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Record W2905948379 · doi:10.1016/j.aquatox.2018.12.012

Control of invasive sea lampreys using the piscicides TFM and niclosamide: Toxicology, successes & future prospects

2018· review· en· W2905948379 on OpenAlexaff
Michael P. Wilkie, Terrance D. Hubert, Michael A. Boogaard, Oana Birceanu

Bibliographic record

VenueAquatic Toxicology · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsWilfrid Laurier University
FundersGreat Lakes Fishery Commission
KeywordsNiclosamideToxicologyBiologyEnvironmental scienceFisheryZoology

Abstract

fetched live from OpenAlex

The invasion of the Laurentian Great Lakes of North America by sea lampreys (Petromyzon marinus) in the early 20th century contributed to the depletion of commercial, recreational and culturally important fish populations, devastating the economies of communities that relied on the fishery. Sea lamprey populations were subsequently controlled using an aggressive integrated pest-management program which employed barriers and traps to prevent sea lamprey from migrating to their spawning grounds and the use of the piscicides (lampricides) 3-trifluoromethyl-4-nitrophenol (TFM) and niclosamide to eliminate larval sea lampreys from their nursery streams. Although sea lampreys have not been eradicated from the Great Lakes, populations have been suppressed to less than 10% of their peak numbers in the mid-1900s. The ongoing use of lampricides provides the foundation for sea lamprey control in the Great Lakes, one of the most successful invasive species control programs in the world. Yet, significant gaps remain in our understanding of how lampricides are taken-up and handled by sea lampreys, how lampricides exert their toxic effects, and how they adversely affect non-target invertebrate and vertebrates species. In this review we examine what has been learned about the uptake, handling and elimination, and the mode of TFM and niclosamide toxicity in lampreys and in non-target animals, particularly in the last 10 years. It is now clear that the mode of TFM toxicity is the same in non-target fishes and lampreys, in which TFM interferes with oxidative phosphorylation by the mitochondria leading to decreased ATP production. Vulnerability to TFM is related to abiotic factors such as water pH and alkalinity, which we propose changes the relative amounts of the bioavailable un-ionized form of TFM in the gill microenvironment. Niclosamide, which is also a molluscicide used to control snails in areas prone to schistosomiasis infections of humans, also likely works by uncoupling oxidative phosphorylation, but less is known about other aspects of its toxicology. The effects of TFM include reductions in energy stores, particularly glycogen and high energy phosphagens. However, non-target fishes readily recover from sub-lethal TFM exposure as demonstrated by the rapid restoration of energy stores and clearance of TFM. Although both TFM and niclosamide are non-persistent in the environment and critical for sea lamprey control, increasing public and institutional concerns about pesticides in the environment makes it imperative to explore other means of sea lamprey control. Accordingly, we also address possible "next-generation" strategies of sea lamprey control including genetic tools such as RNA interference and CRISPR-Cas9 to impair critical physiological processes (e.g. reproduction, digestion, metamorphosis) in lamprey, and the use of green chemistry to develop more environmentally benign chemical methods of sea lamprey control.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.307
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations77
Published2018
Admission routes1
Has abstractyes

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