Gram-Negative and Gram-Positive Antibacterial Properties of the Whole Plant Extract of Willow Herb ( <i>Epilobium angustifolium</i> )
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The emergence of new pathogens and the increase in the number of multidrug-resistant strains in well-established pathogens during the past decade represent a growing public health concern globally. With the current lack of research and development of new antibiotics by large pharmaceutical companies due to poor financial returns, new alternatives need to be explored including natural herbal or plant-based extracts with reported antibacterial properties. Willow herb (Epilobium angustifolium) preparations have been used in traditional aboriginal and folk medicine preparations externally as an antiphlogistic to treat prostate and gastrointestinal disorders and as an antiseptic to treat infected wounds. The authors hypothesized that a whole plant extract of willow herb would exhibit antimicrobial properties on a variety of both Gram-positive and gram-negative bacteria in culture. The authors found that, in comparison to growth controls, willow herb extract significantly inhibited the growth of Micrococcus luteus (p < .01), Staphylococcus aureus (p < .05), Escherichia coli (p < .001), and Pseudomonas aeruginosa (p < .001). They also found that willow herb extract inhibited the growth of bacteria in culture more effectively than vancomycin (p < .05) or tetracycline (p < .004). These results provide preliminary support for the traditional folkloric claim that the plant willow herb possesses antibacterial properties against a variety of gram-positive and gram-negative bacteria. Given that whole plant extract was utilized for this study, further investigations are warranted to determine which specific part of the plant (i.e., leaves, stem, roots, and flowers) possess the antibacterial properties.
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.
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 | 0.001 |
| 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 it