Article in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 37% of its field
1 · What the graph read from it
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.
2 · The registry
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.
3 · Its place in the literature
Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
9 authors at 4 institutions in 2 countries.
Janine WörthmüllerLaboratory of Experimental and Translational Oncology, Department of Oncology, Microbiology and Immunology (OMI), Faculty of Science and Medicine, University of Fribourg, 1700 Fribourg, Switzerland.ORCID 0000-0003-2487-7029
Simona DislerLaboratory of Experimental and Translational Oncology, Department of Oncology, Microbiology and Immunology (OMI), Faculty of Science and Medicine, University of Fribourg, 1700 Fribourg, Switzerland.
Sylvain PradervandLausanne Genomic Technologies Facility (LGTF), University of Lausanne, 1015 Lausanne, Switzerland.
François RichardLaboratory for Translational Breast Cancer Research, KU Leuven, 3000 Leuven, Belgium.ORCID 0000-0003-4353-3619
Lisa HaerriLaboratory of Experimental and Translational Oncology, Department of Oncology, Microbiology and Immunology (OMI), Faculty of Science and Medicine, University of Fribourg, 1700 Fribourg, Switzerland.
Gustavo A Ruiz BuendíaTranslational Data Science-Facility, AGORA Cancer Research Center, Swiss Institute of Bioinformatics (SIB), Bugnon 25A, 1005 Lausanne, Switzerland.
Nadine FournierTranslational Data Science-Facility, AGORA Cancer Research Center, Swiss Institute of Bioinformatics (SIB), Bugnon 25A, 1005 Lausanne, Switzerland.
Christine DesmedtLaboratory for Translational Breast Cancer Research, KU Leuven, 3000 Leuven, Belgium.
Curzio RüeggLaboratory of Experimental and Translational Oncology, Department of Oncology, Microbiology and Immunology (OMI), Faculty of Science and Medicine, University of Fribourg, 1700 Fribourg, Switzerland.ORCID 0000-0001-9137-7695
University of Fribourg · CHKU Leuven · BESIB Swiss Institute of Bioinformatics · CHUniversity of Lausanne · CH
Funding
No grant is acknowledged in the PubMed record.
6 · The paper itself
Abstract
MAGI1 acts as a tumor suppressor in estrogen receptor-positive (ER
Indexed as
Breast NeoplasmsGuanylate KinasesAdaptor Proteins, Signal TransducingCell Adhesion MoleculesCell Line, TumorDNA DamageFemaleHumansPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktAdaptor Proteins, Signal TransducingCell Adhesion MoleculesGuanylate KinasesMAGI1 protein, humanPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktbreast cancerDNA damageDNA repairHDACMAGI1MAPK signalingPARP1PI3K/AKT signalingsenescence
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.
MAGI1 Prevents Senescence and Promotes the DNA Damage Response in ER · full record | OpenQuestion