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Applied Sciences
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Metabolomic Analysis in Human Diseases: Latest Advances and Prospects
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Metabolomic Analysis in Human Diseases: Latest Advances and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (10 May 2023) | Viewed by 7098

Special Issue Editor

Dr. Jose L. Izquierdo-García

E-Mail Website
Guest Editor
Chemistry in Phamaceutical Sciences, Complutense University of Madrid, 28040 Madrid, Spain
Interests: metabolomics; respiratory diseases; nuclear magnetic resonance; hyperpolarization

Special Issue Information

Dear Colleagues,

This Special Issue on the topic “Metabolomic Analysis in Human Diseases” aims to cover all the latest outstanding developments of metabolomic approaches to study human disorders. It is difficult to go deeper into the understanding of the development of human diseases because there are many factors involved. In practice, the way to approach the study of the biological systems is its segregation in different levels. This has resulted in the emergence of the “omics,” such as genomics, proteomics, transcriptomics, or metabolomics, which are studies focused in the characterization and quantification of one of these fields. In this particular case, the main aim of a metabolomics study is the comprehensive report of metabolites, specifically to determine the concentration changes that suffer a list of metabolites and their interactions across the “metabolic network” under a specific condition. This Special Issue will describe recent research and developments in the field of metabolomics in human health.

The objective of this Special Issue is to present some research underlying new technical approaches to monitor human metabolism such as hyperpolarization, MS metabolic imaging, benchtop devices, but also new software approaches. This issue will also cover metabolomic studies in clinical samples and basic studies with cells and animal models for the characterization of metabolic reprograming induced by the human diseases. The knowledge that has arisen from studies in metabolomics may translate into new treatment targets and a better diagnostic and prognostic tools in daily clinics.

Dr. Jose L. Izquierdo-García
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. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • Metabolomics
  • Nuclear Magnetic Resonance Spectroscopy
  • Mass Spectrometry
  • MALDI Imaging
  • Hyperpolarization
  • Benchtop NMR
  • Bioinformatics
  • Multi-omics
  • Metabolic Flux
  • Fluxomics
  • Precision medicine
  • Profiling
  • Fingerprinting
  • Metabolite target analysis
  • Systems biology

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Published Papers (3 papers)

