RT info:eu-repo/semantics/article
T1 Artificial neural networks coupled with MALDI-TOF MS serum fingerprinting to classify and diagnose pathological pain subtypes in preclinical models.
A1 Peña Méndez, Eladia María
A1 Deulofeu, Meritxell
A1 M. Peña-Méndez, Eladia
A1 Vaňhara, Petr
A1 Havel, Josef
A1 Moráň, Lukáš
A1 Pečinka, Lukáš
A1 Bagó-Mas, Anna
A1 Verdú, Enrique
A1 Salvadó, Victoria
A1 Boadas-Vaello, Pere
A2 University of Girona (MPCUdG2016/087)
La MARATÓ de TV3 Foundation (201705.30.31)
Masaryk University (MUNI/11/ACC/3/2022MUNI/A/1398/2021, MUNI/A/1412/2021), Brno, Czech Republic
K1 neuropathic pain
K1 fibromyalgia
K1 mass spectrometry
K1 artificial intelligence
K1 MALDI-TOF MS
K1 diagnostics
AB Pathological pain subtypes can be classified as eitherneuropathic pain, caused by a somatosensory nervous system lesion ordisease, or nociplastic pain, which develops without evidence ofsomatosensory system damage. Since there is no gold standard for thediagnosis of pathological pain subtypes, the proper classification ofindividual patients is currently an unmet challenge for clinicians. Whilethe determination of specific biomarkers for each condition by currentbiochemical techniques is a complex task, the use of multimoleculartechniques, such as matrix-assisted laser desorption/ionization time-offlight mass spectrometry (MALDI-TOF MS), combined with artificialintelligence allows specific fingerprints for pathological pain-subtypes tobe obtained, which may be useful for diagnosis. We analyzed whether theinformation provided by the mass spectra of serum samples of fourexperimental models of neuropathic and nociplastic pain combined withtheir functional pain outcomes could enable pathological pain subtype classification by artificial neural networks. As a result, a simpleand innovative clinical decision support method has been developed that combines MALDI-TOF MS serum spectra and painevaluation with its subsequent data analysis by artificial neural networks and allows the identification and classification ofpathological pain subtypes in experimental models with a high level of specificity.
YR 2023
FD 2023
LK http://riull.ull.es/xmlui/handle/915/35190
UL http://riull.ull.es/xmlui/handle/915/35190
LA en
NO This work was supported by the University of Girona (MPCUdG2016/087) and La MARATÓ de TV3 Foundation (201705.30.31) from Catalonia; and by Masaryk University (MUNI/11/ACC/3/2022, MUNI/A/1398/2021, MUNI/A/1412/2021), Brno, Czech Republic. The authors also thank the staff of the animal care facility of the University of Barcelona (Campus Bellvitge) for their skillful technical assistance. The Mass Spectrometry Core Facility of FNUSA-ICRC is acknowledged for their support and assistance in this wor
DS Repositorio institucional de la Universidad de La Laguna
RD 27-dic-2024