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Rapid Evaporative Ionization Mass Spectrometry-Based Lipidomics for Identification of Canine Mammary Pathology.
Mangraviti, Domenica; Abbate, Jessica Maria; Iaria, Carmelo; Rigano, Francesca; Mondello, Luigi; Quartuccio, Marco; Marino, Fabio.
Afiliação
  • Mangraviti D; Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, Polo Universitario Papardo, University of Messina, 98166 Messina, Italy.
  • Abbate JM; Department of Veterinary Sciences, Polo Universitario Annunziata, University of Messina, 98168 Messina, Italy.
  • Iaria C; Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, Polo Universitario Papardo, University of Messina, 98166 Messina, Italy.
  • Rigano F; Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, Polo Universitario Papardo, University of Messina, 98166 Messina, Italy.
  • Mondello L; Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, Polo Universitario Papardo, University of Messina, 98166 Messina, Italy.
  • Quartuccio M; Chromaleont s.r.l., c/o, Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, 98168 Messina, Italy.
  • Marino F; Unit of Food Science and Nutrition, Department of Medicine, University Campus Bio-Medico of Rome, 00128 Rome, Italy.
Int J Mol Sci ; 23(18)2022 Sep 12.
Article em En | MEDLINE | ID: mdl-36142485
ABSTRACT
The present work proposes the use of a fast analytical platform for the mass spectrometric (MS) profiling of canine mammary tissues in their native form for the building of a predictive statistical model. The latter could be used as a novel diagnostic tool for the real-time identification of different cellular alterations in order to improve tissue resection during veterinary surgery, as previously validated in human oncology. Specifically, Rapid Evaporative Ionization Mass Spectrometry (REIMS) coupled with surgical electrocautery (intelligent knife-iKnife) was used to collect MS data from histologically processed mammary samples, classified into healthy, hyperplastic/dysplastic, mastitis and tumors. Differences in the lipid composition enabled tissue discrimination with an accuracy greater than 90%. The recognition capability of REIMS was tested on unknown mammary samples, and all of them were correctly identified with a correctness score of 98-100%. Triglyceride identification was increased in healthy mammary tissues, while the abundance of phospholipids was observed in altered tissues, reflecting morpho-functional changes in cell membranes, and oxidized species were also tentatively identified as discriminant features. The obtained lipidomic profiles represented unique fingerprints of the samples, suggesting that the iKnife technique is capable of differentiating mammary tissues following chemical changes in cellular metabolism.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Mama / Lipidômica Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals / Female / Humans Idioma: En Revista: Int J Mol Sci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Mama / Lipidômica Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals / Female / Humans Idioma: En Revista: Int J Mol Sci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Itália