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'Cutting the cable' between CD8+ T and T regulatory cells enhances checkpoint immunotherapy

Checkpoint immunotherapy utilizing PD-1 blockade has become the standard of care for metastatic melanoma. While this treatment is effective in 40% of patients, the other 60% develop resistance, leading to tumor regrowth. A multidisciplinary research team led by the University of California, Irvine has identified a new strategy that could enhance the therapeutic effectiveness of this therapy by targeting the communication between immune cells within the tumor. ....

Irvine School , United States , Francesco Marangoni , Shannon Geels , Multiscale Cell Fate Research , Uc Irvine School Of Medicine , University Of California , Saint John Cancer Institute In Santa Monica , Department Of Physiology Biophysics , University Of Alabama At Birmingham , Institute For Immunology , Harvard Medical School , Cancer Cell , Complex Biological Systems , Simons Center , Saint John , Cancer Institute , Santa Monica , Massachusetts General Hospital , Harvard Medical , Treg Crosstalk Improves ,

Single-cell and spatial transcriptomics identify a macrophage population associated with skeletal muscle fibrosis

Single-cell and spatial transcriptomics identify a macrophage population associated with skeletal muscle fibrosis
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UCI researchers join forces to tackle challenges in human health and the environment

UCI researchers join forces to tackle challenges in human health and the environment
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UCI researchers eavesdrop on cellular conversations

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IMAGE: Overview of how CellChat can convert molecular language of cells into the translation that is interpretable by researchers.
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Credit: Suoqin Jin, Qing Nie & Maksim Plikus / UCI
Irvine, Calif. An interdisciplinary team of biologists and mathematicians at the University of California, Irvine has developed a new tool to help decipher the language cells use to communicate with one another.
In a paper published today in
Nature Communications, the researchers introduce CellChat, a computational platform that enables the decoding of signaling molecules that transmit information and commands between the cells that come together to form biological tissues and even entire organs. ....

United States , Orange County , Maksim Plikus , Suoqin Jin , Howard Gillman , Christianf Guerrero , Raul Ramos , Lihua Zhang , Yale University , University Of California , Nature Communications , National Taiwan University , Multiscale Cell Fate Research , Uci Center , Association Of American Universities , Qing Nie , Simons Center , American Universities , Chancellor Howard Gillman , Cell Biology , Developmental Reproductive Biology , Molecular Biology , Algorithms Models , ஒன்றுபட்டது மாநிலங்களில் , ஆரஞ்சு கவுண்டி , ஹோவர்ட் கில்மேன் ,

New deep-learning framework predicts gene regulation at single-cell level

New deep-learning framework predicts gene regulation at single-cell level
Scientists at the University of California, Irvine have developed a new deep-learning framework that predicts gene regulation at the single-cell level.
Deep learning, a family of machine-learning methods based on artificial neural networks, has revolutionized applications such as image interpretation, natural language processing and autonomous driving. In a study published recently in
Science Advances, UCI researchers describe how the technique can also be successfully used to observe gene regulation at the cellular level. Until now, that process had been limited to tissue-level analysis.
According to co-senior author Xiaohui Xie, UCI professor of computer science, the framework enables the study of transcription factor binding at the cellular level, which was previously impossible due to the intrinsic noise and sparsity of single-cell data. A transcription factor is a protein that controls ....

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