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BackgroundAortic enlargement and impaired bioelasticity are of interest in several cardiac and non-cardiac diseases as they can lead to cardiovascular complications. Cardiovascular magnetic resonance (CMR) is increasingly accepted as a noninvasive tool in cardiovascular evaluation. Assessment of aortic anatomy and bioelasticity, namely aortic distensibility and pulse wave velocity (PWV), by CMR is accurate and reproducible and could help to identify anatomical and bioelastic abnormalities of the aorta. However, normal CMR values for healthy children and young adults are lacking.MethodsSeventy-one heart-healthy subjects (age 16.4 ± 7.6 years, range 2.3 - 28.3 years) were examined using a 3.0 Tesla CMR scanner. Aortic cross-sectional areas and aortic distensibility were measured at four positions of the ascending and descending thoracic aorta. PWV was assessed from aortic blood flow velocity measurements in a aortic segment between the ascending aorta and the proximal descending aorta. The Lambda-Mu-Sigma (LMS) method was used to obtain percentile curves for aortic cross-sectional areas, aortic distensibility and PWV according to age.ResultsAortic areas, PWV and aortic distensibility (aortic cross-sectional areas: r = 0.8 to 0.9, p < 0.001; PWV: r = 0.25 to 0.32, p = 0.047 to 0.009; aortic distensibility r = -0.43 to -0.62, p < 0.001) correlated with height, weight, body surface area, and age. There were no significant sex differences.ConclusionsThis study provides percentile curves for cross-sectional areas, distensibility and pulse wave velocity of the thoracic aorta in children and young adolescents between their 3rd and 29th year of life. These data may serve as a reference for the detection of pathological changes of the aorta in cardiovascular disease.

Palbociclib is a CDK4/6 inhibitor that received FDA approval for treatment of hormone receptor positive (HR+) HER2 negative (HER2neg) advanced breast cancer. To better personalize patients treatment it is critical to identify subgroups that would mostly benefit from it. We hypothesize that complex alterations of the Retinoblastoma (Rb) pathway might be implicated in resistance to CDK4/6 inhibitors and aim to investigate whether signatures of Rb loss-of-function would identify breast cancer cell lines resistant to palbociclib. We established a gene expression signature of Rb loss-of-function (RBsig) by identifying genes correlated with E2F1 and E2F2 expression in breast cancers within The Cancer Genome Atlas. We assessed the RBsig prognostic role in the METABRIC and in a comprehensive breast cancer meta-dataset. Finally, we analyzed whether RBsig would discriminate palbociclib-sensitive and -resistant breast cancer cells in a large RNA sequencing-based dataset. The RBsig was associated with RB1 genetic status in all tumors (p <7e-32) and in luminal or basal subtypes (p < 7e-11 and p < 0.002, respectively). The RBsig was prognostic in the METABRIC dataset (discovery: HR = 1.93 [1.5-2.4] p = 1.4e-08; validation: HR = 2.01 [1.6-2.5] p = 1.3e-09). Untreated and endocrine treated patients with estrogen receptor positive breast cancer expressing high RBsig had significantly worse recurrence free survival compared to those with low RBsig (HR = 2.37 [1.8 − 3.2] p = 1.87e−08 and HR = 2.62 [1.9− 3.5] p = 8.6e−11, respectively). The RBsig was able to identify palbociclib resistant and sensitive breast cancer cells (ROC AUC = 0,7778). Signatures of RB loss might be helpful in personalizing treatment of patients with HR+/HER2neg breast cancer. Further validation in patients receiving palbociclib is warranted.

Human activities are altering the fundamental geography of biogeochemicals. Yet we lack an understanding of how the spatial patterns in organismal stoichiometry affect biogeochemical processes and the tools to predict the impacts of global changes on biogeochemical processes. In this contribution we develop stoichiometric distribution models (StDMs), which allow us to map spatial structure in resource elemental composition across a landscape and evaluate spatial responses of consumers. We parameterise StDMs for a consumer-resource (moose-white birch) system and demonstrate that we can develop predictive models of resource stoichiometry across a landscape and that such models could improve our predictions of consumer space use. With results from our study system application, we argue that explicit consideration of the spatial patterns in organismal elemental composition may uncover emergent individual, population, community and ecosystem properties that are not revealed at the local extents routinely used in ecological stoichiometry. We discuss perspectives for further developments and application of StDMs to advance three emerging frameworks for spatial ecosystem ecology in an era of global change; meta-ecosystem theory, macroecological stoichiometry and remotely sensed biogeochemistry. Progress on these emerging frameworks will allow for the integration of ecological stoichiometry and individual space use and fitness.