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There are various production items in the industrial internet of things (IIoT) environment, such as pedestrians, robots, automated automated guided vehicles, etc. The practice industrial environment requires simultaneous communication and sensing of production items to achieve intelligent production and control. Thus, sensing methods not only require the integration of communication but also achieve sensing tasks such as recognition and positioning. Compared with traditional sensing media, visible light sensing has the advantages of high-speed communication, high sensing accuracy, and security, low energy consumption, and has become a potential sensing technology. Based on the strong directivity of visible light spatial radiation and the consistency of light intensity and position, this paper proposes a multi-scale visible light sensing-region convolutional neural network (VLS-RCNN) framework based on shadow features for multiple target sensing. The framework enables the recognition and positioning to use shared visible light shadow features to assist each other, and the multi-scale compensation strategy of the shadow region makes the framework more robust. The simulation results show that positioning results in the sensing area improve the recognition accuracy. The recognition results also reduce the positioning error without additional overhead. Therefore, this paper provides a new perspective for the sensing technology in the future IIoT, which should be considered to sense objects of interest by utilizing the inherent characteristics of visible light.

The industrial Internet of Things (IIoT) environment involves multiple production items, such as robots and automated guided vehicles (AGVs), among others. The practical industrial scenario requires communication of production items while also considering mobile recognition and positioning. Hence the perception approach requires not only combining communications but also realizing the recognition and positioning of multiple communication cells. This Letter proposes a multi-optical cell recognition and positioning framework based on LED image features. The LED images are obtained by a CMOS image sensor. This framework utilizes convolutional neural networks (CNN) to train LED images for recognition between multiple optical cells and locates precise positions through region recognition within the optical cells. The experimental results show that the mean accuracy of the CNN model for two LED cells is above 99%, and the mean accuracy of region recognition within the optical cell is as high as 100%, which is significantly better than other traditional recognition algorithms. Therefore, the proposed framework can provide location-aware services for visible light communication and has a wide application prospect in IIoT.

In the industrial environment, the positioning of mobile terminals plays an important role in production scheduling. Visible light positioning (VLP) based on a CMOS image sensor has been widely considered as a promising indoor positioning technology. However, the existing VLP technology still faces many challenges, such as modulation and decoding schemes, and strict synchronization requirements. In this paper, a visible light area recognition framework based on convolutional neural network (CNN) is proposed, where the training data is the LED images acquired by the image sensor. The mobile terminal positioning can be realized from the perspective of recognition without modulating LED. The experimental results show that the mean accuracy of the optimal CNN model is as high as 100% for the two-class and the four-class area recognitions, and is more than 95% for the eight-class area recognition. These results are obviously superior to other traditional recognition algorithms. More importantly, the model has high robustness and universality, which can be applied to various types of LED lights.

The etiology of preeclampsia (PE) is still unknown, and excessive immune activation is an important component of its pathogenesis. Programmed cell death protein 1 (PD-1) is one of immune checkpoints which may prevent overactivated immune attack and lead to a tolerant immune microenvironment. Little is known about the involvement of PD-1-mediated immunoregulation at the maternal-fetal interface in PE. To investigate the inflammatory pattern and the involvement of PD-1 in the decidua of women with PE, decidual tissues were obtained from PE and control pregnant women. Quantitative RT-PCR analysis of the mRNA levels of the inflammatory cytokines was performed. PD-1 expression was detected by immunohistochemistry, western blot analysis, and flow cytometry. To prove the role of PD-1, decidual immune cells were incubated with blocking antibodies, and the inflammatory cytokines were detected by ELISA. We observed that the mRNA levels of IL-1β, IL-6, TNF-α, and IFN-γ were higher in the decidua of the PE group than in the decidua of the control group. The mRNA levels of IL-4 and IL-10 were lower in PE. The expression level of PD-1 was significantly downregulated, and the proportion (%) of PD-1 + CD45 + cells was significantly lower in PE. There was a significant linear correlation between PD-1 expression and common proinflammatory cytokines in the decidua. Anti-PD-1 blocking antibody significantly increased the secretion of proinflammatory cytokines. Our data suggested that the inflammatory pattern and decreased PD-1 expression in the decidua might play an active role in the local immunoregulatory mechanisms of PE. The PD-1 pathway in the maternal-fetal interface possibly function to break the tolerant immune microenvironment in PE via inflammatory cytokines., (© 2022. Society for Reproductive Investigation.)

