Arhgef16, a novel Elmo1 binding partner, promotes clearance of apoptotic cells via RhoG-dependent Rac1 activation

AbstractElmo is an evolutionarily conserved mammalian ortholog of Caenorhabditis elegans CED-12 with proposed roles during the removal of apoptotic cells, cell migration, neurite outgrowth, and myoblast fusion (Katoh and Negishi (2003) [1], Park and Tosello (2007) [2], Grimsley et al. (2004) [3], Hamoud et al. (2014) [4]). Elmo mediates these cellular processes by interacting with various proteins located in the plasma membrane, cytoplasm and nucleus, and by modulating their activities although it has no intrinsic catalytic activity (Park and Tosello (2007) [2], Hamoud et al. (2014) [4], Li et al. (2013) [5], Margaron, Fradet and Cote (2013) [6], and Mauldin et al. (2013)[7]). Because there are a limited number of proteins known to interact with Elmo, we performed a yeast two-hybrid screen using Elmo1 as bait to identify Elmo1-interacting proteins and to evaluate their mode of regulation. Arhgef16 was one of the proteins identified through the screen and subsequent analyses revealed that Arhgef16 interacted with Elmo1 in mammalian cells as well. Expression of Arhgef16 in phagocytes promoted engulfment of apoptotic cells, and engulfment mediated by Arhgef16 increased synergistically in the presence of Elmo1 but was abrogated in the absence of Elmo1. In addition, Arhgef16-mediated removal of apoptotic cells was dependent on RhoG, but independent of Dock1. Taken together, this study suggests that the newly identified Elmo1-interacting protein, Arhgef16, functions synergistically with Elmo1 to promote clearance of apoptotic cells in a RhoG-dependent and Dock1-independent manner

Strength Characteristics of Controlled Low-Strength Materials with Waste Paper Sludge Ash (WPSA) for Prevention of Sewage Pipe Damage

In this study, the effects of the mixing conditions of waste paper sludge ash (WPSA) on the strength and bearing capacity of controlled low-strength material (CLSM) were evaluated, and the optimal mixing conditions were used to evaluate the strength characteristics of CLSM with recyclable WPSA. The strength and bearing capacity of CLSM with WPSA were evaluated using unconfined compressive strength tests and plate bearing tests, respectively. The unconfined compressive strength test results show that the optimal mixing conditions for securing 0.8–1.2 MPa of target strength under 5% of cement content conditions can be obtained when both WPSA and fly ash are used. This is because WPSA and fly ash, which act as binders, have a significant impact on overall strength when the cement content is low. The bearing capacity of weathered soil increased from 550 to 575 kPa over time, and CLSM with WPSA increased significantly, from 560 to 730 kPa. This means that the bearing capacity of CLSM with WPSA was 2.0% higher than that of weathered soil immediately after construction; furthermore, it was 27% higher at 60 days of age. In addition, the allowable bearing capacity of CLSM corresponding to the optimal mixing conditions was evaluated, and it was found that this value increased by 30.4% until 60 days of age. This increase rate was 6.7 times larger than that of weathered soil (4.5%). Therefore, based on the allowable bearing capacity calculation results, CLSM with WPSA was applied as a sewage pipe backfill material. It was found that CLSM with WPSA performed better as backfill and was more stable than soil immediately after construction. The results of this study confirm that CLSM with WPSA can be utilized as sewage pipe backfill material

Effect of Prior Direction Expectation on the Accuracy and Precision of Smooth Pursuit Eye Movements

© Copyright © 2019 Kim, Park and Lee.The integration of sensory with top–down cognitive signals for generating appropriate sensory–motor behaviors is an important issue in understanding the brain’s information processes. Recent studies have demonstrated that the interplay between sensory and high-level signals in oculomotor behavior could be explained by Bayesian inference. Specifically, prior knowledge for motion speed introduces a bias in the speed of smooth pursuit eye movements. The other important prediction of Bayesian inference is variability reduction by prior expectation; however, there is insufficient evidence in oculomotor behaviors to support this prediction. In the present study, we trained monkeys to switch the prior expectation about motion direction and independently controlled the strength of the motion stimulus. Under identical sensory stimulus conditions, we tested if prior knowledge about the motion direction reduced the variability of open-loop smooth pursuit eye movements. We observed a significant reduction when the prior expectation was strong; this was consistent with the prediction of Bayesian inference. Taking advantage of the open-loop smooth pursuit, we investigated the temporal dynamics of the effect of the prior to the pursuit direction bias and variability. This analysis demonstrated that the strength of the sensory evidence depended not only on the strength of the sensory stimulus but also on the time required for the pursuit system to form a neural sensory representation. Finally, we demonstrated that the variability and directional bias change by prior knowledge were quantitatively explained by the Bayesian observer model11sciescopu

