Evidence map›Paper›PMID 31238709›Full record

ArticleBioTechniques2019

High-throughput quantitative detection of basal autophagy and autophagic flux using image cytometry.

Gopika SenthilKumar, Justin H Skiba, Randall J Kimple

Open access · goldAbstract read
In one paragraph

Article in BioTechniques, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

12 citing papers in PubMed, 18 citations in OpenAlex.

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  11. Potential of NovelFrontiers in pharmacology · 2022
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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

3 authors at 1 institution in 1 country.

Gopika SenthilKumarDepartment of Human Oncology & UW Carbone Cancer Center, University of Wisconsin School of Medicine & Public Health, 750 Highland Ave, Madison, WI 53726, USA.
Justin H SkibaDepartment of Human Oncology & UW Carbone Cancer Center, University of Wisconsin School of Medicine & Public Health, 750 Highland Ave, Madison, WI 53726, USA.
Randall J KimpleDepartment of Human Oncology & UW Carbone Cancer Center, University of Wisconsin School of Medicine & Public Health, 750 Highland Ave, Madison, WI 53726, USA.
University of Wisconsin Carbone Cancer Center · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI AMY TRENTHAM-DIETZ · 1985 to 2026
$142.6M
Project 4: Role of Receptor Tyrosine Kinase AXL in HNSCC Therapy ResistanceP50DE026787 · NIDCR · UNIVERSITY OF WISCONSIN-MADISON · PI YU, MENGGANG · 2016 to 2020
$10.8M
NCI NIH HHS P30 CA014520NIDCR NIH HHS P50 DE026787
6 · The paper itself

Abstract

Quantitative assessment of changes in macro-autophagy is often performed through manual quantification of the number of LC3B foci in immunofluorescence microscopy images. This method is highly laborious, subject to image-field selection and foci-counting bias, and is not sensitive for analyzing changes in basal autophagy. Alternative methods such as flow cytometry and transmission electron microscopy require highly specialized, expensive instruments and time-consuming sample preparation. Immunoblots are prone to exposure-related variations and noise that prevents accurate quantification. We report a high-throughput, inexpensive, reliable and objective method for studying basal level and flux changes in late-stage autophagy using image cytometry and acridine orange staining.

Indexed as

AutophagyAcridine OrangeCell LineFluorescent DyesHumansImage CytometryAcridine OrangeFluorescent Dyesacridine orangeautophagyimage cytometer

Identifiers

PMID31238709
PMCPMC7141596
OpenAlexW2954718153

What OpenQuestion holds

Textmetadata
LicenceTDM
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.