‘World class universities’ (WCU) are an issue of intense debate among the academic community. To define a WCU supposes that only those universities that fit the ‘quality’ criteria established under benchmarking conditions can be considered as such. The good news is that several dimensions could be used to defined excellence, not only classical academic and research criteria. This paper intends to address conceptual aspects of WCU with regard to relations between university ‘mission’ development and why, how and when an institution is considered a WCU from non‐classical criteria. The main purpose of this paper is to propose new dimensions to rank University Missions. Going beyond teaching and research, the University Third Mission – services to Society – has at least 3 dimensions: a non profit – social – approach; an entrepreneur focus; and an innovative approximation. This paper will consider the various implications that a third mission measurement and benchmark could introduce in the controversial ranking business.

Background: Polymorphic variations in the serotonin transporter gene (5-HTT) moderate the depressogenic effects of tryptophan depletion. After childbirth there is a sharp reduction in brain tryptophan availability, thus polymorphic variations in5-HTTmay play a similar role in the post-partum period.Aims: To study the role of5-HTTpolymorphic variations in mood changes after delivery.Method: One thousand, eight hundred and four depression-free Spanish women were studied post-partum. We evaluated depressive symptoms at 2–3 days, 8 weeks and 32 weeks post-partum. We used diagnostic interview to confirm major depression for all probable cases. Based on two polymorphisms of5-HTT(5-HTTLPR and STin2 VNTR), three genotype combinations were created to reflect different levels of5-HTTexpression.Results: One hundred and seventy-three women (12.7%) experienced major depression during the 32-week post-partum period. Depressive symptoms were associated with the high-expression5-HTTgenotypes in a dose–response fashion at 8 weeks post-partum, but not at 32 weeks.Conclusions: High-expression5-HTTgenotypes may render women more vulnerable to depressive symptoms after childbirth.

Tumor segmentation is one of the key steps in imaging processing. The goals of this study were to assess the inter-observer variability in manual segmentation of neuroblastic tumors and to analyze whether the state-of-the-art deep learning architecture nnU-Net can provide a robust solution to detect and segment tumors on MR images. A retrospective multicenter study of 132 patients with neuroblastic tumors was performed. Dice Similarity Coefficient (DSC) and Area Under the Receiver Operating Characteristic Curve (AUC ROC) were used to compare segmentation sets. Two more metrics were elaborated to understand the direction of the errors: the modified version of False Positive (FPRm) and False Negative (FNR) rates. Two radiologists manually segmented 46 tumors and a comparative study was performed. nnU-Net was trained-tuned with 106 cases divided into five balanced folds to perform cross-validation. The five resulting models were used as an ensemble solution to measure training (n = 106) and validation (n = 26) performance, independently. The time needed by the model to automatically segment 20 cases was compared to the time required for manual segmentation. The median DSC for manual segmentation sets was 0.969 (±0.032 IQR). The median DSC for the automatic tool was 0.965 (±0.018 IQR). The automatic segmentation model achieved a better performance regarding the FPRm. MR images segmentation variability is similar between radiologists and nnU-Net. Time leverage when using the automatic model with posterior visual validation and manual adjustment corresponds to 92.8%.