ArticleCancer discovery2015
Mass Cytometry: A High-Throughput Platform to Visualize the Heterogeneity of Acute Myeloid Leukemia.
Article in Cancer discovery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Epigenetic mechanisms of drug resistance in acute myeloid leukemia: advances in small-molecule targeted therapy.Frontiers in pharmacology · 2025Review
- Of Cytometry, Stem Cells and Fountain of Youth.Stem cell reviews and reports · 2017Review
Corrections and comments
- Comment on
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Behbehani and colleagues use mass cytometry to profile the heterogeneity of acute myeloid leukemia (AML ) as compared with normal hematopoiesis. By using this approach and characterizing leukemic stem cells, important differences in response to chemotherapy between AML subsets can potentially be explained and new targeted approaches considered.
Indexed as
Identifiers
26224083What 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.