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
한국미생물생명공학회 Journal of Microbiology and Biotechnology Journal of Microbiology and Biotechnology 제25권 제7호
발행연도
2015.1
수록면
1,163 - 1,169 (7page)

이용수

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

초록· 키워드

오류제보하기
Poly-gamma-glutamic acid (γ-PGA) is a natural polymer that is synthesized by Bacillus species and has been reported to have antitumor activity. The aim of this study was to investigate the effect of γ-PGA on the treatment of vaginal intraepithelial neoplasia (VAIN). A retrospective observational study on γ-PGA therapy for biopsy-proven VAIN was conducted. The efficacy was assessed by evaluating the results of Pap cytology and the viral load of high-risk HPV at three time points: at enrollment, and at the first and second post-treatment visits. Of 17 patients treated with γ-PGA, only 12 patients who had a high-risk HPV infection were included in the analysis. Histology was VAIN1 in seven patients, VAIN2 in two patients, and VAIN3 in three patients. γ-PGA was administered for newly diagnosed VAIN in five (41.7%) patients and persistent VAIN in seven (58.3%) patients for the mean time of 4.5 months. At the first and second post-treatment visits, cytological regression was observed in five (41.7%) and six (50%) patients, respectively. Regarding the HPV load, the overall response rate was 66.7%, and the mean level was 670.6 ± 292.5 RLU at the first follow-up, which was lower than the initial viral load of 1,494.8 ± 434.5 RLU (p = 0.084). At the second follow-up, the overall response rate was 58.3%, and the mean viral load level was 924.2 ± 493.7 RLU. γ-PGA may be helpful for the cytological regression and reduction of viral load in patients with high-risk HPV-positive VAIN, suggesting that γ-PGA is a promising treatment option for primary or persistent VAIN.

목차

등록된 정보가 없습니다.

참고문헌 (22)

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