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Record W1990769245 · doi:10.3389/fonc.2014.00306

Reduced Intracellular Drug Accumulation in Drug-Resistant Leukemia Cells is Not Only Solely Due to MDR-Mediated Efflux but also to Decreased Uptake

2014· article· en· W1990769245 on OpenAlexafffund
Angela Oliveira Pisco, Dean A. Jackson, Sui Huang

Bibliographic record

VenueFrontiers in Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsUniversity of Calgary
FundersNational Cancer InstituteBiotechnology and Biological Sciences Research CouncilNational Institutes of HealthAlberta InnovatesUniversity of Manchester
KeywordsEffluxDrugPharmacologyIntracellularMultiple drug resistanceDrug resistanceLeukemiaCancer researchMedicineChemistryBiologyInternal medicineBiochemistryGenetics

Abstract

fetched live from OpenAlex

Expression of ABC family transporter proteins that promote drug efflux from cancer cells is a widely observed mechanism of multi-drug resistance of cancer cells. Cell adaptation in long-term culture of HL60 leukemic cells in the presence of chemotherapy leads to induction and maintenance of the ABC transporters expression, preventing further accumulation of drugs. However, we found that decreased accumulation of drugs and fluorescent dyes also contributed by a reduced uptake by the resistant cells. Confocal time-lapse microscopy and flow cytometry revealed that fluid-phase endocytosis was diminished in drug-resistant cells compared to drug-sensitive cells. Drug uptake was increased by insulin co-treatment when cells were grown in methylcellulose and monitored under the microscope, but not when cultured in suspension. We propose that multi-drug resistance is not only solely achieved by enhanced efflux capacity but also by supressed intake of the drug, offering an alternative target to overcome drug resistance or potentiate chemotherapy.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.001

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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), 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

Citations29
Published2014
Admission routes2
Has abstractyes

Explore more

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