The effects of tea polyphenols on<i>Candida albicans</i>: inhibition of biofilm formation and proteasome inactivation
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 adherence of Candida albicans to one another and to various host and biomaterial surfaces is an important prerequisite for the colonization and pathogenesis of this organism. Cells in established biofilms exhibit different phenotypic traits and are inordinately resistant to antimicrobial agents. Recent studies have shown that black and green tea polyphenols exhibit both antimicrobial and strong cancer-preventive properties. Experiments were conducted to determine the effects of these polyphenols on C. albicans. Standard growth curves demonstrated a 40% reduction in the growth rate constant (K) with a 2 mg/mL concentration of Polyphenon 60, a green tea extract containing a mixture of polyphenolic compounds. Cultures treated with 1.0 micromol/L -(-)epigallocatechin-3-gallate (EGCG), the most abundant polyphenol, displayed a 75% reduction of viable cells during biofilm formation. Established biofilms treated with EGCG were also reduced, by 80%, as determined through XTT (2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide) colorimetric assays. Identical concentrations of epigallocatechin and epicatechin-3-gallate demonstrated similar biofilm inhibition. Further investigations regarding the possible mechanism of polyphenol action indicate that in vivo proteasome activity was significantly decreased when catechin-treated yeast cells were incubated with a fluorogenic peptide substrate that measured proteasomal chymotrypsin-like and peptidyl-glutamyl peptide-hydrolyzing activities. Impairment of proteasomal activity by tea polyphenols contributes to cellular metabolic and structural disruptions that expedite the inhibition of biofilm formation and maintenance by C. albicans.
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 | 0.000 | 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) | 0.000 | 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