Jin Liu's Impact on UCLA and Beyond: A Multifaceted Examination

This article explores the significant contributions and research impact of figures associated with UCLA, particularly focusing on Jin Liu and the extensive work of researchers like Dr. An and Tatiana Segura. It delves into their contributions across various fields, including gene therapy, biomaterials, and biomedical engineering, highlighting their influence on both the academic landscape of UCLA and the broader scientific community.

Sion An's Pioneering Work in Gene Therapy and HIV Research

Dr. Sion An, affiliated with UCLA, has made substantial contributions to the field of gene therapy, particularly in the context of HIV-1 infection. His research focuses on developing innovative strategies to combat HIV-1 through gene modification of hematopoietic stem/progenitor cells (HSPC). These cells are crucial because they can differentiate into all types of blood cells, including those targeted by HIV-1.

Clonal Repopulation Studies

One critical aspect of Dr. An's work involves understanding the clonal dynamics of gene-modified HSPCs in vivo. In a study published in Stem Cell Research & Therapy, Suryawanshi et al. (2021) investigated the longitudinal clonal tracking in humanized mice. The study revealed that gene-modified human HSPCs maintained sustained polyclonal repopulation, even with vector integration bias. This finding is significant because it suggests that gene therapy approaches using HSPCs can lead to a diverse and stable population of modified cells, enhancing the potential for long-term therapeutic benefits.

Another study by Suryawanshi et al. (2020) published in Science Advances, examined whether pre-existing HIV-1 infection affects the clonal repopulation of HSPCs gene-modified with anti-HIV-1 RNAi. The results indicated that the clonal repopulation of these modified HSPCs was not adversely affected by pre-existing HIV-1 infection. This is a crucial insight as it suggests that gene therapy can be effective even in individuals already infected with HIV-1.

HSPC-Based Gene Therapy

Dr. An's research also explores the use of HSPC-based gene therapy to model anti-HIV-1 strategies in humanized mice. Khamaikawin et al. (2017) detailed this approach in Molecular Therapy Methods & Clinical Development. The study demonstrated the feasibility and efficacy of using humanized mice to model and study the effects of gene therapy on HIV-1 infection. This method allows for a more accurate preclinical evaluation of new therapeutic strategies.

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Engineering Cellular Resistance to HIV-1

Burke et al. (2015) in Molecular Therapy Nucleic Acids described engineering cellular resistance to HIV-1 infection in vivo using a dual therapeutic lentiviral vector. This innovative approach combines two therapeutic strategies-a short hairpin RNA (shRNA) targeting CCR5 and the C46 fusion inhibitor-to provide a more robust defense against HIV-1. The study highlights the potential of lentiviral vectors in delivering therapeutic genes to combat HIV-1 infection.

RNAi-Mediated CCR5 Knockdown

Shimizu et al. (2015) focused on RNAi-mediated CCR5 knockdown to provide HIV-1 resistance to memory T cells in humanized BLT mice. Published in Molecular Therapy Nucleic Acids, this study demonstrated that reducing CCR5 expression, a key co-receptor for HIV-1 entry, can effectively protect memory T cells from HIV-1 infection. This approach is particularly significant because memory T cells play a critical role in the immune response.

Impact on Human Immunology and Immunotherapy

Smith et al. (2016) in Stem Cells and Development, discussed propagating humanized BLT mice for the study of human immunology and immunotherapy. This work underscores the importance of humanized mouse models in advancing our understanding of the human immune system and developing new immunotherapeutic strategies.

HIV-1 Diversification and Evolution

Sato et al. (2014) investigated the role of APOBEC3D and APOBEC3F in promoting HIV-1 diversification and evolution in a humanized mouse model. Published in PLoS Pathogens, this study revealed that these enzymes potently enhance HIV-1 diversification, which has implications for understanding viral evolution and developing effective antiviral therapies.

