Microfluidic Shear Processing Control of Biological Reduction Stimuli-Responsive Polymer Nanoparticles for Drug Delivery
Why this work is in the frame
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Bibliographic record
Abstract
pharmacological properties for selective drug delivery. This work leverages previous fundamental work on microfluidic control of the physicochemical properties of GSH-responsive PNPs containing cleavable disulfide groups in two different locations (core and interface, DualM PNPs). In this paper, we employ a two-phase gas-liquid microfluidic reactor for the flow-directed manufacturing of paclitaxel-loaded or DiI-loaded DualM PNPs (PAX-PNPs or DiI-PNPs, where DiI is a fluorescent drug surrogate dye). We find that both PAX-PNPs and DiI-PNPs exhibit similar flow-tunable sizes, morphologies, and internal structures to those previously described for empty DualM PNPs. Fluorescent imaging of DiI-PNP formulations shows that microfluidic manufacturing greatly improves the homogeneity of drug dispersion within the PNP population compared to standard bulk microprecipitation. Encapsulation of PAX in DualM PNPs significantly increases its selectivity to cancerous cells, with various PAX-PNP formulations showing higher cytotoxicity against cancerous MCF-7 cells than against non-cancerous HaCaT cells, in contrast to free PAX, which showed similar cytotoxicity in the two cell lines. In addition, the characterization of DualM PNP formulations formed at various microfluidic flow rates reveals that critical figures of merit for drug delivery function-including encapsulation efficiencies, GSH-triggered release rates, rates of cell uptake, cytotoxicities, and selectivity to cancerous cells-exhibit microfluidic flow tunability that mirrors trends in PNP size. These results highlight the potential of two-phase microfluidic manufacturing for controlling both structure and drug delivery function of biological stimuli-responsive nanomedicines toward improved therapeutic outcomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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