A collection of genetic mouse lines and related tools for inducible and reversible intersectional mis-expression

Thanks to many advances in genetic manipulation, mouse models have become very powerful in their ability to interrogate biological processes. In order to precisely target expression of a gene of interest to particular cell types, intersectional genetic approaches using two promoter/enhancers unique to a cell type are ideal. Within these methodologies, variants that add temporal control of gene expression are the most powerful. We describe the development, validation and application of an intersectional approach that involves three transgenes, requiring the intersection of two promoter/enhancers to target gene expression to precise cell types. Furthermore, the approach uses available lines expressing tTA/rTA to control the timing of gene expression based on whether doxycycline is absent or present, respectively. We also show that the approach can be extended to other animal models, using chicken embryos. We generated three mouse lines targeted at the Tigre (Igs7) locus with TRE-loxP-tdTomato-loxP upstream of three genes (p21, DTA and Ctgf), and combined them with Cre and tTA/rtTA lines that target expression to the cerebellum and limbs. Our tools will facilitate unraveling biological questions in multiple fields and organisms.

Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis

The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians

BACKGROUND AND PURPOSE

ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated.

METHODS

Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome.

RESULTS

In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P < 0.0001). 394 (61.2%) of physicians' estimates about the percentage probability of post-thrombolysis symptomatic intracranial haemorrhage were accurate compared with 583 (90.5%) of SEDAN score estimates (P < 0.0001). 160 (24.8%) of physicians' estimates about post-thrombolysis 3-month percentage probability of mRS 0-2 were accurate compared with 240 (37.3%) DRAGON score estimates (P < 0.0001). 260 (40.4%) of physicians' estimates about the percentage probability of post-thrombolysis mRS 5-6 were accurate compared with 518 (80.4%) DRAGON score estimates (P < 0.0001).

CONCLUSIONS

ASTRAL, DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke.