Novel ZnO hollow-nanocarriers containing paclitaxel targeting folate-receptors in a malignant pH-microenvironment for effective monitoring and promoting breast tumor regression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Low pH in the tumor micromilieu is a recognized pathological feature of cancer. This attribute of cancerous cells has been targeted herein for the controlled release of chemotherapeutics at the tumour site, while sparing healthy tissues. To this end, pH-sensitive, hollow ZnO-nanocarriers loaded with paclitaxel were synthesized and their efficacy studied in breast cancer in vitro and in vivo. The nanocarriers were surface functionalized with folate using click-chemistry to improve targeted uptake by the malignant cells that over-express folate-receptors. The nanocarriers released ~75% of the paclitaxel payload within six hours in acidic pH, which was accompanied by switching of fluorescence from blue to green and a 10-fold increase in the fluorescence intensity. The fluorescence-switching phenomenon is due to structural collapse of the nanocarriers in the endolysosome. Energy dispersion X-ray mapping and whole animal fluorescent imaging studies were carried out to show that combined pH and folate-receptor targeting reduces off-target accumulation of the nanocarriers. Further, a dual cell-specific and pH-sensitive nanocarrier greatly improved the efficacy of paclitaxel to regress subcutaneous tumors in vivo. These nanocarriers could improve chemotherapy tolerance and increase anti-tumor efficacy, while also providing a novel diagnostic read-out through fluorescent switching that is proportional to drug release in malignant tissues.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| 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 | 0.001 |
| 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 it