699. SCADOXUS NUTANS

Scadoxus nutans (Friis & I. Björnstad) Friis & Nordal is described and illustrated; its habitat, distribution and conservation status are discussed.     

Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs

One of the most important applications of genomic selection in maize breeding is to predict and identify the best untested lines from biparental populations, when the training and validation sets are derived from the same cross. Nineteen tropical maize biparental populations evaluated in multienvironment trials were used in this study to assess prediction accuracy of different quantitative traits using low-density (~200 markers) and genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs), respectively. An extension of the Genomic Best Linear Unbiased Predictor that incorporates genotype × environment (GE) interaction was used to predict genotypic values; cross-validation methods were applied to quantify prediction accuracy. Our results showed that: (1) low-density SNPs (~200 markers) were largely sufficient to get good prediction in biparental maize populations for simple traits with moderate-to-high heritability, but GBS outperformed low-density SNPs for complex traits and simple traits evaluated under stress conditions with low-to-moderate heritability; (2) heritability and genetic architecture of target traits affected prediction performance, prediction accuracy of complex traits (grain yield) were consistently lower than those of simple traits (anthesis date and plant height) and prediction accuracy under stress conditions was consistently lower and more variable than under well-watered conditions for all the target traits because of their poor heritability under stress conditions; and (3) the prediction accuracy of GE models was found to be superior to that of non-GE models for complex traits and marginal for simple traits.     

Ecological succession and its impact on malaria vectors and their predators in borrow pits in western Ethiopia

Soil pits excavated for home construction are important larval habitats for malaria vectors in certain parts of Africa. Borrow pits in diverse stages of ecological succession in a maize‐farming region of Western Ethiopia were surveyed to assess the relationships between stage of succession and the structure and composition of invertebrate and plant communities, with particular attention to Anopheles gambiae s.l. and An. coustani, the primary local malaria vectors. An array of 82 borrow pits was identified in a multi‐lobed drainage basin in the community of Woktola. Each pit was evaluated on its physical features and by faunal and floral surveys during August, 2011, at the height of the longer rainy season (kiremt). Anopheles gambiae s.l. and An. coustani were the sole immature anophelines collected, often coexisting with Culex spp. Sedges were the most common plants within these pits, and included Cyperus elegantulus, C. flavescens, C. erectus and C. assimilis. The legume Smithia abyssinica, Nile grass (Acroceras macrum), cutgrass (Leersia hexandra), clover (Trifolium spp.), and the edible herb Centella asiatica, were also common in these habitats. No plant species in particular was strongly and consistently predictive of the presence or absence of mosquito immatures, particularly with regard to An. coustani. The presence of An.gambiae s.l. immatures in borrow pit habitats was negatively correlated with the presence of backswimmers (Notonectidae) (Z = −2.34, P = 0.019). Young (freshly excavated) borrow pits more likely contained immature An. gambiae s.l. (Z =‐2.86, P=0.004). Ecological succession was apparent in older pits, and as they aged, they became less likely to serve as habitats for An. gambiae s.l. (Z=0.26, P=0.796), and more likely to support An. coustani (Z=0.728, P=0.007). As borrow pits age they become less suitable for An. gambiae s.l. breeding and more likely to harbor An. coustani. The abundance of notonectids in habitats was a negative indicator for An. gambiae s.l. abundance. Plant species are not reliable indicators for the presence or absence of malaria vectors in borrow pits.     

The implementation and impact of a pilot hydrocele surgery camp for LF-endemic communities in Ethiopia

BackgroundEthiopia aims to eliminate lymphatic filariasis by 2020, through a dual approach of mass drug administration to interrupt transmission and morbidity control which includes making hydrocele surgery available in all endemic areas. Locating patients requiring surgery, providing high quality surgeries, and following up patients are all formidable challenges for many resource-challenged or difficult-to-reach communities. To date, hydrocele surgery in Ethiopia has only occurred when a patient has the knowledge, time and resources to travel to regional hospitals. Ethiopia tested the novel approach of using a surgical camp, defined as mobilizing, transporting, providing surgery at a static site, and following up of a large cohort of hydrocele patients within a hospital’s catchment area, to address delays in seeking and receiving care.Methodology and resultsHealth extension workers mobilized 252 patients with scrotal swelling from a list of 385 suspected hydrocele cases from seven endemic districts in the region of Beneshangul-Gumuz. Clinical health workers and surgeons confirmed 119 as eligible for surgery. Of 70 additional patients who self-referred, 56 were eligible for surgery. Over a two-week period at a regional hospital, 175 hydrocele excision surgeries were conducted. After discharge three days after surgery, trained clinical health workers followed up with the patients on Day 5, Day 8, Day 14 and 1st-month benchmarks with a randomized follow-up of a selection of patients conducted at 9–12 months. There were no post-operative complications upon discharge at Day 3 and 22, while minor complications occurred (12.6%) between Day 3 and one month. The 9–12 month follow-up found patients self-reported an improvement in quality of life, health and economic status.ConclusionA hydrocele surgery camp was effective at providing a large number of quality surgeries in a short time. Using peripheral health workers to mobilize and follow up patients helped address delays in seeking and receiving quality care. Mainstreaming patient mobilization and follow-up into a community health system could be effective in other countries. The camp’s results also influenced two regions in Ethiopia to change their policies in order to offer free hydrocele surgery (including patient transport, consultation, surgery, diagnostic tests and necessary medications).     

