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Record W4206623560 · doi:10.1039/d1ra06488f

Improvement of cytotoxicity and necrosis activity of ganoderic acid a through the development of PMBN-A.Her2-GA as a targeted nano system

2022· article· en· W4206623560 on OpenAlexaff
Puria Motamed Fath, Maedeh Rahimnejad, Shima Moradi‐Kalbolandi, Behzad Hosseinzadeh, Tahereh Jamshidnejad-Tosaramandani

Bibliographic record

VenueRSC Advances · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsCytotoxicityChemistryNanotechnologyIn vitroBiochemistryMaterials science

Abstract

fetched live from OpenAlex

-(MEONP)]), is considered as a promising amphiphilic polymer that could be easily targeted and conjugated to hydrophobic substances with low bioavailability. To target breast cancer cells overexpressing human epidermal receptor 2 (HER2) receptors, anti-HER2 monoclonal antibody (A.Her2) was conjugated to PMBN and afterward loaded with ganoderic acid A (GA-A) as an anti-cancer metabolite. The efficacy of conjugation and loading was reasonably favourable. The rod shape of the polymer with a size of approximately 160 ± 30 nm was confirmed. Our results indicated that PMBN-A.Her2-GA is an anionic nanostructure with an appropriate form and capable of being applied in cancer therapy. Subsequently, cytotoxicity analysis revealed an improved anti-proliferative effect of GA-A.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2022
Admission routes1
Has abstractyes

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