Identification and Functional Analysis of a de novo IKZF3 Mutation in a Pediatric Patient with Combined Immunodeficiency.

AIOLOS, a vital member of the IKAROS protein family, plays a significant role in lymphocyte development and function through DNA binding and protein-protein interactions. Mutations in the IKZF3 gene, which encodes AIOLOS, lead to a rare combined immunodeficiency often linked with infections and malignancy. In this study, we evaluated a 1-year-4-month-old female patient presenting with recurrent infections, diarrhea, and failure to thrive. Laboratory investigations revealed decreased T lymphocyte and immunoglobulin levels. Through whole-exome and Sanger sequencing, we discovered a de novo mutation in IKZF3 (NM_012481; exon 5 c.571G > C, p.Gly191Arg), corresponding to the third DNA-binding zinc finger region of the encoded protein AIOLOS. Notably, the patient with the AIOLOS G191R mutation showed reduced recent thymic emigrants in naïve CD4+T cells compared to healthy counterparts of the same age, while maintaining normal levels of Th1, Th2, Th17, Treg, and Tfh cells. This mutation also resulted in decreased switched memory B cells and lower CD23 and IgM expression. In vitro studies revealed that AIOLOS G191R does not impact the expression of AIOLOS but compromises its stability, DNA binding and pericentromeric targeting. Furthermore, AIOLOS G191R demonstrated a dominant-negative effect over the wild-type protein. This case represents the first reported instance of a mutation in the third DNA-binding zinc finger region of AIOLOS highlighting its pivotal role in immune cell functionality.

A Framework and Algorithm for Human-Robot Collaboration Based on Multimodal Reinforcement Learning.

Despite the emergence of various human-robot collaboration frameworks, most are not sufficiently flexible to adapt to users with different habits. In this article, a Multimodal Reinforcement Learning Human-Robot Collaboration (MRLC) framework is proposed. It integrates reinforcement learning into human-robot collaboration and continuously adapts to the user's habits in the process of collaboration with the user to achieve the effect of human-robot cointegration. With the user's multimodal features as states, the MRLC framework collects the user's speech through natural language processing and employs it to determine the reward of the actions made by the robot. Our experiments demonstrate that the MRLC framework can adapt to the user's habits after repeated learning and better understand the user's intention compared to traditional solutions.

A Massage Area Positioning Algorithm for Intelligent Massage System.

A growing number of studies have been conducted over the past few years on the positioning of daily massage robots. However, most methods used for research have low interactivity, and a systematic method should be designed for accurate and intelligent positioning, thus compromising usability and user experience. In this study, a massage positioning algorithm with online learning capabilities is presented. The algorithm has the following main innovations: (1) autonomous massage localization can be achieved by gaining insights into natural human-machine interaction behavior and (2) online learning of user massage habits can be achieved by integrating recursive Bayesian ideas. As revealed by the experimental results, combining natural human-computer interaction and online learning with massage positioning is capable of helping people get rid of positioning aids, reducing their psychological and cognitive load, and achieving a more desirable positioning effect. Furthermore, the results of the analysis of user evaluations further verify the effectiveness of the algorithm.

Dexamethasone and lenvatinib inhibit migration and invasion of non-small cell lung cancer by regulating EKR/AKT and VEGF signal pathways.

Migration and invasion is one of the most important features in tumor metastasis and development. Non-small cell lung cancer (NSCLC) is one of the most common types of cancer globally, and has been linked to air contamination. Evidence indicates that cysteine-rich angiogenic inducer 61 (CYR61) is associated with the migration and invasion of NSCLC. Overexpression of CYR61 protein promotes the migration and the transition of tumor-derived vascular endothelial cells in NSCLC. However, the association between CYR61 and NSCLC remains poorly understood. Lenvatinib is an oral multi-target drug that targets various receptors upon tumor angiogenesis. Dexamethasone is widely approved for combination therapy in patients with NSCLC. In the current study, the expression and function of CYR61 in NSCLC was analyzed during the progression of NSCLC. Inhibitory effects on migration and invasion induced by lenvatinib and dexamethasone were determined by migratory and invasion assays. Migratory pathways of extracellular signal-regulated kinases (ERK) and protein kinase B (AKT) were also investigated by targeting vascular endothelial growth factor (VEGF) and CYR61 via synergistic treatment with transforming growth factor-ß1 (TGF-ß1) and dexamethasone. Therapeutic outcomes of combined treatment with lenvatinib and dexamethasone were assessed in NSCLC-bearing mice. The results of the present study indicate that cooperative treatment of lenvatinib and dexamethasone significantly inhibited TGF-ß1-induced cell migration and suppressed tumor growth (P<0.01). Notably, the results demonstrated that dexamethasone eradicated the promotion effects of TGF-ß1 on the AKT/epithelial-mesenchymal transition process and lenvatinib extinguished tumor cell metastasis by targeting VEGF. The results of the current study also demonstrate that dexamethasone suppressed the expression of CAG-I and enhanced expression of matrix metalloproteinase-1. Synergistic treatment for NSCLC was demonstrated to be efficacious. In conclusion, dexamethasone inhibited AKT/ERK phosphorylation and lenvatinib antagonism bound VEGF leading to the limitation of migration and invasion of cancer cells in NSCLC.

