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Gene filtering strategies for machine learning guided biomarker discovery using neonatal sepsis RNA-seq data

Machine learning (ML) algorithms are powerful tools that are increasingly being used for sepsis biomarker discovery in RNA-Seq data. RNA-Seq datasets contain multiple sources and types of noise (operator, technical and non-systematic) that may bias ML classification. Normalisation and independent gene filtering approaches described in RNA-Seq workflows account for some of this variability and are typically only targeted at differential expression analysis rather than ML applications.

The ventilatory response to hypoxia is blunted in some preterm infants during the second year of life

Preterm birth and subsequent neonatal ventilatory treatment disrupts development of the hypoxic ventilatory response (HVR). An attenuated HVR has been identified in preterm neonates, however it is unknown whether the attenuation persists into the second year of life.

Identification of distinct functional thymic programming of fetal and pediatric human γδ thymocytes via single-cell analysis

Developmental thymic waves of innate-like and adaptive-like γδ T cells have been described, but the current understanding of γδ T cell development is mainly limited to mouse models.