Skew-normal random-effects model for meta-analysis of diagnostic test accuracy (DTA) studies

Hierarchical models are recommended for meta-analyzing diagnostic test accuracy (DTA) studies. The bivariate random-effects model is currently widely used to synthesize a pair of test sensitivity and specificity using logit transformation across studies. This model assumes a bivariate normal distribution for the random-effects. However, this assumption is restrictive and can be violated. When the assumption fails, inferences could be misleading. In this paper, we extended the current bivariate random-effects model by assuming a flexible bivariate skew-normal distribution for the random-effects in order to robustly model logit sensitivities and logit specificities. The marginal distribution of the proposed model is analytically derived so that parameter estimation can be performed using standard likelihood methods. The method of weighted-average is adopted to estimate the overall logit-transformed sensitivity and specificity. An extensive simulation study is carried out to investigate the performance of the proposed model compared to other standard models. Overall, the proposed model performs better in terms of confidence interval width of the average logit-transformed sensitivity and specificity compared to the standard bivariate linear mixed model and bivariate generalized linear mixed model. Simulations have also shown that the proposed model performed better than the well-established bivariate linear mixed model in terms of bias and comparable with regards to the root mean squared error (RMSE) of the between-study (co)variances. The proposed method is also illustrated using a published meta-analysis data.     

Vapor Phase Deposition, Structure, and Plasmonic Properties of Polymer-Based Composites Containing Ag–Cu Bimetallic Nanoparticles

Nanocomposite (NC) thin films with noble metal nanoparticles embedded in a dielectric material show very attractive plasmonic properties due to dielectric and quantum confinement effects. For single component nanoparticles (NPs), the plasmon resonance frequency can only be tuned in a narrow range. Much interest aroused in bimetallic nanoparticles (BNPs), however many wet chemical approaches do not allow large variation of the NP alloy composition and filling factor. Here, we report a vapor phase co-deposition method to produce polymer–metal NCs with embedded Ag_1 − x Cu _x alloy particles. The method allows production of NPs with controlled alloy composition (x), metal filling (f) and nanostructure in a protecting Teflon AF matrix. The nanostructure size and shape were characterized by transmission electron microscope. Energy dispersive X-ray spectroscopy was used to determine x and f. The optical properties and the position of surface plasmon resonances were studied by UV–Vis spectroscopy. The plasmon resonances can be tuned over a large range of the visible spectrum associated with the change in x, f, and nanostructure. For low filling factors and small particle sizes, only one resonance peak was observed. This is attributed to enhanced miscibility at the nanoscale. Double plasmon resonances were seen for larger particle sizes in accord with phase separation expected from the bulk phase diagram and were explained in terms of the formation of core-shell structures with Cu core and Ag shell. Changes upon annealing at 200 °C are also reported.     

Epilithic diatoms as indicators in tropical African rivers (Lake Victoria catchment)

We investigated epilithic diatoms in rivers draining to the Nyanza Bay in Lake Victoria (Kenya) with the aim of determining environmental gradients in the assemblages and testing the usefulness of diatom metrics from temperate regions. Spatial and temporal variations of assemblages were studied in 12 sites of three rivers. Kibos, Nyando, and Kisat rivers contained 224 diatom taxa collected on seven sampling occasions over 4 years. Species richness showed a marginal decrease downstream and was the lowest at sites with high conductivity and ammonia–nitrogen levels. Two-Way Indicator Species Analysis and Canonical Correspondence Analysis revealed two major groups of river sites. Conductivity, alkalinity, turbidity, dissolved oxygen, and silicate were the most important variables influencing species distribution. Ecological diatom metrics of temperate regions and the Specific Pollution sensitivity Index showed good relationships with environmental variables. Both diatom assemblages and averaged indicator values were strong in predicting sites of ecological deterioration and in differentiating an upstream site of better quality (drinking water supply of Kisumu), thereby confirming epilithic diatoms as suitable water quality indicators in equatorial rivers. The use of metrics initially designed for temperate rivers, however, appears less valuable in good quality tropical rivers because potential indicators are not considered.     

