five

Antimalarial test data

收藏
DataCite Commons2026-04-20 更新2026-04-25 收录
下载链接:
https://datadryad.org/dataset/doi:10.5061/dryad.2z34tmpjx
下载链接
链接失效反馈
官方服务:
资源简介:
Background Malaria, despite progresses, is still causing huge number of malaria cases and deaths. Successful control of this disease demands the availability of drugs with high efficacy and minimal toxicity. In addition to modern medicines, traditional medicinal plants have long been used for managing malaria. However, many of these medicinal plants are not scientifically validated. Objective This study was conducted to assess the invivo antimalarial activity of Zehneria scabra, against Plasmodium berghei in swiss albino mice. Materials and methods Maceration technique has been used to extract the plant, and four doses of the extract ranging from 25-150 mg/kg were used. Tween 80 was used as negative control, and chloroquine was used a standard drug. The level of parasitemia and malaria-related variations including, packed cell volume, survival time, temperature and body weight were measured, and these records were used to weigh the extract-treated groups against both controls. Results The extract was found to have a significant parasite suppression in both four-day suppressive and Rane’s models (p<0.001), as well as in prophylactic model at 100 mg/kg and 150 mg/kg (P<0.001). In line with this parasitemia reduction, the doses 100 mg/kg and 150 mg/kg in the four-day suppressive test, and 150 mg/kg in Rane’s test had significant (p<0.05) effect in prolonging survival time. While reduction in packed cell volume was prevented in all models at doses of 100 mg/kg and 150 mg/kg (p<0.05), temperature decline was lessened at 100 mg/kg and 150 mg/kg in four-day suppressive model, and at 150 mg/kg in Rane’s model (p<0.05). Conclusion The antimalarial activity found in this study confirm the traditional use and invitro antimalarial effect of the plant, and if studied further, it may produce active constituent(s) that can be used as a lead compound (s) against malaria.
提供机构:
Dryad
创建时间:
2020-09-04
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作