co-exist, leading to rich plasma dynamics and fully developed broadband turbulence. Edge-Turbulence and Flow Experiments in NSTX: A series of Gas Puff Imaging (GPI) observations on NSTX revealed a quasi-periodic oscillation in the plasma edge preceding the L-H transition in a limited set of neutral beam heated plasmas. These ~3 kHz flow oscillations exhibit both long wavelength and long correlation lengths, suggesting they are zonal-flow-like. The flow oscillations are strongly correlated with modulations of the level of edge turbulence, thus the system appears to undergo a predator--prey-type limit-cycle preceding the L-H transition. However, a clear trigger for the L-H transition was not observed. Reynolds stress profiles were obtained directly from image velocimetry for L-mode periods ELM-Precursor Studies in NSTX: A separate study based on NSTX-GPI data captured the two-dimensional evolution of edge-localized mode (ELM) precursors. Precursor events were observed preceding ELMs and ELM-induced H–L back-transitions in radio-frequency heated H-mode plasmas, and the growth of the precursor mode through the ELM filamentation was imaged in the plane perpendicular to the local B-field. Strong edge intensity modulations appeared to propagate in the electron diamagnetic direction while steadily drifting radially outwards. Intensity fluctuations were observed at frequencies around 20 kHz and wavenumbers of 0.05-0.2 cm -1 . Upon growing to a trigger point, precursor fluctuations were seen to form filamentary structures and move into the scrape-off layer (SOL) explosively with radial velocities peaking at 8 km/s. Once in the SOL, filaments reverse their propagation direction and travel in the ion diamagnetic direction. Edge intensity fluctuations were strongly correlated with magnetic signals from Mirnov coils, and toroidally distributed coils estimated toroidal mode numbers of n=5-10. Quantitatively similar precursors have been observed in ohmic H-mode plasmas as well, though significantly fewer events are seen in the ohmic cases and none were observed in the near-threshold NBI H-modes studied. Development of Velocimetry and Image Analysis Techniques: Along with the experiments listed above, the Colorado group has continued to explore various velocimetry techniques and their range of validity. We have developed a “linear optical flow” code, which calculates smooth velocity maps while accurately assessing local regions of high curl. This is critical for separating spatial scales of velocity behavior, and thus transport. This code has recently come on-line, and we are currently using it to revisit a number of older datasets. Additionally, we have worked on developing pattern-recognition techniques for imaging diagnostics, based on established digital image compression algorithms. This has the potential to open the analysis of turbulent plasma behavior beyond the well-trodden Fourier and wavelet approaches. Finally, we have extended several of these image-analysis routines to multiple other diagnostic sets, including GPI datasets in NSTX and ECEI imaging on DIII-D. In one study, correlation maps were used to measure the full 2-D mode structure of drift-wave level structures using ECEI for the first time. This enabled direct comparison to gyrokinetic simulations using the GEM code, from which is was determined that TEM modes were being measured in DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching

An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.

3D imaging↗

Integrated solutions to SHM problems: an overview of SHM research at the LANL/UCSD engineering institute

This seminar will provide an overview of structural health monitoring (SHM) research that is being undertaken at Los Alamos National Laboratory (LANL). The seminar will begin by stating that SHM should be viewed as an important component of the more comprehensive intelligent life-cycle engineering process. Then LANL's statistical pattern recognition paradigm for addressing SHM problems will be introduced and current research that is focused on each part of the paradigm will be discussed. In th is paradigm, the process can be broken down into four parts: (1) Operational Evaluation, (2) Data Acquisition and Cleansing, (3) Feature Extraction, and (4) Statistical Model Development for Feature Discrimination. When one attempts to apply this paradigm to data from real world structures, it quickly becomes apparent that the ability to cleanse, compress, normalize and fuse data to account for operational and environmental variability is a key implementation issue when addressing Parts 2-4 of this paradigm. This discussion will be followed by the introduction a new project entitled 'Intelligent Wind Turbines' which is the focus of much of our current SHM research . This summary will be followed by a discussion of issues that must be addressed if this technology is to make the transition from research to practice and new research directions that are emerging for SHM.

