Advancements in biomarkers and machine learning for predicting of bronchopulmonary dysplasia and neonatal respiratory distress syndrome in preterm infants DOI Creative Commons

Hanieh Talebi,

Seyed Alireza Dastgheib, Maryam Vafapour

et al.

Frontiers in Pediatrics, Journal Year: 2025, Volume and Issue: 13

Published: April 25, 2025

Recent advancements in biomarker identification and machine learning have significantly enhanced the prediction diagnosis of Bronchopulmonary Dysplasia (BPD) neonatal respiratory distress syndrome (nRDS) preterm infants. Key predictors BPD severity include elevated cytokines like Interleukin-6 (IL-6) Tumor Necrosis Factor-alpha (TNF-α), as well inflammatory markers such Neutrophil-to-Lymphocyte Ratio (NLR) soluble gp130. Research into endoplasmic reticulum stress-related genes, differentially expressed ferroptosis-related genes provides valuable insights BPD's pathophysiology. Machine models XGBoost Random Forest identified important biomarkers, including CYYR1, GALNT14, OLAH, improving diagnostic accuracy. Additionally, a five-gene transcriptomic signature shows promise for early at-risk neonates, underscoring significance immune response factors BPD. For nRDS, biomarkers lecithin/sphingomyelin (L/S) ratio oxidative stress indicators been effectively used innovative methods, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) high-content screening ABCA3 modulation. algorithms Partial Least Squares Regression (PLSR) C5.0 shown potential accurately identifying critical health indicators. Furthermore, advanced feature extraction methods analyzing cry signals offer non-invasive means to differentiate between conditions sepsis nRDS. Overall, these findings emphasize importance combining analysis with computational techniques improve clinical decision-making intervention strategies managing nRDS vulnerable

Language: Английский

Decoding bronchopulmonary dysplasia in premature infants through an epigenetic lens DOI Creative Commons
Seyed Alireza Dastgheib, Reza Bahrami, Mohammad Golshan-Tafti

et al.

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 12

Published: April 3, 2025

This review provides a comprehensive overview of the evolving insights into epigenetic mechanisms associated with bronchopulmonary dysplasia (BPD). It specifically highlights roles DNA methylation, histone modifications, and RNA regulation in development BPD premature infants. results from complex interactions among genetic factors, environmental exposures, neonatal stressors. Key findings suggest that intrauterine hypoxia, hyperoxia, nutrition can lead to alterations, affecting gene expression which may serve as biomarkers for early detection. RUNX3 is identified critical transcription factor influencing lung inflammation, while changes methylation dynamics cord blood are linked immune dysregulation BPD. The role m6A regulators IGF2BP family affects mRNA stability relevant Additionally, specific histones microRNAs, particularly miR-17∼92 cluster, implicated pulmonary vascular regulation. Long non-coding RNAs (lncRNAs), such MALAT1, also play via competitive endogenous networks, indicating their potential therapeutic targets. interplay these underscores need further research develop targeted interventions aimed at reducing severity enhancing health outcomes at-risk neonates.

Language: Английский

Citations

0
Advancements in biomarkers and machine learning for predicting of bronchopulmonary dysplasia and neonatal respiratory distress syndrome in preterm infants DOI Creative Commons

Hanieh Talebi,

Seyed Alireza Dastgheib, Maryam Vafapour

et al.

Frontiers in Pediatrics, Journal Year: 2025, Volume and Issue: 13

Published: April 25, 2025

Recent advancements in biomarker identification and machine learning have significantly enhanced the prediction diagnosis of Bronchopulmonary Dysplasia (BPD) neonatal respiratory distress syndrome (nRDS) preterm infants. Key predictors BPD severity include elevated cytokines like Interleukin-6 (IL-6) Tumor Necrosis Factor-alpha (TNF-α), as well inflammatory markers such Neutrophil-to-Lymphocyte Ratio (NLR) soluble gp130. Research into endoplasmic reticulum stress-related genes, differentially expressed ferroptosis-related genes provides valuable insights BPD's pathophysiology. Machine models XGBoost Random Forest identified important biomarkers, including CYYR1, GALNT14, OLAH, improving diagnostic accuracy. Additionally, a five-gene transcriptomic signature shows promise for early at-risk neonates, underscoring significance immune response factors BPD. For nRDS, biomarkers lecithin/sphingomyelin (L/S) ratio oxidative stress indicators been effectively used innovative methods, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) high-content screening ABCA3 modulation. algorithms Partial Least Squares Regression (PLSR) C5.0 shown potential accurately identifying critical health indicators. Furthermore, advanced feature extraction methods analyzing cry signals offer non-invasive means to differentiate between conditions sepsis nRDS. Overall, these findings emphasize importance combining analysis with computational techniques improve clinical decision-making intervention strategies managing nRDS vulnerable

Language: Английский

Citations

0