Inhibition of Thioredoxin Reductase by Targeted Selenopolymeric Nanocarriers Synergizes the Therapeutic Efficacy of Doxorubicin in MCF7 Human Breast Cancer Cells
Why this work is in the frame
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Bibliographic record
Abstract
Increasing evidence suggests selenium nanoparticles (Se NPs) as potential cancer therapeutic agents and emerging drug delivery carriers, yet, the molecular mechanism of their anticancer activity still remains unclear. Recent studies indicate thioredoxin reductase (TrxR), a selenoenzyme, as a promising target for anticancer therapy. The present study explored the TrxR inhibition efficacy of Se NPs as a plausible factor impeding tumor growth. Hyaluronic acid (HA)-functionalized selenopolymeric nanocarriers (Se@CMHA NPs) were designed wielding chemotherapeutic potential for target specific Doxorubicin (DOX) delivery. Se@CMHA nanocarriers are thoroughly characterized asserting their chemical and physical integrity and possess prolonged stability. DOX-loaded selenopolymeric nanocarriers (Se@CMHA-DOX NPs) exhibited enhanced cytotoxic potential toward human cancer cells compared to free DOX in an equivalent concentration eliciting its selectivity. In first-of-its-kind findings, selenium as Se NPs in these polymeric carriers progressively inhibit TrxR activity, further augmenting the anticancer efficacy of DOX through a synergistic interplay between DOX and Se NPs. Detailed molecular studies on MCF7 cells also established that upon exposure to Se@CMHA-DOX NPs, MCF7 cells endure G2/M cell cycle arrest and p53-mediated caspase-independent apoptosis. To gauge the relevance of the developed nanosystem in in vivo settings, three-dimensional tumor sphere model mimicking the overall tumor environment was also performed, and the results clearly depict the effectiveness of our nanocarriers in reducing tumor activity. These findings are reminiscent of the fact that our Se@CMHA-DOX NPs could be a viable modality for effective cancer chemotherapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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