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

Mechanisms of Oncogene Activation

The main modifications that characterize cancer are represented by alterations in oncogenes, tumor-suppressor genes, and non-coding RNA genes. Most of these alterations are somatic and the process is a multistep one. Tumors often arise from an initial transformed cell, and after subsequent genetic alterations different cytogenetically clones lead to tumor heterogeneity

EARTH QUAKE PROGNOSTICATION USING DATA MINING AND CURVE FITTING TECHNIQUES

The title “EARTHQUAKE PROGNOSTICATION” is a Global Earthquake prediction, that is used to predict that an earthquake of a specific magnitude will occur in a particular place at a particular time, we however cannot tell the exact time and date the earthquake is going to occur but we can well predict that an earthquake will affect a given location over a certain number of years. The “Gutenberg Richter power-law distribution of earthquake sizes” implies that the largest events are surrounded by a large number of small events, with this statement we collected the data sets of all the EARTHQUAKES of magnitude ranging from small to big since 1900 to 2010 all over the world. After collecting this data we performed clustering techniques to the datasets available with latitude, longitude and time as parameters, which helped to find similarities between them and discovered patterns using non-linear regression functions that helped to forecast earthquakes. This prediction is based on both the historical seismic catalogue and the structural zoning

COVID deaths in South Africa: 99 days since South Africa’s first death

Background. Understanding the pattern of deaths from COVID-19 in South Africa (SA) is critical to identifying individuals at high risk of dying from the disease. The Minister of Health set up a daily reporting mechanism to obtain timeous details of COVID-19 deaths from the provinces to track mortality patterns.Objectives. To provide an epidemiological analysis of the first COVID-19 deaths in SA.Methods. Provincial deaths data from 28 March to 3 July 2020 were cleaned, information on comorbidities was standardised, and data were aggregated into a single data set. Analysis was performed by age, sex, province, date of death and comorbidities.Results. SA reported 3 088 deaths from COVID-19, i.e. an age-standardised death rate of 64.5 (95% confidence interval (CI) 62.3 - 66.8) deaths per million population. Most deaths occurred in Western Cape (65.5%) followed by Eastern Cape (16.8%) and Gauteng (11.3%). The median age of death was 61 years (interquartile range 52 - 71). Males had a 1.5 times higher death rate compared with females. Individuals with two or more comorbidities accounted for 58.6% (95% CI 56.6 - 60.5) of deaths. Hypertension and diabetes were the most common comorbidities reported, and HIV and tuberculosis were more common in individuals aged <50 years.Conclusions. Data collection for COVID-19 deaths in provinces must be standardised. Even though the data had limitations, these findings can be used by the SA government to manage the pandemic and identify individuals who are at high risk of dying from COVID-19

The effects of foreign direct investment on youth unemployment in the Southern African Development Community

Open Access ArticleThis paper examines the effect of foreign direct investment (FDI) on youth unemployment in the Southern African Development Community (SADC) region using panel data from the World Bank World Development Indicators for the period 1994–2017. Results from the Feasible Generalized Least Squares (FGLS-Parks) technique show that FDI has an insignificant effect on reducing youth unemployment in the SADC region. This could be because the type of FDI in the region is partly mergers and acquisitions, which has fewer jobs creating capacity compared to Greenfield investment. This suggests the need for governments in the region to pursue labour-absorbing FDI policies and also ensure that foreign investment inflows are channelled towards labour-intensive sectors that have high labour absorptive capacity such as horticulture and floriculture

Gender differences in technology adoption and agricultural productivity: evidence from Malawi

Open Access Article; Published online: 21 Jul 2022It is widely recognized that female farmers have considerably less access to productive assets and support services than male farmers. There is limited evidence of gender gaps in technology adoption and agricultural productivity after accounting for the differential access to factors of production between males and females. This study investigates the gender differences in the adoption of improved technologies and agricultural productivity in Malawi using nationally representative data collected from 1600 households and 5238 plots. We used a multivariate probit model to analyze the gender differences in the adoption of improved technologies, including intercropping, use of improved varieties, crop rotation and residue retention, manure use, and minimum tillage. To analyze gender differences in agricultural productivity, we used an exogenous switching regression (ESR) model and recentered influence function decomposition. We found that female plot managers were more likely to adopt intercropping and minimum tillage but less likely to adopt crop rotation and use improved varieties than male plot managers. The ESR model estimation results showed that female-managed plots were 14.6–23.1% less productive than male-managed plots. The gender productivity gaps also indicated that female plot managers had an 8.2% endowment advantage but a 23.1% structural disadvantage than male plot managers. The importance of structural effects in accounting for the gender productivity gap highlights the need for policies and agricultural development programs that consider the underlying factors shaping gender productivity gaps rather than focusing solely on agricultural production factors

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