Preclinical Safety and Efficacy

Wolstein et al. (2014) assessed the preclinical safety and efficacy of an anti-HIV-1 lentiviral vector containing a short hairpin RNA to CCR5 and the C46 fusion inhibitor. Published in Molecular Therapy Methods & Clinical Development, this study provided critical data supporting the potential clinical use of this lentiviral vector for HIV-1 therapy.

High-Throughput Screening of siRNAs

Pang et al. (2014) described a high-throughput screening method for identifying effective siRNAs using luciferase-linked chimeric mRNA. Published in PLoS One, this method facilitates the rapid identification of potent siRNAs for gene silencing, which is valuable for developing gene therapies.

Dynamics of HSPC Repopulation

Kim et al. (2014) examined the dynamics of HSPC repopulation in nonhuman primates using a decade-long clonal-tracking study. Published in Cell Stem Cell, this research provided insights into the long-term behavior of HSPCs, which is crucial for understanding the durability of gene therapy outcomes.

Vectored Immunoprophylaxis

Balazs et al. (2014) explored vectored immunoprophylaxis to protect humanized mice from mucosal HIV transmission. Published in Nature Medicine, this study demonstrated the potential of using viral vectors to deliver antibodies that prevent HIV transmission, offering a novel approach to HIV prevention.

HIV-1 Vpr and Viral Replication

Sato et al. (2013) investigated how HIV-1 Vpr accelerates viral replication during acute infection by exploiting proliferating CD4+ T cells in vivo. Published in PLoS Pathogens, this study shed light on the mechanisms by which HIV-1 enhances its replication, which is important for developing targeted antiviral strategies.

Engineering HIV-1-Resistant T-Cells

Ringpis et al. (2012) focused on engineering HIV-1-resistant T-cells from short-hairpin RNA-expressing hematopoietic stem/progenitor cells in humanized BLT mice. Published in PLoS One, this study demonstrated the feasibility of creating T-cells resistant to HIV-1 infection through genetic modification of HSPCs.

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Neutralizing IgA and Mucosal Transmission

Hur et al. (2012) examined the inhibitory effect of HIV-specific neutralizing IgA on mucosal transmission of HIV in humanized mice. Published in Blood, this study highlighted the potential of using IgA antibodies to prevent HIV transmission at mucosal sites.

HIV-1 Reporter Virus

Suree et al. (2012) introduced a novel HIV-1 reporter virus with a membrane-bound Gaussia princeps luciferase. Published in the Journal of Virological Methods, this reporter virus allows for the sensitive and quantitative monitoring of HIV-1 infection and replication.

Vpu and HIV-1 Propagation

Sato et al. (2012) investigated how Vpu augments the initial burst phase of HIV-1 propagation and downregulates BST2 and CD4 in humanized mice. Published in the Journal of Virology, this study elucidated the role of Vpu in enhancing HIV-1 replication, which is important for developing targeted antiviral therapies.

HIV Latency

Marsden et al. (2012) studied HIV latency in the humanized BLT mouse. Published in the Journal of Virology, this research provided insights into the mechanisms of HIV latency, which is a major obstacle to curing HIV infection.

High-Throughput Quantification of HSPC Clones

Kim et al. (2010) developed a high-throughput, sensitive method for quantifying repopulating hematopoietic stem cell clones. Published in the Journal of Virology, this method is valuable for tracking the behavior of HSPCs in vivo.

Inhibition of HIV-1 Infection

Liang et al. (2010) explored the inhibition of HIV-1 infection by a unique short hairpin RNA to chemokine receptor 5 delivered into macrophages through hematopoietic progenitor cell transduction. Published in the Journal of Gene Medicine, this study demonstrated the potential of using shRNAs to inhibit HIV-1 infection in macrophages.

CCR5 Down-Regulation

Shimizu et al. (2010) described a highly efficient short hairpin RNA that potently down-regulates CCR5 expression in systemic lymphoid organs in the hu-BLT mouse model. Published in Blood, this study highlighted the effectiveness of shRNAs in reducing CCR5 expression, a key target for HIV-1 therapy.

