Evidence map›Paper›PMID 29260425›Full record

ArticleJournal of bioenergetics and biomembranes2018

Study of the properties of doxorubicin-resistant cells affected by acute leucosis.

Marina Yu Skorkina, Elena A Shamray, Victoria A Salo, Anatoly S Buchelnikov, Maxim P Evstigneev

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of bioenergetics and biomembranes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 47% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

Marina Yu SkorkinaDepartment of Biology, Belgorod State University, 85 Pobedy str, 308015, Belgorod, Russia. skorkina@bsu.edu.ru.
Elena A ShamrayDepartment of Biology, Belgorod State University, 85 Pobedy str, 308015, Belgorod, Russia.
Victoria A SaloDepartment of Physics, Sevastopol State University, 33 Universitetskaya str, 299053, Sevastopol, Russia.
Anatoly S BuchelnikovTheodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, 41 Sredniy Avenue, 199034, Saint Petersburg, Russia. a.buchelnikov@spbu.ru.
Maxim P EvstigneevDepartment of Physics, Sevastopol State University, 33 Universitetskaya str, 299053, Sevastopol, Russia.
Belgorod National Research University · RUMarine Hydrophysical Institute · RUSevastopol National Technical University · UASt Petersburg University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The stiffness of cell membrane was found to be one of the factors determining resistance of a cell in vitro to antibiotic doxorubicin action. Membranes of surviving cells are negatively charged (-35 - -30 mV) and have high values of stiffness (2.2-5.1 μРа) at the doxorubicin concentrations in the medium of 1-500 μg/ml. If the drug concentration and exposure time are being increased, only cells with 'soft' membrane (0.25-1 μРа) and positive surface potential (15-29 mV) survive. The data obtained have important prognostic value in studying drug resistance of tumour blood cells and can be used as objective markers of efficiency of the antitumor therapy.

Indexed as

Drug Resistance, NeoplasmAcute DiseaseAnimalsAntibiotics, AntineoplasticBiomarkers, PharmacologicalCell MembraneCell SurvivalDoxorubicinHumansLeukemiaMembrane PotentialsPrognosisAntibiotics, AntineoplasticBiomarkers, PharmacologicalDoxorubicinAcute leucosisAtomic force microscopyBiomembraneDoxorubicinMembrane stiffnessSurface potential

Identifiers

PMID29260425
OpenAlexW2779683841

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.