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Research

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13 pages, 1429 KiB  
Article
Comparison of Algorithms to Compute Relaxation Time Maps in Magnetic Resonance Imaging
by Ignacio Rodriguez, Jose Luis Izquierdo-Garcia, Ehsan Yazdanparast, David Castejón and Jesús Ruiz-Cabello
Appl. Sci. 2023, 13(7), 4083; https://doi.org/10.3390/app13074083 - 23 Mar 2023
Viewed by 1612
Abstract
Magnetic resonance imaging (MRI) is a valuable diagnostic tool that provides detailed information about the structure and function of tissues in the human body. In particular, measuring relaxation times, such as T1 and T2, can provide important insights into the composition and properties [...] Read more.
Magnetic resonance imaging (MRI) is a valuable diagnostic tool that provides detailed information about the structure and function of tissues in the human body. In particular, measuring relaxation times, such as T1 and T2, can provide important insights into the composition and properties of different tissues. Accurate relaxation time mapping is therefore critical for clinical diagnosis and treatment planning, as it can help to identify and characterize pathological conditions, monitor disease progression, and guide interventions. However, the computation of relaxation time maps in MRI is a complex and challenging task that requires sophisticated mathematical algorithms. Thus, there is a need for robust and accurate algorithms that can reliably extract the desired information from MRI data. This article compares the performance of the Reduced Dimension Nonlinear Least Squares (RD-NLS) algorithm versus several widely used algorithms to compute relaxation times in MRI, such as Levenberg-Marquardt and Nelder-Mead. RD-NLS simplifies the search space for the optimum fit by leveraging the partial linear relationship between signal intensity and model parameters. The comparison was performed on several datasets and signal models, resulting in T1 and T2 maps. The algorithms were evaluated based on their fit error, with the RD-NLS algorithm showing a lower error than other fit-ting algorithms. The improvement was particularly notable in T1 maps, with less of a difference in T2 maps. Additionally, the average T1 values computed with different algorithms differed by up to 14 ms, indicating the importance of algorithm selection. These results suggest that the RD-NLS algorithm outperforms other commonly used algorithms for computing relaxation times in MRI. Full article
(This article belongs to the Special Issue Metabolomic Analysis in Human Diseases: Latest Advances and Prospects)
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11 pages, 962 KiB  
Article
Serum MicroRNAs as Biomarkers of Sepsis and Resuscitation
by Lorena Oteiza, Antonio Ferruelo, Nicolás Nín, Mario Arenillas, Marta de Paula, Rachele Pandolfi, Laura Moreno, Raquel Herrero, Paloma González-Rodríguez, Óscar Peñuelas, Francisco Pérez-Vizcaíno and José A. Lorente
Appl. Sci. 2021, 11(23), 11549; https://doi.org/10.3390/app112311549 - 6 Dec 2021
Cited by 2 | Viewed by 2195
Abstract
There is a lack of biomarkers of sepsis and the resuscitation status. Our objective was to prove that the serum expression of certain microribonucleic acids (miRNAs) is differentially regulated in sepsis and is sensitive to different resuscitation regimes. Anesthetized pigs (Sus scrofa [...] Read more.
There is a lack of biomarkers of sepsis and the resuscitation status. Our objective was to prove that the serum expression of certain microribonucleic acids (miRNAs) is differentially regulated in sepsis and is sensitive to different resuscitation regimes. Anesthetized pigs (Sus scrofa domesticus) received no treatment (n = 15) or intravenous live E. coli (n = 24). The septic animals received 0.9% saline at 4 mL/kg/h (n = 8) (low resuscitation group (LoR)) or 10–17 mL/kg/h (high resuscitation group (HiR)) (n = 8 each group). Blood samples were obtained at the end of the experiment for measurement of seven different miRNAs (RT-qPCR, Qiagen, Hilden, Germany). The serum expression of miR-146a-5p and miR-34a-5p increased significantly in the septic group, and miR-146a-5p was significantly lower in the HiR group than in the LoR group. The toll-like receptor signaling pathway involving 22 target proteins was significantly (adjusted p = 3.87 × 10−4) regulated by these two microRNAs (KEGG). Highly significant (p value = 2.22 × 10−16) protein–protein interactions (STRING) were revealed for these 22 hits. MiR-146a-5p and miR-34a-5p were identified as biomarkers of sepsis, and miRNA146a-5p seemed to be a biomarker of the intensity of the resuscitation. Full article
(This article belongs to the Special Issue Metabolomic Analysis in Human Diseases: Latest Advances and Prospects)
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Review

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7 pages, 630 KiB  
Review
Further Advances in Atrial Fibrillation Research: A Metabolomic Perspective
by Laura Arbeloa-Gómez, Jaime Álvarez-Vidal and Jose Luis Izquierdo-García
Appl. Sci. 2022, 12(6), 3201; https://doi.org/10.3390/app12063201 - 21 Mar 2022
Viewed by 2535
Abstract
Atrial fibrillation involves an important type of heart arrhythmia caused by a lack of control in the electrical signals that arrive in the heart, produce an irregular auricular contraction, and induce blood clotting, which finally can lead to stroke. Atrial fibrillation presents some [...] Read more.
Atrial fibrillation involves an important type of heart arrhythmia caused by a lack of control in the electrical signals that arrive in the heart, produce an irregular auricular contraction, and induce blood clotting, which finally can lead to stroke. Atrial fibrillation presents some specific characteristics, but it has been treated and prevented using conventional methods similar to those applied to other cardiovascular diseases. However, due to the influence of this pathology on the mortality caused by cerebrovascular accidents, further studies on the molecular mechanism of atrial fibrillation are required. Our aim here is provide a compressive review of the use of metabolomics on this condition, from the study of the metabolic profile of plasma to the development of animal models. In summary, most of the reported studies highlighted alterations in the energetic pathways related to the development of the condition. Full article
(This article belongs to the Special Issue Metabolomic Analysis in Human Diseases: Latest Advances and Prospects)
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