Non-Cytotoxic shRNA

Shimizu et al. (2009) characterized a potent non-cytotoxic shRNA directed to the HIV-1 co-receptor CCR5. Published in Genetic Vaccines and Therapy, this study demonstrated the potential of using non-cytotoxic shRNAs to inhibit HIV-1 infection.

Stable Reduction of CCR5 by RNAi

An et al. (2007) reported on the stable reduction of CCR5 by RNAi through hematopoietic stem cell transplant in non-human primates. Published in the Proceedings of the National Academy of Sciences, this research provided evidence that RNAi can be used to stably reduce CCR5 expression in vivo.

Human Immune System Mouse Model

An et al. (2007) introduced the human immune system (HIS) RAG-/-{gamma}c-/- mouse, a novel chimeric mouse model for HIV-1 infection. Published in Clinical Vaccine Immunology, this model is valuable for studying HIV-1 infection and evaluating new therapies.

Optimization and Functional Effects of shRNA

An et al. (2006) discussed the optimization and functional effects of stable short hairpin RNA expression in primary human lymphocytes via lentiviral vectors. Published in Molecular Therapy, this study provided insights into optimizing shRNA expression for gene therapy.

Efficient Lentiviral Vectors for shRNA Delivery

An et al. (2003) described efficient lentiviral vectors for short hairpin RNA delivery into human cells. Published in Human Gene Therapy, this work highlighted the potential of lentiviral vectors for delivering shRNAs for gene silencing.

Lentivirus-Delivered Stable Gene Silencing

Stewart et al. (2003) reported on lentivirus-delivered stable gene silencing by RNAi in primary cells. Published in RNA, this study demonstrated the potential of using lentiviruses to achieve stable gene silencing.

Inhibiting HIV-1 Infection by siRNA

Qin et al. (2003) explored inhibiting HIV-1 infection in human T-cells by lentiviral-mediated delivery of siRNA against CCR5. Published in the Proceedings of the National Academy of Sciences, this research provided evidence that siRNAs can be used to inhibit HIV-1 infection.

Lentivirus Vector-Mediated Gene Transfer

An et al. (2001) reported on lentivirus vector-mediated hematopoietic stem cell gene transfer of the common gamma-chain cytokine receptor in rhesus macaques. Published in the Journal of Virology, this study demonstrated the potential of lentiviral vectors for gene therapy.

Envelope Gene of HERV-W

An et al. (2001) showed that the envelope gene of the human endogenous retrovirus HERV-W encodes a functional retrovirus envelope. Published in the Journal of Virology, this finding has implications for understanding the role of endogenous retroviruses.

HIV Env-Independent Infection

Pang et al. (2000) described human immunodeficiency virus env-independent infection of human CD4 (-) cells. Published in the Journal of Virology, this study provided insights into alternative mechanisms of HIV infection.

Marking and Gene Expression by a Lentivirus Vector

An et al. (2000) reported on marking and gene expression by a lentivirus vector in transplanted human and non-human primate CD34+ cells. Published in the Journal of Virology, this study demonstrated the potential of lentiviral vectors for gene therapy.

Inducible HIV-1 Vector

An et al. (1999) introduced an inducible HIV-1 vector which effectively suppresses HIV-1 replication. Published in the Journal of Virology, this vector is valuable for studying HIV-1 replication and developing new therapies.

Transduction of Human Lymphoid Progenitor Cells

An et al. (1997) reported on high-efficiency transduction of human lymphoid progenitor cells and expression in differentiated T cells. Published in the Journal of Virology, this study demonstrated the potential of using lentiviral vectors for gene therapy.

Tatiana Segura's Contributions to Biomaterials and Tissue Engineering

Tatiana Segura is a distinguished Professor of Biomedical Engineering, Neurology, and Dermatology at Duke University. Her research is primarily focused on biomaterials and engineering biomaterial-soft tissue interactions to facilitate repair and regeneration.

Academic and Career Overview

Professor Segura received her B.S. degree in Bioengineering from UC Berkeley and her Ph.D. in Chemical Engineering from Northwestern University. She began her career in Biomaterials research during her doctoral work with Prof. Lonnie Shea, designing hydrogels for local non-viral gene delivery. She continued her Biomaterials training during her postdoctoral work with Jeffrey Hubbell, focusing on hydrogels and self-assembled polysulfides for gene delivery.

