First-in-human in-vivo depiction of paraganglioma metabolism by hyperpolarised 13C-magnetic resonance.

Phaeochromocytomas (PCC) and paragangliomas (PGL), cumulatively referred to as PPGLs, are neuroendocrine tumours arising from neural crest-derived cells in the sympathetic and parasympathetic nervous systems. Predicting future tumour behaviour and the likelihood of metastatic disease remains problematic as genotype-phenotype correlations are limited, the disease has variable penetrance and, to date, no reliable molecular, cellular or histological markers have emerged. Tumour metabolism quantification can be considered as a method to delineating tumour aggressiveness by utilising hyperpolarised 13 C-MR (HP-MR). The technique may provide an opportunity to non-invasively characterise disease behaviour. Here, we present the first instance of the analysis of PPGL metabolism via HP-MR in a single case.

Generation of glucocorticoid-producing cells derived from human pluripotent stem cells.

Adrenal insufficiency is a life-threatening condition resulting from the inability to produce adrenal hormones in a dose- and time-dependent manner. Establishing a cell-based therapy would provide a physiologically responsive approach for the treatment of this condition. We report the generation of large numbers of human-induced steroidogenic cells (hiSCs) from human pluripotent stem cells (hPSCs). Directed differentiation of hPSCs into hiSCs recapitulates the initial stages of human adrenal development. Following expression of steroidogenic factor 1, activation of protein kinase A signaling drives a steroidogenic gene expression profile most comparable to human fetal adrenal cells, and leads to dynamic secretion of steroid hormones, in vitro. Moreover, expression of the adrenocorticotrophic hormone (ACTH) receptor/co-receptor (MC2R/MRAP) results in dose-dependent ACTH responsiveness. This protocol recapitulates adrenal insufficiency resulting from loss-of-function mutations in AAAS, which cause the enigmatic triple A syndrome. Our differentiation protocol generates sufficient numbers of hiSCs for cell-based therapy and offers a platform to study disorders causing adrenal insufficiency.

A Digital Health Solution for Child Growth Monitoring at Home: Testing the Accuracy of a Novel "GrowthMonitor" Smartphone Application to Detect Abnormal Height and Body Mass Indices.

Objective: To develop and evaluate a smartphone application that accurately measures height and provides notifications when abnormalities are detected. Patients and Methods: A total of 145 (75 boys) participants with a mean age ± SD of 8.7±4.5 years (range, 1.0-17.0 years), from the Children's Hospital at Barts Health Trust, London, United Kingdom, were enrolled in the study. "GrowthMonitor" (UCL Creatives) iPhone application (GMA) measures height using augmented reality. Using population-based (UK-WHO) references, algorithms calculated height SD score (HSDS), distance from target height (THSDSDEV), and HSDS change over time (ΔHSDS). Pre-established thresholds discriminated normal/abnormal growth. The GMA and a stadiometer (Harpenden; gold standard) measured standing heights of children at routine clinic visits. A subset of parents used GMA to measure their child's height at home. Outcome targets were 95% of GMA measurements within ±0.5 SDS of the stadiometer and the correct identification of abnormal HSDS, THSDSDEV, and ΔHSDS. Results: Bland-Altman plots revealed no appreciable bias in differences between paired study team GMA and stadiometer height measurements, with a mean of the differences of 0.11 cm with 95% limits of agreement of -2.21 to 2.42 cm. There was no evidence of greater bias occurring for either shorter/younger children or taller/older children. The 2 methods of measurements were highly correlated (R=0.999). GrowthMonitor iPhone application measurements performed by parents in clinic and at home were slightly less accurate. The κ coefficient indicated reliable and consistent agreement of flag alerts for HSDS (κ=0.74) and THSDSDEV (κ=0.88) between 83 paired GMA and stadiometer measurements. GrowthMonitor iPhone application yielded a detection rate of 96% and 97% for HSDS-based and THSDSDEV-based red flags, respectively. Forty-two (18 boys) participants had GMA calculated ΔHSDS using an additional height measurement 6-16 months later, and no abnormal flag alerts were triggered for ΔHSDS values. Conclusion: GrowthMonitor iPhone application provides the potential for parents/carers and health care professionals to capture serial height measurements at home and without specialized equipment. Reliable interpretation and flagging of abnormal measurements indicate the potential of this technology to transform childhood growth monitoring.