A human brainstem glioma xenograft model enabled for bioluminescence imaging

Despite the use of radiation and chemotherapy, the prognosis for children with diffuse brainstem gliomas is extremely poor. There is a need for relevant brainstem tumor models that can be used to test new therapeutic agents and delivery systems in pre-clinical studies. We report the development of a brainstem-tumor model in rats and the application of bioluminescence imaging (BLI) for monitoring tumor growth and response to therapy as part of this model. Luciferase-modified human glioblastoma cells from five different tumor cell sources (either cell lines or serially-passaged xenografts) were implanted into the pontine tegmentum of athymic rats using an implantable guide-screw system. Tumor growth was monitored by BLI and tumor volume was calculated by three-dimensional measurements from serial histopathologic sections. To evaluate if this model would allow detection of therapeutic response, rats bearing brainstem U-87 MG or GS2 glioblastoma xenografts were treated with the DNA methylating agent temozolomide (TMZ). For each of the tumor cell sources tested, BLI monitoring revealed progressive tumor growth in all animals, and symptoms caused by tumor burden were evident 26–29 days after implantation of U-87 MG, U-251 MG, GBM6, and GBM14 cells, and 37–47 days after implantation of GS2 cells. Histopathologic analysis revealed tumor growth within the pons in all rats and BLI correlated quantitatively with tumor volume. Variable infiltration was evident among the different tumors, with GS2 tumor cells exhibiting the greatest degree of infiltration. TMZ treatment groups were included for experiments involving U-87 MG and GS2 cells, and in each case TMZ delayed tumor growth, as indicated by BLI monitoring, and significantly extended survival of animal subjects. Our results demonstrate the development of a brainstem tumor model in athymic rats, in which tumor growth and response to therapy can be accurately monitored by BLI. This model is well suited for pre-clinical testing of therapeutics that are being considered for treatment of patients with brainstem tumors

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Contingent values as implicit contracts: estimating minimum legal willingness to pay for conservation of large carnivores in Sweden

Contingent valuation, Willingness-to-pay, Minimum legal WTP, Discrete choice, Carnivores, Q51,

Identifying and searching for conserved RNA localisation signals.

RNA localisation is an important mode of delivering proteins to their site of function. Cis-acting signals within the RNAs, which can be thought of as zip-codes, determine the site of localisation. There are few examples of fully characterised RNA signals, but the signals are thought to be defined through a combination of primary, secondary, and tertiary structures. In this chapter, we describe a selection of computational methods for predicting RNA secondary structure, identifying localisation signals, and searching for similar localisation signals on a genome-wide scale. The chapter is aimed at the biologist rather than presenting the details of each of the individual methods