Novel 5-aryloxypyrimidine SEN1576 as a candidate for the treatment of Alzheimer's disease

Prefibrillar assembly of amyloid-ß (Aß) is a major event underlying the development of neuropathology and dementia in Alzheimer's disease (AD). This study determined the neuroprotective properties of an orally bioavailable Aß synaptotoxicity inhibitor, SEN1576. Binding of SEN1576 to monomeric Aß 1–42 was measured using surface plasmon resonance. Thioflavin-T and MTT assays determined the ability of SEN1576 to block Aß 1–42-induced aggregation and reduction in cell viability, respectively. In vivo long-term potentiation (LTP) determined effects on synaptic toxicity induced by intracerebroventricular (i.c.v.) injection of cell-derived Aß oligomers. An operant behavioural schedule measured effects of oral administration following i.c.v. injection of Aß oligomers in normal rats. SEN1576 bound to monomeric Aß 1–42, protected neuronal cells exposed to Aß 1–42, reduced deficits in in vivo LTP and behaviour. SEN1576 exhibits the necessary features of a drug candidate for further development as a disease modifying treatment for the early stages of AD-like dementia.

Investigating the Potential Impact of Four-dimensional Computed Tomography (4DCT) on Toxicity, Outcomes and Dose Escalation for Radical Lung Cancer Radiotherapy

AIMS: To investigate the potential dosimetric and clinical benefits predicted by using four-dimensional computed tomography (4DCT) compared with 3DCT in the planning of radical radiotherapy for non-small cell lung cancer.

MATERIALS AND METHODS:
Twenty patients were planned using free breathing 4DCT then retrospectively delineated on three-dimensional helical scan sets (3DCT). Beam arrangement and total dose (55 Gy in 20 fractions) were matched for 3D and 4D plans. Plans were compared for differences in planning target volume (PTV) geometrics and normal tissue complication probability (NTCP) for organs at risk using dose volume histograms. Tumour control probability and NTCP were modelled using the Lyman-Kutcher-Burman (LKB) model. This was compared with a predictive clinical algorithm (Maastro), which is based on patient characteristics, including: age, performance status, smoking history, lung function, tumour staging and concomitant chemotherapy, to predict survival and toxicity outcomes. Potential therapeutic gains were investigated by applying isotoxic dose escalation to both plans using constraints for mean lung dose (18 Gy), oesophageal maximum (70 Gy) and spinal cord maximum (48 Gy).

RESULTS:
4DCT based plans had lower PTV volumes, a lower dose to organs at risk and lower predicted NTCP rates on LKB modelling (P < 0.006). The clinical algorithm showed no difference for predicted 2-year survival and dyspnoea rates between the groups, but did predict for lower oesophageal toxicity with 4DCT plans (P = 0.001). There was no correlation between LKB modelling and the clinical algorithm for lung toxicity or survival. Dose escalation was possible in 15/20 cases, with a mean increase in dose by a factor of 1.19 (10.45 Gy) using 4DCT compared with 3DCT plans.

CONCLUSIONS:
4DCT can theoretically improve therapeutic ratio and dose escalation based on dosimetric parameters and mathematical modelling. However, when individual characteristics are incorporated, this gain may be less evident in terms of survival and dyspnoea rates. 4DCT allows potential for isotoxic dose escalation, which may lead to improved local control and better overall survival.

A cluster randomised controlled trial of “Bookstart+”: a book gifting programme

Purpose – The purpose of this paper is to evaluate the effectiveness of a free book gifting programme, called “Bookstart+”, in improving family reading outcomes.

Design/methodology/approach – Bookstart+ consists of a pack of books and reading materials provided to families at their two-year-old child's statutory health visit. The pack is accompanied by a short priming demonstration, delivered by the health visitor, on shared reading. The evaluation took the form of a randomised controlled trial (RCT) with 460 families from the client lists of 115 health visitors.

Findings – The study found evidence of: a positive significant effect on parents’ attitudes to reading and books (Cohen's d=+0.192, p=0.034); no significant effect on parental attitudes to their child reading (d=+0.085, p=0.279); and a negative effect, approaching significance, on public library usage (d=-0.160, p=0.055).

Research limitations/implications – The attrition rate was high, with only 43.9 per cent of the target families completing all of the research. However, this level of attrition did not lead to any significant differences between the control and intervention groups on their pre-test measures.

Practical implications – The study provides recommendations for free book gifting service provision in relation to pack contents and delivery.

Originality/value – This paper contributes to the limited international RCT evidence on free book gifting programmes.

Did children’s perceptions of an after-school social learning program predict change in their behavior?

This research explored the influence of children’s perceptions of a pro-social behavior after-school program on actual change in the children’s behavioral outcomes over the program’s duration. Children’s perceptions of three program processes were collected as well as self-reported pro-social and anti-social behavior before and after the program. Statistical models showed that: Positive perceptions of the program facilitators’ dispositions significantly predicted reductions in anti-social behavior; and positive perceptions with the program activities significantly predicted gains in pro-social behavior. The children’s perceptions of their peers’ behavior in the sessions were not found to a significant predictor of behavioral change. The two significant perceptual indicators predicted a small percentage of the change in the behavioral outcomes. However, as after-school social learning programs have a research history of problematic implementation children’s perceptions should be considered in future program design, evaluation and monitoring.

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality-forecasting models be associated with real-world trends in health-related variables? Does inclusion of health-related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle-related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models.