메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Manxin Fang (Yichun University) Wei Hu (Yichun University) Ben Liu (Yichun University)
저널정보
대한수의학회 Journal of Veterinary Science Journal of Veterinary Science 제22권 제5호
발행연도
2021.9
수록면
136 - 150 (15page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
It has been speculated that bats serve as reservoirs of a huge variety of emerging coronaviruses (CoVs) that have been responsible for severe havoc in human health systems as well as negatively affecting human economic and social systems. A prime example is the currently active severe acute respiratory syndrome (SARS)-CoV2, which presumably originated from bats, demonstrating that the risk of a new outbreak of bat coronavirus is always latent. Therefore, an in-depth investigation to better comprehend bat CoVs has become an important issue within the international community, a group that aims to attenuate the consequences of future outbreaks. In this review, we present a concise introduction to CoVs found in bats and discuss their distribution in Southeast Asia. We also discuss the unique adaptation features in bats that confer the ability to be a potential coronavirus reservoir. In addition, we review the bat coronavirus-linked diseases that have emerged in the last two decades. Finally, we propose key factors helpful in the prediction of a novel coronavirus outbreak and present the most recent methods used to forecast an evolving outbreak.

목차

ABSTRACT
IMPLICATIONS
INTRODUCTION
SOUTHERN ASIA DISTRIBUTION AND GLOBAL DISSEMINATION OF BAT CORONAVIRUSES
BATS AS POTENTIAL CORONAVIRUS RESERVOIRS: IMMUNOLOGICAL CHARACTERISTICS
BATS AS POTENTIAL CORONAVIRUS RESERVOIRS: EXPERIMENTAL INFECTION STUDIES
NOVEL CORONAVIRUS-ASSOCIATED DISEASES AND THEIR POSSIBLE RELATIONSHIP WITH BAT CORONAVIRUSES
LEARNING TO PREDICT A NOVEL CORONAVIRUS OUTBREAK AND DISEASE SPREAD
CONCLUSIONS
REFERENCES

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2023-528-001326648