The effect of caudal block on functional residual capacity and ventilation homogeneity in healthy children

Caudal block results in a motor blockade that can reduce abdominal wall tension. This could interact with the balance between chest wall and lung recoil pressure and tension of the diaphragm, which determines the static resting volume of the lung. On this rationale, we hypothesised that caudal block causes an increase in functional residual capacity and ventilation distribution in anaesthetised children. Fifty-two healthy children (15-30 kg, 3-8 years of age) undergoing elective surgery with general anaesthesia and caudal block were studied and randomly allocated to two groups: caudal block or control. Following induction of anaesthesia, the first measurement was obtained in the supine position (baseline). All children were then turned to the left lateral position and patients in the caudal block group received a caudal block with bupivacaine. No intervention took place in the control group. After 15 nun in the supine position, the second assessment was performed. Functional residual capacity and parameters of ventilation distribution were calculated by a blinded reviewer. Functional residual capacity was similar at baseline in both groups. In the caudal block group, the capacity increased significantly (p < 0.0001) following caudal block, while in the control group, it remained unchanged. In both groups, parameters of ventilation distribution were consistent with the changes in functional residual capacity. Caudal block resulted in a significant increase in functional residual capacity and improvement in ventilation homogeneity in comparison with the control group. This indicates that caudal block might have a beneficial effect on gas exchange in anaesthetised, spontaneously breathing preschool-aged children with healthy lungs.

Trait physiology and crop modelling to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. We explore whether a crop growth and development modelling framework can link phenotype complexity to underlying genetic systems in a way that strengthens molecular breeding strategies. We use gene-to-phenotype simulation studies on sorghum to consider the value to marker-assisted selection of intrinsically stable QTLs that might be generated by physiological dissection of complex traits. The consequences on grain yield of genetic variation in four key adaptive traits – phenology, osmotic adjustment, transpiration efficiency, and staygreen – were simulated for a diverse set of environments by placing the known extent of genetic variation in the context of the physiological determinants framework of a crop growth and development model. It was assumed that the three to five genes associated with each trait, had two alleles per locus acting in an additive manner. The effects on average simulated yield, generated by differing combinations of positive alleles for the traits incorporated, varied with environment type. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages with gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies. We simulated a marker-assisted selection (MAS) breeding strategy based on the analyses of gene effects. When marker scores were allocated based on the contribution of gene effects to yield in a single environment, there was a wide divergence in rate of yield gain over all environments with breeding cycle depending on the environment chosen for the QTL analysis. It was suggested that knowledge resulting from trait physiology and modelling would overcome this dependency by identifying stable QTLs. The improved predictive power would increase the utility of the QTLs in MAS. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate QTLs.