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Record W3006403931 · doi:10.1039/c9dt04576g

<i>In situ</i>one-step synthesis of polymer-functionalized palladium nanoparticles: an efficient anticancer agent against breast cancer

2020· article· en· W3006403931 on OpenAlexaff
Vaikundamoorthy Ramalingam, Harshavardhan Mohan

Bibliographic record

VenueDalton Transactions · 2020
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsNutrasource
Fundersnot available
KeywordsBreast cancerIn situChemistryCancer cellRaman spectroscopyIn vitroFourier transform infrared spectroscopyMaterials scienceCancerNuclear chemistryCancer researchBiochemistryChemical engineeringOrganic chemistryMedicineInternal medicine

Abstract

fetched live from OpenAlex

band modes of PVP. Microscopic analysis showed that the PVP-PdNPs have a narrow size distribution with spherical shapes and a size range between 9 and 15 nm. The SAED and XRD patterns confirmed that the crystalline structure is face-centered cubic in nature, and EDAX mapping confirmed the formulation of PVP on the surface of the PdNPs. Further, in vitro MTT assay analysis showed that the PVP-PdNPs exhibit excellent cytotoxic activity against human breast cancer MCF7 cells in a dose-dependent manner. The PVP-PdNPs generate continuous ROS in the mitochondria; this leads to the damage of the mitochondrial membrane potential and nuclear DNA and induces apoptosis through caspase3/7 enzymatic activity. Together, the PVP-PdNPs are a promising potential anticancer agent against human breast cancer.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.018
GPT teacher head0.245
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2020
Admission routes1
Has abstractyes

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