ArticleBiophysical journal2011
Rapid, massively parallel single-cell drug response measurements via live cell interferometry.
Article in Biophysical journal, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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.
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
34 citing papers in PubMed, 70 citations in OpenAlex.
- Label-free interferometry platform for drug response profiling of bioprinted tumor organoids at single-organoid resolution.Nature protocols · 2026Review
- Determination of Drug Sensitivity in Patient Derived Models of Breast Cancer by Multiparametric QPI.bioRxiv : the preprint server for biology · 2025Article
- Rapid mechanical phenotyping of breast cancer cells based on stochastic intracellular fluctuations.iScience · 2024Article
- Quantitative phase microscopies: accuracy comparison.Light, science & applications · 2024Review
- Superhydrophobicity Effects on Spheroid Formation and Polarization of Macrophages.Pharmaceuticals (Basel, Switzerland) · 2024Article
- LVING reveals the intracellular structure of cell growth.Scientific reports · 2024Article
- Spheroid Formation and Recovery Using Superhydrophobic Coating for Regenerative Purposes.Pharmaceutics · 2023Article
- Drug screening at single-organoid resolution via bioprinting and interferometry.Nature communications · 2023Article
- Fabrication and validation of an LED array microscope for multimodal, quantitative imaging.HardwareX · 2023Article
- Review
- Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer.Communications biology · 2022Article
- Measuring the size and growth of single cells.Biophysics reports · 2022Article
- Article
- Viscoelasticity, Like Forces, Plays a Role in Mechanotransduction.Frontiers in cell and developmental biology · 2022Review
- Rapid, label-free classification of tumor-reactive T cell killing with quantitative phase microscopy and machine learning.Scientific reports · 2021Article
- Computational interference microscopy enabled by deep learning.APL photonics · 2021Article
- Single cell biomass tracking allows identification and isolation of rare targeted therapy-resistant DLBCL cells within a mixed population.The Analyst · 2021Article
- Computationally enhanced quantitative phase microscopy reveals autonomous oscillations in mammalian cell growth.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Cell viscoelasticity is linked to fluctuations in cell biomass distributions.Scientific reports · 2020Article
- Identifying fates of cancer cells exposed to mitotic inhibitors by quantitative phase imaging.The Analyst · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
A central question in cancer therapy is how individual cells within a population of tumor cells respond to drugs designed to arrest their growth. However, the absolute growth of cells, their change in physical mass, whether cancerous or physiologic, is difficult to measure directly with traditional techniques. Here, we develop live cell interferometry for rapid, real-time quantification of cell mass in cells exposed to a changing environment. We used tunicamycin induction of the unfolded protein stress response in multiple myeloma cells to generate a mass response that was temporally profiled for hundreds of cells simultaneously. Within 2 h, the treated cells were growth suppressed compared to controls, with a few cells in both populations showing a robust increase (+15%) or little change (<5%) in mass accumulation. Overall, live cell interferometry provides a conceptual advance for assessing cell populations to identify, monitor, and measure single cell responses, such as to therapeutic drugs.
Indexed as
Identifiers
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.