Bibliographic record
Abstract
The aim of this study was to screen antibacterial, antifungal and cytotoxic activities of crude metabolites of a bacterium DADA-1AIMR-24 isolated from soil in Rajshahi division, Bangladesh.The antibacterial activity of crude extracts was tested by agar well diffusion technique against Bacillus cereus, Staphylococcus aureus ATCC-259233, Listeria monocytogenes, Agrobacterium spp., Escherichia coli FPFC-1407, Shigella dysenteriae AL-35587, Shigella sonnei and Shigella boydii.At the same time, antifungal activity was also conducted by disc diffusion method against Aspergillus niger, Tichoderma herzanium, and Microphomina phaseolina.The MIC values of the extract against Bacillus cereus, Staphylococcus aureus ATCC-259233, E. coli FPFC-1407, Shigella dysenteriae AL-35587, Shigella sonnei, Shigella boydii were 64, 64, 64, 64, 64 and 32 µg/ml respectively.The minimum bactericidal concentration (MBC) was also determined (Table 2).The MBC values of the extract were 128, 128, 128, 128, 128 and 64 µg/ml.As the MBC value was higher than the MIC value, it is clear that the extract was bacteriosatic not bactericidal.The approximate counts of bacteria in the MIC tubes were also determined (table 2).The brine shrimp lethality bioassay was conducted to determine the cytotoxic nature of crude extracts, which showed that the degree of lethality of extracts was directly proportional to the concentration (LC50 21.55 μg/ml) compounds in the crude extract but due to low production of metabolites, we could not extract sufficient amounts as it took long time to produce metabolites.Further work is necessary to isolate and characterize the active compounds.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.910 | 0.935 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".