Synergistic Effect of Polysaccharide Gums and Antimicrobial Agents on Susceptibility and Protein Expression of Select Pathogenic Microorganisms in Milk
Bibliographic record
Abstract
The quest for the use of natural ingredients as preservatives and antimicrobial agents is rising. Polysaccharide gums are usually used as emulsifying agents and as preservatives. The objective of this study was to investigate the combined effect of five different polysaccharide gums and antimicrobial agents on growth, susceptibility and protein expression of select pathogenic microorganisms in milk. Antimicrobial susceptibility and protein concentration were determined by disc diffusion and Pierce BCA assay, respectively. The proteome pattern and the number of protein spots were determined by two-dimensional gel electrophoresis. The results showed that xanthan (6.68±0.02 Log CFU/mL) caused the most growth inhibition of Salmonella enterica, compared to the control. Inclusion of pectin led to a significant (P<0.0001) 2-log reduction of Salmonella enterica during a 2-day refrigerated storage (4 oC). The highest inhibition zones (20.50±0.70) was observed in E. coli O157:H7 exposed to carrageenan-maltodextrin-cefixime. The proteome pattern was impacted by the gums with protein band of size 30kDa being the most prominent band. The highest number of protein spots (35) were obtained in locust bean treated samples. These findings indicated that tested gums affected microbial protein expression and were effective in inhibitory activity against tested pathogens specifically Escherichia coli O157:H7, thus gums hold great promise as some antimicrobial agents. Further characterization of protein targets is warranted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".