Immune Checkpoint LAG3 and Its Ligand FGL1 in Cancer

LAG3 is the most promising immune checkpoint next to PD-1 and CTLA-4. High LAG3 and FGL1 expression boosts tumor growth by inhibiting the immune microenvironment. This review comprises four sections presenting the structure/expression, interaction, biological effects, and clinical application of LAG3/FGL1. D1 and D2 of LAG3 and FD of FGL1 are the LAG3-FGL1 interaction domains. LAG3 accumulates on the surface of lymphocytes in various tumors, but is also found in the cytoplasm in non-small cell lung cancer (NSCLC) cells. FGL1 is found in the cytoplasm in NSCLC cells and on the surface of breast cancer cells. The LAG3-FGL1 interaction mechanism remains unclear, and the intracellular signals require elucidation. LAG3/FGL1 activity is associated with immune cell infiltration, proliferation, and secretion. Cytokine production is enhanced when LAG3/FGL1 are co-expressed with PD-1. IMP321 and relatlimab are promising monoclonal antibodies targeting LAG3 in melanoma. The clinical use of anti-FGL1 antibodies has not been reported. Finally, high FGL1 and LAG3 expression induces EGFR-TKI and gefitinib resistance, and anti-PD-1 therapy resistance, respectively. We present a comprehensive overview of the role of LAG3/FGL1 in cancer, suggesting novel anti-tumor therapy strategies.

The role of phosphatidylserine on the membrane in immunity and blood coagulation

The negatively charged aminophospholipid, phosphatidylserine (PtdSer), is located in the inner leaflet of the plasma membrane in normal cells, and may be exposed to the outer leaflet under some immune and blood coagulation processes. Meanwhile, Ptdser exposed to apoptotic cells can be recognized and eliminated by various immune cells, whereas on the surface of activated platelets Ptdser interacts with coagulation factors prompting enhanced production of thrombin which significantly facilitates blood coagulation. In the case where PtdSer fails in exposure or mistakenly occurs, there are occurrences of certain immunological and haematological diseases, such as the Scott syndrome and Systemic lupus erythematosus. Besides, viruses (e.g., Human Immunodeficiency Virus (HIV), Ebola virus (EBOV)) can invade host cells through binding the exposed PtdSer. Most recently, the Corona Virus Disease 2019 (COVID-19) has been similarly linked to PtdSer or its receptors. Therefore, it is essential to comprehensively understand PtdSer and its functional characteristics. Therefore, this review summarizes Ptdser, its eversion mechanism; interaction mechanism, particularly with its immune receptors and coagulation factors; recognition sites; and its function in immune and blood processes. This review illustrates the potential aspects for the underlying pathogenic mechanism of PtdSer-related diseases, and the discovery of new therapeutic strategies as well.

Succinyl-κ-carrageenan Silver Nanotriangles Composite for Ammonium Localized Surface Plasmon Resonance Sensor

This research investigates the physicochemical properties of biopolymer succinyl-κ-carrageenan as a potential sensing material for NH4+ Localized Surface Plasmon Resonance (LSPR) sensor. Succinyl-κ-carrageenan was synthesised by reacting κ-carrageenan with succinic anhydride. FESEM analysis shows succinyl-κ-carrageenan has an even and featureless topology compared to its pristine form. Succinyl-κ-carrageenan was composited with silver nanoparticles (AgNP) as LSPR sensing material. AFM analysis shows that AgNP-Succinyl-κ-carrageenan was rougher than AgNP-Succinyl-κ-carrageenan, indicating an increase in density of electronegative atom from oxygen compared to pristine κ-carrageenan. The sensitivity of AgNP-Succinyl-κ-carrageenan LSPR is higher than AgNP-κ-carrageenan LSPR. The reported LOD and LOQ of AgNP-Succinyl-κ-carrageenan LSPR are 0.5964 and 2.7192 ppm, respectively. Thus, AgNP-Succinyl-κ-carrageenan LSPR has a higher performance than AgNP-κ-carrageenan LSPR, broader detection range than the conventional method and high selectivity toward NH4+. Interaction mechanism studies show the adsorption of NH4+ on κ-carrageenan and succinyl-κ-carrageenan were through multilayer and chemisorption process that follows Freundlich and pseudo-second-order kinetic model.

RENT-SEEKING DECISIONS OF THE MAIN PARTICIPANTS IN CONSTRUCTION PROJECTS BASED ON EVOLUTIONARY-GAME AND SYSTEM DYNAMICS

The performance of a construction project can be severely harmed by its participants’ rent-seeking. In order to prevent such attempt, this research integrates the evolutionary game theory with system dynamics method to simulate the impact of the change of some factors that may cause/reduce rent-seeking. Based on the analysis of the behavioral characteristics and interactive relationships of the main participants (the owner, supervisor, and contractor), an evolutionary game model is constructed and simulated with the method of system dynamics based on the replication dynamic equation of the mixed strategy solution of the three-party static game model. By assigning the parameters of project scale, supervision likelihood, supervision success rate, supervision cost, and penalty intensity, the interaction mechanism of the participants on each factor is revealed through a case-based simulation. The results show that the impacts of these factors on participants’ rent-seeking decisions are significantly different. Furthermore, some management suggestions are provided to prevent rent-seeking for project owner according to the research conclusions. This research can help the project owners take proper measures to prevent rent-seeking of the supervisors and the contractors to improve the performances of the projects.

