Amino‐Substituted 2,2′‐Bipyridine Ligands as Fluorescent Indicators for Zn<sup>II</sup> and Applications for Fluorescence Imaging of Prostate Cells
Bibliographic record
Abstract
Abstract ZnII concentrations in malignant prostate tissues are much lower than in benign or healthy, suggesting that ZnII levels are a potential biomarker for prostate cancer (PCa). Five 2,2′‐bipyridine ligands were synthesized containing amino substituents with varying electron‐donating ability for investigation as fluorescent ZnII indicators. The excited state characteristics of the ligands were explored by UV/Vis and fluorescence spectroscopy. 3,3′‐Diamino‐2,2′‐bipyridine (1) was previously shown to be weakly fluorescent as a result of π→π* transitions. The other four ligands have properties consistent with an n→π* intraligand charge transfer excited state. Strongly donating amino and aminophenyl (2 and 4) substituents gave low quantum yields, while weaker donating benzimidazole substituents (6 and 7) gave high quantum yields. Absorption and fluorescence wavelengths underwent bathochromic shifts upon ZnII binding in a majority of cases. Quantum yields drastically increased upon ZnII binding for 1 and 2, but decreased for 4, 6, and 7. Compounds 6 and 7 were incubated with PC‐3, DU 145 and BPH‐1 cells to determine their ZnII sensing abilities in a biological system. Weak fluorescence was observed in BPH‐1 cells and subsequent incubation with ZnII caused fluorescence intensity to increase. No fluorescence was observed in PCa cell lines. Further investigation of these ligands may allow for quantitative determination of ZnII concentrations in ex vivo tissue samples.
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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".