She started her independent career at UCLA in the Department of Chemical and Biomolecular Engineering, eventually becoming a Professor. At UCLA, she was actively involved in service, including serving as department Vice Chair and running the Graduate Program. At Duke, she has continued her service at the department, school, and university level, chairing multiple committees, mentoring assistant professors, and co-directing the Center for Biotechnology and Tissue Engineering.

Research Focus and Innovations

Professor Segura’s research is centered on biomaterials and engineering biomaterial-soft tissue interactions to promote repair and regeneration. Together with her lab members, she designs new biomaterial interventions that can:

Promote brain plasticity after stroke.
Promote scarless healing in skin wounds.
Induce tolerance of transplanted skin.
Promote constructive immune responses after biomaterial implantation.

Key Publications and Research Findings

Professor Segura has published extensively, with over 100 peer-reviewed papers and reviews. Her work has significantly contributed to the understanding and advancement of biomaterials in regenerative medicine.

Suarez-Arnedo et al. conducted a comparative proteomic analysis of skin wound healing responses to biomaterial treatments, identifying key pathways governing differential regenerative outcomes.
Phan et al. explored the co-delivery of synaptogenic and angiogenic nanoparticles in MAP scaffolds to enhance post-stroke synapse formation.
Palomino et al. focused on resolving the glycosaminoglycan signature of ischemic stroke brain using PRM-based IR-MALDESI mass spectrometry imaging.
Rodriguez-Rivera et al. investigated how microgel aspect ratio influences injectable granular hydrogel scaffold pore structure and cellular invasion for tissue repair.
Ouyang et al. studied polysialic acid-functionalized MAP scaffolds to promote regulatory immune responses after ischemic stroke.
Riley et al. developed metrics for studying the porous void space of packed particles.
Erning et al. explored the delivery of angiogenic therapy from flowable hyaluronic acid porous scaffolds for functional improvement after stroke.
Bai et al. worked on unraveling the molecular dynamics of wound healing by integrating spatially resolved lipidomics and temporally resolved proteomics.
Miller et al. designed wound healing splinting devices for faster access and use.
Shetty et al. developed anti-cytokine active immunotherapy based on supramolecular peptides for alleviating IL-1β-mediated inflammation.
Anderson et al. engineered the microstructure and spatial bioactivity of MAP scaffolds to instruct vasculogenesis in vitro and modify vessel formation in vivo.
Wilson et al. used SDF-1 bound heparin nanoparticles to recruit progenitor cells for their differentiation and promotion of angiogenesis after stroke.
Kurt et al. worked on gene delivery from granular scaffolds for tunable biologics manufacturing.
Wang et al. optimized neurotransmitter pathway detection by IR-MALDESI-MSI in mouse brain.
Curvino et al. engaged natural antibody responses for the treatment of inflammatory bowel disease via phosphorylcholine-presenting nanofibres.
Liu et al. explored the role of spatial confinement in immune cell recruitment and regeneration of skin wounds.
Riley et al. focused on the identification and analysis of 3D pores in packed particulate materials.
Phan et al. reviewed biology-driven material design for ischaemic stroke repair.
Riley et al. studied the void volume fraction of granular scaffolds.

Awards and Recognition

Professor Segura has received numerous awards and distinctions, including:

Senior Member of the National Academy of Inventors.
Acta Biomaterialia Silver Medal.
CAREER Award from the National Science Foundation.
Outstanding Young Investigator Award from the American Society of Gene and Cell Therapy.
National Scientist Development Grant from the American Heart Association.
Fellow of the American Institute for Medical and Biological Engineers (AIMBE).

Li Shen's Work in Biomedical Informatics and AI

Dr. Li Shen is a Professor and Interim Director of the Division of Informatics in the Department of Biostatistics, Epidemiology, and Informatics (DBEI) at the Perelman School of Medicine at the University of Pennsylvania. His research focuses on trustworthy AI, machine learning, biomedical and health informatics, NLP/LLMs, medical image computing, network science, and multi-omics and systems biology, with applications across complex disorders.

