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Molecular Mechanisms and Signalling Pathways in Cardiovascular Pathophysiology
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Molecular Mechanisms and Signalling Pathways in Cardiovascular Pathophysiology

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: 30 January 2025 | Viewed by 1891

Special Issue Editor

Dr. Ernesto Alejandro Aiello

E-Mail Website
Guest Editor
Centro de Investigaciones Cardiovasculares “Dr. Horacio E. Cingolani”, Facultad de Ciencias Médicas, Universidad Nacional de La Plata—CONICET, La Plata, Buenos Aires 1900, Argentina
Interests: arrhythmia; heart; vascular; signaling; cardiovascular disease; mechanism

Special Issue Information

Dear Colleagues,

As is well known, cardiovascular diseases are the leading cause of death worldwide. Understanding the pathophysiological processes that lead to the wide variety of these pathologies is essential to establishing the most appropriate treatments to combat them. In recent years, special interest has been gained in research into the subcellular processes associated with the pathophysiological particularity of each patient, with the aim of steering to more precise therapeutic strategies. This is why basic research into the cardiovascular pathophysiological intracellular signaling pathways and the molecular mechanisms involved in them is of crucial importance. Thus, this Special Issue welcomes articles that present new evidence that strengthens the knowledge of these pathophysiological mechanisms of the cardiovascular system, including cardiac and vascular excitation–contraction coupling dysfunction, endothelial damage, hypertension, heart failure, maladaptive hypertrophy, diabetic heart, and altered bioenergetics, among other mechanisms. In summary, this Special Issue aims to focus on both basic science and translational research to gain a better understanding of the pathophysiological mechanisms leading to cardiovascular diseases.

Dr. Ernesto Alejandro Aiello
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • heart
  • vascular
  • signaling
  • cardiovascular disease
  • mechanism

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Published Papers (2 papers)

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Research

14 pages, 1672 KiB  
Article
Metabolomics-Based Machine Learning for Predicting Mortality: Unveiling Multisystem Impacts on Health
by Anniina Oravilahti, Jagadish Vangipurapu, Markku Laakso and Lilian Fernandes Silva
Int. J. Mol. Sci. 2024, 25(21), 11636; https://doi.org/10.3390/ijms252111636 - 30 Oct 2024
Viewed by 609
Abstract
Reliable predictors of long-term all-cause mortality are needed for middle-aged and older populations. Previous metabolomics mortality studies have limitations: a low number of participants and metabolites measured, measurements mainly using nuclear magnetic spectroscopy, and the use only of conventional statistical methods. To overcome [...] Read more.
Reliable predictors of long-term all-cause mortality are needed for middle-aged and older populations. Previous metabolomics mortality studies have limitations: a low number of participants and metabolites measured, measurements mainly using nuclear magnetic spectroscopy, and the use only of conventional statistical methods. To overcome these challenges, we applied liquid chromatography–tandem mass spectrometry and measured >1000 metabolites in the METSIM study including 10,197 men. We applied the machine learning approach together with conventional statistical methods to identify metabolites associated with all-cause mortality. The three independent machine learning methods (logistic regression, XGBoost, and Welch’s t-test) identified 32 metabolites having the most impactful associations with all-cause mortality (25 increasing and 7 decreasing the risk). From these metabolites, 20 were novel and encompassed various metabolic pathways, impacting the cardiovascular, renal, respiratory, endocrine, and central nervous systems. In the Cox regression analyses (hazard ratios and their 95% confidence intervals), clinical and laboratory risk factors increased the risk of all-cause mortality by 1.76 (1.60–1.94), the 25 metabolites by 1.89 (1.68–2.12), and clinical and laboratory risk factors combined with the 25 metabolites by 2.00 (1.81–2.22). In our study, the main causes of death were cancers (28%) and cardiovascular diseases (25%). We did not identify any metabolites associated with cancer but found 13 metabolites associated with an increased risk of cardiovascular diseases. Our study reports several novel metabolites associated with an increased risk of mortality and shows that these 25 metabolites improved the prediction of all-cause mortality beyond and above clinical and laboratory measurements. Full article
(This article belongs to the Special Issue Molecular Mechanisms and Signalling Pathways in Cardiovascular Pathophysiology)
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13 pages, 5343 KiB  
Article
Activation of G Protein-Coupled Estrogen Receptor (GPER) Negatively Modulates Cardiac Excitation–Contraction Coupling (ECC) through the PI3K/NOS/NO Pathway
by Leandro A. Diaz-Zegarra, María S. Espejo, Alejandro M. Ibañez, Mónica E. Rando, Lucia E. Pagola, Verónica C. De Giusti and Ernesto A. Aiello
Int. J. Mol. Sci. 2024, 25(16), 8993; https://doi.org/10.3390/ijms25168993 - 19 Aug 2024
Viewed by 957
Abstract
The G-protein-coupled estrogen receptor (GPER) has been described to exert several cardioprotective effects. However, the exact mechanism involved in cardiac protection remains unclear. The aim of this study is to investigate the role of GPER activation on excitation–contraction coupling (ECC) and the possibility [...] Read more.
The G-protein-coupled estrogen receptor (GPER) has been described to exert several cardioprotective effects. However, the exact mechanism involved in cardiac protection remains unclear. The aim of this study is to investigate the role of GPER activation on excitation–contraction coupling (ECC) and the possibility that such effect participates in cardioprotection. The cardiac myocytes of male Wistar rats were isolated with a digestive buffer and loaded with Fura-2-AM for the measurement of intracellular calcium transient (CaT). Sarcomere shortening (SS) and L-type calcium current (ICaL) were also registered. The confocal technique was used to measure nitric oxide (NO) production in cells loaded with DAF-FM-diacetate. Cardiac myocytes exposed to 17-β-estradiol (E2, 10 nM) or G-1 (1 μM) for fifteen minutes decreased CaT, SS, and ICaL. These effects were prevented using G-36 (antagonist of GPER, 1 μM), L-Name (NO synthase -NOS- inhibitor, 100 nM), or wortmannin (phosphoinositide-3-kinase -PI3K- inhibitor, 100 nM). Moreover, G1 increased NO production, and this effect was abolished in the presence of wortmannin. We concluded that the selective activation of GPER with E2 or G1 in the isolated cardiac myocytes of male rats induced a negative inotropic effect due to the reduction in ICaL and the decrease in CaT. Finally, the pathway that we proposed to be implicated in these effects is PI3K-NOS-NO. Full article
(This article belongs to the Special Issue Molecular Mechanisms and Signalling Pathways in Cardiovascular Pathophysiology)
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