Evidence map›Paper›PMID 39532983›Full record

ArticleScientific reports2024

A statistical mechanics investigation of unfolded protein response across organisms.

Nicole Luchetti, Keith M Smith, Margherita A G Matarrese, Alessandro Loppini, Simonetta Filippi, Letizia Chiodo

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

6 authors.

Nicole LuchettiDepartment of Engineering, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, Rome, 00128, Italy. n.luchetti@unicampus.it.
Keith M SmithComputer and Information Sciences, University of Strathclyde, 26 Richmond Street, Glasgow, G1 1XH, United Kingdom.
Margherita A G MatarreseDepartment of Engineering, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, Rome, 00128, Italy.
Alessandro LoppiniDepartment of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, Rome, 00128, Italy.
Simonetta FilippiDepartment of Engineering, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, Rome, 00128, Italy. s.filippi@unicampus.it.
Letizia ChiodoDepartment of Engineering, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, Rome, 00128, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Living systems rely on coordinated molecular interactions, especially those related to gene expression and protein activity. The Unfolded Protein Response is a crucial mechanism in eukaryotic cells, activated when unfolded proteins exceed a critical threshold. It maintains cell homeostasis by enhancing protein folding, initiating quality control, and activating degradation pathways when damage is irreversible. This response functions as a dynamic signaling network, with proteins as nodes and their interactions as edges. We analyze these protein-protein networks across different organisms to understand their intricate intra-cellular interactions and behaviors. In this work, analyzing twelve organisms, we assess how fundamental measures in network theory can individuate seed proteins and specific pathways across organisms. We employ network robustness to evaluate and compare the strength of the investigated protein-protein interaction networks, and the structural controllability of complex networks to find and compare the sets of driver nodes necessary to control the overall networks. We find that network measures are related to phylogenetics, and advanced network methods can identify main pathways of significance in the complete Unfolded Protein Response mechanism.

Indexed as

Protein Interaction MapsUnfolded Protein ResponseAnimalsHumansPhylogenySignal TransductionComplex networksEndoplasmic reticulum stressNetwork analysisProtein-protein interactions

Identifiers

PMID39532983
PMCPMC11557608

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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.