Evidence map›Paper›PMID 38274749›Full record

ArticleFrontiers in microbiology2023

Effectiveness assessment of using water environmental microHI to predict the health status of wild fish.

Haile Yang, Jia Zhong, Xiaoqian Leng, Jinming Wu, Peilin Cheng, Li Shen, Jinping Wu, Pengcheng Li, Hao Du

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Effect of ectoparasiteFrontiers in veterinary science · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Haile Yang *Key Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.
Jia Zhong *Key Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.
Xiaoqian LengKey Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.
Jinming WuKey Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.
Peilin ChengKey Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.
Li ShenKey Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.
Jinping WuKey Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.
Pengcheng LiKey Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.
Hao DuKey Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aquatic wildlife health assessment is critically important for aquatic wildlife conservation. However, the health assessment of aquatic wildlife (especially aquatic wild animals) is difficult and often accompanied by invasive survey activities and delayed observability. As there is growing evidence that aquatic environmental microbiota could impact the health status of aquatic animals by influencing their symbiotic microbiota, we propose a non-invasive method to monitor the health status of wild aquatic animals using the environmental microbiota health index (microHI). However, it is unknown whether this method is effective for different ecotype groups of aquatic wild animals. To answer this question, we took a case study in the middle Yangtze River and studied the water environmental microbiota and fish gut microbiota at the fish community level, population level, and ecotype level. The results showed that the gut microHI of the healthy group was higher than that of the unhealthy group at the community and population levels, and the overall gut microHI was positively correlated with the water environmental microHI, whereas the baseline gut microHI was species-specific. Integrating these variations in four ecotype groups (filter-feeding, scraper-feeding, omnivorous, and carnivorous), only the gut microHI of the carnivorous group positively correlated with water environmental microHI. Alcaligenaceae, Enterobacteriaceae, and Achromobacter were the most abundant groups with health-negative-impacting phenotypes, had high positive correlations between gut sample group and environment sample group, and had significantly higher abundance in unhealthy groups than in healthy groups of carnivorous, filter-feeding, and scraper-feeding ecotypes. Therefore, using water environmental microHI to indicate the health status of wild fish is effective at the community level, is effective just for carnivorous fish at the ecotype level. In the middle Yangtze River, Alcaligenaceae, Enterobacteriaceae (family level), and

Indexed as

aquatic wildlifeenvironmental microbiotagut microbiotahealth monitoringmicrobial phenotypesmicrobiota health index (microHI)

Identifiers

PMID38274749
PMCPMC10808811

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.