ArticleProceedings of the National Academy of Sciences of the United States of America2018
Noninvasive detection of macrophage activation with single-cell resolution through machine learning.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.
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Who cites it
70 citing papers in PubMed, 1 synthesis or guideline pooled it, 154 citations in OpenAlex.
- Illuminating Immunity: A Systematic Review of Immune Cell Autofluorescence.Journal of biophotonics · 2025Pooled it
- Cell-Based Immuno-Biosensors Using Microfluidics.Sensors (Basel, Switzerland) · 2026Review
- Integrating spatial and chemical information enhances differentiation of non-alcoholic steatohepatitis states in Raman imaging.Scientific reports · 2025Article
- Decoding Immunodeficiencies with Artificial Intelligence: A New Era of Precision Medicine.Biomedicines · 2025Review
- Deep metabolic profiling of immune cells by spectral flow cytometry-A comprehensive validation approach.iScience · 2025Article
- Noninvasive andThe Analyst · 2025Article
- Characterization of a Single-Capture Bright-Field and Off-Axis Digital Holographic Microscope for Biological Applications.Sensors (Basel, Switzerland) · 2025Article
- Self-Calibrated Stimulated Raman Scattering Spectroscopy for Rapid Cholangiocarcinoma Diagnosis.Analytical chemistry · 2025Article
- Current Trends in In Vitro Diagnostics Using Surface-Enhanced Raman Scattering in Translational Biomedical Research.Biosensors · 2025Review
- Glioblastoma drives protease-independent extracellular matrix invasion of microglia.Materials today. Bio · 2025Article
- Mapping Selenium Nanoparticles Distribution Inside Cells through Confocal Raman Microspectroscopy.ACS applied materials & interfaces · 2025Article
- Towards high-accuracy bacterial taxonomy identification using phenotypic single-cell Raman spectroscopy data.ISME communications · 2025Article
- Unveiling the Molecular Secrets: A Comprehensive Review of Raman Spectroscopy in Biological Research.ACS omega · 2024Review
- mJournal of dental research · 2024Article
- Monitoring lipopolysaccharide-induced macrophage polarization by surface-enhanced Raman scattering.Mikrochimica acta · 2024Article
- Raman spectroscopic deep learning with signal aggregated representations for enhanced cell phenotype and signature identification.PNAS nexus · 2024Article
- Modulating and Imaging Macrophage Reprogramming for Cancer Immunotherapy.Phenomics (Cham, Switzerland) · 2024Review
- Non-invasive detection of regulatory T cells with Raman spectroscopy.Scientific reports · 2024Article
- Raman micro-spectroscopy as a tool to study immunometabolism.Biochemical Society transactions · 2024Review
- Deep learning classification for macrophage subtypes through cell migratory pattern analysis.Frontiers in cell and developmental biology · 2024Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a method enabling the noninvasive study of minute cellular changes in response to stimuli, based on the acquisition of multiple parameters through label-free microscopy. The retrieved parameters are related to different attributes of the cell. Morphological variables are extracted from quantitative phase microscopy and autofluorescence images, while molecular indicators are retrieved via Raman spectroscopy. We show that these independent parameters can be used to build a multivariate statistical model based on logistic regression, which we apply to the detection at the single-cell level of macrophage activation induced by lipopolysaccharide (LPS) exposure and compare their respective performance in assessing the individual cellular state. The models generated from either morphology or Raman can reliably and independently detect the activation state of macrophage cells, which is validated by comparison with their cytokine secretion and intracellular expression of molecules related to the immune response. The independent models agree on the degree of activation, showing that the features provide insight into the cellular response heterogeneity. We found that morphological indicators are linked to the phenotype, which is mostly related to downstream effects, making the results obtained with these variables dose-dependent. On the other hand, Raman indicators are representative of upstream intracellular molecular changes related to specific activation pathways. By partially inhibiting the LPS-induced activation using progesterone, we could identify several subpopulations, showing the ability of our approach to identify the effect of LPS activation, specific inhibition of LPS, and also the effect of progesterone alone on macrophage cells.
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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.