Simin Li

ORCID: 0000-0002-6540-6138
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About
Contact & Profiles
Research Areas
  • Ionic liquids properties and applications
  • T-cell and B-cell Immunology
  • Immunotherapy and Immune Responses
  • Immune Cell Function and Interaction
  • Neuropeptides and Animal Physiology
  • Mast cells and histamine
  • Phase Equilibria and Thermodynamics
  • Machine Learning in Materials Science
  • RNA Interference and Gene Delivery
  • Invertebrate Immune Response Mechanisms
  • Enzyme Catalysis and Immobilization
  • IL-33, ST2, and ILC Pathways
  • Respiratory viral infections research
  • Catalysis and Oxidation Reactions
  • Olfactory and Sensory Function Studies
  • Phagocytosis and Immune Regulation
  • Hippo pathway signaling and YAP/TAZ
  • Computational Drug Discovery Methods
  • Lipid Membrane Structure and Behavior
  • Virus-based gene therapy research
  • Insect Utilization and Effects
  • Innovative Microfluidic and Catalytic Techniques Innovation
  • Receptor Mechanisms and Signaling
  • Crustacean biology and ecology
  • Chemical Thermodynamics and Molecular Structure

University of Chinese Academy of Sciences
2024

Institute of Process Engineering
2024

First Hospital of Jilin University
2023

Jilin University
2023

Osaka University
2017

Beijing Normal University
2016-2017

Jiangxi Academy of Environmental Sciences
2015

Okayama University
2010-2011

Abstract Although the differentiation of CD4 + T cells is widely studied, mechanisms antigen-presenting cell-dependent T-cell modulation are unclear. Here, we investigate role dendritic cell (DC)-dependent in autoimmune and antifungal inflammation find that mammalian sterile 20-like kinase 1 (MST1) signalling from DCs negatively regulates IL-17 producing-CD4 helper (Th17) differentiation. MST1 deficiency increases production by cells, whereas ectopic expression inhibits it. Notably,...

10.1038/ncomms14275 article EN cc-by Nature Communications 2017-02-01

Graphical Abstract The PEG-PLGA nanoparticles effectively delivered R848 and CD47 siRNA into tumor cells, resulting in simultaneous activation of DCs downregulation expression on thereby enhancing antitumor immune responses by T cells.

10.3389/fphar.2023.1142374 article EN cc-by Frontiers in Pharmacology 2023-03-31

A novel histamine receptor subtype, H(3) receptor, mediates inhibition of peripheral autonomic neurotransmission. The present study was designed to examine vascular effects by using a selective agonist, R-(-)-alpha methylhistamine (alpha-methylhistamine), in rat mesenteric resistance arteries. isolated beds were perfused with Krebs solution and perfusion pressure measured. Active tone produced containing 7 microM methoxamine. In preparations intact endothelium, alpha-methylhistamine (1-100...

10.1248/bpb.33.58 article EN Biological and Pharmaceutical Bulletin 2010-01-01

We have already reported that the inactivated Sendai virus (hemagglutinating of Japan; HVJ ) envelope ( ‐E) has multiple anticancer effects, including induction cancer‐selective cell death and activation immunity. The ‐E stimulates dendritic cells to produce cytokines chemokines such as β‐interferon, interleukin‐6, chemokine (C‐C motif) ligand 5, (C‐X‐C 10, which activate both CD 8 + T natural killer NK recruit them tumor microenvironment. However, effect ‐ E on modulating sensitivity cancer...

10.1111/cas.13408 article EN cc-by-nc-nd Cancer Science 2017-09-25

Ionic liquids (ILs) have shown promising potential in membrane protein extraction; however, the underlying mechanism remains unclear. Herein, we employed GPU-accelerated molecular dynamics (MD) simulations to investigate dynamic insertion process of ILs into cell membranes containing proteins. Our findings reveal that spontaneously insert membrane, and presence proteins significantly decelerates rate IL membrane. Specifically, relationship between inserting free energy exhibits non-monotonic...

10.1021/acs.jpcb.3c08451 article EN The Journal of Physical Chemistry B 2024-05-01

Heat capacity at constant pressure (Cp) of a molecular liquid medium is not only basic physical property applicable in the calculation microscopic characteristics but also crucial chemical engineering processes. In this work, we utilized machine learning (ML) methodologies based on an established database to develop predictive models for Cp fluids. The training data these were sourced from literature and densityFfunctional theory (DFT) calculations, with simplified input line entry system...

10.1021/acs.iecr.4c02495 article EN Industrial & Engineering Chemistry Research 2024-08-20
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