Comparison of extraction methods for the characterization of extracellular polymeric substances from aggregates of three biofilm-forming phototrophic microorganisms
Bibliographic record
Abstract
This paper aims to define a robust procedure to extract extracellular polymeric substances (EPS) from aggregates of three benthic phototrophic microorganisms: the cyanobacterium Phormidium autumnale, the diatom Nitzschia palea, and the green alga Uronema confervicolum. This study focuses on the extraction efficiency of polysaccharide and protein EPS by using two physical methods (sonication, cation exchange resin) and three chemical methods (formamide, EDTA, Tween 20) with minimum cell lysis. Cell lysis was evaluated by monitoring chlorophyll a release. The results indicated that sonication or incubation of the algae aggregates with 0.25% Tween 20 induced a high level of cell lysis. A combined extraction approach, with an initial dispersing pretreatment (Ultra-Turrax, 13 500 r·min–1, 1 min), followed by formamide addition (0.22%) and then incubation with Dowex cation exchange resin (50 g per g of dry biomass), provided the highest amount of extracted EPS (mostly proteins), with low cell lysis. Furthermore, extracted EPS were characterized by size exclusion chromatography, and the obtained fingerprints revealed similar profiles for the three benthic microorganisms with a majority of low molecular weight polymers (400 to 11 300 Da). However, additional EPS of high (>600 000 Da) and intermediate (20 000 to 80 000 Da) molecular sizes were specifically detected in the diatom extracts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".