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Usage Information

Regulation of selective class switching provides long-term therapeutic benefits for hay fever
Naoki Morita, Kohta Yamamoto, Ryutaro Tamano, Peng Gao, Takahiro Nagatake, Takenori Inomata, Tianxiang Huang, Yasuhiro Yamada, Takahiro Adachi, Manabu Sugai, Keiichi I. Nakayama, Hirotatsu Kojima, Reiko Shinkura
Naoki Morita, Kohta Yamamoto, Ryutaro Tamano, Peng Gao, Takahiro Nagatake, Takenori Inomata, Tianxiang Huang, Yasuhiro Yamada, Takahiro Adachi, Manabu Sugai, Keiichi I. Nakayama, Hirotatsu Kojima, Reiko Shinkura
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Research Article Immunology Inflammation

Regulation of selective class switching provides long-term therapeutic benefits for hay fever

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Abstract

IgA protects the body from invaders in the mucosal sites, but its role in allergic diseases, such as hay fever, is poorly understood. We demonstrate an increased susceptibility to cedar-pollen-induced hay fever associated with increasing pollen penetration into the body in IgA-deficient mice, indicating that IgA prevents pollen invasion in the mucosa. We identified bryostatin 1, an anticarcinogenic protein kinase Cδ (PKCδ) activator, as an IgA/IgE class-switching regulator in B cells. Bryostatin 1 enhanced IgA production through induction of germline transcript α (GLTα) via the PKCδ/MEK/ERK/RUNX1 pathway and suppressed IgE by reducing GLTε through the PKCδ/STAT5/ID2 pathway. Production of Th2 cytokines and eosinophil infiltration in the lungs was also reduced. Furthermore, hay fever alleviation by bryostatin 1 demonstrated diminished symptoms in mice in vivo 3 months subsequent to intranasal administration.

Authors

Naoki Morita, Kohta Yamamoto, Ryutaro Tamano, Peng Gao, Takahiro Nagatake, Takenori Inomata, Tianxiang Huang, Yasuhiro Yamada, Takahiro Adachi, Manabu Sugai, Keiichi I. Nakayama, Hirotatsu Kojima, Reiko Shinkura

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Usage data is cumulative from October 2025 through July 2026.

Usage JCI PMC
Text version 2,679 110
PDF 756 25
Figure 987 0
Table 313 0
Supplemental data 470 0
Citation downloads 337 0
Totals 5,542 135
Total Views 5,677

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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