Estrogen treatment decreases matrix metalloproteinase (MMP)-9 in autoimmune demyelinating disease through estrogen receptor alpha (ERalpha).

Matrix metalloproteinases (MMPs) have a crucial function in migration of inflammatory cells into the central nervous system (CNS). Levels of MMP-9 are elevated in multiple sclerosis (MS) and predict the occurrence of new active lesions on magnetic resonance imaging (MRI). This translational study aims to determine whether in vivo treatment with the pregnancy hormone estriol affects MMP-9 levels from immune cells in patients with MS and mice with experimental autoimmune encephalomyelitis (EAE). Peripheral blood mononuclear cells (PBMCs) collected from three female MS patients treated with estriol and splenocytes from EAE mice treated with estriol, estrogen receptor (ER) alpha ligand, ERbeta ligand or vehicle were stimulated ex vivo and analyzed for levels of MMP-9. Markers of CNS infiltration were assessed using MRI in patients and immunohistochemistry in mice. Supernatants from PBMCs obtained during estriol treatment in female MS patients showed significantly decreased MMP-9 compared with pretreatment. Decreases in MMP-9 coincided with a decrease in enhancing lesion volume on MRI. Estriol treatment of mice with EAE reduced MMP-9 in supernatants from autoantigen-stimulated splenocytes, coinciding with decreased CNS infiltration by T cells and monocytes. Experiments with selective ER ligands showed that this effect was mediated through ERalpha. In conclusion, estriol acting through ERalpha to reduce MMP-9 from immune cells is one mechanism potentially underlying the estriol-mediated reduction in enhancing lesions in MS and inflammatory lesions in EAE

Does cooperative membership increase and accelerate agricultural technology adoption? Empirical evidence from Zambia

Open Access Article; Published online: 20 Jun 2020In developing countries, agricultural cooperatives are increasingly being used to promote improved agricultural technologies and alleviate food insecurity and poverty. However, little is known about the role of agricultural cooperatives in accelerating the adoption of improved agricultural technologies. Using a comprehensive balanced household panel and varietal data, this study applied the difference-in-difference model to identify factors affecting farmers’ decision to become cooperative members and the impact of cooperative membership on the adoption of improved maize, inorganic fertilizer and crop rotation. Furthermore, the study used the inverse probability weighted regression adjustment model to analyze the impact of cooperative membership on the speed of adoption of improved maize varieties. We found that cooperative membership increased the probability of technology adoption by 11–24 percentage points. Results further indicated that the average time to adoption was about 8 years, but it was shorter for cooperative members. The results showed that, on average, cooperative membership increased the speed of adoption of improved maize by 1.6–4.3 years. Generally, the results suggest the need for policies which promote farmer organizations such as cooperatives coupled with effective extension services for faster and greater adoption of improved technologies

A partnership-based model for embedding employability in urban planning education

This paper proposes a partnership-based model for embedding employability in urban planning education. The model is based on the author’s experiences of implementing an international project which supported the development of employability skills in urban and regional planning education in Malawi. Since independence, urban planners have typically trained outside the country, attending university in the UK and other Commonwealth countries. More recently, the paradigm has shifted towards in-country education delivered by academic staff cognisant with the opportunities and challenges of development in Malawi. There remains, though, a gap between graduate knowledge of the subject and the skills necessary to pursue a professional career in the sector. Although there is no consensus yet on the meaning of employability in the literature, lessons from the project indicate that academic–public–private collaboration helps incorporate in curriculum skills that employers anticipate. Applicability of these principles is however context dependent, particularly in the emerging economy context where institutional capacity may be less developed compared to elsewhere

The use of technology enhanced learning in health research capacity development: lessons from a cross country research partnership.

