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Record W2982988000 · doi:10.1016/j.mex.2019.10.024

An efficient and affordable laboratory method to produce and sustain high concentrations of microcystins by Microcystis aeruginosa

2019· article· en· W2982988000 on OpenAlexafffund
René S. Shahmohamadloo, Xavier Ortiz Almirall, Claire Holeton, Richard Chong-Kit, David G. Poirier, Satyendra P. Bhavsar, Paul K. Sibley

Bibliographic record

VenueMethodsX · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversity of TorontoQueen's UniversityMinistry of the Environment, Conservation and ParksUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrocystis aeruginosaMicrocystisMicrocystinCyanobacteriaEnvironmental chemistryNational laboratoryEnvironmental scienceBiologyChemistryEngineeringBacteriaEngineering physics

Abstract

fetched live from OpenAlex

Microcystis aeruginosa is a cosmopolitan cyanobacteria that continues to jeopardize freshwater ecosystem services by releasing the hepatotoxin microcystin, which can, in some cases, cause death to aquatic fauna and even humans. Currently, our abilities to understand the mechanisms of microcystin toxicology are limited by the lack of a method for producing high concentrations, which are central to large-scale and long-term research in natural systems. Here we present an efficient and affordable laboratory method to produce high concentrations of microcystins by a toxigenic strain of M. aeruginosa . Through batch culture studies, we yielded microcystins at concentrations that are environmentally relevant to freshwaters around the world (1–300 μg L −1 ), maintained these concentrations without resupplying fresh medium (further reducing costs), and utilized rate equations to model the relationship between the environmental conditions in the cultures and changes occurring within the M. aeruginosa cells. Our assessment suggests that steady production of microcystins depends on the availability of carbon throughout the experiment. Hence, we recommend the use of tissue culture treated flasks with a vented cap to ensure the production of microcystins is uninterrupted. This method demonstrates that microcystins can be produced in the laboratory at concentrations relevant to freshwater ecosystems. •The method demonstrates M. aeruginosa CPCC 300 is a reliable strain of freshwater cyanobacteria that can yield microcystins at environmentally relevant concentrations. •Validation showed M. aeruginosa CPCC 300 is resilient in carbon-limited situations and may respond to stress by shifting the ratio of microcystin congeners. •Cell culture flasks with vented caps —filled no more than 50 % of the flask volume to allow for sufficient air exchange— are an excellent and cost-effective approach to maintaining cell growth and producing microcystins at a range between 300 to 1200 μg L −1 .

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.003
GPT teacher head0.244
Teacher spread0.241 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations15
Published2019
Admission routes2
Has abstractyes

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