Research and Contributions

Dr. Shen's work spans several critical areas in biomedical informatics and artificial intelligence. His research aims to develop and apply advanced computational methods to understand, diagnose, and treat complex diseases. His expertise includes:

Trustworthy AI: Developing AI systems that are reliable, ethical, and transparent for use in healthcare.
Machine Learning: Applying machine learning techniques to analyze large datasets and extract meaningful insights for disease prediction and diagnosis.
Biomedical and Health Informatics: Integrating and analyzing diverse biomedical data to improve healthcare outcomes.
NLP/LLMs: Utilizing natural language processing and large language models to extract information from clinical text and improve patient care.
Medical Image Computing: Developing algorithms for analyzing medical images to aid in diagnosis and treatment planning.
Network Science: Applying network analysis techniques to understand complex biological systems and disease mechanisms.
Multi-Omics and Systems Biology: Integrating multi-omics data (genomics, proteomics, metabolomics) to gain a comprehensive understanding of disease biology.

Team and Collaborations

Dr. Shen leads a diverse team of researchers, including postdoctoral fellows, PhD students, master's students, and undergraduate students. His collaborations extend across various departments and institutions, fostering interdisciplinary research and innovation. Key members of his team include:

Postdoctoral Fellows:
- Dr. Bojian Hou: Expertise in computer science and technology.
- Dr. Davoud Ataee Tarzanagh: Background in mathematics and signal processing.
- Dr. Tianhua Zhai: Specialization in computational drug discovery and machine learning.
PhD Students:
- Jenna Ballard: Focus on genomics and computational biology.
- Jiong Chen: Expertise in bioengineering.
- Sophie Kearney: Specialization in genomics and computational biology.
- Boning Tong: Background in bioengineering.
- Frederick Xu: Expertise in biomedical engineering and computer science.
- Kayla Xu: Focus on quantitative biology.
- Thomas Yu: Specialization in biostatistics.
Master's Students:
- Jingyi Gong: Focus on data science.
- Ravi: Expertise in machine learning and neuroimaging.
- Rahul: Specialization in multimodal AI systems in healthcare.
- Lining Wang: Background in statistics and economics.
- Zhao Zhang: Expertise in electrical engineering.
- Lening Zhao: Specialization in bioengineering.
Undergraduate Students:
- Grace: Studying computer science.
- William: Majoring in computer science.
- Joseph Lee: Studying networked and social systems and data science.
- Benjamin: Majoring in computer science.
- Wesley: Majoring in computer science.
- Helen Luo: Studying computer science.
- Alvin: Majoring in neuroscience and computational science and engineering.
- Angel Shi: Studying neuroscience and design.
- Shyam: Studying bioengineering.
- Chantal van Dongeren: Studying bioengineering.
- Gabe: Studying computer science and economics.
- Megan: Studying biology and computer science.
- Charles: Studying bioengineering and computer science.

Visiting Scholars

Dr. Shen’s lab also hosts visiting scholars who contribute to the research environment with their unique expertise:

Dr. Sang Hyun Park: Visiting professor from DGIST, specializing in robotics and mechatronics engineering.
Siwoo Nam: Visiting student from DGIST, focusing on cell nuclei segmentation techniques.
Sion An: Visiting student from DGIST, specializing in computer science.
Ruochen Jin: Visiting student from ECNU, focusing on software engineering.

Key Projects and Contributions

Dr. Shen's research projects aim to address critical challenges in healthcare through advanced computational techniques. His contributions include:

Developing AI models for early diagnosis and prediction of complex diseases.
Creating tools for analyzing medical images to improve diagnostic accuracy.
Integrating multi-omics data to understand disease mechanisms and identify potential therapeutic targets.
Applying natural language processing to extract valuable information from clinical records.
Building trustworthy AI systems that ensure fairness, transparency, and reliability in healthcare applications.

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