ArticleScience translational medicine2015
Automated identification of abnormal respiratory ciliary motion in nasal biopsies.
Article in Science translational medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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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.
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.
Who cites it
17 citing papers in PubMed, 47 citations in OpenAlex.
- Systematic review of artificial intelligence and digital-automated tools for screening, diagnosis and characterisation of primary ciliary dyskinesia.ERJ open research · 2026Article
- Quantitative analysis of mucociliary activity by computational high-speed video reflection microscopy.European biophysics journal : EBJ · 2026Article
- Machine Learning Analysis of Cilia-Driven Particle Transport Distinguishes Primary Ciliary Dyskinesia Cilia from Normal Cilia.bioRxiv : the preprint server for biology · 2025Article
- Ciliary Videomicroscopy: A Long Beat from the European Respiratory Society Guidelines to the Recognition as a Confirmatory Test for Primary Ciliary Dyskinesia.Diagnostics (Basel, Switzerland) · 2021Review
- CiliarMove: new software for evaluating ciliary beat frequency helps find novel mutations by a Portuguese multidisciplinary team on primary ciliary dyskinesia.ERJ open research · 2021Article
- The use of biophysical approaches to understand ciliary beating.Biochemical Society transactions · 2020Review
- Phenotyping ciliary dynamics and coordination in response to CFTR-modulators in Cystic Fibrosis respiratory epithelial cells.Nature communications · 2019Article
- Quantifying Ciliary Dynamics during Assembly Reveals Stepwise Waveform Maturation in Airway Cells.American journal of respiratory cell and molecular biology · 2018Article
- Review
- A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks.NeuroImage · 2018Article
- Seeing cilia: imaging modalities for ciliary motion and clinical connections.American journal of physiology. Lung cellular and molecular physiology · 2018Review
- Impaired Ciliogenesis in differentiating human bronchial epithelia exposed to non-Cytotoxic doses of multi-walled carbon Nanotubes.Particle and fibre toxicology · 2017Article
- Assessing the Collective Dynamics of Motile Cilia in Cultures of Human Airway Cells by Multiscale DDM.Biophysical journal · 2017Article
- A new index for characterizing micro-bead motion in a flow induced by ciliary beating: Part I, experimental analysis.PLoS computational biology · 2017Article
- Assessment of ciliary phenotype in primary ciliary dyskinesia by micro-optical coherence tomography.JCI insight · 2017Article
- Primary Ciliary Dyskinesia.Clinics in chest medicine · 2016Review
- The evolving spectrum of ciliopathies and respiratory disease.Current opinion in pediatrics · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Motile cilia lining the nasal and bronchial passages beat synchronously to clear mucus and foreign matter from the respiratory tract. This mucociliary defense mechanism is essential for pulmonary health, because respiratory ciliary motion defects, such as those in patients with primary ciliary dyskinesia (PCD) or congenital heart disease, can cause severe sinopulmonary disease necessitating organ transplant. The visual examination of nasal or bronchial biopsies is critical for the diagnosis of ciliary motion defects, but these analyses are highly subjective and error-prone. Although ciliary beat frequency can be computed, this metric cannot sensitively characterize ciliary motion defects. Furthermore, PCD can present without any ultrastructural defects, limiting the use of other detection methods, such as electron microscopy. Therefore, an unbiased, computational method for analyzing ciliary motion is clinically compelling. We present a computational pipeline using algorithms from computer vision and machine learning to decompose ciliary motion into quantitative elemental components. Using this framework, we constructed digital signatures for ciliary motion recognition and quantified specific properties of the ciliary motion that allowed high-throughput classification of ciliary motion as normal or abnormal. We achieved >90% classification accuracy in two independent data cohorts composed of patients with congenital heart disease, PCD, or heterotaxy, as well as healthy controls. Clinicians without specialized knowledge in machine learning or computer vision can operate this pipeline as a "black box" toolkit to evaluate ciliary motion.
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What OpenQuestion holds
Registered trials
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.