Mast Cell-Mediated Inhibition of Abdominal Neutrophil Inflammation by a PEGylated TLR7 Ligand

Although the mechanisms for sustained chemokine gradients and recurring cell infiltration in sterile peritonitis have not been elucidated, toll-like receptors (TLRs) have been implicated. To abate the deleterious recruitment of neutrophils in sterile inflammation, we repeatedly administered a TLR7 ligand that hyposensitized to TLR7 and receptors that converged on the MyD88-signaling intermediary and reduced cellular infiltration in murine autoimmune models of multiple sclerosis and arthritis. To reduce potential adverse effects, a polyethylene glycol polymer was covalently attached to the parent compound (Tolerimod1). The proinflammatory potency of Tolerimod1 was 10-fold less than the unconjugated TLR7 ligand, and Tolerimod1 reduced neutrophil recruitment in chemically induced peritonitis and colitis. The effects of Tolerimod1 were mediated by the radioresistant cells in radiation chimeric mice and by mast cells in reconstituted mast cell-deficient mice (KitW-sh). Although the Tolerimod1 had weak proinflammatory agonist activity, it effectively reduced neutrophil recruitment in sterile peritoneal inflammation

Vision-based human action quality assessment: A systematic review

Human Action Quality Assessment (AQA), which aims to automatically evaluate the performance of actions executed by humans, is an emerging field of human action analysis. Although many review articles have been conducted for human action analysis fields such as action recognition and action prediction, there is a lack of up-to-date and systematic reviews related to AQA. This paper aims to provide a systematic literature review of existing papers on vision-based human AQA. This systematic review was rigorously conducted following the PRISMA guideline through the databases of Scopus, IEEE Xplore, and Web of Science in July 2024. Ninety-six research articles were selected for the final analysis after applying inclusion and exclusion criteria. This review presents an overview of various aspects of AQA, including existing applications, data acquisition methods, public datasets, state-of-the-art methods and evaluation metrics. We observe an increase in the number of studies in AQA since 2019, primarily due to the advent of deep learning methods and motion capture devices. We categorize these AQA methods into skeleton-based and video-based methods based on the data modality used. There are different evaluation metrics for various AQA tasks. SRC is the most commonly used evaluation metric, with fifty-six out of ninety-six selected papers using it to evaluate their models. Sports event scoring, surgical skill evaluation and rehabilitation assessment are the most popular three scenarios in this direction based on existing papers and there are more new scenarios being explored such as piano skill assessment. Furthermore, the existing challenges and future research directions are provided, which can be a helpful guide for researchers to explore AQA

Ethacrynic Acid Exhibits Selective Toxicity to Chronic Lymphocytic Leukemia Cells by Inhibition of the Wnt/β-Catenin Pathway

Aberrant activation of Wnt/β-catenin signaling promotes the development of several cancers. It has been demonstrated that the Wnt signaling pathway is activated in chronic lymphocytic leukemia (CLL) cells, and that uncontrolled Wnt/β-catenin signaling may contribute to the defect in apoptosis that characterizes this malignancy. Thus, the Wnt signaling pathway is an attractive candidate for developing targeted therapies for CLL. assays further confirmed the inhibitory effect of EA on Wnt/β-catenin signaling. Cell viability assays showed that EA selectively induced cell death in primary CLL cells. Exposure of CLL cells to EA decreased the expression of Wnt/β-catenin target genes, including LEF-1, cyclin D1 and fibronectin. Immune co-precipitation experiments demonstrated that EA could directly bind to LEF-1 protein and destabilize the LEF-1/β-catenin complex. N-acetyl-L-cysteine (NAC), which can react with the α, β-unsaturated ketone in EA, but not other anti-oxidants, prevented the drug's inhibition of Wnt/β-catenin activation and its ability to induce apoptosis in CLL cells.Our studies indicate that EA selectively suppresses CLL survival due to inhibition of Wnt/β-catenin signaling. Antagonizing Wnt signaling in CLL with EA or related drugs may represent an effective treatment of this disease

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Stochastic Bandits with Graph Feedback in Non-Stationary Environments

We study a variant of stochastic bandits where the feedback model is specified by a graph. In this setting, after playing an arm, one can observe rewards of not only the played arm but also other arms that are adjacent to the played arm in the graph. Most of the existing work assumes the reward distributions are stationary over time, which, however, is often violated in common scenarios such as recommendation systems and online advertising. To address this limitation, we study stochastic bandits with graph feedback in non-stationary environments and propose algorithms with graph-dependent dynamic regret bounds. When the number of reward distribution changes L is known in advance, one of our algorithms achieves an Õ(√(αLT)) dynamic regret bound. We also develop an adaptive algorithm that can adapt to unknown L and attain an Õ(√(θLT)) dynamic regret. Here, α and θ are some graph-dependent quantities and T is the time horizon

Localization of the Naturally Occurring Plasmid ColE1 at the Cell Pole

The naturally occurring plasmid ColE1 was found to localize as a cluster in one or both of the cell poles of Escherichia coli. In addition to the polar localization of ColE1 in most cells, movement of the plasmid to the midcell position was observed in time-lapse studies. ColE1 could be displaced from its polar location by the p15A replicon, pBAD33, but not by plasmid RK2. The displacement of ColE1 by pBAD33 resulted in an almost random positioning of ColE1 foci in the cell and also in a loss of segregational stability, as evidenced by the large number of cells carrying pBAD33 with no visible ColE1 focus and as confirmed by ColE1 stability studies. The addition of the active partitioning systems of the F plasmid (sopABC) or RK2 (O(B1) incC korB) resulted in movement of the ColE1 replicon from the cell pole to within the nucleoid region. This repositioning did not result in destabilization but did result in an increase in the number of plasmid foci, most likely due to partial declustering. These results are consistent with the importance of par regions to the localization of plasmids to specific regions of the cell and demonstrate both localization and dynamic movement for a naturally occurring plasmid that does not encode a replication initiation protein or a partitioning system that is required for plasmid stability

Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization

We aim to design universal algorithms for online convex optimization, which can handle multiple common types of loss functions simultaneously. The previous state-of-the-art universal method has achieved the minimax optimality for general convex, exponentially concave and strongly convex loss functions. However, it remains an open problem whether smoothness can be exploited to further improve the theoretical guarantees. In this paper, we provide an affirmative answer by developing a novel algorithm, namely UFO, which achieves O(√L*), O(d log L*) and O(log L*) regret bounds for the three types of loss functions respectively under the assumption of smoothness, where L* is the cumulative loss of the best comparator in hindsight, and d is dimensionality. Thus, our regret bounds are much tighter when the comparator has a small loss, and ensure the minimax optimality in the worst case. In addition, it is worth pointing out that UFO is the first to achieve the O(log L*) regret bound for strongly convex and smooth functions, which is tighter than the existing small-loss bound by an O(d) factor.</jats:p