Evidence map›Paper›PMID 40683937›Full record

ArticleScientific reports2025

Novel model of cardiac hypertrophy with cardiorenal dysfunction.

Amanda de Almeida Silva, Leonardo Jensen, Juliana Romeu Marques, Bruno Nascimento-Carvalho, Leandro Eziquiel de Souza, Maikon Barbosa da Silva, Nathalia Juocys Dias Moreira, Mariana Matera Veras, Dunia Waked, Felipe Lima Souza and 6 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

16 authors.

Amanda de Almeida SilvaExperimental Pathophysiology Program, University of São Paulo Medical School, São Paulo, Brazil. manda.a.silva94@gmail.com.
Leonardo JensenExperimental Hypertension Laboratory, Heart Institute, São Paulo, Brazil.
Juliana Romeu MarquesExperimental Hypertension Laboratory, Heart Institute, São Paulo, Brazil.
Bruno Nascimento-CarvalhoExperimental Hypertension Laboratory, Heart Institute, São Paulo, Brazil.
Leandro Eziquiel de SouzaExperimental Hypertension Laboratory, Heart Institute, São Paulo, Brazil.
Maikon Barbosa da SilvaExperimental Hypertension Laboratory, Heart Institute, São Paulo, Brazil.
Nathalia Juocys Dias MoreiraExperimental Hypertension Laboratory, Heart Institute, São Paulo, Brazil.
Mariana Matera VerasEnvironmental and Experimental Pathology Laboratory, University of São Paulo Medical School, São Paulo, Brazil.
Dunia WakedEnvironmental and Experimental Pathology Laboratory, University of São Paulo Medical School, São Paulo, Brazil.
Felipe Lima SouzaLaboratory of Basic Science in Renal Diseases (LIM-12), Division of Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil.
Mirela Aparecida Rodrigues SantinhoLaboratory of Basic Science in Renal Diseases (LIM-12), Division of Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil.
Guilherme LunardonDepartment of Anatomy, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil.
Elia Garcia CaldiniExperimental Pathophysiology Program, University of São Paulo Medical School, São Paulo, Brazil.
Lúcia da Conceição AndradeLaboratory of Basic Science in Renal Diseases (LIM-12), Division of Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil.
Gabriela Placoná DinizDepartment of Anatomy, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil.
Maria Cláudia IrigoyenExperimental Pathophysiology Program, University of São Paulo Medical School, São Paulo, Brazil.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 312962/2020-7Fundação de Amparo à Pesquisa do Estado de São Paulo 2018/19006-2
6 · The paper itself

Abstract

Cardiovascular diseases (CVDs) are a leading global cause of mortality. Hypertension (HTN) is a primary risk factor for developing and progressing CVDs, like cardiac hypertrophy and renal dysfunction. The use of experimental models to better understand the mechanisms linking HTN, cardiac hypertrophy, and renal dysfunction is essential. We aim to investigate whether cardiac hypertrophy induced by the aortic constriction model (TAC), combined with sodium oxalate (OXA) gavage, can serve as a novel model of cardiac hypertrophy with cardiorenal dysfunction. Four groups of C57BL/6 mice were randomized: SHAM (sham surgery and vehicle gavage), TAC (TAC surgery and vehicle gavage), OXA (sham surgery and OXA gavage), and TAC + OXA (TAC surgery and OXA gavage). In the eighth week, the TAC group exhibited elevated systolic carotid pressure, cardiac hypertrophy, increased end-diastolic volume and LV internal diameter, and renal inflammation, but did not exhibit renal dysfunction. OXA gavage intensely increased autonomic modulation as a whole (SD-PI: SHAM = 5.97 ± 1.31 vs. OXA = 15.55 ± 4.03, p < 0.01), caused an increase in the gene expression of SERCA2, changed the LV relaxation phase and induced renal injury, but did not cause an increase in carotid pressure or cardiac hypertrophy. The combination of TAC with OXA gavage in the TAC + OXA group caused increased carotid pressures, cardiac hypertrophy, pulmonary congestion, loss of baroreflex sensitivity (alpha index: SHAM = 3.64 ± 1.0 vs. TAC + OXA = 0.68 ± 0.13, p < 0.04), increased expression of SERCA2 and induced renal dysfunction. Conclusion: The combination of TAC with OXA gavage generated a novel model of cardiac hypertrophy with cardiorenal dysfunction, with a greater state of cardiac decompensation than when TAC and OXA are used separately, and caused significant renal dysfunction, a situation not observed in the TAC model or the OXA gavage model.

Indexed as

CardiomegalyCardio-Renal SyndromeAnimalsDisease Models, AnimalHypertensionMaleMiceMice, Inbred C57BLOxalatesSarcoplasmic Reticulum Calcium-Transporting ATPasesOxalatesSarcoplasmic Reticulum Calcium-Transporting ATPases

Identifiers

PMID40683937
PMCPMC12276227

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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.