Genetic diversity in traditional Ethiopian highland maize accessions assessed by AFLP markers and morphological traits

In the highland regions of Ethiopia the heterogeneity of the land, the climate, and soil favors the presence of a large number of landraces. We analyzed a representative sample of 62 traditional Ethiopian highland maize accessions, using amplified fragment length polymorphism (AFLP^®) markers and morphological traits with the aim to group the accessions based on the their genetic profiles and morphological traits, to study agroecological variation and to assess the level of correlation between phenotypic and genetic distances. Eight EcoRI/MseI primer combinations and 15 morphological traits were used. The accessions varied significantly for all of the measured morphological traits. Of a total of 650 AFLP markers that were scored, 89.5% were polymorphic. Pair-wise genetic distance estimates based on AFLP data revealed dissimilarity coefficients ranging from 0.32 to 0.69 (mean of 0.57). Cluster analysis of the AFLP data grouped most accessions collected from the Northern highlands into one major cluster. It, however, failed to separate the Western and Southern accessions into different clusters. Regardless of the large variation in environmental conditions between agroecologies, only 9% of the total genetic variation was found between agroecologies, whereas 91% was found within agroecologies in Ethiopia. This finding may be explained by long distance seed exchange, continuous seed introduction and gene flow between agroecologies. The relationship between morphological and AFLP-based distances was significant and positive. Based on this study, three groups of highland accessions, with distinctive genetic profiles and morphological traits were identified. This information will be useful for further collections and conservation of the unique diversity included in the highland maize landraces of Ethiopia.     

Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices

Genomic prediction models are often calibrated using multi-generation data. Over time, as data accumulates, training data sets become increasingly heterogeneous. Differences in allele frequency and linkage disequilibrium patterns between the training and prediction genotypes may limit prediction accuracy. This leads to the question of whether all available data or a subset of it should be used to calibrate genomic prediction models. Previous research on training set optimization has focused on identifying a subset of the available data that is optimal for a given prediction set. However, this approach does not contemplate the possibility that different training sets may be optimal for different prediction genotypes. To address this problem, we recently introduced a sparse selection index (SSI) that identifies an optimal training set for each individual in a prediction set. Using additive genomic relationships, the SSI can provide increased accuracy relative to genomic-BLUP (GBLUP). Non-parametric genomic models using Gaussian kernels (KBLUP) have, in some cases, yielded higher prediction accuracies than standard additive models. Therefore, here we studied whether combining SSIs and kernel methods could further improve prediction accuracy when training genomic models using multi-generation data. Using four years of doubled haploid maize data from the International Maize and Wheat Improvement Center (CIMMYT), we found that when predicting grain yield the KBLUP outperformed the GBLUP, and that using SSI with additive relationships (GSSI) lead to 5–17% increases in accuracy, relative to the GBLUP. However, differences in prediction accuracy between the KBLUP and the kernel-based SSI were smaller and not always significant.Subject terms: Quantitative trait, Genetic models     

Veterinary medicinal product usage among food animal producers and its health implications in Central Ethiopia

Background

Antimicrobials and anthelmintics are the most commonly used veterinary drugs to control animal diseases. However, widespread use of these drugs could contribute to the emergence of drug resistance. Information on the practice of antimicrobial usage among food animal raising communities in Central Ethiopia is scarce. We used a standardised questionnaire survey to assess knowledge, awareness, and practices related to drug use and resistance in food animals among the farmers in and around Bishoftu town.

Results

Of the total of 220 livestock owners interviewed, around 80% of the respondents were not able to define what antimicrobials are and for what purposes they are used. Only 14.1% (n?=?31) of the respondents had awareness about antimicrobial resistance (AMR) and its consequences; and 35.5% (n?=?11/31) and 9.7% (n?=?3/31) of them agreed that the irrational use of antimicrobials in animals could lead to AMR in animals and humans. Oxytetracycline was the most commonly available antibiotic in veterinary drug shops/pharmacies and the most widely used drug in the area. However, 43.3% of the respondents did not see clinical improvements after using antibiotics. Similarly, the respondents explained that no response was observed in 73.3, 70.8 and 52.5% of the cases after medication with anthelmintics, antiprotozoal and acaricides, respectively. About 56.7% of the respondents considered traditional medicines equally important to modern medicines. It was also noted that there were illegal drug vendors, dispensing medicines under unfavourable conditions which include a direct exposure to sunlight, which practice violates the drug handling and storage recommendations given by WHO.

Conclusion

The study revealed that there is a general lack of awareness among food animal owners about the correct use of antibiotics and anthelmintics. The widespread misuse and improper drug dispensing and handling practices observed in this study can affect the drug quality and can also contribute to the development of drug resistance in central Ethiopia.