Antibacterial and Antioxidant Activity of Extracts from Selected Probiotic Bacteria
Bibliographic record
Abstract
<p>Probiotic extracts can potentially be used as bio-preservatives and in reduction of oxidative stress. The study investigated the antibacterial and antioxidant activity of methanol extracts from freeze-dried cells of probiotic <em>Lactobacillus</em> strains identified using molecular techniques. The quantitative microplate method, which employed <em>p</em>-iodonitrotetrazolium (INT) and the method by Brand-Williams et al. (1995) were employed to investigate quantitatively the antibacterial and the antioxidant activity, respectively, of probiotic extracts. The MIC values extracts from most probiotic strains, tested against indicator bacterial pathogens, were in the range of 1.25 – 5 mg/mL while that of <em>Lb. casei</em> strain B and <em>Lc. lactis</em> subsp <em>lactis</em> strain X was at least 20 mg/mL after 24 h of incubation at 37°C. At the highest extract concentration of 20 mg/mL used in the study, <em>Lb. acidophilus</em>, <em>Lb. rhamnosus</em> and <em>Lb. casei</em> strains had 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activities of 77.9 - 86.1%, 45.7 - 86.4% and 36.9 – 45.8% respectively. Quantitative antibacterial and antioxidant activities of methanol extracts from freeze-dried cells of probiotic <em>Lactobacillus</em> strains was determined for the first time.</p>
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".