Identification of malaria hot spots for focused intervention in tribal state of India: a GIS based approach

<p>Abstract</p> <p>Background</p> <p>In India, presently malaria shows a declining trend whereas <it>Plasmodium falciparum (Pf) </it>cases show an up trend. In central India, specifically, Madhya Pradesh (M.P.) a forested and tribal area, control of malaria is logistically difficult and outbreaks are frequently recorded, reasons for this being inadequate surveillance, poor reporting, a time lag in reporting to decision makers and a lack of geo referenced information to pin point the trouble spots for a timely preventive action.</p> <p>Results</p> <p>An information management system based on Geographic Information System (GIS) using district and block wise malaria data, has been constructed for Madhya Pradesh for quick retrieval of info and dynamic generation of maps to highlight hot spots of malaria for formulating prompt and focused malaria control strategy. Out of total 48 districts consisting of 313 blocks, based on certain criteria GIS identified 58 blocks falling in 25 districts as Hot Spots. Malaria flares up from these pockets whenever favourable conditions for transmission occurs. It was suggested to National Vector Borne Disease Control Programme (NVBDCP) that focused malaria control in these hot pockets may be taken up on priority during the year 2007, it was implemented by State Health Authorities, M.P. under the directive of NVBDCP. Implementation of control measures were evaluated by NVBDCP.</p> <p>Conclusion</p> <p>GIS mapping would make it easy to update information instantly and to identify the trouble spots at the village level within the district which is the lowest unit equipped with computer facilities and the information can reach instantly to state and the policy makers to formulate focused and cost effective malaria control strategy. This is the first time when GIS has been used in national control programme for tribal malaria.</p

Positional dependence of transcriptional inhibition by DNA torsional stress in yeast chromosomes

How DNA helical tension is constrained along the linear chromosomes of eukaryotic cells is poorly understood. In this study, we induced the accumulation of DNA (+) helical tension in Saccharomyces cerevisiae cells and examined how DNA transcription was affected along yeast chromosomes. The results revealed that, whereas the overwinding of DNA produced a general impairment of transcription initiation, genes situated at <100 kb from the chromosomal ends gradually escaped from the transcription stall. This novel positional effect seemed to be a simple function of the gene distance to the telomere: It occurred evenly in all 32 chromosome extremities and was independent of the atypical structure and transcription activity of subtelomeric chromatin. These results suggest that DNA helical tension dissipates at chromosomal ends and, therefore, provides a functional indication that yeast chromosome extremities are topologically open. The gradual escape from the transcription stall along the chromosomal flanks also indicates that friction restrictions to DNA twist diffusion, rather than tight topological boundaries, might suffice to confine DNA helical tension along eukaryotic chromatin

Developmental delay and progressive seizures in 2-month-old child with diffuse MRI abnormalities

2 month-old infant presented with seizures, radiological findings of diffuse elevated T2 signal with frontal lobe sparing and extensive symmetrical post contrast enhancement. At autopsy, the brain stem was pale and atrophic, with areas of cystic degeneration. Medullary sections showed perivascular Rosenthal fibre deposition

Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks

We have compared a recently developed module-based algorithm LeMoNe for reverse-engineering transcriptional regulatory networks to a mutual information based direct algorithm CLR, using benchmark expression data and databases of known transcriptional regulatory interactions for Escherichia coli and Saccharomyces cerevisiae. A global comparison using recall versus precision curves hides the topologically distinct nature of the inferred networks and is not informative about the specific subtasks for which each method is most suited. Analysis of the degree distributions and a regulator specific comparison show that CLR is 'regulator-centric', making true predictions for a higher number of regulators, while LeMoNe is 'target-centric', recovering a higher number of known targets for fewer regulators, with limited overlap in the predicted interactions between both methods. Detailed biological examples in E. coli and S. cerevisiae are used to illustrate these differences and to prove that each method is able to infer parts of the network where the other fails. Biological validation of the inferred networks cautions against over-interpreting recall and precision values computed using incomplete reference networks.Comment: 13 pages, 1 table, 6 figures + 6 pages supplementary information (1 table, 5 figures

Plasmodium P-Type Cyclin CYC3 Modulates Endomitotic Growth during Oocyst Development in Mosquitoes

Cell-cycle progression and cell division in eukaryotes are governed in part by the cyclin family and their regulation of cyclin-dependent kinases (CDKs). Cyclins are very well characterised in model systems such as yeast and human cells, but surprisingly little is known about their number and role in Plasmodium, the unicellular protozoan parasite that causes malaria. Malaria parasite cell division and proliferation differs from that of many eukaryotes. During its life cycle it undergoes two types of mitosis: endomitosis in asexual stages and an extremely rapid mitotic process during male gametogenesis. Both schizogony (producing merozoites) in host liver and red blood cells, and sporogony (producing sporozoites) in the mosquito vector, are endomitotic with repeated nuclear replication, without chromosome condensation, before cell division. The role of specific cyclins during Plasmodium cell proliferation was unknown. We show here that the Plasmodium genome contains only three cyclin genes, representing an unusual repertoire of cyclin classes. Expression and reverse genetic analyses of the single Plant (P)-type cyclin, CYC3, in the rodent malaria parasite, Plasmodium berghei, revealed a cytoplasmic and nuclear location of the GFP-tagged protein throughout the lifecycle. Deletion of cyc3 resulted in defects in size, number and growth of oocysts, with abnormalities in budding and sporozoite formation. Furthermore, global transcript analysis of the cyc3-deleted and wild type parasites at gametocyte and ookinete stages identified differentially expressed genes required for signalling, invasion and oocyst development. Collectively these data suggest that cyc3 modulates oocyst endomitotic development in Plasmodium berghei

Validating module network learning algorithms using simulated data

In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance. Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators.Comment: 13 pages, 6 figures + 2 pages, 2 figures supplementary informatio

Vascular Imaging With 18^{18}F-Fluorodeoxyglucose Positron Emission Tomography Is Influenced by Hypoxia

This study was funded by a programme grant (RG/10/007/28300) from the British Heart Foundation (BHF). Dr. Joshi was supported by a BHF Clinical Research Training Fellowship (FS/12/29/29463), a British Atherosclerosis Society Binks Trust Travel Award, and a Raymond and Beverly Sackler PhD Studentship. Dr. Manavaki is funded by the NIHR Cambridge Biomedical Research Centre. Dr. Rudd is partially supported by the NIHR Cambridge Biomedical Research Centre, the BHF, The Wellcome Trust, and the EPSRC Cambridge Centre for Mathematical Imaging in Healthcare

Mineral dust increases the habitability of terrestrial planets but confounds biomarker detection

Identification of habitable planets beyond our solar system is a key goal of current and future space missions. Yet habitability depends not only on the stellar irradiance, but equally on constituent parts of the planetary atmosphere. Here we show, for the first time, that radiatively active mineral dust will have a significant impact on the habitability of Earth-like exoplanets. On tidally-locked planets, dust cools the day-side and warms the night-side, significantly widening the habitable zone. Independent of orbital configuration, we suggest that airborne dust can postpone planetary water loss at the inner edge of the habitable zone, through a feedback involving decreasing ocean coverage and increased dust loading. The inclusion of dust significantly obscures key biomarker gases (e.g. ozone, methane) in simulated transmission spectra, implying an important influence on the interpretation of observations.We demonstrate that future observational and theoretical studies of terrestrial exoplanets must consider the effect of dust