A GATA4-regulated secretory program suppresses tumors through recruitment of cytotoxic CD8 T cells

The GATA4 transcription factor acts as a master regulator of development of multiple tissues. GATA4 also acts in a distinct capacity to control a stress-inducible pro-inflammatory secretory program that is associated with senescence, a potent tumor suppression mechanism, but also operates in non-senescent contexts such as tumorigenesis. This secretory pathway is composed of chemokines, cytokines, growth factors, and proteases. Since GATA4 is deleted or epigenetically silenced in cancer, here we examine the role of GATA4 in tumorigenesis in mouse models through both loss-of-function and overexpression experiments. We find that GATA4 promotes non-cell autonomous tumor suppression in multiple model systems. Mechanistically, we show that Gata4-dependent tumor suppression requires cytotoxic CD8 T cells and partially requires the secreted chemokine CCL2. Analysis of transcriptome data in human tumors reveals reduced lymphocyte infiltration in GATA4-deficient tumors, consistent with our murine data. Notably, activation of the GATA4-dependent secretory program combined with an anti-PD-1 antibody robustly abrogates tumor growth in vivo.

Regulatory T cells suppress the formation of super-effector CD8 T cells by limiting IL-2

Regulatory T cells (Tregs) are indispensable for maintaining self-tolerance by suppressing conventional T cells. On the other hand, Tregs may promote tumor growth by inhibiting anti-cancer immunity. In this study, we identified that Tregs increase the quorum of self-reactive CD8+ T cells required for the induction of experimental autoimmune diabetes. Their major suppression mechanism is limiting available IL-2, a key cytokine for activated T cells. Specifically, Tregs inhibit the formation of a previously uncharacterized subset of antigen-stimulated CD8+ T cells. Since these T cells express high levels of IL-7 receptor and cytotoxic molecules (KLRK1, GZMB), and show superior cell killing abilities, we call them super-effector T cells. The administration of agonistic IL-2 immunocomplexes phenocopies the absence of Tregs, i.e., it induces super-effector T cells, promotes autoimmunity, and enhances anti-tumor responses. Counterparts of super-effector T cells were found in the human blood, revealing them as a potential target for immunotherapy.

Evaluation Technology of Classroom Students’ Learning State Based on Deep Learning

Facial features are an effective representation of students’ fatigue state, and the eye is more closely related to fatigue state. However, there are three main problems in the existing research: (1) the positioning of the eye is vulnerable to the external environment; (2) the ocular features need to be artificially defined and extracted for state judgment; and (3) although the student fatigue state detection based on convolutional neural network has a high accuracy, it is difficult to apply in the terminal side in real time. In view of the above problems, a method of student fatigue state judgment is proposed which combines face detection and lightweight depth learning technology. First, the AdaBoost algorithm is used to detect the human face from the input images, and the images marked with human face regions are saved to the local folder, which is used as the sample dataset of the open-close judgment part. Second, a novel reconstructed pyramid structure is proposed to improve the MobileNetV2-SSD to improve the accuracy of target detection. Then, the feature enhancement suppression mechanism based on SE-Net module is introduced to effectively improve the feature expression ability. The final experimental results show that, compared with the current commonly used target detection network, the proposed method has better classification ability for eye state and is improved in real-time performance and accuracy.

Hunt for rare processes and long-lived particles at FCC-ee

In this essay, we discuss the possibilities and associated challenges concerning beyond the Standard Model searches at FCC-ee, such as rare decays of heavy-flavoured particles and long-lived particles. The Standard Model contains several suppression mechanisms, which cause a given group of processes to happen rarely, resulting in rare decays. The interest in these decays lies in the fact that the physics beyond the Standard Model does not need to be affected by the same suppression mechanism and therefore can naturally manifest in these decays. Their interest is reinforced by the recent report of several measurements of b-flavoured rare decays, showing deviations with respect to the Standard Model predictions. We will show how the FCC-ee project has unique capabilities to address these scientific questions and will consider the related detector design challenges to meet. Another group of processes discussed are those that produce new particles with relatively long lifetimes that travel substantial distances inside the detectors before decaying. Models containing long-lived particles can give answers to many open questions of the Standard Model, such as the nature of dark matter, or the neutrino masses, among others, while providing an interesting experimental complement to mainstream searches. Long-lived particles often display unique experimental signatures, such as displaced tracks and vertices, “disappearing” tracks, or anomalously charged jets. Due to this, they are affected by very low background levels but in exchange, they often require dedicated reconstruction algorithms and triggers. The discovery of any of the discussed cases would have a critical impact in High Energy Physics, and FCC-ee could provide a unique experimental opportunity to explore them. Moreover, the searches proposed here could motivate an out-of-the-box optimization of the experimental conditions that could bring in innovative solutions, such as new, possibly very large tracking detectors; or cutting-edge reconstruction algorithms that would boost the FCC-ee reach for unusual final states.