Detachment-Based Equilibrium of Anoikic Cell Death and Autophagic Cell Survival Through Adaptor Protein p66(Shc).

Anoikis (detachment-induced cell death) confers a tumor-suppressive function in metastatic cancer cells. Autophagy, a conserved self-degradative process, enhances the anoikis resistance of detached cancer cells by maintaining cellular homeostasis. However, the mechanism of regulating cell fate-decision by balancing anoikis and autophagy has been poorly understood. Our previous studies have shown that the adaptor protein p66(Shc) mediates anoikis through RhoA activation and inhibits tumor metastasis in vivo. We also found that p66(Shc) depletion mitigates nutrient-deprivation-induced autophagy. These findings suggest p66(Shc) may coordinately regulate these two processes. To verify this hypothesis, we investigated the effect of p66(Shc) on the cell death of detached lung cancer cells, and measured autophagy markers and autophagic flux. Results showed that p66(Shc) depletion significantly inhibited anoikis, and reduced the formation of LC3B-II and the degradation of Sequestosome 1 (SQSTM1, p62) in detachment-induced cells. Using monodansylcadaverine (MDC)-LysoTracker double staining and monomeric Cherry (mCherry)-GFP-LC3 assay, we found that the autophagic flux was also mitigated by p66(Shc) depletion. In addition, p66(Shc) knockdown increased the formation of full-length X-linked inhibitor of apoptosis (XIAP)-associated factor 1 (XAF1), which enhances anoikis sensitivity. In conclusion, p66(Shc) plays an essential role in detachment-based equilibrium of anoikic cell death and autophagic cell survival.

The effect of ionizing radiation on mRNA levels of the DNA damage response genes rad9, rad1 and hus1 in various mouse tissues.

Rad9, Rad1 and Hus1 are essential genes conserved from yeast to humans. They form a heterotrimer complex (9-1-1 complex) that participates in the cell cycle checkpoint activation and DNA damage repair in eukaryotic cells. Rad9, Rad1 and Hus1 deficient cells are hypersensitive to ionizing radiation and mouse cells deleted for anyone of the three genes are highly sensitive to the killing by gamma rays. We propose that ionizing radiation-induced transcription of these genes is a mechanism by which cells respond to radiation-induced damage. In this study we used quantitative real-time RT-PCR(qPCR) to analyze the mRNA levels of Rad9, Rad1 and Hus1 in various tissues isolated from mice that were either mock irradiated or exposed to 10 Gy gamma radiation. Our results indicated that the mRNA levels of Rad9, Rad1 and Hus1 genes were very different among these tissues, and we found high natural levels of mRNA in the spleen, lung, ovary and testis of mice before exposure to radiation. The mRNA levels of the three genes were well correlated across these tissues, being high, medium or low in each of the tissues simultaneously. The mRNA levels of the three genes were analyzed at 2, 6, 12, 24 and 48 h after irradiation. In most tissues Rad9 was strongly induced at 2 and 12 h time points and Hus1 was strongly induced at 2, 12 and 48 h time points, but Rad1 was minimally induced in most of the tissues with the exception of slightly higher levels in the heart and lung tissues at the 48 h time point. These results suggest that the regulation mechanisms for the mRNA levels of the three genes in response to ionizing radiation are complex and not well orchestrated. We also detected the induction of Rad9 and Hus1 proteins in the heart and liver of the animals after irradiation, and found that Rad9 protein levels were highly induced in both the heart and liver, while the Hus1 protein levels were significantly induced only in the liver, suggesting that Rad9 and Hus1 protein levels are not regulated in a coordinated manner in response to irradiation. We then went on to measure the mRNA levels of the three genes and the Rad9 and Hus1 protein levels in the mouse liver cell line (NCTC 1469) in response to irradiation in vitro. All three genes in the cultured cells were minimally induced at mRNA level, obviously different from the highly dynamic induction in liver. Rad9 and Hus1 were significantly induced at the protein level, but the induced Rad9 protein levels were higher than the Hus1 levels. Taken together, the good correlation of the mRNA levels of Rad9, Hus1 and Rad1 genes across different tissues isolated from the animals that were mock irradiated and the lack of correlation in mRNA as well as protein levels after irradiation suggest that the 9-1-1 complex has evolved to play various physiological roles in tissues rather than dealing with high doses of gamma radiation or other genotoxic agents.