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基于最大熵的生态位模型用于绘制泰国猫后睾吸虫第一中间宿主螺蛳——暹罗豆螺的分布地图。

Ecological Niche Model based on Maximum Entropy for mapping distribution of Bithynia siamensis goniomphalos, first intermediate host snail of Opisthorchis viverrini in Thailand.

作者信息

Pratumchart Khanittha, Suwannatrai Kulwadee, Sereewong Chanisala, Thinkhamrop Kavin, Chaiyos Jukkrid, Boonmars Thidarat, Suwannatrai Apiporn T

机构信息

Department of Parasitology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand.

Department of Biology, Faculty of Science and Technology, Sakon Nakhon Rajabhat University, Sakon Nakhon 47000, Thailand.

出版信息

Acta Trop. 2019 May;193:183-191. doi: 10.1016/j.actatropica.2019.03.004. Epub 2019 Mar 5.

Abstract

The snail Bithynia siamensis goniomphalos acts as first intermediate host of the liver fluke, Opisthorchis viverrini, which causes opisthorchiasis in humans. In this study, we used a geographic information system (GIS), remote sensing (RS) and software using the maximum entropy (MaxEnt) algorithm to predict the distribution of B. s. goniomphalos in Thailand on the basis of environmental and climatic factors. The MaxEnt model for B. s. goniomphalos was excellent, with average test AUC values of 0.89. The predicted distribution of B. s. goniomphalos was affected by altitude, land cover, normalized difference vegetation index (NDVI), precipitation in the driest month (BIO 14), land surface temperature (LST) and soil pH. The areas suitable for B. s. goniomphalos were mostly in Northeast Thailand and some northern parts of the country. The presence of B. s. goniomphalos decreases with increasing altitude and increasing NDVI value. Bithynia s. goniomphalos is most likely to occur in paddy fields and cropland. Opisthorchiasis prevalence was directly proportional to the likelihood of snail occurrence as predicted by the model. This is the first time this ecological niche model has been used to predict Bithynia snail distribution and hence to provide a basis for future work of opisthorchiasis prevention in opisthorchiasis-endemic countries.

摘要

暹罗豆螺指名亚种是肝吸虫华支睾吸虫的第一中间宿主,华支睾吸虫可导致人类感染华支睾吸虫病。在本研究中,我们使用地理信息系统(GIS)、遥感(RS)以及采用最大熵(MaxEnt)算法的软件,基于环境和气候因素预测泰国暹罗豆螺指名亚种的分布。暹罗豆螺指名亚种的MaxEnt模型表现出色,平均测试AUC值为0.89。暹罗豆螺指名亚种的预测分布受海拔、土地覆盖、归一化植被指数(NDVI)、最干旱月份降水量(BIO 14)、地表温度(LST)和土壤pH值的影响。适合暹罗豆螺指名亚种生存的区域主要在泰国东北部以及该国的一些北部地区。暹罗豆螺指名亚种的出现概率随海拔升高和NDVI值增加而降低。暹罗豆螺指名亚种最有可能出现在稻田和农田中。华支睾吸虫病的流行率与模型预测的蜗牛出现概率成正比。这是首次使用这种生态位模型来预测豆螺的分布,从而为华支睾吸虫病流行国家未来的华支睾吸虫病预防工作提供依据。

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