Evidence map›Paper›PMID 30824798›Full record

ArticleScientific reports2019

Distribution of organic and inorganic mercury across the pelts of Canadian river otter (Lontra canadensis).

Kristin M Eccles, Eric S Littlewood, Philippe J Thomas, Hing Man Chan

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 25% of its field
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

2 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Review
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

4 authors at 2 institutions in 1 country.

Kristin M EcclesDepartment of Biology, University of Ottawa, 180, Gendron Hall, 30 Marie Curie, Ottawa, ON, K1N 6N5, Canada.
Eric S LittlewoodDepartment of Biology, University of Ottawa, 180, Gendron Hall, 30 Marie Curie, Ottawa, ON, K1N 6N5, Canada.
Philippe J ThomasDepartment of Biology, University of Ottawa, 180, Gendron Hall, 30 Marie Curie, Ottawa, ON, K1N 6N5, Canada.
Hing Man ChanDepartment of Biology, University of Ottawa, 180, Gendron Hall, 30 Marie Curie, Ottawa, ON, K1N 6N5, Canada. laurie.chan@uottawa.ca.ORCID 0000-0003-4351-7483
University of Ottawa · CAEnvironment and Climate Change Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fur is a common biomarker of environmental mercury (Hg) exposure. Further, there are well-established relationships between total mercury (THg) in fur and organs. However, these models assumed that THg is uniformly distributed across the fur in a pelt. In this study, we assess the distribution of THg and methylmercury (MeHg) across the pelts of four river otters (Lontra canadensis). THg concentrations were measured in the topcoat (n = 95) and undercoat fur (n = 95). MeHg was measured in a subset of these samples (n = 10). Patterns of THg and MeHg were explored using cluster analyses and ANOVAs. Significant differences existed between THg in topcoat and undercoat and between anatomical region (head/body/tail/legs) and fur regions (dorsal/ventral/furline). The cluster analysis showed significant THg clusters in undercoat fur and to a lesser extent topcoat fur. Further, the error rate for predicting internal THg is lowest in the forebody region of the topcoat, thus, making this the optimal region to sample for biomonitoring. Fur samples taken outside of this region could result in prediction error as high as 140% when estimating internal organ THg. The ratio of MeHg in THg in topcoat fur was measured at 95.7 ± 3.4% indicating THg concentrations can be used to assess MeHg exposure.

Identifiers

PMID30824798
PMCPMC6397270
OpenAlexW2917079617

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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.