Root Reinforcement Effect on Cover Slopes of Solid Waste Landfill in Soil Bioengineering

This study investigated the effect of vegetation plant roots on the stability of the cover slopes of solid waste landfills. A large direct shear test and a root tensile strength test were conducted to quantify the effect of rooted soil of revegetation plants on the increment in shear strength of the soil as a method to protect the cover slope of solid waste landfills. In the large direct shear test, an increase in the shear strength of the ground with the presence of roots was observed, and the root reinforcement proposed in the literature was modified and proposed by analyzing the correlation between the root diameter and the tensile strength according to water content. The stability of the slope revegetation of a landfill facility, considering the root reinforcement effect of revegetation, was calculated by conducting a slope stability analysis reflecting the unsaturated seepage analysis of rainfall conditions for various analysis conditions, such as the gradient, the degree of compactness, the thickness of the cover, and the rooted soil depth of the landfill facility

Multivariate EEG activity reflects the Bayesian integration and the integrated Galilean relative velocity of sensory motion during sensorimotor behavior

Humans integrate multiple sources of information for action-taking, using the reliability of each source to allocate weight to the data. This reliability-weighted information integration is a crucial property of Bayesian inference. In this study, participants were asked to perform a smooth pursuit eye movement task in which we independently manipulated the reliability of pursuit target motion and the direction-of-motion cue. Through an analysis of pursuit initiation and multivariate electroencephalography activity, we found neural and behavioral evidence of Bayesian information integration: more attraction toward the cue direction was generated when the target motion was weak and unreliable. Furthermore, using mathematical modeling, we found that the neural signature of Bayesian information integration had extra-retinal origins, although most of the multivariate electroencephalography activity patterns during pursuit were best correlated with the retinal velocity errors accumulated over time. Our results demonstrated neural implementation of Bayesian inference in human oculomotor behavior. © 2023, The Author(s).11Nsciescopu

Proposal of Construction Method of Smart Liner to Block and Detect Spreading of Soil Contaminants by Oil Spill

Soil is an important factor for public health, and when a soil contaminant occurs by oil spill, it has a great impact on the ecosystem, including humans. Accordingly, the area is blocked using a vertical barrier, and various remediation methods are being applied when an oil spill occurs. This study intends to use a smart liner to prevent and detect the spreading of soil contaminants in a situation in which oil spill detection is important. However, the smart liner is in the form of a fiber, so it is impossible to construct it in a general method. Therefore, the roll spreading and inserting method (RSIM) is proposed for smart liner construction. RSIM is a method of installing a supporting pile after excavating the ground and connecting the smart liner vertically to the ground surface. This method is the first method proposed in this study, and the design and concept have not been established. In this study, a conceptual design was established to apply RSIM in the actual field, and a scale model experiment was performed to prove it. As a result of the scale model experiment, the applicability of RSIM was confirmed. Finally, numerical analysis using Abaqus/CAE was performed to carry out the detailed design of RSIM (installation conditions such as dimensions). Analysis parameters were embedded depth, thickness, diameter, and material properties of a supporting pile according to the ground type. As a result of the analysis, it was confirmed that the results of RSIM analysis were interacting with all parameters according to the ground conditions. Therefore, it was confirmed that the actual design should be based on ground investigation and economic conditions, not standardized regulations

Spectrum Index for Estimating Ground Water Content Using Hyperspectral Information

