ArticleScientific reports2019
The influence of spatial and temporal resolutions on the analysis of cell-cell interaction: a systematic study for time-lapse microscopy applications.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 42 citations in OpenAlex.
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- TrackRefiner a tool for refinement of bacillus cell tracking data.NPJ systems biology and applications · 2025Article
- Deriving the A/B Cells Policy as a Robust Multi-Object Cell Pipeline for Time-Lapse Microscopy.International journal of molecular sciences · 2025Article
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- ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells.Cyborg and bionic systems (Washington, D.C.) · 2025Article
- Patch-Based Far-Infrared Radiation (FIR) Therapy Does Not Impact Cell Tracking or Motility of Human Melanoma Cells In Vitro.Current issues in molecular biology · 2024Article
- Assessing personalized responses to anti-PD-1 treatment using patient-derived lung tumor-on-chip.Cell reports. Medicine · 2024Article
- Generative models of morphogenesis in developmental biology.Seminars in cell & developmental biology · 2023Review
- Microsystem Advances through Integration with Artificial Intelligence.Micromachines · 2023Review
- Organ-on-a-chip meets artificial intelligence in drug evaluation.Theranostics · 2023Review
- Liver-on-a-chip: Considerations, advances, and beyond.Biomicrofluidics · 2022Review
- Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response.Scientific reports · 2022Article
- Optimizing Long-Term Live Cell Imaging.Methods in molecular biology (Clifton, N.J.) · 2022Article
- An Overview of Organs-on-Chips Based on Deep Learning.Research (Washington, D.C.) · 2022Review
- Apoptosis mapping in space and time of 3D tumor ecosystems reveals transmissibility of cytotoxic cancer death.PLoS computational biology · 2021Article
- Oncoimmunology Meets Organs-on-Chip.Frontiers in molecular biosciences · 2021Review
- A Camera Sensors-Based System to Study Drug Effects On In Vitro Motility: The Case of PC-3 Prostate Cancer Cells.Sensors (Basel, Switzerland) · 2020Article
- Deciphering Cancer Cell Behavior From Motility and Shape Features: Peer Prediction and Dynamic Selection to Support Cancer Diagnosis and Therapy.Frontiers in oncology · 2020Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cell-cell interactions are an observable manifestation of underlying complex biological processes occurring in response to diversified biochemical stimuli. Recent experiments with microfluidic devices and live cell imaging show that it is possible to characterize cell kinematics via computerized algorithms and unravel the effects of targeted therapies. We study the influence of spatial and temporal resolutions of time-lapse videos on motility and interaction descriptors with computational models that mimic the interaction dynamics among cells. We show that the experimental set-up of time-lapse microscopy has a direct impact on the cell tracking algorithm and on the derived numerical descriptors. We also show that, when comparing kinematic descriptors in two diverse experimental conditions, too low resolutions may alter the descriptors' discriminative power, and so the statistical significance of the difference between the two compared distributions. The conclusions derived from the computational models were experimentally confirmed by a series of video-microscopy acquisitions of co-cultures of unlabelled human cancer and immune cells embedded in 3D collagen gels within microfluidic devices. We argue that the experimental protocol of acquisition should be adapted to the specific kind of analysis involved and to the chosen descriptors in order to derive reliable conclusions and avoid biasing the interpretation of results.
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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.