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Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models

[Image: see text] Pathological pain subtypes can be classified as either neuropathic pain, caused by a somatosensory nervous system lesion or disease, or nociplastic pain, which develops without evidence of somatosensory system damage. Since there is no gold standard for the diagnosis of pathologica...

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Autores principales: Deulofeu, Meritxell, Peña-Méndez, Eladia M., Vaňhara, Petr, Havel, Josef, Moráň, Lukáš, Pečinka, Lukáš, Bagó-Mas, Anna, Verdú, Enrique, Salvadó, Victoria, Boadas-Vaello, Pere
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9853500/
https://www.ncbi.nlm.nih.gov/pubmed/36584284
http://dx.doi.org/10.1021/acschemneuro.2c00665
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author Deulofeu, Meritxell
Peña-Méndez, Eladia M.
Vaňhara, Petr
Havel, Josef
Moráň, Lukáš
Pečinka, Lukáš
Bagó-Mas, Anna
Verdú, Enrique
Salvadó, Victoria
Boadas-Vaello, Pere
author_facet Deulofeu, Meritxell
Peña-Méndez, Eladia M.
Vaňhara, Petr
Havel, Josef
Moráň, Lukáš
Pečinka, Lukáš
Bagó-Mas, Anna
Verdú, Enrique
Salvadó, Victoria
Boadas-Vaello, Pere
author_sort Deulofeu, Meritxell
collection PubMed
description [Image: see text] Pathological pain subtypes can be classified as either neuropathic pain, caused by a somatosensory nervous system lesion or disease, or nociplastic pain, which develops without evidence of somatosensory system damage. Since there is no gold standard for the diagnosis of pathological pain subtypes, the proper classification of individual patients is currently an unmet challenge for clinicians. While the determination of specific biomarkers for each condition by current biochemical techniques is a complex task, the use of multimolecular techniques, such as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), combined with artificial intelligence allows specific fingerprints for pathological pain-subtypes to be obtained, which may be useful for diagnosis. We analyzed whether the information provided by the mass spectra of serum samples of four experimental models of neuropathic and nociplastic pain combined with their functional pain outcomes could enable pathological pain subtype classification by artificial neural networks. As a result, a simple and innovative clinical decision support method has been developed that combines MALDI-TOF MS serum spectra and pain evaluation with its subsequent data analysis by artificial neural networks and allows the identification and classification of pathological pain subtypes in experimental models with a high level of specificity.
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spelling pubmed-98535002023-01-21 Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models Deulofeu, Meritxell Peña-Méndez, Eladia M. Vaňhara, Petr Havel, Josef Moráň, Lukáš Pečinka, Lukáš Bagó-Mas, Anna Verdú, Enrique Salvadó, Victoria Boadas-Vaello, Pere ACS Chem Neurosci [Image: see text] Pathological pain subtypes can be classified as either neuropathic pain, caused by a somatosensory nervous system lesion or disease, or nociplastic pain, which develops without evidence of somatosensory system damage. Since there is no gold standard for the diagnosis of pathological pain subtypes, the proper classification of individual patients is currently an unmet challenge for clinicians. While the determination of specific biomarkers for each condition by current biochemical techniques is a complex task, the use of multimolecular techniques, such as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), combined with artificial intelligence allows specific fingerprints for pathological pain-subtypes to be obtained, which may be useful for diagnosis. We analyzed whether the information provided by the mass spectra of serum samples of four experimental models of neuropathic and nociplastic pain combined with their functional pain outcomes could enable pathological pain subtype classification by artificial neural networks. As a result, a simple and innovative clinical decision support method has been developed that combines MALDI-TOF MS serum spectra and pain evaluation with its subsequent data analysis by artificial neural networks and allows the identification and classification of pathological pain subtypes in experimental models with a high level of specificity. American Chemical Society 2022-12-30 /pmc/articles/PMC9853500/ /pubmed/36584284 http://dx.doi.org/10.1021/acschemneuro.2c00665 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Deulofeu, Meritxell
Peña-Méndez, Eladia M.
Vaňhara, Petr
Havel, Josef
Moráň, Lukáš
Pečinka, Lukáš
Bagó-Mas, Anna
Verdú, Enrique
Salvadó, Victoria
Boadas-Vaello, Pere
Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models
title Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models
title_full Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models
title_fullStr Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models
title_full_unstemmed Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models
title_short Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models
title_sort artificial neural networks coupled with maldi-tof ms serum fingerprinting to classify and diagnose pathological pain subtypes in preclinical models
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9853500/
https://www.ncbi.nlm.nih.gov/pubmed/36584284
http://dx.doi.org/10.1021/acschemneuro.2c00665
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