ArticleFrontiers in oncology2019
Quantitative Spatial Analysis of Metabolic Heterogeneity Across
Article in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- FLIMExplorer: interactive GUI for object-based visualization and analysis of fluorescence lifetime images.JPhys photonics · 2026Article
- Article
- Functional Assays to Guide Personalized Oncological Treatment of Patients with Soft-Tissue Sarcomas.Cancers · 2025Review
- Bridging the gap between tumor and disease: Innovating cancer and glioma models.The Journal of experimental medicine · 2025Review
- Detection and characterization of colorectal cancer by autofluorescence lifetime imaging on surgical specimens.Scientific reports · 2024Article
- Evaluation of Cellpose segmentation with sequential thresholding for instance segmentation of cytoplasms within autofluorescence images.Computers in biology and medicine · 2024Article
- Insights into metabolic heterogeneity of colorectal cancer gained from fluorescence lifetime imaging.eLife · 2024Article
- Imaging immunometabolismImmunometabolism (Cobham, Surrey) · 2024Article
- Mapping Spatiotemporal Heterogeneity in Tumor Profiles by Integrating High-Throughput Imaging and Omics Analysis.ACS omega · 2023Review
- POSEA: A novel algorithm to evaluate the performance of multi-object instance image segmentation.PloS one · 2023Article
- Integrating a dynamic central metabolism model of cancer cells with a hybrid 3D multiscale model for vascular hepatocellular carcinoma growth.Scientific reports · 2022Article
- Comparing the Secretomes of Chemorefractory and Chemoresistant Ovarian Cancer Cell Populations.Cancers · 2022Review
- Label-free sensing of cells with fluorescence lifetime imaging: The quest for metabolic heterogeneity.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Article
- Review
- The Hallmarks of Cancer as Ecologically Driven Phenotypes.Frontiers in ecology and evolution · 2021Article
- Review
- Targeting Glucose Metabolism to Overcome Resistance to Anticancer Chemotherapy in Breast Cancer.Cancers · 2020Review
- Label-free redox imaging of patient-derived organoids using selective plane illumination microscopy.Biomedical optics express · 2020Article
- Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications.Journal of biomedical optics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Metabolic preferences of tumor cells vary within a single tumor, contributing to tumor heterogeneity, drug resistance, and patient relapse. However, the relationship between tumor treatment response and metabolically distinct tumor cell populations is not well-understood. Here, a quantitative approach was developed to characterize spatial patterns of metabolic heterogeneity in tumor cell populations within
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.