An acidic pH independent piperazine–TPE AIEgen as a unique bioprobe for lysosome tracing
Bibliographic record
Abstract
Lysosomes are involved in a multitude of cellular processes and their dysfunction is associated with various diseases. They are the most acidic organelles (pH 3.8-6.6, size 0.1-1.2 μm) with the highest viscosity (47-190 cP at 25 °C) in the cell. Because of their acidity, pH dependent non-AIE active fluorescent lysosomal probes have been developed that rely on protonation inhibited photoinduced electron transfer (PET). In this work, an acidic pH independent lysosome targetable piperazine-TPE (PIP-TPE) AIEgen has been designed with unique photophysical properties making it a suitable probe for quantifying viscosity. In a non-aggregated state PIP-TPE shows deep-blue emission as opposed to its yellowish-green emission in the bulk. It possesses high specificity for lysosomes with negligible cytotoxicity and good tracing ability due to its better photostability compared to LysoTracker Red. In contrast to most known lysosome probes that rely solely on PET, restriction of intramolecular motion (RIM) due to the larger viscosity inside the lysosomes is the mechanism responsible for PIP-TPE's fluorescence. PIP-TPE's high selectivity is attributed to its unique molecular design that features piperazine fragments providing a perfect balance between lipophilicity and polarity.
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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".