Galectin-1 inhibits oral-intestinal allergy syndrome
Bibliographic record
Abstract
// Rui-Di Xie 1, 2, * , Ling-Zhi Xu 1, * , Li-Tao Yang 3, 4, * , Shuai Wang 3 , Qi Liu 2 , Zhi-Gang Liu 1 , Ping-Chang Yang 1 1 The Research Center of Allergy & Immunology, Shenzhen University School of Medicine, Shenzhen, China 2 Periodontal Department, the Affiliated Hospital of Zunyi Medical College, Zunyi, China 3 The ENT Hospital of Shenzhen University and Shenzhen ENT Institute, Shenzhen, China 4 Brain Body Institute, McMaster University, Hamilton, ON, Canada * These authors contributed equally to this work Correspondence to: Ping-Chang Yang, email: pcy2356@szu.edu.cn Zhi-Gang Liu, email: lzg@szu.edu.cn Qi Liu, email: liuqi1964@hotmail.com Keywords: oral mucosa, oral allergy, peanut, micro RNA-98, galectin-1 Received: August 25, 2016 Accepted: December 27, 2016 Published: January 10, 2017 ABSTRACT Background and aims: The pathogenesis of oral-intestinal allergy syndrome (OIAS) has not been well understood. Published data indicate that galectin (Gal) 1 has immune regulatory functions. This study tests a hypothesis that Gal1 inhibits oral-intestinal allergy syndrome. Methods: Mice were sensitized to peanut extracts (PE) via the buccal mucosa with or without using Gal1 together. Results: Upon re-exposure to specific antigen, the OIAS mice showed the systemic allergic response, the oral allergic reactions, and intestinal allergic inflammation, including increases in serum histamine, drop of the core temperature, higher levels of PE-specific IgE and interleukin (IL)-4. Increases in mast cell and eosinophil in the oral mucosa and intestinal mucosa were also observed. The OIAS was inhibited by co-administration with Gal1 via a mechanism of suppressing micro RNA (miR)-98 and reversing the expression of IL-10 in CD14+ cells in the intestine. Conclusions: The OIAS can be induced by applying specific antigens to the oral mucosa, which can be inhibited by co-administration with Gal1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".