Evidence map›Paper›PMID 34702318›Full record

ArticlePlant methods2021

Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis.

Arpan Kumar Basak, Mohamadreza Mirzaei, Kazimierz Strzałka, Kenji Yamada

Open access · goldAbstract read
In one paragraph

Article in Plant methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Phenotypic characteristics of the mycelium ofFrontiers in bioengineering and biotechnology · 2024
    Article
  5. A novel co-culture model of human prostate epithelial and stromal cells for androgenic and antiandrogenic screening.Toxicology in vitro : an international journal published in association with BIBRA · 2023
    Article
  6. 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

4 authors at 1 institution in 1 country.

Arpan Kumar BasakFaculty of Biology, Jagiellonian University, Krakow, Poland.
Mohamadreza MirzaeiMalopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
Kazimierz StrzałkaMalopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
Kenji YamadaMalopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland. kenji.yamada@uj.edu.pl.ORCID http://orcid.org/0000-0003-4872-3729
Jagiellonian University · PL

Funding

Fundacja na rzecz Nauki Polskiej TEAM/2017-4/41Narodowe Centrum Badań i Rozwoju WND-POWR 03.02.00-00-I021/16Narodowym Centrum Nauki UMO-2016/23/B/NA1/01847
6 · The paper itself

Abstract

backgroundCellular components are controlled by genetic and physiological factors that define their shape and size. However, quantitively capturing the morphological characteristics and movement of cellular organelles from micrograph images is challenging, because the analysis deals with complexities of images that frequently lead to inaccuracy in the estimation of the features. Here we show a unique quantitative method to overcome biases and inaccuracy of biological samples from confocal micrographs.

resultsWe generated 2D images of cell walls and spindle-shaped cellular organelles, namely ER bodies, with a maximum contrast projection of 3D confocal fluorescent microscope images. The projected images were further processed and segmented by adaptive thresholding of the fluorescent levels in the cell walls. Micrographs are composed of pixels, which have information on position and intensity. From the pixel information we calculated three types of features (spatial, intensity and Haralick) in ER bodies corresponding to segmented cells. The spatial features include basic information on shape, e.g., surface area and perimeter. The intensity features include information on mean, standard deviation and quantile of fluorescence intensities within an ER body. Haralick features describe the texture features, which can be calculated mathematically from the interrelationship between the pixel information. Together these parameters were subjected to multivariate analysis to estimate the morphological diversity. Additionally, we calculated the displacement of the ER bodies using the positional information in time-lapse images. We captured similar morphological diversity and movement within ER body phenotypes in several microscopy experiments performed in different settings and scanned under different objectives. We then described differences in morphology and movement of ER bodies between A. thaliana wild type and mutants deficient in ER body-related genes.

conclusionsThe findings unexpectedly revealed multiple genetic factors that are involved in the shape and size of ER bodies in A. thaliana. This is the first report showing morphological characteristics in addition to the movement of cellular components and it quantitatively summarises plant phenotypic differences even in plants that show similar cellular components. The estimation of morphological diversity was independent of the cell staining method and the objective lens used in the microscopy. Hence, our study enables a robust estimation of plant phenotypes by recognizing small differences in complex cell organelle shapes and their movement, which is beneficial in a comprehensive analysis of the molecular mechanism for cell organelle formation that is independent of technical variations.

Indexed as

Confocal microscopyER-BodyHaralick featureMorphologyQuantitative analysis

Identifiers

PMID34702318
PMCPMC8549183
OpenAlexW3172409678

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.