Maximum Likelihood Estimation in Gaussian Chain Graph Models under the Alternative Markov Property

The AMP Markov property is a recently proposed alternative Markov property for chain graphs. In the case of continuous variables with a joint multivariate Gaussian distribution, it is the AMP rather than the earlier introduced LWF Markov property that is coherent with data-generation by natural block-recursive regressions. In this paper, we show that maximum likelihood estimates in Gaussian AMP chain graph models can be obtained by combining generalized least squares and iterative proportional fitting to an iterative algorithm. In an appendix, we give useful convergence results for iterative partial maximization algorithms that apply in particular to the described algorithm.Comment: 15 pages, article will appear in Scandinavian Journal of Statistic

Discovering a junction tree behind a Markov network by a greedy algorithm

In an earlier paper we introduced a special kind of k-width junction tree, called k-th order t-cherry junction tree in order to approximate a joint probability distribution. The approximation is the best if the Kullback-Leibler divergence between the true joint probability distribution and the approximating one is minimal. Finding the best approximating k-width junction tree is NP-complete if k>2. In our earlier paper we also proved that the best approximating k-width junction tree can be embedded into a k-th order t-cherry junction tree. We introduce a greedy algorithm resulting very good approximations in reasonable computing time. In this paper we prove that if the Markov network underlying fullfills some requirements then our greedy algorithm is able to find the true probability distribution or its best approximation in the family of the k-th order t-cherry tree probability distributions. Our algorithm uses just the k-th order marginal probability distributions as input. We compare the results of the greedy algorithm proposed in this paper with the greedy algorithm proposed by Malvestuto in 1991.Comment: The paper was presented at VOCAL 2010 in Veszprem, Hungar

Qualitative evaluation of a preventive intervention for the offspring of parents with a history of depression

Background: Meta-analyses of randomised controlled trials suggest that psychological interventions to reduce children’s risk of depression are effective. Nevertheless, these effects are modest and diminish over time. The Medical Research Council recommends a mixed-methods approach to the evaluation of complex interventions. By gaining a more thorough understanding of participants’ perspectives, qualitative evaluations of preventive interventions could improve their efficacy, longevity and transfer into clinical practice. Methods: 18 parents and 22 children who had received a 12-session family- and group-based cognitivebehavioural intervention to prevent youth depression as part of a randomised controlled trial took part in semistructured interviews or a focus group about aspects which had been perceived as helpful, elements they were still using after the intervention had ended, and suggestions they had for improving the intervention. Results: The chance to openly share and discuss their experiences of depression within and between families was considered helpful by both children and parents. Children benefitted the most from learning coping strategies for dealing with stress and many still used them in everyday life. Parents profited mostly from increasing positive family time, but noted that maintaining new routines after the end of the intervention proved difficult. Participants were generally content with the intervention but commented on how tiring and time consuming it was. Conclusions: Managing parents’ expectations of family-based interventions in terms of their own mental health needs (versus those of their children) and leaving more room for open discussions may result in interventions which are more appealing to participating families. Increasing intervals between sessions may be one means of improving the longevity of interventions. Trial registration: The original RCT this evaluation is a part of was registered under NCT02115880

Photo-antagonism of the GABAA receptor

Neurotransmitter receptor trafficking is fundamentally important for synaptic transmission and neural network activity. GABAA receptors and inhibitory synapses are vital components of brain function, yet much of our knowledge regarding receptor mobility and function at inhibitory synapses is derived indirectly from using recombinant receptors, antibody-tagged native receptors and pharmacological treatments. Here we describe the use of a set of research tools that can irreversibly bind to and affect the function of recombinant and neuronal GABAA receptors following ultraviolet photoactivation. These compounds are based on the competitive antagonist gabazine and incorporate a variety of photoactive groups. By using site-directed mutagenesis and ligand-docking studies, they reveal new areas of the GABA binding site at the interface between receptor β and α subunits. These compounds enable the selected inactivation of native GABAA receptor populations providing new insight into the function of inhibitory synapses and extrasynaptic receptors in controlling neuronal excitation

Drug Repurposing: Far Beyond New Targets for Old Drugs

Repurposing drugs requires finding novel therapeutic indications compared to the ones for which they were already approved. This is an increasingly utilized strategy for finding novel medicines, one that capitalizes on previous investments while derisking clinical activities. This approach is of interest primarily because we continue to face significant gaps in the drug–target interactions matrix and to accumulate safety and efficacy data during clinical studies. Collecting and making publicly available as much data as possible on the target profile of drugs offer opportunities for drug repurposing, but may limit the commercial applications by patent applications. Certain clinical applications may be more feasible for repurposing than others because of marked differences in side effect tolerance. Other factors that ought to be considered when assessing drug repurposing opportunities include relevance to the disease in question and the intellectual property landscape. These activities go far beyond the identification of new targets for old drugs