A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data.

BACKGROUND: The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. RESULTS: Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. CONCLUSIONS: In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data

Characterization of Phosphate Solubilizing Faba Bean (Vicia faba L.) Nodulating Rhizobia Isolated from Acidic Soils of Wollega, Ethiopia

Some species of rhizobial bacteria nodulating faba bean are characterized by phosphate solubilization. In order to study their in vitro and symbiotic characteristics, twelve rhizobial isolates nodulating faba bean were collected from acidic soil of Wollega, Ethiopia. Solubilization index of the isolates ranges from 1.25 to 2.10. Mean Generation Time of the isolates were less than 2.34; and growth of isolates on Yeast Extract Mannitol agar with bromothymoleblue media were accompanied by change of color from blue to yellow. AUAVR-51 and AUAVR-52 were the highest in TCP-Solubilizion Index. The two isolates were also recognized as stress tolerant when tested in vitro for extreme temperature, osmotic, acidic pH, intrinsic antibiotics, and acidic-aluminum as compared to the other isolates. However, there was no unique metabolic diversity and specialization of AUAVR-51 and AUAVR-52 isolates with respect to carbon and nitrogen source utilization. On the other hand, isolates AUAVR-51 and AUAVR-52 were characterized by effective and highly effective symbiosis on sterile potted sand growth, respectively. In general, phosphate solubilizing rhizobia nodulating faba bean from acidic soil are fast grower; and their solubilization potential varies. However, the contribution of these isolates as double fertilizer should be tested in the real acidic soil characterized by immobilized phosphorous.Keywords: Faba bean Rhizobial isolates Phosphate solubilization Symbiotic effectivenes

Socio-Economic Impact Assessment of Integrated Watershed Management in Sheka Watershed, Ethiopia.

Integrated watershed management (IWSM) was taken as the basic operational unit to rehabilitate degraded watershed and improve agricultural productivity in Ethiopia. However, its effectiveness was rarely evaluated. Therefore, this study assessed the contribution of IWSM in selected socio-economic benefits in Sheka watershed, Ethiopia. Crop grain yield measurements and questionnaire survey data collection methods were employed. Statistical methods were used to analyze the data. The results revealed that there were significantly higher teff and sorghum grain yields in the treated sub-watershed than the untreated one. Milk yield of local dairy cow and honey bee yield was increased by 12.3% and 24.24%, respectively, after IWSM. Annual household income of downstream beneficiaries of the watershed was significantly higher than upstream beneficiaries. The highest annual income was recorded from the users of both improved livestock and irrigation. The most determinant factors for household annual income were irrigation access, livestock number, cultivated land and off-farm income. The average contribution of income generating activities of IWSM in household annual income was 31.3%. Therefore, IWSM is not only effective in increasing crop and livestock production but also it has high contribution in household annual income.  But high focus should be given to the upper beneficiaries of the watershed so as to minimize the income difference between the upper and lower beneficiaries. Thus, it is better to introduce IWSM in to the untreated watershed. Key words: Integrated watershed management, upstream, downstream, Sheka watershed

Radiological Features and Postoperative Histopathologic Diagnosis of Intracranial Masses at Tikur Anbessa Specialized Hospital and MCM Hospital

Background: Intracranial mass lesions are common causes of neurological morbidity and are detectable by cranial imaging. Given the wide range of pathological processes that can present as intracranial mass lesions, the radiologist can limit the differential diagnosis to inform clinical decision-making. The main objective of this review was to analyze radiologicfeatures and postoperative histopathology diagnosis of intracranial mass lesions.Methods: A cross sectional study was conducted on 96 patients who underwent surgery for intracranial mass lesions at Tikur Anbessa Specialized Hospital (TASH) and Myungsung Christian Medical Center (MCM) in a period of 3 years (Feb 2009-Dec 2011). Patients werelimited to those who had histopathologic result and either CT (n=67), MRI (n=14) scan report or both (n=15).Results: Histopathologically confirmed intracranial masses constituted meningioma = 32 (39%), glioma =15 (18.3%), pituitary adenoma = 14 (17%), and tuberculoma = 6 (7.3%).The CT scan sensitivity, specificity, and accuracy in differentiating meningiomas from other intracranial masses, taking the first differential as most likely diagnosis, was 80%, 95% and 88.6% whereas for gliomas it was 71%, 85.7% and 83% respectively. The higher rate of meningiomas found in this study may result from surgeons bias toward preference of resection of extra axial tumors or longer survival of meningioma patients.Conclusion: Meningiomas were the commonest histologically diagnosed intracranial mass lesions followed by glioma, but their prevalence may have been overestimated in this study because surgeons are more likely to resect them and confirm their diagnosis. Tuberculoma was the commonest non-tumor lesion. CT scan was more accurate, sensitive and specific in diagnosing benign than malignant masses

Occurrence of fungal diseases of Coffea arabica L. in montane rainforests of Ethiopia

