Energy Trade-off and 4 Extreme Human Body Types.

Background: Resource trade-off theory suggests that increased performance on a given trait comes at the cost of decreased performance on other traits.

Methods: Growth data from 1889 subjects (996 girls) were used from the GrowUp1974 Gothenburg study. Energy Trade-Off (ETO) between height and weight for individuals with extreme body types was characterized using a novel ETO-Score (ETOS).

Family Size and the Age at Infancy-Childhood Transition Determine a Child's Compromised Growth in Large Families.

Background: Data on growth of Israeli school children show that children from Jewish ultra-orthodox Haredi and Bedouin Arab families have a higher prevalence of stature below the 3rd percentile. While these populations are usually from lower socioeconomic strata, they also have larger families. This study aimed to evaluate if family structure and the timing of a child's infancy-childhood transition (ICT) are central to variations in stature.

Uncoupling of the Infancy Life History Stage.

Background: The life history of Homo sapiens is unique in having a comparatively short stage of infancy which lasts for 2-3 years. Infancy is characterized by suckling of breast milk, the development of sensorimotor cognition, the acquisition of language, mini-puberty, deciduous dentition, and almost complete skull growth. Infancy ends with the infancy-childhood growth transition (ICT) and separation from the mother.

Personalized approach to childhood obesity: Lessons from gut microbiota and omics studies. Narrative review and insights from the 29th European childhood obesity congress.

The traditional approach to childhood obesity prevention and treatment should fit most patients, but misdiagnosis and treatment failure could be observed in some cases that lie away from average as part of individual variation or misclassification. Here, we reflect on the contributions that high-throughput technologies such as next-generation sequencing, mass spectrometry-based metabolomics and microbiome analysis make towards a personalized medicine approach to childhood obesity. We hypothesize that diagnosing a child as someone with obesity captures only part of the phenotype; and that metabolomics, genomics, transcriptomics and analyses of the gut microbiome, could add precision to the term "obese," providing novel corresponding biomarkers.

Prediction of Adult Height by Machine Learning Technique.

Context: Prediction of AH is frequently undertaken in the clinical setting. The commonly used methods are based on the assessment of skeletal maturation. Predictive algorithms generated by machine learning, which can already automatically drive cars and recognize spoken language, are the keys to unlocking data that can precisely inform the pediatrician for real-time decision making.