Barriers to effectiveness: artemisinin combination therapies (ACTs) and the health system

As international funding for malaria programmes plateaus, it is critical to better understand how to implement interventions such as first-line Artemisinin Combination Therapies (ACTs) most effectively through an existing health system. This thesis presents an expansion of a mathematical model of malaria transmission to provide insight to the role of health systems factors as barriers to the effectiveness of ACTs, and interventions to overcome them; considering dimensions of access to care, different sectors through which care is delivered, and the quality of care provided. Data from the IMPACT 2 study in Tanzania was used to parameterise this approach. Primary-care based interventions had most impact on transmission. In low-prevalence scenarios some single interventions, e.g. ensuring 100% care-seeking, eliminated parasite prevalence. Diagnostic-led therapy with adequate stocks of ACTs was as effective in all settings as a policy of presumptive treatment, reducing parasite prevalence in under-fives in moderate transmission settings by up to 86% depending on the sector of implementation. Modelling combinations of hospital-based interventions shifted the pattern of severe malaria away from a peak at early ages (greater than 70% relative reduction in 0-5 year olds in medium transmission settings) towards a more sustained lower incidence across 0-20 years of age as seen in low prevalence settings. This was not immune-mediated and demonstrates the role of health systems interventions preventing the development of severe malaria in those at risk, and reducing mortality. Weak health systems and a poorly controlled diversity of antimalarial sources act as barriers to deploying ACTs effectively both as a control measure and first-line treatment. Addressing these constraints needs consideration of existing healthcare provision and local priorities, e.g. reducing ACT wastage, but through specific planning may improve progress towards targets set by Roll Back Malaria to decrease clinical disease and mortality, and in low transmission settings, to approach elimination.Open Acces

Overcoming health systems barriers to successful malaria treatment.

The success of malaria control programmes is recognised to be handicapped by the capacity of the health system to deliver interventions such as first-line treatment at optimal coverage and quality. Traditional approaches to strengthening the health system such as staff training have had a less sustained impact than hoped. However, novel strategies including the use of mobile phones to ease stockouts, task-shifting to community health workers, and inclusion of the informal sector appear more promising. As global health funding slows, it is critical to better understand how to deliver a proven intervention most effectively through the existing system

Histone H3 Lysine 36 modification distinguishes transcribed and non-transcribed regions of the S. cerevisiae genome

Chromatin plays a dynamic role in regulating gene transcription. Regulation of accessibility of DNA template is mediated in part by nucleosome occupancy such that nucleosomes are relatively depleted upstream of genes and relatively enriched in the coding regions. One of the factors that influence this differential nucleosome occupancy is histone post translational modifications. One such modification is dimethylation of histone H3 at Lysine 36 (H3K36me2). It is mediated by Set2, a histone methyl transferase (HMT) in yeast which had been shown to associate with RNA polymerase II (RNA pol-II) during transcription elongation at individual loci. To study the role of Set2 in gene regulation, I sought to determine the genome wide localization of H3K36me2. Using chromatin immunoprecipitation followed by DNA microarray hybridization (ChIP-chip), we show that H3K36me2 is predominantly localized to RNA pol-II transcribed regions and is depleted in the regulatory (promoter) regions genome-wide. Mating loci, telomeres, RNA pol-III transcribed regions have scarce or low levels of H3K36me2. H3K36me2 modification begins within RNA pol-II transcribed ORFs at approximately same location, independent of the length of the ORF. This further confirms that Set2 associates with RNA pol-II after the initiation phase of transcription. Levels of H3K36me2 do not correlate with the transcriptional frequencies of genes. However, genes that are transcribed at some detectably level tend to have higher levels of H3K36me2 than genes that are completely repressed. H3K36me2 therefore acts as a mark that demarcates coding and regulatory regions. The function of such a mark became clear with the finding by other groups that localization of Set2 and H3K36me2 at coding regions was essential for maintaining the fidelity of transcriptional initiation. Absence of Set2 leads to hyperacetylation in the coding regions and, as a consequence, aberrant initiation events. My studies show that H3K36me2 is a chromatin mark that demarcates functionally distinct regions of the genome by marking the coding regions specifically. Studies by others show that this localization of H3K36me2 is important for maintaining proper chromatin structure. H3 Lysine 36 is also acetylated and ChIP-chip analysis showed that H3K36ac is enriched in the promoter regions in the entire yeast genome. The function of H3K36ac is not yet known but it is possible that one way H3K36me2 is restricted to the coding regions by acetylating this residue in the regulatory regions. Another way organisms demarcate specific functional boundaries is by restricting tri methyl Lysine 4 at histone H3 (H3K4me3) to the 5' end of coding regions. Ctk1, a kinase that has been shown to phosphorylate Serine 2 of C-terminal domain (CTD) of RNA pol-II was shown to regulate the levels of H3K4me3. Ctk1 is required for the recruitment of Set2 to RNA pol-II. My genome wide studies show that absence of Ctk1 causes spreading of H3K4me3 into the 3' region of ORFs globally resulting in disruption of chromatin structure within the ORFs and occurrence of aberrant transcription initiation. These studies show that specific histone modification patterns are important for maintaining chromatin structure. Organisms have developed multiple mechanisms to ensure proper localization of these modifications disruption of which could cause disturbances in transcriptional programs

Gender, Agriculture, and Nutrition in South Asia: Conceptualising the Links

Even with higher economic growth and an overall reduction in poverty, there exists child undernutrition, maternal undernutrition and diverse forms of micro nutrient deficiencies – a phenomenon labelled as the South Asian Paradox. Eradicating undernutrition requires a dedicated effort to alleviating child undernutrition, as South Asia accounts for forty percent of the world’s undernourished children. Agricultural growth, by enabling farming households to grow more/better food for self-consumption, and opening opportunities for employment, can contribute importantly to this process. This brief sets out the conceptual starting points for LANSA research on the gender-agriculture pathways to improve nutritional outcomes.Department for International Development (DFID)UKAI

