ZnO-Salen NPs Employed as Chemosensor for Detection of Al3+ and K+ in Aqueous Medium, Developing Human Cell Images
Bibliographic record
Abstract
Abstract ZnO nanoparticles (NPs) were prepared and characterized by different analytical methods and then they were used to decorate with N , N ´-bis(salicylidene)ethylenediamine (salen) in order to perform as receptor for the metal ions in an aqueous medium. The results show that ZnO-salen selectively detects Al 3+ ions in aqueous medium since the intensity of fluorescence has been enhanced significantly. However, the presence of K + in the medium further intensified the fluorescence emission for the [ZnO-salen-Al 3+ ] system. The above system has been applied to recognize Al 3+ and K + in cells by developing the cell images, for which, the fluorescence image is brightened if a human glioblastoma U251 cell contains [ZnO-salen-Al 3+ ] + K + ions, consisting of the fluorescence titration. The binding global constant for Al 3+ and the subsequent recognition of K + by ZnO-salen resulted in β 2 (Al 3+ ) = 6.61 × 10 3 and β 2 (K + ) = 3.71 × 10 3 with a detection limit of 36.51 µM for Al 3+ and 17.39 µM for K + . In the cell toxicity analysis, the cell viability was over 85% for the ZnO-salen even in the concentration as high as 100 mM.
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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) | 0.001 | 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".