In vitro studies of the interaction of poly(NIPAm/MAA) nanoparticles with proteins and cells
Bibliographic record
Abstract
The pH- and temperature-responsive poly(N-isopropylacrylamide-co-methacrylic acid) (PNIPAm/MAA) nanoparticles are of potential application in targeted drug delivery. Their responsive properties in the presence of human serum albumin were investigated using dynamic light scattering (DLS), protein assay, and electron spin resonance (ESR) spectroscopy. Their interaction with human monocytes and polymorphonuclear leukocytes (PMNLs) was studied using scanning electron microscopy (SEM) and oxygen consumption method. The nanoparticles exhibited a volume phase transition at 35-40 degrees C in Hanks balanced salt solution (HBSS) and in phosphate buffer solution (PBS) of pH 7.4. The diameter of the nanoparticles decreased slightly in the presence of HSA at 25 degrees C at neutral pH, whereas an increase in the diameter in pH 6 PBS at 40 degrees C was revealed. The amount of albumin adsorbed onto the nanoparticles decreased with increasing temperature. The ESR spectra of spin labeled HSA indicated a more restricted environment in the nanoparticles at elevated temperatures. The stimulation of PMNL oxygen consumption by PNIPAm based nanoparticles, an indication of phagocytosis of the particles, was not observed regardless whether the nanoparticles were incubated in plasma or serum. In contrast, the more hydrophobic polystyrene (PSt) particles induced a significant increase in the rate of oxygen consumption after the incubation. PNIPAm/MAA-grafted-PSt particles behaved similarly to the PNIPAm/MAA nanoparticles, suggesting that surface properties dictate the recognition of colloids by PMNLs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".