인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Background Malignant luminal alimentary tract tumor chemotherapy remains a great challenge at present due to risks and toxicities associated with current chemodrugs, as well as the potential for treatment resistance. Layered double hydroxide (LDH)/ethylenediamine tetraacetic acid (EDTA), such a tumor disaggregation-based treatment reagent for alimentary tract cancers was assessed in six patients bearing luminal tumors. The aim of this study was to evaluate the bio-safety and efficacy of LDH/EDTA for treating luminal alimentary tract tumors with high malignance. Methods Two patients with colorectal cancer received intestinal perfusion of LDH/EDTA by colonoscopy every week for 6 weeks, and four patients with esophagus tumors received oral administration of LDH/EDTA for at least 1 month. The efficacy of LDH/EDTA were evaluated by determining tumor size reductions through contrast-enhanced CT imaging. Tumor cell dissociation was evaluated by flow cytometry to validate the tumor disaggregation. Results The colorectal cancer patients presented 33.3% and 16.7% reductions in tumor size after LDH/EDTA treatment. Additionally, symptoms of intestinal obstruction were largely alleviated. Four esophagus cancer patients experienced 6.7%, 26.7%, 16.7% and 15.4% reductions in tumor size, respectively, and symptoms of dysphagia were largely alleviated. All enrolled patients had normal physical condition based on blood routine examinations and hepatic and renal function examinations. Conclusions Tumor disaggregation strategy for luminal alimentary tract tumor removal is a highly promising, mild, noninvasive modality, which offers an unprecedented paradigm for highly effective and safe treatment for patients with luminal alimentary tract tumors. This study is registered with www.chictr.org.cn (ChiCTR2200061587, ChiCTR2200065010).
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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