Intelligent Contracts in Engineering Enterprise Supply Management

Intellectual contracts based on blockchain technology improve the efficiency of supply management of an automobile enterprise by optimizing the transactional costs of supply logistics. The present research featured KAMAZ PTC. The goal was to develop an interaction mechanism for all participants of an intellectual contract in supply activities. The article includes a review of Russian and foreign publications about intellectual contracts in various business spheres, supply management efficiency, optimization of transactional costs, and blockchain technology. The study made it possible to build an interaction mechanism of the parties involved in a blockchain intellectual contract. It also revealed a pattern of changes introduced to the intellectual contract at different stages of interaction between the initiator and suppliers. The authors also highlighted the difference between smart contract and intellectual contract. An intellectual contract appears as a logical development of a smart contract and allows the sides to change the terms. The party interaction mechanism can improve the supply efficiency as it optimizes the magnitude of transactional costs.

Biomedical relation extraction via knowledge-enhanced reading comprehension

Background In biomedical research, chemical and disease relation extraction from unstructured biomedical literature is an essential task. Effective context understanding and knowledge integration are two main research problems in this task. Most work of relation extraction focuses on classification for entity mention pairs. Inspired by the effectiveness of machine reading comprehension (RC) in the respect of context understanding, solving biomedical relation extraction with the RC framework at both intra-sentential and inter-sentential levels is a new topic worthy to be explored. Except for the unstructured biomedical text, many structured knowledge bases (KBs) provide valuable guidance for biomedical relation extraction. Utilizing knowledge in the RC framework is also worthy to be investigated. We propose a knowledge-enhanced reading comprehension (KRC) framework to leverage reading comprehension and prior knowledge for biomedical relation extraction. First, we generate questions for each relation, which reformulates the relation extraction task to a question answering task. Second, based on the RC framework, we integrate knowledge representation through an efficient knowledge-enhanced attention interaction mechanism to guide the biomedical relation extraction. Results The proposed model was evaluated on the BioCreative V CDR dataset and CHR dataset. Experiments show that our model achieved a competitive document-level F1 of 71.18% and 93.3%, respectively, compared with other methods. Conclusion Result analysis reveals that open-domain reading comprehension data and knowledge representation can help improve biomedical relation extraction in our proposed KRC framework. Our work can encourage more research on bridging reading comprehension and biomedical relation extraction and promote the biomedical relation extraction.

miR-622 Induces Breast Cancer Cell MCF-7 Proliferation, Migration, and Invasion by Directly Negatively Targeting EYA1

Breast cancer is the most common female cancer in the world. Breast cancer patients are currently treated with a combination of surgery, chemotherapy, radiotherapy, and targeted therapy, but the 5-year overall survival rate is still low. Therefore, we plan to explore the potential interaction mechanism between miR-622 and EYA1 in the breast cancer cells and their effect on proliferation, migration, and invasion of breast cancer, to lay a foundation for the gene therapy of breast cancer and improve the therapeutic effect. This study found that miR-622 was highly expressed in breast cancer cell lines, while EYA1 was poorly. In MCF-7 cell line, miR-622 had the highest expression level, while EYA1 had the lowest. Besides, the bioinformatics analysis showed that EYA1 possesses putative miR-622 binding sites within its 3 ′ UTR. The increased miR-622 significantly enhanced the proliferation, migration, and invasion of MCF-7 cell line and inhibited luciferase reporter activity in the 3 ′ UTR of EYA1-WT. When upregulating the expression of miR-622, the mRNA and protein expression levels of EYA1 were significantly decreased. We also found that the silencing of EYA1 promoted the proliferation, migration, and invasion of breast cancer MCF-7 cell line. These results indicate that miRNA-622 plays a tumor-promoting role in breast cancer through targeted negative regulation of EYA1, suggesting that miRNA-622 may become a potential target for breast cancer treatment.

Impact Forces and Energy of Flow-like Landslides Against Protection Barriers: a New MPM-validated Empirical Formulation

Full understanding the interaction mechanisms between flow-like landslides and the impacted protection structures is an open issue. In fact, while researchers have used several approaches, from experimental to numerical, it is true that the adequate assessment of the hydromechanical behaviour of the landslide body requires both a multiphase and large deformation approach.This paper firstly proposes a conceptual framework for a specific type of protection structure, namely a rigid barrier fixed to the base ground. Two different approaches are proposed: i) an advanced hydro-mechanical numerical model based on Material Point Method is tested in simulating the whole complex landslide-structure-interaction mechanism(s), ii) a more simplified empirical model is casted to estimate the impact force and the time evolution of kinetic energy. The calibration and validation of the empirical formulation are pursued, respectively, based on the MPM numerical results, and referring to a large dataset of field evidence for the peak impact pressure. Finally, the performance of the newly proposed empirical method is compared to the methods available in the literature and its advantages are outlined.