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Record W4390954842 · doi:10.34117/bjdv10n1-084

Application of cyanobacteria in radioactive waste

2024· article· en· W4390954842 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrazilian Journal of Development · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCyanobacteriaEnvironmental scienceRadioactive wasteEnvironmental chemistryPollutionMicroorganismWaste managementBacteriaBiologyChemistryEcology

Abstract

fetched live from OpenAlex

The extremely toxic radioactive wastes whose radioactivity persists for thousands of years are accumulated through nuclear power plants, mining companies, industries, and research centers, among others. However, the lack of technology for the treatment and removal of radioactivity from radioactive waste becomes a bottleneck for research. Currently, there are temporary solutions, and the radioactive waste continues to increase. Given this scenario it is necessary to seek alternatives for the treatment of radioactive waste with efficiency and low cost, without polluting the environment, and that is not harmful to human health. One way to reduce this type of pollution is to use microorganisms, especially cyanobacteria, which comprise one of the largest, most ecologically diverse, successful, and important group of bacteria on Earth. These bacteria have a great ability to remove pollutants, such as heavy metals, textile dyes, pesticides, etc., but their role in the degradation of recalcitrant and radioactive compounds is still scarce. The present work aimed to investigate the potential of cyanobacteria isolated from different environments to remove radiolabeled molecules from radioactive waste (containing 14C radioisotopes). Seven cyanobacteria, Synechococcus sp. CENA136 (isolated from the Mangrove of Cardoso Island), Phormidium autumnale UTEX 1580 (collection of UTEX cultures - fish aquarium), Nostoc sp CENA420 (Antarctica), Limnothrix sp. CENA458 (isolated from the reservoir), Oscillatoria acuminata CENA525 (isolated from the Pantanal), Nodularia sp CENA215 (isolated from Caatinga), and Trichormus SP UFV-56 (isolated from the Federal University of Viçosa-MG) were used in the present study. Cyanobacteria were maintained in Z8, BG-11, and SWBG-11 liquid culture medium under constant fluorescent lighting of 40 µmol photons·m-2·s-1 and a controlled temperature of 23 ± 1°C. Radioactive waste containing several 14C organic molecules, solubilized in organic solvents was used. The inoculums were obtained from 50 mL of culture medium. The radioactive waste was added at concentrations of 0, 5, 10 and 15%. To investigate the removal of the radioactivity present in the waste, analysis was performed by Liquid Scintillation Counting (LSC) in the beginning and final cultivation and HPLC (coupled to a flow scintillation analyzer) in order to evaluate the profile of radioactive molecules present in the waste. Intracellularly accumulated radioactivity was also assessed by LSC after cell disruption. The ability to accumulate radioactive molecules intracellularly was observed in all cyanobacteria, but Nostoc sp CENA420 accumulated 43% and Trichormus sp UFV-56 accumulated 68%, both cultivated with 15% of radioactive waste. These results showed that the cyanobacteria Nostoc sp CENA420 and Trichormus sp UFV-56 consumed 87 and 86% of radioactive molecules, respectively, being of great potential for the removal of radiolabeled radioactive waste molecules. Research using cyanobacteria to remove radiolabeled molecules from radioactive waste is still at an early stage but is a promising alternative to biological treatment.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

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

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 head0.005
GPT teacher head0.216
Teacher spread0.211 · 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