Quality control considerably affects road stability and operability and is directly linked to the underlying ground compaction. The degree of compaction is largely determined by water content, which is typically measured at the actual construction site. However, conventional methods for measuring water content do not capture entire construction sites efficiently. Therefore, this study aimed to apply remote sensing of hyperspectral information to efficiently measure the groundwater content of large areas. A water content prediction equation was developed through an indoor experiment. The experimental samples comprised 0–40% (10% increase) of fine contents added to standard sand. As high water content is not required in road construction, 0–15% (1% increase) of water content was added. The test results were normalized, the internal and external environments were controlled for precise results, and a wavelength–reflection curve was derived for each test case. Data variability analyses were performed, and the appropriate wavelength for water content reflection, as well as reflectance, was determined and converted into a spectrum index. Finally, various fitting models were applied to the corresponding spectrum index for water content prediction. Reliable results were obtained with the reflectance corresponding to a wavelength of 720 nm applied as the spectrum index

Numerical Analysis of Factors Influencing the Ground Surface Settlement above a Cavity

In this study, ground stability was evaluated through vertical displacement distribution and surface settlement results. In particular, a finite element analysis was conducted considering various factors (namely, cavity type and area, traffic load, pavement thickness, and elastic modulus) that affect a road above a cavity. The aim of this study was to evaluate the effect of pavement layer and traffic load condition on surface settlement according to the cavity shape. Field measurement results were analyzed and compared with the results of previous studies to verify the reliability of the numerical analysis method applied herein. After performing the numerical analysis using the verified method, ground stability was evaluated by analyzing the underground mechanical behavior of a road above a cavity. To this end, the correlations among the vertical displacement distribution, surface settlement, and influencing factors obtained from the analysis results were analyzed. In the numerical analysis, the ground was simulated with a hardening soil model based on the elastoplastic theory. This mechanical soil model can accurately reproduce the behavior of actual ground and can closely represent the mechanical behavior of the soil surrounding a cavity according to the cavity generation. In addition, the elapsed time was not considered when applying a load on the pavement layer, and a uniformly distributed load was applied. Consequently, it was found that, with increasing cavity area and traffic load and decreasing pavement thickness and elastic modulus, the vertical displacement and maximum surface settlement above the cavity increased, and the reduction in ground stability was greater. Furthermore, the reduction in ground stability was greater when the cavity was rectangular than when it was circular

Prior expectation enhances sensorimotor behavior by modulating population tuning and subspace activity in sensory cortex

Prior knowledge facilitates our perception and goal-directed behaviors, particularly when sensory input is lacking or noisy. However, the neural mechanisms underlying the improvement in sensorimotor behavior by prior expectations remain unknown. In this study, we examine the neural activity in the middle temporal (MT) area of visual cortex while monkeys perform a smooth pursuit eye movement task with prior expectation of the visual target's motion direction. Prior expectations discriminately reduce the MT neural responses depending on their preferred directions, when the sensory evidence is weak. This response reduction effectively sharpens neural population direction tuning. Simulations with a realistic MT population demonstrate that sharpening the tuning can explain the biases and variabilities in smooth pursuit, suggesting that neural computations in the sensory area alone can underpin the integration of prior knowledge and sensory evidence. State-space analysis further supports this by revealing neural signals of prior expectations in the MT population activity that correlate with behavioral changes.11Nsciescopu

DualBlock: Adaptive Intra-Slot CSMA/CA for TSCH

IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) has drawn significant attention as a low-power network solution for the Internet of Things (IoT). To make the TSCH scalable and robust, slot scheduling is an important issue that needs to be addressed. The research community has made significant strides with various autonomous or decentralized technologies in recent years. While these techniques try to provide non-overlapped slots for each link, they take collision for granted when multiple links utilize the same slot. In this paper, we challenge the perspective, investigate what happens within a TSCH slot, and find room for performance improvement even when multiple links unfortunately share a slot. To this end, we propose DualBlock that provides another chance for collision avoidance when multiple links try to utilize a slot at the same time by enabling clear channel assessment (CCA) and random backoff within the congested slot. In addition, given that the intra-slot backoff consumes more energy, a control mechanism is added that adjusts maximum backoff by monitoring network congestion level. DualBlock operates in a distributed manner for scalability. Extensive experiments demonstrate that TSCH networks achieve significant performance improvement in many aspects when DualBlock is combined with a scheduler (i.e., Orchestra), up to 3.6 times higher packet delivery ratio and 75% less radio duty cycle.N