2013
DOI: 10.1177/0300985813502815
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Immune System Cells in Healthy Ferrets

Abstract: The ferret has emerged as an excellent animal model to characterize several physiologic and pathologic conditions. The distribution and characterization of different types of immune system cells were studied in healthy ferret tissues. Eight primary antibodies were tested for immunohistochemistry in formalin-fixed tissues: anti-CD3, anti-CD79α, anti-CD20, anti-HLA-DR, anti-lysozyme, anti-CD163, anti-SWC3, and anti-Mac387. The anti-CD3 antibody labeled T cells mainly in interfollicular and paracortical areas of … Show more

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Cited by 15 publications
(13 citation statements)
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“…Phenotyping of the different inflammatory cell lineages following IHC were performed on the lungs of the infected and control animals to determine which inflammatory cell types were associated with the different lung lesional patterns. Neutrophils and macrophages were detected by IHC using anti-lysozyme polyclonal antibodies (Dako, Polyclonal Rabbit Anti-Human Lysozyme EC 3.2.1.17, ref A0099), T and B cells were detected using anti-CD3 (Dako, Polyclonal Rabbit Anti-Human CD3, n°I S503) and anti-CD20 (Thermo Scientific, CD20 Rabbit Polyclonal Antibody, ref RB-9013-P) polyclonal antibodies as previously described [29,30].…”
Section: Immunophenotyping and Quantification Of Lung Inflammatory Cellsmentioning
confidence: 99%
“…Phenotyping of the different inflammatory cell lineages following IHC were performed on the lungs of the infected and control animals to determine which inflammatory cell types were associated with the different lung lesional patterns. Neutrophils and macrophages were detected by IHC using anti-lysozyme polyclonal antibodies (Dako, Polyclonal Rabbit Anti-Human Lysozyme EC 3.2.1.17, ref A0099), T and B cells were detected using anti-CD3 (Dako, Polyclonal Rabbit Anti-Human CD3, n°I S503) and anti-CD20 (Thermo Scientific, CD20 Rabbit Polyclonal Antibody, ref RB-9013-P) polyclonal antibodies as previously described [29,30].…”
Section: Immunophenotyping and Quantification Of Lung Inflammatory Cellsmentioning
confidence: 99%
“…Gene expression studies, using information gathered from the draft genome and cross-reactive probes for microarrays, have confirmed the biphasic kinetics of innate and adaptive immune responses following viral infection (42)(43)(44)(45). While limited, serological reagents (46,47) have been used in a number of applications, including immunohistochemical analyses to study pathological features of disease as it relates to the virus/host interface (48). Additionally, other studies have quantified antibody-secreting cells within the draining lymph node in live attenuated influenza virus vaccine (LAIV) recipients, finding that the abundance of these cells inversely correlated with virus replication during a heterologous virus challenge (49).…”
mentioning
confidence: 94%
“…Markers targeting B‐cell antigens such as CD79a, CD20 and surface immunoglobulin also allow ferret B cells to be examined by immunohistochemistry and flow cytometry in ferret tissues . B‐cell frequencies are also transiently decreased 2 d.p.i after infection, with a corresponding increase in secondary lymphoid organs 2‐5 d.p.i .…”
Section: Ferrets As An Immunological Model For Studying Influenzamentioning
confidence: 99%
“…Such non‐neutralising mechanisms have been shown to be important for broadly protective responses against antigenically distinct strains of influenza and development of universal influenza vaccines. Many of the current ADCC and related assays rely on the detection of Ab‐mediated activation of NK cells to express cytokines such as IFN‐γ or degranulation markers such as CD107a, but there are currently no reagents to differentiate NK cells from other cytotoxic lymphocyte populations such as CD8+ T cells . While a ferret‐specific T‐cell IFN‐γ expression assays to measure CD8 T‐lymphocyte activation have been developed and validated, the future elucidation of corresponding antibody/Fc receptor ferret orthologues will enable ferrets to be used to evaluate ADCC responses.…”
Section: Key Knowledge Gaps To Address In Order To Improve the Immunomentioning
confidence: 99%