Graphene Oxide Membrane Immobilized Aptamer as a Highly Selective Hormone Removal
Bibliographic record
Abstract
Three-dimensional (3D) reduced graphene oxide (rGO) modified by polyethyleneimine (PEI) was prepared and functionalized by fluorophore-labeled dexamethasone-aptamer (Flu-DEX-apt) via π-π stacking interaction. The rGO/PEI/Flu-DEX-apt was used as a selective membrane for dexamethasone hormone removal from water. The prepared rGO/PEI/Flu-DEX-apt membranes were stable, insoluble, and easily removable from liquid media. The membrane was characterized by Raman spectroscopy, scanning electron spectroscopy, and FTIR spectroscopy. The rGO/PEI/Flu-DEX-apt membrane showed high sensitivity and specificity toward the dexamethasone hormone in the presence of other steroid hormone analogs, such as progesterone, estrone, estradiol, and 19-norethindrone. The fluorescence and UV-visible spectroscopy were used to confirm the membranes performance and the quantification of hormones removal. The resulting data clearly show that the graphene oxide concentration influence the aptamers and analytes interaction (π-π stacking interaction). It was found that by varying the graphene oxide concentration yields to different porosities of rGO/PEI/Flu-DEX-apt membranes affects the adsorption recovery rate, as well as the specificity and selectivity toward the dexamethasone hormone.
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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 | 0.001 | 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".