Discriminating fingerprints of chronic neuropathic pain
following spinal cord injury using artificial neural networks
and mass spectrometry analysis of female mice serum

J 2024

Discriminating fingerprints of chronic neuropathic pain following spinal cord injury using artificial neural networks and mass spectrometry analysis of female mice serum

DEULOFEU FIGUERAS, Meritxell; Eladia M PENA-MENDEZ; Petr VAŇHARA; Josef HAVEL; Lukáš MORÁŇ et. al.

Základní údaje

Originální název

Discriminating fingerprints of chronic neuropathic pain following spinal cord injury using artificial neural networks and mass spectrometry analysis of female mice serum

Autoři

DEULOFEU FIGUERAS, Meritxell; Eladia M PENA-MENDEZ; Petr VAŇHARA; Josef HAVEL; Lukáš MORÁŇ; Lukáš PEČINKA; Anna BAGO-MAS; Enrique VERDU; Victoria SALVADO a Pere BOADAS-VAELLO

Vydání

NEUROCHEMISTRY INTERNATIONAL, OXFORD, PERGAMON-ELSEVIER SCIENCE LTD, 2024, 0197-0186

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30103 Neurosciences

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 4.000

Kód RIV

RIV/00216224:14110/24:00137842

Organizační jednotka

Lékařská fakulta

DOI

https://doi.org/10.1016/j.neuint.2024.105890

UT WoS

001346534500001

EID Scopus

2-s2.0-85207293963

Klíčová slova anglicky

Central neuropathic pain; spinal cord injury; mass spectrometry; Artificial intelligence; Artificial neural networks; MALDI-TOF MS; Spectral profiles

Štítky

14110517, 14313010, podil, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 27. 2. 2025 08:40, Mgr. Marie Novosadová Šípková, DiS.

Anotace

V originále

Spinal cord injury (SCI) often leads to central neuropathic pain, a condition associated with significant morbidity and is challenging in terms of the clinical management. Despite extensive efforts, identifying effective biomarkers for neuropathic pain remains elusive. Here we propose a novel approach combining matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with artificial neural networks (ANNs) to discriminate between mass spectral profiles associated with chronic neuropathic pain induced by SCI in female mice. Functional evaluations revealed persistent chronic neuropathic pain following mild SCI as well as minor locomotor disruptions, confirming the value of collecting serum samples. Mass spectra analysis revealed distinct profiles between chronic SCI and sham controls. On applying ANNs, 100% success was achieved in distinguishing between the two groups through the intensities of m/z peaks. Additionally, the ANNs also successfully discriminated between chronic and acute SCI phases. When reflexive pain response data was integrated with mass spectra, there was no improvement in the classification. These findings offer insights into neuropathic pain pathophysiology and underscore the potential of MALDI-TOF MS coupled with ANNs as a diagnostic tool for chronic neuropathic pain, potentially guiding attempts to discover biomarkers and develop treatments.

Návaznosti

MUNI/A/1398/2021, interní kód MU

Název: Zdroje pro tkáňové inženýrství 12 (Akronym: TissueEng 12)

Investor: Masarykova univerzita, Zdroje pro tkáňové inženýrství 12

MUNI/A/1412/2021, interní kód MU

Název: Výzkum geologických, biologických a pokročilých syntetických materiálů metodami analytickými a fyzikálně-chemickými (Akronym: ANFYZCHEM)

Investor: Masarykova univerzita, Výzkum geologických, biologických a pokročilých syntetických materiálů metodami analytickými a fyzikálně-chemickými

MUNI/A/1598/2023, interní kód MU

Název: Zdroje pro tkáňové inženýrství 14

Investor: Masarykova univerzita, Zdroje pro tkáňové inženýrství 14

Citovat

DEULOFEU FIGUERAS, Meritxell; Eladia M PENA-MENDEZ; Petr VAŇHARA; Josef HAVEL; Lukáš MORÁŇ; Lukáš PEČINKA; Anna BAGO-MAS; Enrique VERDU; Victoria SALVADO a Pere BOADAS-VAELLO. Discriminating fingerprints of chronic neuropathic pain following spinal cord injury using artificial neural networks and mass spectrometry analysis of female mice serum. NEUROCHEMISTRY INTERNATIONAL. OXFORD: PERGAMON-ELSEVIER SCIENCE LTD, 2024, roč. 181, December 2024, s. 1-13. ISSN 0197-0186. Dostupné z: https://doi.org/10.1016/j.neuint.2024.105890.

