Article in Molecular & cellular proteomics : MCP, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 32% 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
5 citing papers in PubMed, 32 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
7 authors at 3 institutions in 1 country.
Samuel W EntwisleMolecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington; Department of Genome Sciences, University of Washington, Seattle, Washington.
Camila Martinez CalejmanUniversity of Massachusetts, Worcester, Massachusetts.
Anthony S ValenteDepartment of Genome Sciences, University of Washington, Seattle, Washington.
Robert T LawrenceMolecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington; Department of Genome Sciences, University of Washington, Seattle, Washington.
Chien-Min HungUniversity of Massachusetts, Worcester, Massachusetts.
David A GuertinUniversity of Massachusetts, Worcester, Massachusetts. Electronic address: David.Guertin@umassmed.edu.
Judit VillénMolecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington; Department of Genome Sciences, University of Washington, Seattle, Washington. Electronic address: jvillen@uw.edu.
University of Washington · USUniversity of Massachusetts Chan Medical School · USUMass Memorial Health Care · US
Funding
SPECIFICITY OF OXYGEN DNA DAMAGE AND MUTAGENESISP01AG001751 · NIA · UNIVERSITY OF WASHINGTON · PI RABINOVITCH, PETER S · 1985 to 2021
$29.6M
University of Washington Nathan Shock Center of Excellence in the Basic Biology of AgingP30AG013280 · NIA · UNIVERSITY OF WASHINGTON · PI Su-In Lee · 1995 to 2026
$27.1M
INTERDISCIPLINARY TRAINING IN GENOMIC SCIENCEST32HG000035 · NHGRI · UNIVERSITY OF WASHINGTON · PI Bruce Colston Trapnell · 1995 to 2026
$24.2M
Mechanistic Target of Rapamycin Pathways in Metabolism and Energy ExpenditureR01DK094004 · NIDDK · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI GUERTIN, DAVID A · 2013 to 2023
$4.5M
Emergent properties of signaling network degradation that mediate homeostatic failure during agingR01AG056359 · NIA · UNIVERSITY OF WASHINGTON · PI KAEBERLEIN, MATT, VILLEN, JUDIT · 2017 to 2021
$2.9M
Mechanisms of mitochondrial disease suppression in Ndufs4 knockout miceR01NS098329 · NINDS · UNIVERSITY OF WASHINGTON · PI KAEBERLEIN, MATT, VILLEN, JUDIT · 2017 to 2021
$2.4M
Towards a comprehensive roadmap of cellular signaling.R35GM119536 · NIGMS · UNIVERSITY OF WASHINGTON · PI VILLEN, JUDIT · 2016 to 2020
$2.2M
Acetyl-CoA metabolism and nutrient sensing in adipocytesR01DK116005 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI GUERTIN, DAVID A, WELLEN, KATHRYN ELAINE · 2019 to 2022
$2.0M
Elucidating the AKT-dependent and AKT-independent mechanisms of metabolic control by mTORC2R01CA196986 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI GUERTIN, DAVID A · 2015 to 2019
$1.9M
University of Washington PhD Training in Big Data for Genomics and NeuroscienceT32LM012419 · NLM · UNIVERSITY OF WASHINGTON · PI DANIEL, THOMAS L., FAIRHALL, ADRIENNE L · 2016 to 2019
Stimulating brown adipose tissue (BAT) activity represents a promising therapy for overcoming metabolic diseases. mTORC2 is important for regulating BAT metabolism, but its downstream targets have not been fully characterized. In this study, we apply proteomics and phosphoproteomics to investigate the downstream effectors of mTORC2 in brown adipocytes. We compare wild-type controls to isogenic cells with an induced knockout of the mTORC2 subunit RICTOR (
Indexed as
Adipocytes, BrownAnimalsChromatography, LiquidGene Knockout TechniquesGene OntologyGlycolysisInsulinLipogenesisMechanistic Target of Rapamycin Complex 2MiceMitochondriaPhosphorylationProteomeProto-Oncogene Proteins c-aktRapamycin-Insensitive Companion of mTOR ProteinSignal TransductionInsulinMechanistic Target of Rapamycin Complex 2ProteomeProto-Oncogene Proteins c-aktRapamycin-Insensitive Companion of mTOR Proteinrictor protein, mouseadipocytesinsulin signalingmTORPhosphoproteomephosphorylationsignaling circuitssignal transductiontargeted mass spectrometry
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.
Proteome and Phosphoproteome Analysis of Brown Adipocytes Reveals That RICTOR Loss Dampens Global Insulin/AKT Signaling. · full record | OpenQuestion