Intranasal delivery of transforming growth factor-beta1 in mice after stroke reduces infarct volume and increases neurogenesis in the subventricular zone

<p>Abstract</p> <p>Background</p> <p>The effect of neurotrophic factors in enhancing stroke-induced neurogenesis in the adult subventricular zone (SVZ) is limited by their poor blood-brain barrier (BBB) permeability.</p> <p>Intranasal administration is a noninvasive and valid method for delivery of neuropeptides into the brain, to bypass the BBB. We investigated the effect of treatment with intranasal transforming growth factor-β1 (TGF-β1) on neurogenesis in the adult mouse SVZ following focal ischemia. The modified Neurological Severity Scores (NSS) test was used to evaluate neurological function, and infarct volumes were determined from hematoxylin-stained sections. Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) labeling was performed at 7 days after middle cerebral artery occlusion (MCAO). Immunohistochemistry was used to detect bromodeoxyuridine (BrdU) and neuron- or glia-specific markers for identifying neurogenesis in the SVZ at 7, 14, 21, 28 days after MCAO.</p> <p>Results</p> <p>Intranasal treatment of TGF-β1 shows significant improvement in neurological function and reduction of infarct volume compared with control animals. TGF-β1 treated mice had significantly less TUNEL-positive cells in the ipsilateral striatum than that in control groups. The number of BrdU-incorporated cells in the SVZ and striatum was significantly increased in the TGF-β1 treated group compared with control animals at each time point. In addition, numbers of BrdU- labeled cells coexpressed with the migrating neuroblast marker doublecortin (DCX) and the mature neuronal marker neuronal nuclei (NeuN) were significantly increased after intranasal delivery of TGF-β1, while only a few BrdU labeled cells co-stained with glial fibrillary acidic protein (GFAP).</p> <p>Conclusion</p> <p>Intranasal administration of TGF-β1 reduces infarct volume, improves functional recovery and enhances neurogenesis in mice after stroke. Intranasal TGF-β1 may have therapeutic potential for cerebrovascular disorders.</p

Anti-angiogenic effect of high doses of ascorbic acid

Pharmaceutical doses of ascorbic acid (AA, vitamin C, or its salts) have been reported to exert anticancer activity in vitro and in vivo. One proposed mechanism involves direct cytotoxicity mediated by accumulation of ascorbic acid radicals and hydrogen peroxide in the extracellular environment of tumor cells. However, therapeutic effects have been reported at concentrations insufficient to induce direct tumor cell death. We hypothesized that AA may exert anti-angiogenic effects. To test this, we expanded endothelial progenitor cells (EPCs) from peripheral blood and assessed, whether or not high dose AA would inhibit EPC ability to migrate, change energy metabolism, and tube formation ability. We also evaluated the effects of high dose AA on angiogenic activities of HUVECs (human umbilical vein endothelial cells) and HUAECs (human umbilical arterial endothelial cells). According to our data, concentrations of AA higher than 100 mg/dl suppressed capillary-like tube formation on Matrigel for all cells tested and the effect was more pronounced for progenitor cells in comparison with mature cells. Co-culture of differentiated endothelial cells with progenitor cells showed that there was incorporation of EPCs in vessels formed by HUVECs and HUAECs. Cell migration was assessed using an in vitro wound healing model. The results of these experiments showed an inverse correlation between AA concentrations relative to both cell migration and gap filling capacity. Suppression of NO (nitric oxide) generation appeared to be one of the mechanisms by which AA mediated angiostatic effects. This study supports further investigation into non-cytotoxic antitumor activities of AA

Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins

<p>Abstract</p> <p>Background</p> <p>Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites.</p> <p>Results</p> <p>We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information.</p> <p>Conclusion</p> <p>While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structure-based P-site prediction method has been made available at <url>http://phos3d.mpimp-golm.mpg.de</url>.</p

The development and pilot testing of a rapid assessment tool to improve local public health system capacity in Australia

<p>Abstract</p> <p>Background</p> <p>To operate effectively the public health system requires infrastructure and the capacity to act. Public health's ability to attract funding for infrastructure and capacity development would be enhanced if it was able to demonstrate what level of capacity was required to ensure a high performing system. Australia's public health activities are undertaken within a complex organizational framework that involves three levels of government and a diverse range of other organizations. The question of appropriate levels of infrastructure and capacity is critical at each level. Comparatively little is known about infrastructure and capacity at the local level.</p> <p>Methods</p> <p>In-depth interviews were conducted with senior managers in two Australian states with different frameworks for health administration. They were asked to reflect on the critical components of infrastructure and capacity required at the local level. The interviews were analyzed to identify the major themes. Workshops with public health experts explored this data further. The information generated was used to develop a tool, designed to be used by groups of organizations within discrete geographical locations to assess local public health capacity.</p> <p>Results</p> <p>Local actors in these two different systems pointed to similar areas for inclusion for the development of an instrument to map public health capacity at the local level. The tool asks respondents to consider resources, programs and the cultural environment within their organization. It also asks about the policy environment - recognizing that the broader environment within which organizations operate impacts on their capacity to act. Pilot testing of the tool pointed to some of the challenges involved in such an exercise, particularly if the tool were to be adopted as policy.</p> <p>Conclusion</p> <p>This research indicates that it is possible to develop a tool for the systematic assessment of public health capacity at the local level. Piloting the tool revealed some concerns amongst participants, particularly about how the tool would be used. However there was also recognition that the areas covered by the tool were those considered relevant.</p

Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting

<p>Abstract</p> <p>Background</p> <p>The World Health Organisation estimates that by 2030 there will be approximately 350 million people with type 2 diabetes. Associated with renal complications, heart disease, stroke and peripheral vascular disease, early identification of patients with undiagnosed type 2 diabetes or those at an increased risk of developing type 2 diabetes is an important challenge. We sought to systematically review and critically assess the conduct and reporting of methods used to develop risk prediction models for predicting the risk of having undiagnosed (prevalent) or future risk of developing (incident) type 2 diabetes in adults.</p> <p>Methods</p> <p>We conducted a systematic search of PubMed and EMBASE databases to identify studies published before May 2011 that describe the development of models combining two or more variables to predict the risk of prevalent or incident type 2 diabetes. We extracted key information that describes aspects of developing a prediction model including study design, sample size and number of events, outcome definition, risk predictor selection and coding, missing data, model-building strategies and aspects of performance.</p> <p>Results</p> <p>Thirty-nine studies comprising 43 risk prediction models were included. Seventeen studies (44%) reported the development of models to predict incident type 2 diabetes, whilst 15 studies (38%) described the derivation of models to predict prevalent type 2 diabetes. In nine studies (23%), the number of events per variable was less than ten, whilst in fourteen studies there was insufficient information reported for this measure to be calculated. The number of candidate risk predictors ranged from four to sixty-four, and in seven studies it was unclear how many risk predictors were considered. A method, not recommended to select risk predictors for inclusion in the multivariate model, using statistical significance from univariate screening was carried out in eight studies (21%), whilst the selection procedure was unclear in ten studies (26%). Twenty-one risk prediction models (49%) were developed by categorising all continuous risk predictors. The treatment and handling of missing data were not reported in 16 studies (41%).</p> <p>Conclusions</p> <p>We found widespread use of poor methods that could jeopardise model development, including univariate pre-screening of variables, categorisation of continuous risk predictors and poor handling of missing data. The use of poor methods affects the reliability of the prediction model and ultimately compromises the accuracy of the probability estimates of having undiagnosed type 2 diabetes or the predicted risk of developing type 2 diabetes. In addition, many studies were characterised by a generally poor level of reporting, with many key details to objectively judge the usefulness of the models often omitted.</p

A systematic review of mental disorder, suicide, and deliberate self harm in lesbian, gay and bisexual people

Background: Lesbian, gay and bisexual (LGB) people may be at higher risk of mental disorders than heterosexual people.Method: We conducted a systematic review and meta-analysis of the prevalence of mental disorder, substance misuse, suicide, suicidal ideation and deliberate self harm in LGB people. We searched Medline, Embase, PsycInfo, Cinahl, the Cochrane Library Database, the Web of Knowledge, the Applied Social Sciences Index and Abstracts, the International Bibliography of the Social Sciences, Sociological Abstracts, the Campbell Collaboration and grey literature databases for articles published January 1966 to April 2005. We also used Google and Google Scholar and contacted authors where necessary. We searched all terms related to homosexual, lesbian and bisexual people and all terms related to mental disorders, suicide, and deliberate self harm. We included papers on population based studies which contained concurrent heterosexual comparison groups and valid definition of sexual orientation and mental health outcomes.Results: Of 13706 papers identified, 476 were initially selected and 28 (25 studies) met inclusion criteria. Only one study met all our four quality criteria and seven met three of these criteria. Data was extracted on 214,344 heterosexual and 11,971 non heterosexual people. Meta-analyses revealed a two fold excess in suicide attempts in lesbian, gay and bisexual people [ pooled risk ratio for lifetime risk 2.47 (CI 1.87, 3.28)]. The risk for depression and anxiety disorders (over a period of 12 months or a lifetime) on meta-analyses were at least 1.5 times higher in lesbian, gay and bisexual people (RR range 1.54-2.58) and alcohol and other substance dependence over 12 months was also 1.5 times higher (RR range 1.51-4.00). Results were similar in both sexes but meta analyses revealed that lesbian and bisexual women were particularly at risk of substance dependence (alcohol 12 months: RR 4.00, CI 2.85, 5.61; drug dependence: RR 3.50, CI 1.87, 6.53; any substance use disorder RR 3.42, CI 1.97-5.92), while lifetime prevalence of suicide attempt was especially high in gay and bisexual men (RR 4.28, CI 2.32, 7.88).Conclusion: LGB people are at higher risk of mental disorder, suicidal ideation, substance misuse, and deliberate self harm than heterosexual people