Examination of faecal Bifidobacterium populations in breast- and formula-fed infants during the first 18 months of life.

Bifidobacteria in the infant faecal microbiota have been the focus of much interest, especially during the exclusive milk-feeding period and in relation to the fortification of infant formulae to better mimic breast milk. However, longitudinal studies examining the diversity and dynamics of the Bifidobacterium population of infants are lacking, particularly in relation to the effects of weaning. Using a polyphasic strategy, the Bifidobacterium populations of breast- and formula-fed infants were examined during the first 18 months of life. Bifidobacterium-specific denaturing gradient gel electrophoresis demonstrated that breast-fed infants harboured greater diversity than formula-fed infants and the diversity of the infants' Bifidobacterium populations increased with weaning. Twenty-seven distinctive banding profiles were observed from ∼1100 infant isolates using ribosomal intergenic spacer analysis, 14 biotypes of which were confirmed to be members of the genus Bifidobacterium. Two profiles (H, Bifidobacterium longum subsp. infantis; and I, Bifidobacterium bifidum) were common culturable biotypes, seen in 9/10 infants, while profile E (Bifidobacterium breve) was common among breast-fed infants. Overall, inter- and intra-individual differences were observed in the Bifidobacterium populations of infants between 1 and 18 months of age, although weaning was associated with increased diversity of the infant Bifidobacterium populations. Breast-fed infants generally harboured a more complex Bifidobacterium microbiota than formula-fed infants.

A unified titration formula

In a number of standard titrations, a volume of a monoprotic base MOH at a specific concentration is added to a volume of a monoprotic acid HA at a specific concentrations. Four different types of titration are possible, depending on whether the acid and base are strong or weak. A single unifying formula covering all four cases has been determined.

Measuring departures from Hardy-Weinberg: a Markov chain Monte Carlo method for estimating the inbreeding coefficient

Many well-established statistical methods in genetics were developed in a climate of severe constraints on computational power. Recent advances in simulation methodology now bring modern, flexible statistical methods within the reach of scientists having access to a desktop workstation. We illustrate the potential advantages now available by considering the problem of assessing departures from Hardy-Weinberg (HW) equilibrium. Several hypothesis tests of HW have been established, as well as a variety of point estimation methods for the parameter which measures departures from HW under the inbreeding model. We propose a computational, Bayesian method for assessing departures from HW, which has a number of important advantages over existing approaches. The method incorporates the effects-of uncertainty about the nuisance parameters--the allele frequencies--as well as the boundary constraints on f (which are functions of the nuisance parameters). Results are naturally presented visually, exploiting the graphics capabilities of modern computer environments to allow straightforward interpretation. Perhaps most importantly, the method is founded on a flexible, likelihood-based modelling framework, which can incorporate the inbreeding model if appropriate, but also allows the assumptions of the model to he investigated and, if necessary, relaxed. Under appropriate conditions, information can be shared across loci and, possibly, across populations, leading to more precise estimation. The advantages of the method are illustrated by application both to simulated data and to data analysed by alternative methods in the recent literature.

Principal-agent issues in asset acquisition: UK institutions and their investment agents

This paper explores principal‐agent issues in the stock selection processes of institutional property investors. Drawing upon an interview survey of fund managers and acquisition professionals, it focuses on the relationships between principals and external agents as they engage in property transactions. The research investigated the extent to which the presence of outcome‐based remuneration structures could lead to biased advice, overbidding and/or poor asset selection. It is concluded that institutional property buyers are aware of incentives for opportunistic behaviour by external agents, often have sufficient expertise to robustly evaluate agents’ advice and that these incentives are counter‐balanced by a number of important controls on potential opportunistic behaviour. There are strong counter‐incentives in the need for the agents to establish personal relationships and trust between themselves and institutional buyers, to generate repeat and related business and to preserve or generate a good reputation in the market.

Revealing ensemble state transition patterns in multi-electrode neuronal recordings using hidden Markov models

In order to harness the computational capacity of dissociated cultured neuronal networks, it is necessary to understand neuronal dynamics and connectivity on a mesoscopic scale. To this end, this paper uncovers dynamic spatiotemporal patterns emerging from electrically stimulated neuronal cultures using hidden Markov models (HMMs) to characterize multi-channel spike trains as a progression of patterns of underlying states of neuronal activity. However, experimentation aimed at optimal choice of parameters for such models is essential and results are reported in detail. Results derived from ensemble neuronal data revealed highly repeatable patterns of state transitions in the order of milliseconds in response to probing stimuli.