Coffee Berry Disease (CBD), Colletotrichum kahawae, Coffee Wilt Disease (CWD), Gibberella xylarioides and Coffee Leaf Rust (CLR), Hemileia vastatrix are the three major diseases reducing production and consumption of coffee in Ethiopia. A survey was conducted from July to September 2005 for CBD and CWD and from 2003 until 2007 for CLR in montane rainforest coffee areas of Ethiopia to estimate the occurrence and distribution of these diseases. Diseases were prevalent in all the surveyed forest coffee areas of Ethiopia: Harenna, Bonga, Berhane-Kontir and Yayu. Depending on the forest coffee area the mean percent incidence of CBD ranged from 2 to 40 % in general and from 2 to 17.9 % at Berhane-Kontir and Bonga, respectively. The mean incidence of CWD varied from 2.4 % at Berhane-Kontir to 16.9 % at Yayu forest coffee areas. The mean incidence of CLR also varied for instance in 2005 from 32.2 % at Berhane-Kontir to 96 % at Harenna forest coffee areas. The detection of the diseases during our surveys requires an integrated management of major coffee diseases for a sustainable conservation and wise use of coffee in montane rainforests of Ethiopia

Nutritional, eco-physiological and symbiotic characteristics of rhizobia nodulating faba bean (Vicia faba L.) collected from acidic soils of Ethiopia

Characterization of root nodule bacteria is used for selecting and using them as inoculants to improve legume production. To this end, faba bean (Vicia faba L.) rhizobia were isolated from nodules collected from acidic soils of Central and Southern-Western parts of Ethiopia. A total of hundred rhizobial isolates were collected and characterized based upon their nutritional, ecophysiological and symbiotic characteristics. The isolates produced low to copious amount of extracellular polysaccharides (EPS) and attain colony sizes ranging from 2 to 7 mm with generation time ranging 0.75 to 3.9 h. Most of the isolates were grown at different pH levels ranging 4.5 to 7.0 and temperatures between 4 and 45°C. They were also capable of growing on many carbon sources and most of the nitrogen sources, and showed significant variations in resisting different types of antibiotics and heavy metals. Based on symbiotic efficiency (SE), 56% of the isolates were found to be very effective when applied with both Degaga and Dosha varieties. All taken together, two isolates, HUGAVf1 and HUCDVf5 were nutritionally versatile, showed a wide range of tolerance to the stress in many of the ecophysiological characters and very effective symbiotic performance should be utilized in future faba bean inoculants production.Key words: Rhizobium leguminosarum biovar. viceae, antibiotic tolerance, carbon utilization, fast growing, heavy metals, temperature tolerance

Ending Neglect of older people in the response to Humanitarian Emergencies

Older people make up a significant and growing number of those affected by humanitarian crises, yet they are often not sought out or prioritised within the humanitarian response. Humanitarian agencies, donors, and international bodies neglect older people's health and nutrition. The gaps in knowledge and research about the needs of older people in emergencies are considerable. Older people are not monitored in emergencies and they are not prioritised despite evidence of disproportionate mortality and morbidity in this group. We call for policy changes by humanitarian agencies and donors to ensure that the needs of this vulnerable group are met

Human concept cognition and semantic relations in the unified medical language system: A coherence analysis.

There is almost a universal agreement among scholars in information retrieval (IR) research that knowledge representation needs improvement. As core component of an IR system, improvement of the knowledge representation system has so far involved manipulation of this component based on principles such as vector space, probabilistic approach, inference network, and language modeling, yet the required improvement is still far from fruition. One promising approach that is highly touted to offer a potential solution exists in the cognitive paradigm, where knowledge representation practice should involve, or start from, modeling the human conceptual system. This study based on two related cognitive theories: the theory-based approach to concept representation and the psychological theory of semantic relations, ventured to explore the connection between the human conceptual model and the knowledge representation model (represented by samples of concepts and relations from the unified medical language system, UMLS). Guided by these cognitive theories and based on related and appropriate data-analytic tools, such as nonmetric multidimensional scaling, hierarchical clustering, and content analysis, this study aimed to conduct an exploratory investigation to answer four related questions. Divided into two groups, a total of 89 research participants took part in two sets of cognitive tasks. The first group (49 participants) sorted 60 food names into categories followed by simultaneous description of the derived categories to explain the rationale for category judgment. The second group (40 participants) performed sorting 47 semantic relations (the nonhierarchical associative types) into 5 categories known a priori. Three datasets resulted as a result of the cognitive tasks: food-sorting data, relation-sorting data, and free and unstructured text of category descriptions. Using the data analytic tools mentioned, data analysis was carried out and important results and findings were obtained that offer plausible explanations to the 4 research questions. Major results include the following: (a) through discriminant analysis category members were predicted consistently in 70% of the time; (b) the categorization bases are largely simplified rules, naïve explanations, and feature-based; (c) individuals theoretical explanation remains valid and stays stable across category members; (d) the human conceptual model can be fairly reconstructed in a low-dimensional space where 93% of the variance in the dimensional space is accounted for by the subjects performance; (e) participants consistently classify 29 of the 47 semantic relations; and, (f) individuals perform better in the functional and spatial dimensions of the semantic relations classification task and perform poorly in the conceptual dimension