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Predicting Preterm Birth Using Proteomics.
Maric, Ivana; Stevenson, David K; Aghaeepour, Nima; Gaudillière, Brice; Wong, Ronald J; Angst, Martin S.
Afiliação
  • Maric I; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 453 Quarry Road, Palo Alto, CA 94304, USA. Electronic address: ivanam@stanford.edu.
  • Stevenson DK; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 453 Quarry Road, Palo Alto, CA 94304, USA.
  • Aghaeepour N; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Grant Building, Office 276A, 300 Pasteur Drive, Stanford, CA 94305-5117, USA; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 300
  • Gaudillière B; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Grant Building, Office 276A, 300 Pasteur Drive, Stanford, CA 94305-5117, USA; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 300
  • Wong RJ; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 453 Quarry Road, Palo Alto, CA 94304, USA.
  • Angst MS; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Grant Building, Office 276A, 300 Pasteur Drive, Stanford, CA 94305-5117, USA.
Clin Perinatol ; 51(2): 391-409, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38705648
ABSTRACT
The complexity of preterm birth (PTB), both spontaneous and medically indicated, and its various etiologies and associated risk factors pose a significant challenge for developing tools to accurately predict risk. This review focuses on the discovery of proteomics signatures that might be useful for predicting spontaneous PTB or preeclampsia, which often results in PTB. We describe methods for proteomics analyses, proteomics biomarker candidates that have so far been identified, obstacles for discovering biomarkers that are sufficiently accurate for clinical use, and the derivation of composite signatures including clinical parameters to increase predictive power.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores / Proteômica / Nascimento Prematuro Limite: Female / Humans / Newborn / Pregnancy Idioma: En Revista: Clin Perinatol Ano de publicação: 2024 Tipo de documento: Article País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores / Proteômica / Nascimento Prematuro Limite: Female / Humans / Newborn / Pregnancy Idioma: En Revista: Clin Perinatol Ano de publicação: 2024 Tipo de documento: Article País de publicação: Estados Unidos