Machine learning combined with infrared spectroscopy for detection of hypertension pregnancy: towards newborn and pregnant blood analysis

  • Sara Maria Santos Dias da Silva
  • , Marcelo Saito Nogueira
  • , Jaqueline Maria Brandão Rizzato
  • , Simone de Lima Silva
  • , Sheila Cavalca Cortelli
  • , Roger Borges
  • , Herculano da Silva Martinho
  • , Rodrigo Augusto Silva
  • , Luis Felipe das Chagas e Silva de Carvalho

Research output: Contribution to journalArticlepeer-review

Abstract

Biochemical changes in the cervix during labor are not well understood. This gap in knowledge is significant, as understanding the precise biochemical processes can provide critical insights into the mechanisms of labor and potentially inform better clinical practices for monitoring and managing pregnancy and childbirth. Fourier-transform infrared (FT-IR) spectroscopy as a non-invasive optical technique, it has the potential sensibility to detect biochemical components. This technology operates by meansuring the vibrational energy of molecular composition and structural changes occurring in the tissue. A total of 30 pregnant participants undergoing either spontaneous or induced labor were recruited. We detected several biochemical changes during labor, including a significant decrease in FT-IR spectral features associated with collagen and other extracellular matrix (ECM) proteins, attributed to collagen dispersion. Specifically, the amide I and amide II bands, which are indicative of protein secondary structure, showed marked reductions. Our results have demonstrated that FT-IR spectroscopy is sensitive to multiple biochemical remodeling changes in the cervix during labor. Traditional methods have limitations, either due to their invasiveness or insufficient sensitivity to detect subtle biochemical alterations, therefore, FT-IR spectroscopy may be a valuable noninvasive tool for objective cervical assessment to potentially guide clinical labor management.

Original languageEnglish
Article number358
JournalBMC Pregnancy and Childbirth
Volume25
Issue number1
DOIs
Publication statusPublished - Dec 2025
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Blood pressure
  • Gestational hypertension
  • Hypertensive pregnancy
  • Machine learning
  • Maternal health
  • Medical technology
  • Plasma Newbornblood analysis
  • Pre-eclampsia
  • Pregnancy hypertension
  • Prenatal diagnosis
  • Principal component analysis

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