Evidence map›Paper›PMID 38404534›Full record

ArticleBiophysical reports2024

Philament: A filament tracking program to quickly and accurately analyze in vitro motility assays.

Ryan M Bowser, Gerrie P Farman, Carol C Gregorio

Open access · goldAbstract read
In one paragraph

Article in Biophysical reports, 2024. 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
1.2field-weighted citation impact, top 21% 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, 3 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

3 authors at 1 institution in 1 country.

Ryan M BowserDepartment of Cellular and Molecular Medicine and Sarver Molecular Cardiovascular Research Program, The University of Arizona, Tucson, Arizona.
Gerrie P FarmanDepartment of Cellular and Molecular Medicine and Sarver Molecular Cardiovascular Research Program, The University of Arizona, Tucson, Arizona.
Carol C GregorioDepartment of Cellular and Molecular Medicine and Sarver Molecular Cardiovascular Research Program, The University of Arizona, Tucson, Arizona.
University of Arizona · US

Funding

Deciphering the role of Lmod2 in thin filament length regulation and dilated cardiomyopathyR01HL123078 · NHLBI · UNIVERSITY OF ARIZONA · PI Carol C Gregorio, Shashank Shekhar · 2015 to 2026
$5.6M
REGULATION OF THE ACTIN FILAMENT POINTED END DYNAMICS IN HEALTH AND DISEASER01GM120137 · NIGMS · WASHINGTON STATE UNIVERSITY · PI GALKIN, VITOLD, GREGORIO, CAROL C · 2017 to 2024
$4.0M
Deciphering the roles of FXR1 in health and myopathyR01HL164644 · NHLBI · UNIVERSITY OF ARIZONA · PI GREGORIO, CAROL C · 2022 to 2025
$2.5M
NHLBI NIH HHS R01 HL123078NHLBI NIH HHS R01 HL164644NIGMS NIH HHS R01 GM120137
6 · The paper itself

Abstract

In vitro motility (IVM) assays allow for the examination of the basic interaction between cytoskeletal filaments with molecular motors and the influence many physiological factors have on this interaction. Examples of factors that can be studied include changes in ADP and pH that emulate fatigue, altered phosphorylation that can occur with disease, and mutations within myofilament proteins that cause disease. While IVM assays can be analyzed manually, the main limitation is the ability to extract accurate data rapidly from videos collected without individual bias. While programs have been created in the past to enable data extraction, many are now out of date or require the use of proprietary software. Here, we report the generation of a Python-based tracking program, Philament, which automatically extracts data on instantaneous and average velocities, and allows for fully automated analysis of IVM recordings. The data generated are presented in an easily accessible spreadsheet-based, comma-separated values file. Philament also contains a novel method of quantifying the smoothness of filament motion. By fitting curves to standard deviations of velocity and average velocities, the influence of different experimental conditions can be compared relative to one another. This comparison provides a qualitative measure of protein interactions where steeper slopes indicate more unstable interactions and shallower slopes indicate more stable interactions within the myofilament. Overall, Philament's automation of IVM analysis provides easier entry into the field of cardiovascular mechanics and enables users to create a truly high-throughput experimental data analysis.

Identifiers

PMID38404534
PMCPMC10884813
OpenAlexW4391349674

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.