A DDoS Attack Detection using PCA Dimensionality Reduction and Support Vector Machine

Distributed denial-of-service attack (DDoS) is one of the most frequently occurring network attacks. Because of rapid growth in the communication and computer technology, the DDoS attacks became severe. So, it is essential to research the detection of a DDoS attack. There are different modes of DDoS attacks because of which a single method cannot provide good security. To overcome this, a DDoS attack detection technique is presented in this paper using machine learning algorithm. The proposed method has two phases, dimensionality reduction and model training for attack detection. The first phase identifies important components from the large proportion of the internet data. These extracted components are used as machine learning’s input features in the phase of model detection. Support Vector Machine (SVM) algorithm is used to train the features and learn the model. The experimental results shows that the proposed method detects DDoS attacks with good accuracy

LC/MS:AN ESSENTIAL TOOL IN DRUG DEVELOPMENT

The combination of high-performance liquid chromatography and mass spectrometry (LC/MS) has had a sign cant impact on drug development over the past decade. Continual improvements in LC/MS interface technologies combined with powerful features for structure analysis, qualitative and quantitative,have resulted in a widened scope of application. These improvements coincided with breakthroughs in combinatorial chemistry, molecular biology, and an overall industry trend of accelerated development.The use of high-performance liquid chromatographycombined with mass spectrometry (HPLC MS) or tandem mass spectrometry (HPLC MS MS) has proven to be the analytical technique of choice for most assays used in various stages of new drug discovery. Asummary of the key components of HPLC MS systems, as well as an overview of major application areas that use this technique as part of the drug discovery process, will be described here. This review will also provide an introduction into the various types of mass spectrometers that can be selected for the multiple tasks that can be performed using LC MS as the analytical tool. The strategies for optimizing the use of this technique and also the potential problems and how to avoid them will be highlighted

Ferromagnetism as a universal feature of nanoparticles of the otherwise nonmagnetic oxides

Room-temperature ferromagnetism has been observed in the nanoparticles (7 - 30 nm dia) of nonmagnetic oxides such as CeO2, Al2O3, ZnO, In2O3 and SnO2. The saturated magnetic moments in CeO_2 and Al_2O_3 nanoparticles are comparable to those observed in transition metal doped wide band semiconducting oxides. The other oxide nanoparticles show somewhat lower values of magnetization but with a clear hysteretic behavior. Conversely, the bulk samples obtained by sintering the nanoparticles at high temperatures in air or oxygen became diamagnetic. As there were no magnetic impurities present, we assume that the origin of ferromagnetism may be due to the exchange interactions between localized electron spin moments resulting from oxygen vacancies at the surfaces of nanoparticles. We suggest that ferromagnetism may be a universal characteristic of nanopartilces of metal oxidesComment: 6 pages, 4 figure

Achievements of Soil Research in Dryland Regions of Andhra Pradesh

Not AvailableThe global rainfed crop lands were estimated at 1.132 billion hectares at the end of the last millennium. This is 2.78 times the net irrigated areas (407 m ha) of the world. Rainfed agro-ecosystems occupy a considerable place in Indian agriculture too, covering 80 million ha, in arid, semi-arid and sub-humid climatic zones; constituting nearly 58% of the net cultivated area. Rainfed regions support 60% of livestock, 40% of human population and contribute 40% of food grains and several special attribute commodities. Rainfed agro ecologies are complex, diverse, fragile, risky, under invested and require regionally differentiated investments and management strategies. Achieving high production potential is difficult in these rainfed areas due to vagaries of rainfall.Not Availabl

A VOS analysis of LSTM Learners Classification for Recommendation System

In response to the growing popularity of social web apps, much research has gone into analyzing and developing an AI-based responsive suggestion system. Machine learning and neural networks come in many forms that help online students choose the best texts for their studies. However, when training recommendation models to deal with massive amounts of data, traditional machine learning approaches require additional training models. As a result, they are deemed inappropriate for the personalized recommender generation of learning systems. In this paper, we examine LSTM-based strategies in order to make useful recommendations for future research

Nurturing Agribusiness: A Sustainable Farming System for Tomato Crop Management Leveraging Machine Learning

The agriculture industry is undergoing a transformative shift with the introduction of IoT technology, enabling global connectivity for farmers. This technology offers a plethora of advantages, ranging from precise seed selection based on soil analysis to efficient crop maintenance, water management, and enhanced marketing support for improved profitability. To further enhance tomato farming practices, we propose the implementation of a smart farmer marketing assistant that streamlines the process of segregating yield based on its growth stage, reducing labor and time requirements.Further, the frame work is capable of early-disease management system that can detect  diseases like early blight,light blight, buck eye rot and anthranose and suggest remedy.  By adopting this innovative approach, financial losses associated with traditional methods are minimized.The traditional practice of combining all categories of vegetables (ripened, unripened, and partially rotten) in a single container often results in reduced shelf life for the produce. In our framework, we employ color sorting to categorize the vegetables, ensuring proper packing into their respective bins. This valuable data is made accessible through a cloud environment, providing potential buyers with comprehensive information about the yield, its category, and pricing. This increased visibility empowers farmers to reach a global market and sell their produce at competitive prices. In this context, we present a case study focused on the tomato crop, where we have successfully developed a prototype utilizing ESP32, a color sensor, and Google Firebase. This comprehensive framework effectively harnesses the power of IoT, Machine Learning, and potential marketing strategies, transforming the way farmers manage their crops and connect with buyers on a global scale with highly accurate 87.9% experimental results