Acute liver injury is a common and serious syndrome caused by multiple factors and unclear pathogenesis. If the injury persists, liver injury can lead to cirrhosis and liver failure and ultimately results in the development of liver cancer. Emerging evidence has indicated that long noncoding RNAs (lncRNAs) play an important role in the development of liver injury. However, the role of antisense Igf2r RNA (Airn) in acute liver injury and its underlying mechanism remain largely unclear. In this study, we show that Airn is upregulated in liver tissue and primary hepatocytes from an acute liver injury mouse model. Consistently, Airn is also overexpressed in serum samples of patients with acute-on-chronic liver failure and is negatively correlated with the Model for End-Stage Liver Disease (MELD) score. Moreover, gene knockout and rescue assays reveal that Airn alleviates CCl 4 -induced liver injury by inhibiting hepatocyte apoptosis and oxidative stress in vivo . Further investigation reveals that Airn decreases H 2 O 2 -induced hepatocyte apoptosis in vitro . Mechanistically, we reveal that Airn represses CCl 4 - and H 2 O 2 -induced enhancement of phosphorylation of p65 and IκBα, suggesting that Airn inhibits hepatocyte apoptosis by inactivating the NF-κB pathway. In conclusion, our results demonstrate that Airn can alleviate acute liver injury by inhibiting hepatocyte apoptosis via inactivating the NF-κB signaling pathway, and Airn could be a potential biomarker for acute liver injury.

Background: Long noncoding RNAs (lncRNAs) have emerged as important regulators in a variety of human diseases. The dysregulation of liver sinusoidal endothelial cell (LSEC) phenotype is a critical early event in the fibrotic process. However, the biological function of lncRNAs in LSEC still remains unclear., Methods: The expression level of lncRNA Airn was evaluated in both human fibrotic livers and serums, as well as mouse fibrotic livers. Gain- and loss-of-function experiments were performed to detect the effect of Airn on LSEC differentiation and hepatic stellate cell (HSC) activation in liver fibrosis. Furthermore, RIP, RNA pull-down-immunoblotting, and ChIP experiments were performed to explore the underlying mechanisms of Airn., Results: We have identified Airn was significantly upregulated in liver tissues and LSEC of carbon tetrachloride (CCl 4 )-induced liver fibrosis mouse model. Moreover, the expression of AIRN in fibrotic human liver tissues and serums was remarkably increased compared with healthy controls. In vivo studies showed that Airn deficiency aggravated CCl 4 - and bile duct ligation (BDL)-induced liver fibrosis, while Airn over-expression by AAV8 alleviated CCl 4 -induced liver fibrosis. Furthermore, we revealed that Airn maintained LSEC differentiation in vivo and in vitro. Additionally, Airn inhibited HSC activation indirectly by regulating LSEC differentiation and promoted hepatocyte (HC) proliferation by increasing paracrine secretion of Wnt2a and HGF from LSEC. Mechanistically, Airn interacted with EZH2 to maintain LSEC differentiation through KLF2-eNOS-sGC pathway, thereby maintaining HSC quiescence and promoting HC proliferation., Conclusions: Our work identified that Airn is beneficial to liver fibrosis by maintaining LSEC differentiation and might be a serum biomarker for liver fibrogenesis., (© 2022. The Author(s).)

