Refining empiric subgroups of pediatric sepsis using machine-learning techniques on observational data.

Sepsis contributes to 1 of every 5 deaths globally with 3 million per year occurring in children. To improve clinical outcomes in pediatric sepsis, it is critical to avoid "one-size-fits-all" approaches and to employ a precision medicine approach. To advance a precision medicine approach to pediatric sepsis treatments, this review provides a summary of two phenotyping strategies, empiric and machine-learning-based phenotyping based on multifaceted data underlying the complex pediatric sepsis pathobiology.

Early triggers of moderately high-fat diet-induced kidney damage.

Most of the obesity murine models inducing renal injury use calorie-enriched foods, where fat represents 60% of the total caloric supply, however, this strategy doubles the standard proportion of fat ingestion in obese patients. Therefore, it is crucial to study the impact of a high-fat intake on kidney physiology that resembles common obesity in humans to understand the trigger mechanisms of the long-term consequences of overweight and obesity. In this study, we analyzed whether chronic feeding with a moderately high fat diet (MHFD) representing 45% of total calories, may induce kidney function and structural injury compared to C57BL/6 mice fed a control diet.