MiR-34a Represses Numbl in Murine Neural Progenitor Cells and Antagonizes Neuronal Differentiation

MicroRNA (miRNA) function is required for normal animal development, in particular in differentiation pathways from stem cell and precursor populations. In neurogenesis, it is becoming increasingly appreciated that miRNAs act at many stages to ensure proper progression. In this study we examined the role of miR-34a in neural progenitor cells (NPC) derived from murine embryonic cortex. We found that over-expression of miR-34a in NPC significantly reduced the neuron yield upon in vitro induction of differentiation. MiR-34a has several predicted targets in the Notch pathway, which operates to balance progenitor self-renewal and differentiation during cortical neurogenesis. We tested several Notch pathway players for regulation by miR-34a in undifferentiated NPC, and found that mRNA and protein levels of Numbl, a negative regulator of Notch signaling, as well as two downstream pro-neural genes usually blocked by Notch signaling, NeuroD1 and Mash1, were diminished, while Notch1 and Cbf1 transcripts were enhanced by miR-34a over-expression. Using a luciferase reporter assay, we verified the Numbl 3′-UTR as a direct miR-34a target. Correspondingly, knock-down of endogenous miR-34a resulted in increased Numbl, NeuroD1 and Mash1, and reduced Notch1 transcript levels. Together these results implicate Numbl as a physiologically relevant target of miR-34a in NPC, allowing for enhanced Notch signaling and inhibition of neuronal differentiation. This work extends our understanding of miR-34a-mediated control of cell differentiation from cancer to mammalian nervous system development

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability