Potent Antifungal Activity of Penta-<i>O</i>-galloyl-β-<scp>d</scp>-Glucose against Drug-Resistant <i>Candida albicans</i>, <i>Candida auris</i>, and Other Non-<i>albicans Candida</i> Species
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
High Resolution Image Download MS PowerPoint Slide Among fungal pathogens, infections by drug-resistant Candida species continue to pose a major challenge to healthcare. This study aimed to evaluate the activity of the bioactive natural product, penta- O -galloyl-β- d -glucose (PGG) against multidrug-resistant (MDR) Candida albicans, MDR Candida auris, and other MDR non- albicans Candida species. Here, we show that PGG has a minimum inhibitory concentration (MIC) of 0.25–8 μg mL –1 (0.265–8.5 μM) against three clinical strains of C. auris and a MIC of 0.25–4 μg mL –1 (0.265–4.25 μM) against a panel of other MDR Candida species. Our cytotoxicity studies found that PGG was well tolerated by human kidney, liver, and epithelial cells with an IC 50 > 256 μg mL –1 (>272 μM). We also show that PGG is a high-capacity iron chelator and that deletion of key iron homeostasis genes in C. albicans rendered strains hypersensitive to PGG. In conclusion, PGG displayed potent anti- Candida activity with minimal cytotoxicity for human cells. We also found that the antifungal activity of PGG is mediated through an iron-chelating mechanism, suggesting that the compound could prove useful as a topical treatment for superficial Candida infections.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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