Evaluation of the antibacterial potential of mango (Mangifera indica) seed kernels in Bangladesh
Bibliographic record
Abstract
Antimicrobial resistance is a global threat. On the other hand, Bangladesh produces high-quality mangoes, yet the mango coat and seed kernel, which contain medicinal components, remain unused. Therefore, this study investigated the antibacterial potential and toxicity of ethanol extracts from mango (Mangifera indica) seed kernels, which specifically target the bacterial strains Staphylococcus aureus, Bacillus cereus, Escherichia coli, and Klebsiella sp. Amrapali variant mango seeds were collected, dried, ground into a fine powder, and extracted with ethanol at various ratios. The efficacy of the crude extract was tested via the disc diffusion method. The results demonstrated significant antibacterial activity against gram-positive bacteria (S. aureus and B. cereus), with clear zones of inhibition observed, especially in a dose-dependent manner. The pure crude extract inhibited the growth of S. aureus with a zone of 23 mm, identical to that produced by doxycycline. However, the extract exhibited limited activity against gram-negative bacteria (E. coli and Klebsiella sp.). Additionally, the extract was effective against multidrug-resistant S. aureus. The pure crude extract produced a 22.5 mm zone of inhibition against multidrug-resistant S. aureus, which was slightly smaller than that of gentamicin (23 mm) but larger than those of chloramphenicol (21 mm), vancomycin (20 mm), and tetracycline (16 mm). In vivo toxicity was assessed in mice, revealing no significant adverse effects on the hepatic structure or renal cortex at lower doses (100 μl of pure crude extract). However, higher doses caused mild histopathological changes in the liver and kidneys. These findings suggest that mango seed kernel extract holds promise as an alternative antibacterial agent, particularly against gram-positive and antibiotic-resistant bacteria, while being relatively safe at lower doses. Further research is needed to elucidate the active compounds, mechanisms of action, and broader applications of this extract in combating antibiotic-resistant bacterial infections.
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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) | 0.000 | 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".