Evidence map›Paper›PMID 21956501›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2012

Analyzing cellular immunity to AAV in a canine model using ELISPOT assay.

Zejing Wang, Rainer Storb, Stephen J Tapscott, Stanley Riddell

Open access · greenAbstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 84% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Zejing WangProgram in Transplantation Biology, Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. zwang@fhcrc.org
Rainer Storb
Stephen J Tapscott
Stanley Riddell
Fred Hutch Cancer Center · USCape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa · ZA

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian Esvelt · 1985 to 2026
$296.4M
PRECLINICAL GENE THERAPY STUDIES IN CANINE MUSCULAR DYSTROPHYR01AR056949 · NIAMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI WANG, ZEJING · 2009 to 2013
$3.5M
NCI NIH HHS CA15704NCI NIH HHS P30 CA015704NIAMS NIH HHS R01 AR056949NIAMS NIH HHS R01 AR056949-01A1
6 · The paper itself

Abstract

Adeno-associated viral (AAV) vector-mediated gene transfer represents a promising gene replacement strategy for treating various genetic diseases. One obstacle in using viral-derived vectors for in vivo gene delivery is the development of host immune responses to the vector. Recent studies have demonstrated cellular immune responses specific to capsid proteins of various AAV serotypes in animal models and in human trials for different diseases. We developed a canine-specific ELISPOT assay to detect such immunity in dogs received AAV treatment. Here, we describe in detail the use of a constructed panel of overlapping peptides spanning the entire VP1 sequence of AAV capsid protein to detect specific T-cell responses in peripheral blood in dogs following intramuscular injection of AAV. This high-throughput method allows the identification of T-cell epitopes without the need for large cell numbers and the need for major histocompatibility complex molecule-matched cell lines.

Indexed as

Disease Models, AnimalEnzyme-Linked Immunospot AssayAnimalsDependovirusDogsHumansImmunity, CellularParvoviridae InfectionsT-Lymphocytes

Identifiers

PMID21956501
PMCPMC4516170
OpenAlexW2412573032

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.