Human Alveolar Epithelial Cell Responses to Core–Shell Superparamagnetic Iron Oxide Nanoparticles (SPIONs)
Bibliographic record
Abstract
Superparamagnetic iron oxide nanoparticles (SPIONs) have been prepared and coated with positively (-NH3(+)) and negatively (-COO(-)) charged shells. These NPs, as well as their "bare" precursor, which actually contain surface hydroxyl groups, have been characterized in vitro, and their influence on a human epithelial cell line has been assessed in terms of cell metabolic activity, cellular membrane lysis, mitochondrial activity, and reactive oxygen species production. Their physicochemical characterizations and protein-nanoparticle interactions have been determined using dynamic light scattering, high-resolution transmission electron microscopy, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) spectrometry, and Coomassie Blue fast staining. Cell-SPION interactions have been determined by PrestoBlue resazurin-based, Trypan Blue dye exclusion-based, and MTS cell proliferation assays as well as by reactive oxygen species determination. The results show that different surface characteristics cause different protein corona and cell responses. Some proteins (e.g., albumin) are adsorbed only on positively charged coatings and others (e.g., fibrinogen) only on negatively charged coating. No cell deaths occur, but cell proliferation is influenced by surface chemistry. Proliferation reduction is dose dependent and highest for bare SPIONs. Negatively charged SPIONs were the most biocompatible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".