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

논문 기본 정보

자료유형
학술저널
저자정보
저널정보
대한정신약물학회 Clinical Psychopharmacology and Neuroscience Clinical Psychopharmacology and Neuroscience 제17권 제1호
발행연도
2019.1
수록면
34 - 42 (9page)

이용수

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

초록· 키워드

오류제보하기
Objective: Previous studies have suggested alterations in the kynurenine pathway as a major link between cytokine and neurotransmitter abnormalities in psychiatric disorders. Most of these studies used a cross-sectional case-control study design. However, knowledge is still lacking regarding the stability over time of kynurenine pathway metabolites and the functionally related cytokines. Therefore, we studied the stability of cytokines and tryptophan (TRP) parameters over a period of 12 weeks. Methods: A total of 117 participants-39 with major depression, 27 with somatoform disorder, and 51 healthy controlswere enrolled. Four evaluations, including blood withdrawal and psychometric testing, were performed over a period of 12 weeks. We used ELISA to measure interleukin (IL)-6, IL-1 receptor antagonist (RA) and tumor necrosis factor  (TNF ). High-performance liquid chromatography was used to analyze neurotransmitter variables, i.e. TRP, 5-hydroxyindoleacetic acid (5-HIAA), kynurenine (KYN), 3-OH-kynurenine (3-HK), and kynurenic acid (KYNA). Results: We found no significant fluctuations of TRP, its metabolites (5-HIAA, KYN, KYNA, and 3-HK), or the cytokines (IL-1RA, IL-6, and TNF ) in any of the groups over the 12 weeks. Conclusion: To our knowledge, this is the first longitudinal study performed in psychiatric patients to verify the stability and consequently the reliability of the biological parameters we investigated. Our data indicate that TRP metabolites and cytokines are reliable biological parameters in psychiatric research because they do not fluctuate significantly over time.

목차

등록된 정보가 없습니다.

참고문헌 (37)

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