ArticleImmunology and cell biology2011
Inferring relevant control mechanisms for interleukin-12 signaling in naïve CD4+ T cells.
Article in Immunology and cell biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 25 citations in OpenAlex.
- Transcriptional Analysis of Total CD8Frontiers in immunology · 2022Article
- Dynamic Regulation of JAK-STAT Signaling Through the Prolactin Receptor Predicted by Computational Modeling.Cellular and molecular bioengineering · 2021Article
- Mechanistic modeling quantifies the influence of tumor growth kinetics on the response to anti-angiogenic treatment.PLoS computational biology · 2017Article
- Melanoma exosomes deliver a complex biological payload that upregulates PTPN11 to suppress T lymphocyte function.Pigment cell & melanoma research · 2017Article
- Computational Model Predicts the Effects of Targeting Cellular Metabolism in Pancreatic Cancer.Frontiers in physiology · 2017Article
- Interlocked positive and negative feedback network motifs regulate β-catenin activity in the adherens junction pathway.Molecular biology of the cell · 2015Article
- In silico model-based inference: an emerging approach for inverse problems in engineering better medicines.Current opinion in chemical engineering · 2015Article
- Enhancing the discovery and development of immunotherapies for cancer using quantitative and systems pharmacology: Interleukin-12 as a case study.Journal for immunotherapy of cancer · 2015Review
- Optimal experiment design for model selection in biochemical networks.BMC systems biology · 2014Article
- Target-mediated disposition model describing the dynamics of IL12 and IFNγ after administration of a mifepristone-inducible adenoviral vector for IL-12 expression in mice.The AAPS journal · 2013Article
- A quantitative systems approach to identify paracrine mechanisms that locally suppress immune response to Interleukin-12 in the B16 melanoma model.Integrative biology : quantitative biosciences from nano to macro · 2012Article
- Quantifying crosstalk among interferon-γ, interleukin-12, and tumor necrosis factor signaling pathways within a TH1 cell model.Science signaling · 2012Article
- Understanding immunology via engineering design: the role of mathematical prototyping.Computational and mathematical methods in medicine · 2012Review
- A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12.Molecular cancer · 2010Review
- Timescale analysis of rule-based biochemical reaction networks.Biotechnology progressArticle
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 2 institutions in 1 country.
Funding
Abstract
Interleukin-12 (IL-12) is a key cytokine involved in shaping the cell-mediated immunity to intracellular pathogens. IL-12 initiates a cellular response through the IL-12 signaling pathway, a member of the Janus kinase/signal transducer and activator of transcription (JAK/STAT) family of signaling networks. The JAK/STAT pathway includes several regulatory elements; however, the dynamics of these mechanisms are not fully understood. Therefore, the objective of this study was to infer the relative importance of regulatory mechanisms that modulate the activation of STAT4 in naïve CD4(+) T cells. Dynamic changes in protein expression and activity were measured using flow cytometry and these data were used to calibrate a mathematical model of IL-12 signaling. An empirical Bayesian approach was used to infer the relative strengths of the different regulatory mechanisms in the system. The model predicted that IL-12 receptor expression is regulated by a dynamic, autonomous program that was independent of STAT4 activation. In summary, a mathematical model of the canonical IL-12 signaling pathway used in conjunction with a Bayesian framework provided high-confidence predictions of the system-specific control mechanisms from the available experimental observations.
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.