Metallo-Glycodendrimeric Materials against Enterotoxigenic Escherichia coli
Bibliographic record
Abstract
Conjugation of carbohydrates to nanomaterials has been extensively studied and recognized as an alternative in the biomedical field. Dendrimers synthesized with mannose at the end group and with entrapped zero-valent copper/silver could be a potential candidate against bacterial proliferation. This study is aimed at investigating the bactericidal activity of metal-glycodendrimers. The Cu(I)-catalyzed azide–alkyne cycloaddition (CuAAC) reaction was used to synthesize a new mannosylated dendrimer containing 12 mannopyranoside residues in the periphery. The enterotoxigenic Escherichia coli fimbriae 4 (ETEC:F4) viability, measured at 600 nm, showed the half-inhibitory concentration (IC50) of metal-free glycodendrimers (D), copper-loaded glycodendrimers (D:Cu) and silver-loaded glycodendrimers (D:Ag) closed to 4.5 × 101, 3.5 × 101 and to 1.0 × 10−2 µg/mL, respectively, and minimum inhibitory concentration (MIC) of D, D:Cu and D:Ag of 2.0, 1.5 and 1.0 × 10−4 µg/mL, respectively. The release of bacteria contents onto broth and the inhibition of ETEC:F4 biofilm formation increased with the number of metallo-glycodendrimer materials, with a special interest in silver-containing nanomaterial, which had the highest activity, suggesting that glycodendrimer-based materials interfered with bacteria-bacteria or bacteria–polystyrene interactions, with bacteria metabolism and can disrupt bacteria cell walls. Our findings identify metal–mannose-dendrimers as potent bactericidal agents and emphasize the effect of entrapped zero-valent metal against ETEC:F4.
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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) | 0.000 | 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 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".