@article{2456617,
   author = {Deulofeu Figueras, Meritxell and PenaandMendez, Eladia M and Vaňhara, Petr and HAVEL, Josef and Moráň, Lukáš and Pečinka, Lukáš and BagoandMas, Anna and Verdu, Enrique and Salvado, Victoria and BoadasandVaello, Pere},
   article_location = {OXFORD},
   article_number = {December 2024},
   doi = {https://doi.org/10.1016/j.neuint.2024.105890},
   keywords = {Central neuropathic pain; spinal cord injury; mass spectrometry; Artificial intelligence; Artificial neural networks; MALDI-TOF MS; Spectral profiles},
   language = {eng},
   issn = {0197-0186},
   journal = {NEUROCHEMISTRY INTERNATIONAL},
   title = {Discriminating fingerprints of chronic neuropathic pain following spinal cord injury using artificial neural networks and mass spectrometry analysis of female mice serum},
   url = {https://www.sciencedirect.com/science/article/pii/S0197018624002171?via%3Dihub},
   volume = {181},
   year = {2024}
}

TY  - JOUR
ID  - 2456617
AU  - Deulofeu Figueras, Meritxell - Pena-Mendez, Eladia M - Vaňhara, Petr - HAVEL, Josef - Moráň, Lukáš - Pečinka, Lukáš - Bago-Mas, Anna - Verdu, Enrique - Salvado, Victoria - Boadas-Vaello, Pere
PY  - 2024
TI  - Discriminating fingerprints of chronic neuropathic pain following spinal cord injury using artificial neural networks and mass spectrometry analysis of female mice serum
JF  - NEUROCHEMISTRY INTERNATIONAL
VL  - 181
IS  - December 2024
SP  - 1-13
EP  - 1-13
PB  - PERGAMON-ELSEVIER SCIENCE LTD
SN  - 01970186
KW  - Central neuropathic pain
KW  - spinal cord injury
KW  - mass spectrometry
KW  - Artificial intelligence
KW  - Artificial neural networks
KW  - MALDI-TOF MS
KW  - Spectral profiles
UR  - https://www.sciencedirect.com/science/article/pii/S0197018624002171?via%3Dihub
N2  - Spinal cord injury (SCI) often leads to central neuropathic pain, a condition associated with significant morbidity and is challenging in terms of the clinical management. Despite extensive efforts, identifying effective biomarkers for neuropathic pain remains elusive. Here we propose a novel approach combining matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with artificial neural networks (ANNs) to discriminate between mass spectral profiles associated with chronic neuropathic pain induced by SCI in female mice. Functional evaluations revealed persistent chronic neuropathic pain following mild SCI as well as minor locomotor disruptions, confirming the value of collecting serum samples. Mass spectra analysis revealed distinct profiles between chronic SCI and sham controls. On applying ANNs, 100% success was achieved in distinguishing between the two groups through the intensities of m/z peaks. Additionally, the ANNs also successfully discriminated between chronic and acute SCI phases. When reflexive pain response data was integrated with mass spectra, there was no improvement in the classification. These findings offer insights into neuropathic pain pathophysiology and underscore the potential of MALDI-TOF MS coupled with ANNs as a diagnostic tool for chronic neuropathic pain, potentially guiding attempts to discover biomarkers and develop treatments.
ER  -

DEULOFEU FIGUERAS, Meritxell; Eladia M PENA-MENDEZ; Petr VAŇHARA; Josef HAVEL; Lukáš MORÁŇ; Lukáš PEČINKA; Anna BAGO-MAS; Enrique VERDU; Victoria SALVADO a Pere BOADAS-VAELLO. Discriminating fingerprints of chronic neuropathic pain following spinal cord injury using artificial neural networks and mass spectrometry analysis of female mice serum. \textit{NEUROCHEMISTRY INTERNATIONAL}. OXFORD: PERGAMON-ELSEVIER SCIENCE LTD, 2024, roč.~181, December 2024, s.~1-13. ISSN~0197-0186. Dostupné z: https://doi.org/10.1016/j.neuint.2024.105890.

Přehled o publikaci