ArticleAutophagy reports2025
Image-based temporal profiling of autophagy-related phenotypes.
Article in Autophagy reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The role of autophagy in ocular health: mechanisms, pathologies, and therapeutic strategies.Biology direct · 2026Pooled it
- Image-based morphological profiling of autophagy phenotypes in Zika virus infected cells.bioRxiv : the preprint server for biology · 2025Article
- Let's talk about flux: the rising potential of autophagy rate measurements in disease.Autophagy · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Autophagy is a dynamic process critical in maintaining cellular homoeostasis. Dysregulation of autophagy is linked to many diseases and is emerging as a promising therapeutic target. High-throughput methods to characterise autophagy are essential for accelerating drug discovery and characterising mechanisms of action. In this study, we developed a scalable image-based temporal profiling approach to characterise ~900 morphological features at a single cell level with high temporal resolution. We differentiated drug treatments based on morphological profiles using a random forest classifier with ~90% accuracy and identified the key features that govern classification. Additionally, temporal morphological profiles accurately predicted biologically relevant changes in autophagy after perturbation, such as total cargo degraded. Therefore, this study acts as proof-of-principle for using image-based temporal profiling to differentiate autophagy perturbations in a high-throughput manner and has the potential identify biologically relevant autophagy phenotypes. Ultimately, approaches like image-based temporal profiling can accelerate drug discovery.
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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.