17 WIND ENERGY↗

Attractor comparisons based on density

Recognizing a chaotic attractor can be seen as a problem in pattern recognition. Some feature vector must be extracted from the attractor and used to compare to other attractors. The field of machine learning has many methods for extracting feature vectors, including clustering methods, decision trees, support vector machines, and many others. In this work, feature vectors are created by representing the attractor as a density in phase space and creating polynomials based on this density. Density is useful in itself because it is a one dimensional function of phase space position, but representing an attractor as a density is also a way to reduce the size of a large data set before analyzing it with graph theory methods, which can be computationally intensive. The density computation in this paper is also fast to execute. In this paper, as a demonstration of the usefulness of density, the density is used directly to construct phase space polynomials for comparing attractors. Comparisons between attractors could be useful for tracking changes in an experiment when the underlying equations are too complicated for vector field modeling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Neutron Resonance Spin Determination Using Multi-Segmented Detector DANCE

A sensitive method to determine the spin of neutron resonances is introduced based on the statistical pattern recognition technique. The new method was used to assign the spins of s-wave resonances in {sup 155}Gd. The experimental neutron capture data for these nuclei were measured with the DANCE (Detector for Advanced Neutron Capture Experiment) calorimeter at the Los Alamos Neutron Science Center. The highly segmented calorimeter provided detailed multiplicity distributions of the capture {gamma}-rays. Using this information, the spins of the neutron capture resonances were determined. With these new spin assignments, level spacings are determined separately for s-wave resonances with J{sup {pi}} = 1{sup -} and 2{sup -}.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Generation of mice deficient in RNA-binding motif protein 3 (RBM3) and characterization of its role in innate immune responses and cell growth

Highlights: {yields} We identified RNA-binding motif protein 3 (RBM3) as CpG-B DNA-binding protein. {yields} RBM3 translocates from the nucleus to the cytoplasm and co-localized with CpG-B DNA. {yields} We newly generated Rbm3-deficient (Rbm3{sup -/-}) mice. {yields} DNA-mediated cytokine gene induction was normally occured in Rbm3{sup -/-} cells. {yields}Rbm3{sup -/-} MEFs showed poorer proliferation rate and increased number of G2-phase cells. -- Abstract: The activation of innate immune responses is critical to host defense against microbial infections, wherein nucleic acid-sensing pattern recognition receptors recognize DNA or RNA from viruses or bacteria and activate downstream signaling pathways. In a search for new DNA-sensing molecules that regulate innate immune responses, we identified RNA-binding motif protein 3 (RBM3), whose role has been implicated in the regulation of cell growth. In this study, we generated Rbm3-deficient (Rbm3{sup -/-}) mice to study the role of RBM3 in immune responses and cell growth. Despite evidence for its interaction with immunogenic DNA in a cell, no overt phenotypic abnormalities were found in cells from Rbm3{sup -/-} mice for the DNA-mediated induction of cytokine genes. Interestingly, however, Rbm3{sup -/-} mouse embryonic fibroblasts (MEFs) showed poorer proliferation rates as compared to control MEFs. Further cell cycle analysis revealed that Rbm3{sup -/-} MEFs have markedly increased number of G2-phase cells, suggesting a hitherto unknown role of RBM3 in the G2-phase control. Thus, these mutant mice and cells may provide new tools with which to study the mechanisms underlying the regulation of cell cycle and oncogenesis.

60 APPLIED LIFE SCIENCES↗

Disordered glycometabolism involved in pathogenesis of Kashin–Beck disease, an endemic osteoarthritis in China

Kashin–Beck disease (KBD) is a chronic endemic osteoarthritis in China. Previous studies have suggested a role of metabolic dysfunction in causation of this disease. In this investigation, the metabolomics approach and cell experiments were used to discover the metabolic changes and their effects on KBD chondrocytes. Nuclear magnetic resonance ({sup 1}H NMR) spectroscopy was used to examine serum samples from both the KBD patients and normal controls. The pattern recognition multivariate analysis (OSC–PLS) and quantitative analysis (QMTLS iterator) revealed altered glycometabolism in KBD, with increased glucose and decreased lactate and citrate levels. IPA biological analysis showed the centric location of glucose in the metabolic network. Massive glycogen deposits in chondrocytes and increased uptake of glucose by chondrocytes further confirmed disordered glycometabolism in KBD. An in vitro study showed the effects of disordered glycometabolism in chondrocytes. When chondrocytes were treated with high glucose, expression of type II collagen and aggrecan were decreased, while TNF-α expression, the level of cellular reactive oxygen species and cell apoptosis rates all were increased. Therefore, our results demonstrated that disordered glycometabolism in patients with KBD was linked to the damage of chondrocytes. This may provide a new basis for understanding the pathogenesis of KBD. - Highlights: • Disordered glycometabolism in KBD was demonstrated by combining serum metabolomics and chondrocyte studies. • Glucose and TNF-α were key molecules linked to altered metabolism and inflammation in the pathophysiology of KBD. • The glycometabolism disorder was linked to expression of type II collagen and aggrecan, ROS and apoptosis of KBD chondrocytes.

