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Record W4396610500 · doi:10.11159/nddte24.118

DOX-Couped Polymeric Micelles as a State-of-the-Art Strategy Against Triple Negative Breast Cancer

2024· article· en· W4396610500 on OpenAlexvenueno aff
Berrin Chatzi Memet, Ummugulsum Yildiz, Orhan Burak Eksi, Ömer Aydın

Bibliographic record

VenueProceedings of the World Congress on Recent Advances in Nanotechnology · 2024
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsnot available
Fundersnot available
KeywordsMicelleTriple-negative breast cancerBreast cancerCancerMaterials scienceChemistryCancer researchMedicineOrganic chemistryInternal medicine

Abstract

fetched live from OpenAlex

Triple-negative breast cancer (TNBC), a unique type of breast cancer, is defined by the absence of ER, PR, and HER-2 receptors in the tumor.This particularly aggressive form of breast cancer, TNBC, shows early signs of resistance to chemotherapy [1].One significant challenge with this subtype is its less favorable outlook compared to other types of breast cancer, resulting in lower overall survival rates, frequent relapses, and increased mortality.Current treatments for Triple-Negative Breast Cancer (TNBC) typically include chemotherapy, surgery, and radiation therapy.However, the use of these treatments remains limited due to high systemic toxicity, the development of chemotherapy resistance, tumor heterogeneity, and a high risk of metastasis [2].Therefore, new, and effective treatment approaches should be developed for TNBC.Doxorubicin (DOX) remains the primary chemotherapy agent employed in the traditional treatment of triple-negative breast cancer (TNBC).Nevertheless, its clinical use is suboptimal due to issues such as drug resistance, non-discriminatory distribution, cardiac toxicity, limited solubility and restricted penetration [3].Hence, the development of a drug delivery system that decreases the harmful effects of drug and enhances penetration is essential for the successful treatment of TNBC.With the aim of introducing treatment for TNBC, we have engineered polymeric nanoparticles that are coupled with doxorubicin.In our research, we effectively produced a new negatively charged SPMA/PMMA polymer using RAFT polymerization.Nanoparticles were generated via the nanoprecipitation technique.To create a complex between nanoparticles and DOX, we utilized electrostatic binding.Based on Dynamic Light Scattering (DLS) and ζ-potential assessment, our nanoparticles size increased slightly from 134.3 ± 1 nm to 189.7 ± 10 nm, whereas the charge of the particles were increased from -46.9 mV to -15 mV.Complexes were formed at different weight ratios (1:1, 1:2, 1:5), and the complex with the highest binding efficiency and the smallest size is 1:1 complexation ratio.Upon the formation of a complex between doxorubicin and the nanoparticles (DOX NPs), there was a slight increase in the size of the nanoparticles, growing from 134.3 ± 1 nm to 189.7 ± 10 nm.Simultaneously, the charge of the nanoparticles shifted from -46.9 ±3 mV to -15 ±4 mV.The critical micelle concentration (CMC) was established at 17 μg/mL, and the binding efficiency was assessed at 64.5 ±2 % based on the measurement of free doxorubicin absorbance in the supernatants.While bare NPs did not exhibit significant cytotoxicity, the presence of DOX within the nanocarriers reduced the viability of breast cancer cells, and this effect was observed similarly to free DOX treatment.In line with these results, our biocompatible carrier system, which we designed, successfully delivered DOX to breast cancer cells, and demonstrated its potential as an anti-cancer agent by reducing cell viability.

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 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 score0.468
Threshold uncertainty score0.841

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.256
Teacher spread0.250 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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