The mucosal immune response against the porcine epidemic diarrhea virus (PEDV) is very important in piglets. To develop a PEDV vaccine suitable for inducing high levels of intestinal IgA in piglets, recombinant yeast expressing the PEDV S1 gene was constructed and tested by oral immunization of mice and piglets. The S1-specific IgG and IgA were tested at 0, 14, and 28 days postimmunization (dpi) in mice. Compared to the control group, the mice treated with S1 expressing yeast, demonstrated significantly higher levels of IgG and IgA against PEDV from 14 dpi onward. The recombinant yeast inducing a fecal IgA response in piglets was also tested. PEDV-specific IgA could be detected at 7 dpi and increased to 28 dpi. We demonstrated that whole recombinant yeast can be used as a PEDV vaccine vector for inducing high levels of IgA against PEDV in piglets. This could be a good vaccine candidate for PEDV control in piglets.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1089/vim.2016.0067 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The 100 most-cited articles in WALANT hand surgery: A bibliometric and visualized analysis.
J Hand Surg Eur Vol
January 2025
St Andrew's Centre for Plastic Surgery and Burns, Broomfield Hospital, Chelmsford CM1 7ET, UK.
This bibliometric analysis aimed to define important topics and developments across wide awake local anaesthesia no tourniquet (WALANT) hand surgery, an innovative ambulatory technique that gained popularity during the COVID-19 pandemic. Articles were searched and screened using the Web of Science core collection database. VOSviewer 1.
View Article and Find Full Text PDFEnhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.
J Chem Inf Model
January 2025
Department of Chemical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan.
Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, leading to a scarcity of high-quality activation energy data. In this work, we explore and compare three innovative approaches (transfer learning, delta learning, and feature engineering) to enhance the accuracy of activation energy predictions using graph neural networks, specifically focusing on methods that incorporate low-cost, low-level computational data.
View Article and Find Full Text PDFSpatiotemporal association between monthly PM2.5 levels and cardiorespiratory mortality in Thailand (2015-2019).
Int J Environ Health Res
January 2025
College of Public Health Sciences, Chulalongkorn University, Bangkok, Thailand.
This study examines the spatiotemporal relationship between PM2.5 exposure and cardiorespiratory mortality across Thailand from 2015 to 2019, addressing a critical research gap in geographical coverage. Analysis of satellite-based PM2.
View Article and Find Full Text PDFEnhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.
Comput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.
View Article and Find Full Text PDFPitch-based correspondences related to abstract concepts.
Acta Psychol (Amst)
January 2025
Phonetics and speech synthesis research group, Department of Digital Humanities, Faculty of Arts, University of Helsinki, Unioninkatu 38, Helsinki, Finland. Electronic address:
Previous investigations have shown pitch-based correspondences with various perceptual and conceptual attributes. The present study reveals two novel pitch-based correspondences with highly abstract concepts. Three experiments with varying levels of implicitness of the association task showed that the concepts of future and in are associated with high-pitch sounds, while past and out are associated with low-pitch sounds.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!