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Guangping Gao

Researcher at University of Massachusetts Medical School

Publications -  463
Citations -  31011

Guangping Gao is an academic researcher from University of Massachusetts Medical School. The author has contributed to research in topics: Adeno-associated virus & Genetic enhancement. The author has an hindex of 81, co-authored 423 publications receiving 26503 citations. Previous affiliations of Guangping Gao include Sichuan University & Children's Hospital of Philadelphia.

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Novel adeno-associated viruses from rhesus monkeys as vectors for human gene therapy

TL;DR: Vectors based on AAV7 and AAV8 should be considered for human gene therapy because of low reactivity to antibodies directed to human AAVs and because gene transfer efficiency in muscle was similar to that obtained with the best known serotype, whereas, in liver, gene transfer was substantially higher than previously described.
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Fatal systemic inflammatory response syndrome in a ornithine transcarbamylase deficient patient following adenoviral gene transfer

TL;DR: The death of an 18-year-old male with partial ornithine transcarbamylase (OTC) deficiency who participated in a pilot (safety) study of gene therapy points to the limitations of animal studies in predicting human responses, the steep toxicity curve for replication defective adenovirus vectors, substantial subject-to-subject variation in host responses to systemically administered vectors, and the need for further study of the immune response to these vectors.
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Adeno-associated virus vector as a platform for gene therapy delivery

TL;DR: The fundamentals of AAV and vectorology are discussed, focusing on current therapeutic strategies, clinical progress and ongoing challenges.
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Clades of Adeno-Associated Viruses Are Widely Disseminated in Human Tissues

TL;DR: The potential for using Adeno-associated virus (AAV) as a vector for human gene therapy has stimulated interest in the Dependovirus genus as mentioned in this paper, although analyses of viruses and viral sequences from clinical samples are extremely limited.