Multifunctional Nanoplatform for Targeted Laser-induced Hyperthermia and Microscopy of Breast Cancer Cells using SPION-based Gold and Folic Acid Conjugated Nanodendrimers: An in vitro Assay
Bibliographic record
Abstract
The use of nanotechnology seems to be a promising approach for early detection, imaging and therapy of cancer.In this investigation, 9 nm superparamagnetic iron oxide nanoparticles (SPION) were synthesized and functionalized by third generation polyamidoamine (G3-PAMAM) dendrimer.The magnetodendrimer samples were then conjugated by folic acid molecules for targeting and by gold nanoparticles for photothermal hyperthermia purpose.The gold nanoparticles were synthesized using three reducing agents of sodium borohydride, hydrazine sulfate and presynthesized 10-nm AuNPs.The final nanocomposite is named IDAF NC (Iron oxide-Dendrimer-Gold-Folic acid).Two breast cancer cell lines of MDA MB 231 and MCF 7 were used for cytotoxicity, uptake and photothermal assay.The results confirmed that AuNPs prepared by sodium borohydrate and the pre-synthesized 10-nm AuNPs were larger and those prepared by hydrazine sulfate were smaller and uniformly entrapped within dendrimer cavities.The MDA MB 231-IDAF-Hydr combination exhibited the highest viability percentage at 50 µg/mL before laser irradiation and lowest cancer cell viability of 65% (i.e., highest cell apoptosis and crystallization after irradiation).
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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) | 0.000 | 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".