Studies on the biofilm produced by <i>Pseudomonas aeruginosa</i> grown in different metal fatty acid salt media and its application in biodegradation of fatty acids and bioremediation of heavy metal ions
Bibliographic record
Abstract
Metal fatty acid salts (MFAS) in untreated industrial effluents cause environmental pollution. The use of biocompatible agents for remediation may help in reducing the harm caused to the ambient aquatic organism. Pseudomonas aeruginosa is a ubiquitous organism that thrives under harsh conditions and is resistant to toxic metal ions. The present study shows a proof-of-concept of using this organism in the biodegradation of MFAS. MFAS were prepared and we studied their effect on the growth of the planktonic form and the formation of biofilm by P. aeruginosa. We observed biofilm formation in the presence of all the MFAS when used as the sole carbon source, albeit the quantity of biofilm formed in the presence of cadmium and copper was less. There was no effect on the planktonic form of the organism but the formation of biofilm increased in the presence of magnesium palmitate. This study shows that metal ions play a pivotal role in the formation of biofilm. HPLC (high-performance liquid chromatography) analysis of the biofilm polysaccharide showed that hexose sugar was a major component when compared with pentose sugar. The structure of biofilm polysaccharide and the coordination of the metal ion with the biofilm polysaccharide were confirmed by FTIR (Fourier transform infrared spectroscopy) and Raman spectroscopy.
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 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".