Molecular Clock on a Neutral Network

The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating the topological structure of a neutral network from empirical measurements of the substitution process.Comment: 10 page

The area around the Orion Nebula observed in the CO (J = 1- 0) transition

An area 1 deg2 around the Orion Nebula has been surveyed with a 2.6 km s-1 wide single-channel receiver. The map shows considerable structure in the east including a bright spot 24' (2.8 pc) from the main CO peak

Suspended Education in California

Analyzes data on risk of school suspension by race/ethnicity, gender, and disability status in nearly five hundred districts; highlights research showing suspensions to be ineffective and harmful; and calls for implementing evidence-based alternatives

Honour based violence and the multi-agency approach in Nottingham: response of local agencies to honour based violence

The focus of the research was to gain an understanding of the current levels of HBV in Nottingham and the nature of the multi-agency response. The main aim of the research was to gain an understanding of practitioners' work with a range of issues relating to honour based violence (HBV)within partnership agencies. The revised Violence Against Women and Girls Strategy Action Plan published by the government in2010 (Home Office, 2010) gave precedence to a co-ordinated approach to ending all forms of violence against women including HBV and forced marriage

CASK regulates CaMKII autophosphorylation in neuronal growth, calcium signaling, and learning

Calcium (Ca2+)/calmodulin (CaM)-dependent kinase II (CaMKII) activity plays a fundamental role in learning and memory. A key feature of CaMKII in memory formation is its ability to be regulated by autophosphorylation, which switches its activity on and off during synaptic plasticity. The synaptic scaffolding protein CASK (calcium (Ca2+)/calmodulin (CaM) associated serine kinase) is also important for learning and memory, as mutations in CASK result in intellectual disability and neurological defects in humans. We show that in Drosophila larvae, CASK interacts with CaMKII to control neuronal growth and calcium signalling. Furthermore, deletion of the CaMK-like and L27 domains of CASK (CASK β null) or expression of overactive CaMKII (T287D) produced similar effects on synaptic growth and Ca2+ signalling. CASK overexpression rescues the effects of CaMKII overactivity, consistent with the notion that CASK and CaMKII act in a common pathway that controls these neuronal processes. The reduction in Ca2+ signalling observed in the CASK β null mutant caused a decrease in vesicle trafficking at synapses. In addition, the decrease in Ca2+ signalling in CASK mutants was associated with an increase in Ether-à-go-go (EAG) potassium (K+) channel localisation to synapses. Reducing EAG restored the decrease in Ca2+ signalling observed in CASK mutants to the level of wildtype, suggesting that CASK regulates Ca2+ signalling via EAG. CASK knockdown reduced both appetitive associative learning and odour evoked Ca2+ responses in Drosophila mushroom bodies, which are the learning centres of Drosophila. Expression of human CASK in Drosophila rescued the effect of CASK deletion on the activity state of CaMKII, suggesting that human CASK may also regulate CaMKII autophosphorylation

Scalable Inference for Markov Processes with Intractable Likelihoods

Bayesian inference for Markov processes has become increasingly relevant in recent years. Problems of this type often have intractable likelihoods and prior knowledge about model rate parameters is often poor. Markov Chain Monte Carlo (MCMC) techniques can lead to exact inference in such models but in practice can suffer performance issues including long burn-in periods and poor mixing. On the other hand approximate Bayesian computation techniques can allow rapid exploration of a large parameter space but yield only approximate posterior distributions. Here we consider the combined use of approximate Bayesian computation (ABC) and MCMC techniques for improved computational efficiency while retaining exact inference on parallel hardware