As schizophrenia is genetically and clinically heterogeneous, systematic investigations are required to determine whether ICD-10 or DSM-IV categorical diagnoses identify a phenotype suitable and sufficient for genetic research, or whether correlated phenotypes incorporating neurocognitive performance and personality traits provide a phenotypic characterisation that accounts better for the underlying variation. We utilised a grade of membership (GoM) model (a mathematical typology developed for studies of complex biological systems) to integrate multiple cognitive and personality measurements into a limited number of composite graded traits (latent pure types) in a sample of 61 nuclear families comprising 80 subjects with ICD-10/ DSM-IV schizophrenia or schizophrenia spectrum disorders and 138 nonpsychotic firstdegree relatives. GoM probability scores, computed for all subjects, allowed individuals to be partly assigned to more than one pure type. Two distinct and contrasting neurocognitive phenotypes, one familial, associated with paranoid schizophrenia, and one sporadic, associated with nonparanoid schizophrenia, accounted for 74% of the affected subjects. Combining clinical diagnosis with GoM scores to stratify the entire sample into liability classes, and using variance component analysis (SOLAR), in addition to parametric and nonparametric multipoint linkage analysis, we explored candidate regions on chromosomes 6, 10 and 22. The results indicated suggestive linkage for the familial neurocognitive phenotype (multipoint MLS 2.6 under a low-penetrance model and MLS43.0 under a high-penetrance model) to a 14 cM area on chromosome 6, including the entire HLA region. Results for chromosomes 10 and 22 were negative. The findings suggest that the familial neurocognitive phenotype may be a pleiotropic expression of genes underlying the susceptibility to paranoid schizophrenia. We conclude that use of composite neurocognitive and personality trait measurements as correlated phenotypes supplementing clinical diagnosis can help stratify the liability to schizophrenia across all members of families prior to linkage, allow the search for susceptibility genes to focus selectively on subsets of families at high genetic risk, and augment considerably the power of genetic analysis.

Abstract. Emulsions are widely used as topical formulations in the pharmaceutical and cosmetic industries. They are thermodynamically unstable and require emulsifiers for stabilization. Studies have indicated that emulsifiers could affect topical delivery of actives, and this study was therefore designed to investigate the effects of different polymers, applied as emulsifiers, as well as the effects of pH on the release and topical delivery of the active. O/w emulsions were prepared by the layer-by-layer technique, with whey protein forming the first layer around the oil droplets, while either chitosan or carrageenan was subsequently adsorbed to the protein at the interface. Additionally, the emulsions were prepared at three different pH values to introduce different charges to the polymers. The active ingredient, salicylic acid, was incorporated into the oil phase of the emulsions. Physical characterization of the resulting formulations, i.e., droplet size, zeta potential, stability, and turbidity in the water phase, was performed. Release studies were conducted, after which skin absorption studies were performed on the five most stable emulsions, by using Franz type diffusion cells and utilizing human, abdominal skin membranes. It was found that an increase in emulsion droplet charge could negatively affect the release of salicylic acid from these formulations. Contrary, positively charged emulsion droplets were found to enhance dermal and transdermal delivery of salicylic acid from emulsions. It was hypothesized that electrostatic complex formation between the emulsifier and salicylic acid could affect its release, whereas electrostatic interaction between the emulsion droplets and skin could influence dermal/transdermal delivery of the active.

Objective: The purpose of this paper is to examine strategies that may facilitate the successful implementation of service-wide outcome measures in public mental health services. Conclusions:The available evidence suggests that a top-down approach to the introduction of state-wide routine outcome measurement across all public mental health services is likely to have only limited success. A centrally co-ordinated but locally directed bottom-up approach may be a more successful long-term strategy. Such an approach could make optimum use of a small team of "outcome experts", while the use of strategies such as the development of local clinical guidelines would increase the co-operation and participation of the wider clinical community. An initial collection of clinical and social demographics could provide important contextual information on service populations and would initiate the administrative and communication networks that would need to be developed for later routine, multi-site data collection.

Permeation models are often used to determine diffusion properties of a drug through a membrane as it is released from a delivery system. In order to circumvent problematic in vivo studies, diffusion studies can be performed in vitro, using (semi-)synthetic membranes. In this study salicylic acid permeation was studied, employing a nitrocellulose membrane. Both saturated and unsaturated salicylic acid solutions were studied. Additionally, the transport of salicylic acid through the nitrocellulose membrane was simulated by computational modelling. Experimental observations could be explained by the transport mechanism that was revealed by dissipative particle dynamics (DPD) simulations. The DPD model was developed with the aid of atomistic scale molecular dynamics (AA-MD). The choice of a suitable model membrane can therefore, be predicted by AA-MD and DPD simulations. Additionally, the difference in the magnitude of release from saturated and unsaturated salicylic acid and solutions could also be observed with DPD. Moreover, computational studies can reveal hidden variables such as membrane-permeant interaction that cannot be measured experimentally. A recommendation is made for the development of future model permeation membranes is to incorporate computational modelling to aid the choice of model.