BACKGROUND: With the recognition of the need for research capacity strengthening for advancing health and development, this research capacity article explores the use of technology enhanced learning in the delivery of a collaborative postgraduate blended Master's degree in Malawi. Two research questions are addressed: (i) Can technology enhanced learning be used to develop health research capacity?, and: (ii) How can learning content be designed that is transferrable across different contexts? METHODS: An explanatory sequential mixed methods design was adopted for the evaluation of technology enhanced learning in the Masters programme. A number of online surveys were administered, student participation in online activities monitored and an independent evaluation of the programme conducted. RESULTS: Remote collaboration and engagement are paramount in the design of a blended learning programme and support was needed for selecting the most appropriate technical tools. Internet access proved problematic despite developing the content around low bandwidth availability and training was required for students and teachers/trainers on the tools used. Varying degrees of engagement with the tools used was recorded, and the support of a learning technologist was needed to navigate through challenges faced. CONCLUSION: Capacity can be built in health research through blended learning programmes. In relation to transferability, the support required institutionally for technology enhanced learning needs to be conceptualised differently from support for face-to-face teaching. Additionally, differences in pedagogical approaches and styles between institutions, as well as existing social norms and values around communication, need to be embedded in the content development if the material is to be used beyond the pilot resource-intensive phase of a project

A full Bayesian hierarchical mixture model for the variance of gene differential expression

<p>Abstract</p> <p>Background</p> <p>In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccurate. Visual inspection of graphical summaries of these data usually reveals that heteroscedasticity is present, and the standard approach to address this is to take a log₂transformation. In such circumstances, it is then common to assume that gene variability is constant when an analysis of these data is undertaken. However, this is perhaps too stringent an assumption. More careful inspection reveals that the simple log₂transformation does not remove the problem of heteroscedasticity. An alternative strategy is to assume independent gene-specific variances; although again this is problematic as variance estimates based on few replications are highly unstable. More meaningful and reliable comparisons of gene expression might be achieved, for different conditions or different tissue samples, where the test statistics are based on accurate estimates of gene variability; a crucial step in the identification of differentially expressed genes.</p> <p>Results</p> <p>We propose a Bayesian mixture model, which classifies genes according to similarity in their variance. The result is that genes in the same latent class share the similar variance, estimated from a larger number of replicates than purely those per gene, i.e. the total of all replicates of all genes in the same latent class. An example dataset, consisting of 9216 genes with four replicates per condition, resulted in four latent classes based on their similarity of the variance.</p> <p>Conclusion</p> <p>The mixture variance model provides a realistic and flexible estimate for the variance of gene expression data under limited replicates. We believe that in using the latent class variances, estimated from a larger number of genes in each derived latent group, the <it>p</it>-values obtained are more robust than either using a constant gene or gene-specific variance estimate.</p

The burden of breast, cervical, and colon and rectum cancer in the Balkan countries, 1990–2019 and forecast to 2030.

Background Despite effective prevention and control strategies, in countries of the Balkan region, cancers are the second leading cause of mortality, closely following circulatory system diseases. Objective To describe trends in the burden of breast, cervical, and colon and rectum cancer in the Balkan region and per country between 1990 and 2019, including a forecast to 2030. Methods We described the 2019 Global Burden of Disease (GBD) estimates for breast, cervical, and colon and rectum cancers in eleven Balkan countries over the period 1990–2019, including incidence, years lived with disability (YLD), years of life lost (YLL), and disability-adjusted life years (DALYs) rates per 100,000 population and accompanied 95% uncertainty interval. With the Autoregressive Integrated Moving Average, we forecasted these rates per country up to 2030. Results In the Balkan region, the highest incidence and DALYs rates in the study period were for colon and rectum, and breast cancers. Over the study period, the DALYs rates for breast cancer per 100,000 population were the highest in Serbia (reaching 670.84 in 2019) but the lowest in Albania (reaching 271.24 in 2019). In 2019, the highest incidence of breast cancer (85 /100,000) and highest YLD rate (64 /100,000) were observed in Greece. Romania had the highest incidence rates, YLD rates, DALY rates, and YLL rates of cervical cancer, with respective 20.59%, 23.39% 4.00%, and 3.47% increases for the 1990/2019 period, and the highest forecasted burden for cervical cancer in 2030. The highest incidence rates, YLD rates and DALY rates of colon and rectum cancers were continuously recorded in Croatia (an increase of 130.75%, 48.23%, and 63.28%, respectively), while the highest YLL rates were in Bulgaria (an increase of 63.85%). The YLL rates due to colon and rectum cancers are forecasted to progress by 2030 in all Balkan countries. Conclusion As most of the DALYs burden for breast, cervical, and colon and rectum cancer is due to premature mortality, the numerous country-specific barriers to cancer early detection and quality and care continuum should be a public priority of multi-stakeholder collaboration in the Balkan region