60 APPLIED LIFE SCIENCES↗

TU-F-CAMPUS-T-05: A Cloud-Based Monte Carlo Dose Calculation for Electron Cutout Factors

Purpose: For electron cutouts of smaller sizes, it is necessary to verify electron cutout factors due to perturbations in electron scattering. Often, this requires a physical measurement using a small ion chamber, diode, or film. The purpose of this study is to develop a fast Monte Carlo based dose calculation framework that requires only a smart phone photograph of the cutout and specification of the SSD and energy to determine the electron cutout factor, with the ultimate goal of making this cloud-based calculation widely available to the medical physics community. Methods: The algorithm uses a pattern recognition technique to identify the corners of the cutout in the photograph as shown in Figure 1. It then corrects for variations in perspective, scaling, and translation of the photograph introduced by the user’s positioning of the camera. Blob detection is used to identify the portions of the cutout which comprise the aperture and the portions which are cutout material. This information is then used define physical densities of the voxels used in the Monte Carlo dose calculation algorithm as shown in Figure 2, and select a particle source from a pre-computed library of phase-spaces scored above the cutout. The electron cutout factor is obtained by taking a ratio of the maximum dose delivered with the cutout in place to the dose delivered under calibration/reference conditions. Results: The algorithm has been shown to successfully identify all necessary features of the electron cutout to perform the calculation. Subsequent testing will be performed to compare the Monte Carlo results with a physical measurement. Conclusion: A simple, cloud-based method of calculating electron cutout factors could eliminate the need for physical measurements and substantially reduce the time required to properly assure accurate dose delivery.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Pam2 lipopeptides systemically increase myeloid-derived suppressor cells through TLR2 signaling

Myeloid-derived suppressor cells (MDSCs) are immature myeloid cells that exhibit potent immunosuppressive activity. They are increased in tumor-bearing hosts and contribute to tumor development. Toll-like receptors (TLRs) on MDSCs may modulate the tumor-supporting properties of MDSCs through pattern-recognition. Pam2 lipopeptides represented by Pam2CSK4 serve as a TLR2 agonist to exert anti-tumor function by dendritic cell (DC)-priming that leads to NK cell activation and cytotoxic T cell proliferation. On the other hand, TLR2 enhances tumor cell progression/invasion by activating tumor-infiltrating macrophages. How MDSCs respond to TLR2 agonists has not yet been determined. In this study, we found intravenous administration of Pam2CSK4 systemically up-regulated the frequency of MDSCs in EG7 tumor-bearing mice. The frequency of tumor-infiltrating MDSCs was accordingly increased in response to Pam2CSK4. MDSCs were not increased by Pam2CSK4 stimuli in TLR2 knockout (KO) mice. Adoptive transfer experiments using CFSE-labeled MDSCs revealed that the TLR2-positive MDSCs survived long in tumor-bearing mice in response to Pam2CSK4 treatment. Since the increased MDSC population sustained immune-suppressive properties, our study suggests that Pam2CSK4-triggered TLR2 activation enhances the MDSC potential and suppress antitumor immune response in tumor microenvironment. - Highlights: • Pam2CSK4 administration induces systemic accumulation of CD11b{sup +}Gr1{sup +} MDSCs. • TLR2 is essential for Pam2CSK4-induced accumulation of CD11b{sup +}Gr1{sup +} MDSCs. • Pam2CSK4 supports survival of CD11b{sup +}Gr1{sup +} MDSCs in vivo.

60 APPLIED LIFE SCIENCES↗