Targeting Checkpoint Receptors and Molecules for Therapeutic Modulation of Natural Killer Cells

Among the most promising therapeutic modalities for cancer treatment is the blockade of immune checkpoint pathways, which are frequently co-opted by tumors as a major mechanism of immune escape. CTLA-4 and PD-1 are the representative examples, and their blockade by therapeutic antibodies leads to enhanced anti-tumor immunity with durable clinical responses, but only in a minority of patients. This has highlighted the need to identify and target additional immune checkpoints that can be exploited to further enhance immune responses to refractory cancers. These emerging targets include natural killer (NK) cell-directed checkpoint receptors (KIR and CD94/NKG2A) as well as the NK- and T cell-expressed checkpoints TIM-3, TIGIT, CD96, and LAG-3. Interestingly, the potentiation of anti-tumor immunity by checkpoint blockade relies not only on T cells but also on other components of the innate immune system, including NK cells. NK cells are innate lymphoid cells that efficiently kill tumor cells without MHC specificity, which is complementary to the MHC-restricted tumor lysis mediated by cytotoxic T cells. However, the role of these immune checkpoints in modulating the function of NK cells remains unclear and somewhat controversial. Unraveling the mechanisms by which these immune checkpoints function in NK cells and other immune cells will pave the way to developing new therapeutic strategies to optimize anti-tumor immunity while limiting cancer immune escape. Here, we focus on recent findings regarding the roles of immune checkpoints in regulating NK cell function and their potential application in cancer immunotherapy

Integrated In-vehicle Monitoring System Using 3D Human Pose Estimation and Seat Belt Segmentation

Recently, along with interest in autonomous vehicles, the importance of monitoring systems for both drivers and passengers inside vehicles has been increasing. This paper proposes a novel in-vehicle monitoring system the combines 3D pose estimation, seat-belt segmentation, and seat-belt status classification networks. Our system outputs various information necessary for monitoring by accurately considering the data characteristics of the in-vehicle environment. Specifically, the proposed 3D pose estimation directly estimates the absolute coordinates of keypoints for a driver and passengers, and the proposed seat-belt segmentation is implemented by applying a structure based on the feature pyramid. In addition, we propose a classification task to distinguish between normal and abnormal states of wearing a seat belt using results that combine 3D pose estimation with seat-belt segmentation. These tasks can be learned simultaneously and operate in real-time. Our method was evaluated on a private dataset we newly created and annotated. The experimental results show that our method has significantly high performance that can be applied directly to real in-vehicle monitoring systems.Comment: AAAI 2022 workshop AI for Transportation accepte

Association between Estimated Pulse Wave Velocity and Incident Nonalcoholic Fatty Liver Disease in Korean Adults

Introduction: Nonalcoholic fatty liver disease (NAFLD) is associated with vascular dysfunction, one of the signs of which is arterial stiffness. Carotid-femoral pulse wave velocity (PWV), which is considered the gold standard measure of arterial stiffness, can be estimated using two commonly assessed clinical variables: age and blood pressure. This study aimed to evaluate the association between estimated PWV (ePWV) and the prevalence and incidence of NAFLD among Korean adults. Methods: This study used data from the Ansan-Ansung cohort study, a subset of the Korean Genome and Epidemiology Study, and included 8,336 adult participants with and without NAFLD at baseline. The participants were subdivided into three tertile groups according to ePWV. Results: At baseline, the prevalence of NAFLD was 10.5, 27.5, and 35.0% in the first (lowest), second, and third (highest) tertiles of ePWV, respectively. During the 18-year follow-up period, 2,467 (42.9%) incident cases of NAFLD were identified among 5,755 participants who did not have NAFLD at baseline. After adjustment for clinically relevant variables, participants in the second (adjusted hazard ratio [HR], 1.25; 95% confidence interval [CI], 1.12–1.40) and third (adjusted HR, 1.42; 95% CI, 1.24–1.64) tertiles of ePWV had a significantly higher risk of incident NAFLD than those in the first tertile. Conclusion: Higher ePWV is independently associated with an elevated risk of NAFLD in the general population

Synergistic Signals for Natural Cytotoxicity Are Required to Overcome Inhibition by c-Cbl Ubiquitin Ligase

