Chlorination and ozonation reduce microcystin content and tumour promoting activity of complex cyanobacterial extract
Bibliographic record
Abstract
Despite intensive research and management efforts in the past decades, cyanobacterial blooms and their toxins, such as microcystins (MC), continue to represent a major ecological and health problem in fresh waters throughout the world. Our objective was to compare the efficacy of two commonly used drinking water treatment technologies, chlorination and ozonation, in removing MCs and in reducing tumour promotion-related effects of cyanobacteria, such as inhibition of gap junctional intercellular communication (GJIC) and activation of mitogen activated protein kinases (MAPKs) in a pluripotent rat liver epithelial cell line (WB-F344). This combined chemical and bioassay approach demonstrated that ozone effectively removed all MCs from an extract of globally important bloom-forming cyanobacterium, Microcystis sp. Ozone also significantly reduced the overall tumour promotional potency of the cyanobacterial extract, as indicated by a substantial reduction in the ability of the extract to inhibit GJIC and activate extracellular receptor kinase 1/2 (ERK1/2). Although comparable reduction of total organic carbon was achieved by ozone and chlorine treatment, chlorination was much less effective in removing MCs and reducing the effects on GJIC. Chlorination had a biphasic effect with reduction of extract-induced activation of ERK1/2 at lower doses of chlorine; at high doses of chlorine, however, the by-products of chlorination actually induced the activation of ERK1/2. The extracts induced p38 activation and chlorination was not effective in reversing this effect, while ozone did reverse this effect, but not as much as the activation of ERK1/2. Thus, ozone was effective in reducing the toxicity of cyanobacterial extracts while chlorination was not only lacking efficacy but at high doses further produced by-products that were equally as toxic as the untreated samples. Our study points to advances of ozonation approach and brings evidences supporting the need of effect-based monitoring implementation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".