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Sustainable production of heavy metal-binding levan by a subarctic permafrost thaw lake Pseudomonas strain 2ASCA

2024· article· en· W4394842438 on OpenAlexfundaboutno aff
Ilaria Finore, Giovanni Dal Poggetto, Luigi Leone, Andrea Cattaneo, Barbara Immirzi, Maria Michela Corsaro, Angela Casillo, Annarita Poli

Bibliographic record

VenueInternational Journal of Biological Macromolecules · 2024
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsnot available
FundersSentinelle Nord, Université LavalEuropean Commission
KeywordsSubarctic climatePermafrostStrain (injury)PseudomonasMetalHeavy metalsEnvironmental chemistryEnvironmental scienceChemistryGeologyBacteriaEcologyBiologyPaleontology

Abstract

fetched live from OpenAlex

Pseudomonas strain 2ASCA isolated in subarctic Québec, Canada, produced a cell membrane bound levan-type exopolymer (yield 1.17 g/L), after incubation in growth media containing 6 % sucrose (w/v) at temperature of 15 °C for 96 h. The objective of this study was to optimize levan production by varying the growth parameters. Moreover, the polymer's chemical characterization has been studied with the aim of increasing knowledge and leading to future applications in many fields, including heavy metal remediation. Higher levan yields (7.37 g/L) were reached by setting up microbial fermentation conditions based on the re-use of the molasses obtained from sugar beet processing. Spectroscopy analyses confirmed the levan-type nature of the exopolymer released by strain 2ASCA, consisting of a β-(2,6)-linked fructose repeating unit. Gel permeation chromatography revealed that the polymer has a molecular weight of 13 MDa. Scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS) showed that the levan sequestered with a strong affinity Cr(III), which has never been previously reported, highlighting an interesting biosorption potential. In addition, SEM analysis revealed the formation of nanoparticles in acidified water solution.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.283
Teacher spread0.268 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations8
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Biological MacromoleculesSame topicMicrobial Metabolites in Food BiotechnologyFrench-language works237,207