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Record W4381510863 · doi:10.26434/chemrxiv-2023-tdk1l

Urban stressors impact lipid profiles in freshwater periphytic communities

2023· preprint· en· W4381510863 on OpenAlexaff
Nicolás Mazzella, Romain Vrba, Aurélie Moreira, Nicolas Creusot, Mélissa Éon, Débora Millan-Navarro, Isabelle Lavoie, Soizic Morin

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsInstitut National de la Recherche Scientifique
FundersInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
KeywordsPhototrophLipidomeMicrocosmBiofilmAlgaeBiologyComposition (language)BiocideMicroorganismHeterotrophEnvironmental chemistryEcologyFood scienceChemistryBacteriaBotanyBiochemistryLipid metabolismPhotosynthesis

Abstract

fetched live from OpenAlex

The composition of lipids in algae are significantly influenced by environmental factors, including light intensity. Exposure to organic and inorganic contaminants can also disrupt the synthesis of fatty acids, changing the lipid composition of microalgae in periphytic communities. In this study, we looked at how a biocide such as dodecylbenzyldimethylammonium chloride (BAC 12) and two photoperiod durations can affect a biofilm's polar lipidome in a microcosm experiment. The heterotrophic compartment appeared to be raised by exposure to BAC 12 at the expense of phototrophic organisms. Additionally, the overall decline in polyinsaturated fatty acids indicated that the biofilm's phototrophic organisms were all severely impacted. However, it may be difficult to differentiate the effects of contamination from those of light, since there was no observable effect of photoperiods on the conventional fatty acid determination. The molecular species composition of both glycolipids and phospholipids was investigated in additional multivariate analyses. It was suggested that some molecular species may serve as more specific markers of light duration at the biofilm scale. Lastly, we recommend applying a similar lipidomic approach with monospecific cultures of microalgal strains in future research to support these findings, as the methodology used in this study would be applicable to other biofilm-derived microorganisms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.034
GPT teacher head0.238
Teacher spread0.204 · 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.

Study designObservational
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

Citations2
Published2023
Admission routes1
Has abstractyes

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