Chronic Melatonin Administration Reduced Oxidative Damage and Cellular Senescence in the Hippocampus of a Mouse Model of Down Syndrome

Previous studies have demonstrated that melatonin administration improves spatial learning and memory and hippocampal long-term potentiation in the adult Ts65Dn (TS) mouse, a model of Down syndrome (DS). This functional benefit of melatonin was accompanied by protection from cholinergic neurodegeneration and the attenuation of several hippocampal neuromorphological alterations in TS mice. Because oxidative stress contributes to the progression of cognitive deficits and neurodegeneration in DS, this study evaluates the antioxidant effects of melatonin in the brains of TS mice. Melatonin was administered to TS and control mice from 6 to 12 months of age and its effects on the oxidative state and levels of cellular senescence were evaluated. Melatonin treatment induced antioxidant and antiaging effects in the hippocampus of adult TS mice. Although melatonin administration did not regulate the activities of the main antioxidant enzymes (superoxide dismutase, catalase, glutathione peroxidase, glutathione reductase, and glutathione S-transferase) in the cortex or hippocampus, melatonin decreased protein and lipid oxidative damage by reducing the thiobarbituric acid reactive substances (TBARS) and protein carbonyls (PC) levels in the TS hippocampus due to its ability to act as a free radical scavenger. Consistent with this reduction in oxidative stress, melatonin also decreased hippocampal senescence in TS animals by normalizing the density of senescence-associated â-galactosidase positive cells in the hippocampus. These results showed that this treatment attenuated the oxidative damage and cellular senescence in the brain of TS mice and support the use of melatonin as a potential therapeutic agent for age-related cognitive deficits and neurodegeneration in adults with DS

Risk factors and a predictive model for under-five mortality in Nigeria: evidence from Nigeria demographic and health survey

<p>Abstract</p> <p>Background</p> <p>Under-5 mortality is a major public health challenge in developing countries. It is essential to identify determinants of under-five mortality (U5M) childhood mortality because these will assist in formulating appropriate health programmes and policies in order to meet the United Nations MDG goal. The objective of this study was to develop a predictive model and identify maternal, child, family and other risk factors associated U5M in Nigeria.</p> <p>Methods</p> <p>Population-based cross-sectional study which explored 2008 demographic and health survey of Nigeria (NDHS) with multivariable logistic regression. Likelihood Ratio Test, Hosmer-Lemeshow Goodness-of-Fit and Variance Inflation Factor were used to check the fit of the model and the predictive power of the model was assessed with Receiver Operating Curve (ROC curve).</p> <p>Results</p> <p>This study yielded an excellent predictive model which revealed that the likelihood of U5M among the children of mothers that had their first marriage at age 20-24 years and ≥ 25 years declined by 20% and 30% respectively compared to children of those that married before the age of 15 years. Also, the following factors reduced odds of U5M: health seeking behaviour, breastfeeding children for > 18 months, use of contraception, small family size, having one wife, low birth order, normal birth weight, child spacing, living in urban areas, and good sanitation.</p> <p>Conclusions</p> <p>This study has revealed that maternal, child, family and other factors were important risk factors of U5M in Nigeria. This study has identified important risk factors that will assist in formulating policies that will improve child survival.</p