SummaryNatural killer (NK) cell cytotoxicity toward target cells depends on synergistic coactivation by NK cell receptors such as NKG2D and 2B4. How synergy occurs is not known. Synergistic phosphorylation of phospholipase PLC-γ2, Ca2+ mobilization, and degranulation triggered by NKG2D and 2B4 coengagement were blocked by Vav1 siRNA knockdown, but enhanced by knockdown of c-Cbl. c-Cbl inhibited Vav1-dependent signals, given that c-Cbl knockdown did not rescue the Vav1 defect. Moreover, c-Cbl knockdown and Vav1 overexpression each circumvented the necessity for synergy because NKG2D or 2B4 alone became sufficient for activation. Thus, synergy requires not strict complementation but, rather, strong Vav1 signals to overcome inhibition by c-Cbl. Inhibition of NK cell cytotoxicity by CD94-NKG2A binding to HLA-E on target cells was dominant over synergistic activation, even after c-Cbl knockdown. Therefore, NK cell activation by synergizing receptors is regulated at the level of Vav1 by a hierarchy of inhibitory mechanisms

FLUIDIZATION TECHNOLOGY FOR STABLE STARTUP OF COMMERCIAL FCC UNIT

Conditions for maintaining good fluidization in the start-up of FCC have been determined. Catalyst defluidization and consequent catalyst losses from reactor cyclone are mainly affected by catalyst properties and stripper operating condition based on previous commercial startup experiences. Effect of fine catalyst contents on bed fluidity was determined. Bed fluidity in stripper was analyzed with slip velocity. Finally new startup guide was proposed and it was successfully applied to commercial FCC process of SK energy, Korea

Rotational Resistance of Surface-Treated Mini-implants

Objective: To test the hypothesis that there is no difference in the stability and resistance to rotational moments of early loaded sandblasted and acid-etched (SLA) mini-implants and those of machined-surface implants of the same size and shape. Materials and Methods: A randomized complete block design was used in 12 skeletally mature male beagle dogs. Ninety-six orthodontic mini-implants were tested. Two types of implants were used: some had SLA surface treatment and some had machined surfaces without coating. After 3 weeks of healing, rotational moments of 150 g were applied. The success rates, maximum torque values, angular momentum, and total energy absorbed by the bone were compared. All values were subjected to mixed-model analysis to evaluate the influence of surface treatment, rotational force direction, and site of implantation. Results: The maximum insertion torque and angular momentum of SLA implants were significantly lower than those of machined implants (P = .034, P = .039). The SLA implants had a significantly higher value for total removal energy than the machined implants (P = .046). However, there were no significant differences in total insertion energy, maximum removal torque, and removal angular momentum between the 2 groups. There was no significant difference between clockwise and counterclockwise rotation in all measurements. Conclusion: SLA mini-implants showed relatively lower insertion torque value and angular momentum and higher total energy during removal than the machined implants, suggesting osseointegration of the SLA mini-implant after insertion

Lightweight Monocular Depth Estimation via Token-Sharing Transformer

Depth estimation is an important task in various robotics systems and applications. In mobile robotics systems, monocular depth estimation is desirable since a single RGB camera can be deployable at a low cost and compact size. Due to its significant and growing needs, many lightweight monocular depth estimation networks have been proposed for mobile robotics systems. While most lightweight monocular depth estimation methods have been developed using convolution neural networks, the Transformer has been gradually utilized in monocular depth estimation recently. However, massive parameters and large computational costs in the Transformer disturb the deployment to embedded devices. In this paper, we present a Token-Sharing Transformer (TST), an architecture using the Transformer for monocular depth estimation, optimized especially in embedded devices. The proposed TST utilizes global token sharing, which enables the model to obtain an accurate depth prediction with high throughput in embedded devices. Experimental results show that TST outperforms the existing lightweight monocular depth estimation methods. On the NYU Depth v2 dataset, TST can deliver depth maps up to 63.4 FPS in NVIDIA Jetson nano and 142.6 FPS in NVIDIA Jetson TX2, with lower errors than the existing methods. Furthermore, TST achieves real-time depth estimation of high-resolution images on Jetson TX2 with competitive results.Comment: ICRA 202