Evidence map›Paper›PMID 41550924›Full record

ArticleFrontiers in immunology2025

An integrative model of pro- and anti-inflammatory signaling pathways in macrophage differentiation: the role of NF-

David Martínez-Méndez, Ilean Z Aguilar-Elguea, Lilian S Castelán-Pacheco, Luis Armando Jiménez-Alvarez, Alfredo Cruz-Lagunas, Joaquín Zúñiga, Carlos Villarreal, Leonor Huerta

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Special Issue "Alcohol and Inflammation".International journal of molecular sciences · 2026
    Article
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

8 authors.

David Martínez-MéndezInstituto de Investigaciones Biomédicas, Departamento de Inmunología, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Ilean Z Aguilar-ElgueaInstituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Lilian S Castelán-PachecoInstituto de Investigaciones Biomédicas, Departamento de Inmunología, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Luis Armando Jiménez-AlvarezInstituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Secretaría de Salud, Tecnológico de Monterrey, Escuela de Medicina y Ciencias de la Salud, CCM, Mexico City, Mexico.
Alfredo Cruz-LagunasInstituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Secretaría de Salud, Tecnológico de Monterrey, Escuela de Medicina y Ciencias de la Salud, CCM, Mexico City, Mexico.
Joaquín ZúñigaInstituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Secretaría de Salud, Tecnológico de Monterrey, Escuela de Medicina y Ciencias de la Salud, CCM, Mexico City, Mexico.
Carlos VillarrealInstituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Leonor HuertaInstituto de Investigaciones Biomédicas, Departamento de Inmunología, Universidad Nacional Autónoma de México, Mexico City, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Monocytes are essential players of the innate immune response and adapt their functional states in response to different antigenic and cytokine environments. Integrating the complexity of monocyte intracellular signaling into a mathematical model can support the understanding of dynamic transitions that are crucial for immune regulation. Objective: To formulate a comprehensive mathematical model of monocyte activation, differentiation, and metabolic adaptation dynamics in response to a variety of stimulus and cytokine microenvironment. Methodology: The model comprises a 128-node complex regulatory network based on known components of monocyte activation signal pathways. Node interactions are described by continuous fuzzy logic rules, and includes signaling events induced by LPS, activating IgG immune complexes, ssRNA, and the IFN- Results: The model captures the dynamics of the main events rendering stable states corresponding to the M1, M2, M2b and M2c macrophage profiles. Results are compatible with the predominance of glycolysis in the M1 and M2b, and oxidative phosphorylation in the M2a and M2c responses. The model shows the convergence to the activation of the NF- Conclusion: The complex network approach presented here integrates diverse cytokine and antigenic signaling leading to macrophage responses. It supports a mechanism for the IFN-

Indexed as

Cell DifferentiationCyclic AMP Response Element-Binding ProteinMacrophagesNF-kappa BSignal TransductionCytokinesHumansInflammationMonocytesCREB1 protein, humanCyclic AMP Response Element-Binding ProteinCytokinesNF-kappa Banti-inflammatory cytokinesbiological networkCREBIFN-γinflammationLPSmacrophage differentiationmathematical model

Identifiers

PMID41550924
PMCPMC12808404

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.