To reveal whether STARD5 is a potential biomarker for diagnosis and prognosis of HCC. Using gene expression omnibus and the cancer genome atlas (TCGA) to screen differentially expressed genes in HCC and STARD5 was selected by LASSO algorithm. Then, we analyzed the association between STARD5 and clinical characteristics of HCC patients in TCGA and International Cancer Genome Consortium. Meanwhile, the mRNA and protein level of STARD5 was also verified by collecting 87 cases of HCC patients' liver tissues using qRT-PCR and WB. Next, we applied gene set enrichment analysis (GSEA) for pathways analysis of STARD5. Finally, TIMER1.0 and TISIDB were used to explore the correlation of STARD5 with immune cell infiltration. The expression of STARD5 was lower in HCC and negatively correlated with tumor grade (p < 0.05), while high expression of STARD5 suggested a better prognosis for HCC patients (p < 0.01) and it could be an independent prognostic predictor (p < 0.001). Meanwhile, STARD5 also had strong diagnostic accuracy for HCC patients. GSEA revealed that STARD5-related genes were mainly enriched in E2F targets, G2M checkpoint and KRAS signaling. The TIMER1.0 and TISIDB databases found a negative correlation between STARD5 and tumor immune infiltrating cells. STARD5 could be used as a potential target for HCC diagnosis and prognosis., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Antibody-mediated rejection (AMR) is one of the major causes of graft loss after transplantation. Recently, the regulation of B cell differentiation and the prevention of donor-specific antibody (DSA) production have gained increased attention in transplant research. Herein, we established a secondary allogeneic in vivo skin transplant model to study the effects of romidepsin (FK228) on DSA. The survival of grafted skins was monitored daily. The serum levels of DSA and the number of relevant immunocytes in the recipient spleens were evaluated by flow cytometry. Then, we isolated and purified B cells from B6 mouse spleens in vitro by magnetic bead sorting. The B cells were cultured with interleukin-4 (IL-4) and anti-clusters of differentiation 40 (CD40) antibody with or without FK228 treatment. The immunoglobulin G1 (IgG1) and IgM levels in the supernatant were evaluated by enzyme-linked immunosorbent assay (ELISA). Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) and western blotting were conducted to determine the corresponding levels of messenger RNA (mRNA) and protein expression in cultured cells and the recipient spleens. The results showed that FK228 significantly improved the survival of allogeneic skin grafts. Moreover, FK228 inhibited DSA production in the serum along with the suppression of histone deacetylase 1 (HADC1) and HDAC2 and the upregulation of the acetylation of histones H2A and H3. It also inhibited the differentiation of B cells to plasma cells, decreased the transcription of positive regulatory domain-containing 1 ( Prdm 1) and X-box-binding protein 1 ( Xbp1 ), and decreased the expression of phosphorylated inositol-requiring enzyme 1 α (p-IRE1α), XBP1, and B lymphocyte-induced maturation protein-1 (Blimp-1). In conclusion, FK228 could decrease the production of antibodies by B cells via inhibition of the IRE1α-XBP1 signaling pathway. Thus, FK228 is considered as a promising therapeutic agent for the clinical treatment of AMR.

The excessive accumulation of extracellular matrix (ECM) is a key feature of liver fibrosis and the activated hepatic stellate cells (HSCs) are the major producer of ECM proteins. However, the precise mechanisms and target molecules that are involved in liver fibrosis remain unclear. In this study, we reported that activating transcription factor 3 (ATF3) was over-expressed in mice and human fibrotic livers, in activated HSCs and injured hepatocytes (HCs). Both in vivo and in vitro study have revealed that silencing ATF3 reduced the expression of pro-fibrotic genes and inhibited the activation of HSCs, thus alleviating the extent of liver fibrosis, indicating a potential protective role of ATF3 knockdown. However, ATF3 was not involved in either the apoptosis or proliferation of HCs. In addition, our data illustrated that increased nuclear localization of ATF3 promoted the transcription of fibrogenic genes and lnc-SCARNA10, which functioned as a novel positive regulator of TGF-β signaling in liver fibrogenesis by recruiting SMAD3 to the promoter of these genes. Interestingly, further study also demonstrated that lnc-SCARNA10 promoted the expression of ATF3 in a TGF-β/SMAD3-dependent manner, revealing a TGF-β/ATF3/lnc-SCARNA10 axis that contributed to liver fibrosis by activating HSCs. Taken together, our data provide a molecular mechanism implicating induced ATF3 in liver fibrosis, suggesting that ATF3 may represent a useful target in the development of therapeutic strategies for liver fibrosis.