Bioinformatics Analysis Identifies PLA2G7 as a Key Antigen-Presenting Prognostic Related Gene Promoting Hepatocellular Carcinoma through the STAT1/PD-L1 Axis.

BACKGROUND: Antigen presentation may be an important factor contributing to immune evasion in cancer. This study investigated antigen-presenting prognostic related genes (APPGs) and their potential mechanisms in hepatocellular carcinoma (HCC). METHODS: We constructed a score built upon the core APPGs (APP.Score) through nonnegative matrix factorization (NMF) clustering, weighted gene co-expression network analysis (WGCNA), random forest (RF), and least absolute shrinkage and selection operator (LASSO) methods. We also compared the clinical and molecular characteristics of different APP.Score. Furthermore, in vitro experiments were conducted to validate the expression of core APPGs and investigate the effects of phospholipase A2, group 7 (PLA2G7) knockdown on HCC cell development and programmed death-ligand 1 (PD-L1) expression. RESULTS: APP.Score was positively correlated with immune cell infiltration and levels of immune checkpoint inhibitor-related genes, and negatively correlated with overall survival (OS). The area under the curve values were 0.734, 0.747, and 0.679 for survival periods of 1, 2, and 3 years, respectively, indicating that APP.Score could be an independent prognostic factor for patients with HCC. OS of the high expression group of these genes, including PLA2G7, musculin, heat shock protein family A, secreted phosphoprotein 1, and neutrophil cytosolic factor 2 (NCF2) was lower than that of their low expression group. Moreover, the upregulation of key components of APPGs, except NCF2, was observed in HCC. The inhibition of PLA2G7 suppressed HCC progression and reduced PD-L1 and phosphorylated signal transducer and activator of transcription 1 (p-STAT1)/STAT1 levels in HepG2 and Huh-7 cells. Remarkably, the decrease in PD-L1 expression caused by PLA2G7 silencing was reversed upon treatment with a STAT1 activator. CONCLUSION: The results of this study show that APP.Score could be an independent prognostic factor for patients with HCC, and that PLA2G7 silencing inhibits cancer cell development and PD-L1 expression. We provide a new perspective and potential target for immune research on antigen presentation in HCC.

Financial Support for Agriculture, Chemical Fertilizer Use, and Carbon Emissions from Agricultural Production in China.

In the past 15 years, China has emitted the most carbon dioxide globally. The overuse of chemical fertilizer is an essential reason for agricultural carbon emissions. In recent years, China has paid more and more attention to financial support for agriculture. Therefore, understanding the relationship between chemical fertilizer use, financial support for agriculture, and agricultural carbon emissions will benefit sustainable agricultural production. To achieve the goal of our research, we selected the panel data of 30 provinces (cities) in China from 2000 to 2019 and employed a series of methods in this research. The results demonstrate that: the effect of chemical fertilizer consumption on agricultural carbon emissions is positive. Moreover, financial support for agriculture has a significantly positive impact on reducing carbon emissions from agricultural production. In addition, the results of causality tests testify to one-way causality from financial support for agriculture to carbon emissions from agricultural production, the bidirectional causal relationship between chemical fertilizer use and financial support for agriculture, and two-way causality between chemical fertilizer use and agricultural carbon emissions. Furthermore, the results of variance decomposition analysis represent that financial support for agriculture will significantly affect chemical fertilizer use and carbon emissions in the agricultural sector over the next decade. Finally, we provide several policy suggestions to promote low-carbon agricultural production based on the results of this study. The government should uphold the concept of sustainable agriculture, increase financial support for environmental-friendly agriculture, and encourage the research and use of cleaner agricultural production technologies and chemical fertilizer substitutes.

Selective visual attention during public speaking in an immersive context.

It has recently become feasible to study selective visual attention to social cues in increasingly ecologically valid ways. In this secondary analysis, we examined gaze behavior in response to the actions of others in a social context. Participants (N = 84) were asked to give a 5-minute speech to a five-member audience that had been filmed in 360° video, displayed in a virtual reality headset containing a built-in eye tracker. Audience members were coached to make movements that would indicate interest or lack of interest (e.g., nodding vs. looking away). The goal of this paper was to analyze whether these actions influenced the speaker's gaze. We found that participants showed reliable evidence of gaze towards audience member actions in general, and towards audience member actions involving their phone specifically (compared with other actions like looking away or leaning back). However, there were no differences in gaze towards actions reflecting interest (like nodding) compared with actions reflecting lack of interest (like looking away). Participants were more likely to look away from audience member actions as well, but there were no specific actions that elicited looking away more or less. Taken together, these findings suggest that the actions of audience members are broadly influential in motivating gaze behaviors in a realistic, contextually embedded (public speaking) setting. Further research is needed to examine the ways in which these findings can be elucidated in more controlled laboratory environments as well as in the real world.

Human Gaze Assisted Artificial Intelligence: A Review.

Human gaze reveals a wealth of information about internal cognitive state. Thus, gaze-related research has significantly increased in computer vision, natural language processing, decision learning, and robotics in recent years. We provide a high-level overview of the research efforts in these fields, including collecting human gaze data sets, modeling gaze behaviors, and utilizing gaze information in various applications, with the goal of enhancing communication between these research areas. We discuss future challenges and potential applications that work towards a common goal of human-centered artificial intelligence.