<i>Trypanosoma brucei rhodesiense</i> transmitted by a single tsetse fly bite in vervet monkeys as a model of human African trypanosomiasis

Sleeping sickness is caused by a species of trypanosome blood parasite that is transmitted by tsetse flies. To understand better how infection with this parasite leads to disease, we provide here the most detailed description yet of the course of infection and disease onset in vervet monkeys. One infected tsetse fly was allowed to feed on each host individual, and in all cases infections were successful. The characteristics of infection and disease were similar in all hosts, but the rate of progression varied considerably. Parasites were first detected in the blood 4-10 days after infection, showing that migration of parasites from the site of fly bite was very rapid. Anaemia was a key feature of disease, with a reduction in the numbers and average size of red blood cells and associated decline in numbers of platelets and white blood cells. One to six weeks after infection, parasites were observed in the cerebrospinal fluid (CSF), indicating that they had moved from the blood into the brain; this was associated with a white cell infiltration. This study shows that fly-transmitted infection in vervets accurately mimics human disease and provides a robust model to understand better how sleeping sickness develops

Evidence from GC-TRFLP that Bacterial Communities in Soil Are Lognormally Distributed

The Species Abundance Distribution (SAD) is a fundamental property of ecological communities and the form and formation of SADs have been examined for a wide range of communities including those of microorganisms. Progress in understanding microbial SADs, however, has been limited by the remarkable diversity and vast size of microbial communities. As a result, few microbial systems have been sampled with sufficient depth to generate reliable estimates of the community SAD. We have used a novel approach to characterize the SAD of bacterial communities by coupling genomic DNA fractionation with analysis of terminal restriction fragment length polymorphisms (GC-TRFLP). Examination of a soil microbial community through GC-TRFLP revealed 731 bacterial operational taxonomic units (OTUs) that followed a lognormal distribution. To recover the same 731 OTUs through analysis of DNA sequence data is estimated to require analysis of 86,264 16S rRNA sequences. The approach is examined and validated through construction and analysis of simulated microbial communities in silico. Additional simulations performed to assess the potential effects of PCR bias show that biased amplification can cause a community whose distribution follows a power-law function to appear lognormally distributed. We also show that TRFLP analysis, in contrast to GC-TRFLP, is not able to effectively distinguish between competing SAD models. Our analysis supports use of the lognormal as the null distribution for studying the SAD of bacterial communities as for plant and animal communities

Telomere length and bipolar disorder

Variation in telomere length is heritable and is currently considered a promising biomarker of susceptibility for neuropsychiatric disorders, particularly because of its association with memory function and hippocampal morphology. Here, we investigate telomere length in connection to familial risk and disease expression in bipolar disorder (BD). We used quantitative polymerase chain reactions and a telomere-sequence to single-copy-gene-sequence ratio method to determine telomere length in genomic DNA extracted from buccal smears from 63 patients with BD, 74 first-degree relatives (49 relatives had no lifetime psychopathology and 25 had a non-BD mood disorder) and 80 unrelated healthy individuals. Participants also underwent magnetic resonance imaging to determine hippocampal volumes and cognitive assessment to evaluate episodic memory using the verbal paired associates test. Telomere length was shorter in psychiatrically-well relatives (p=0.007) compared to unrelated healthy participants. Telomere length was also shorter in relatives (regardless of psychiatric status; p<0.01) and patients with BD not on lithium (p=0.02) compared to lithium-treated patients with BD. In the entire sample, telomere length was positively associated with left and right hippocampal volume and with delayed recall. This study provides evidence that shortened telomere length is associated with familial risk for BD. Lithium may have neuroprotective properties that require further investigation using prospective designs

Assessing producers’ perceptions of protecting coffee and apple mangoes as geographical indications in Kenya

Consumers are increasingly demanding for information on product quality, methods and characteristics of geographical region of production. As such, protecting unique products as geographical indications is on the increase. Geographical indications identify a product as originating from a region where a given quality, reputation or other characteristic desired by consumers, is essentially or exclusively attributable to its geographical origin. Having the legal legislation is necessary but not sufficient factor in protection of products as geographical indications (GI). Other essential factors include the producers’ awareness of the uniqueness and willingness to register the product for protection and marketing. Their perceived benefits and other characteristics will influence their decision to register the product as a GI. The study sought to understand underlying variables describing producers’ perceptions of the quality of coffee in Muranga and mango in Makueni as potential geographical indications. At least 132 producers randomly sampled were interviewed in each county using semi-structured questionnaires. The study applied factor analysis to summarise producers’ perceptions and regressed the resulting factors against a set of explanatory variables to determine factors influencing these perceptions. Six and five underlying variable (factors) were identified for coffee and mango producers’ perceptions respectively. The factors explained at least 75.3% and 71.5% of the variance in the original variables for coffee and mango producers’ perceptions respectively. The regression results with varying Fstatistics showed the importance of conducting specific analysis for each product in each region to identify the potential for protecting the products as GI

ASSESSING DIFFERENTIAL GAINS THAT OUTSTANDING AND AVERAGE PERFORMING FARMERS ATTAIN FROM CLIMATE-SMART CASSAVA INNOVATIONS IN NYANDO CLIMATE-SMART VILLAGES, KENYA

In adoption of agricultural innovations, a few farmers attain outstanding outcomes above their peer majority. This reveals a positive deviance behavior in successful deployment of technologies and innovations. Assessing this behavior in climatesmart agriculture (CSA) can reveal the yield gap in triple wins of CSA (adaptation, farm productivity and mitigation). This study investigated differential gains in these CSA triple wins between outstanding (positive deviants) and average (typical) performing farmers who have adopted climate smart cassava innovations in Nyando Climate Smart Villages (CSV). In a household survey, a sample of 150 farmers were reached, which through snowballing approach, peers identified 30 to exhibit positive deviant behaviour. Presenting these in Focus Group Discussion (FGD) with stakeholders further isolated six farmers being those they consider positive deviants (PDs) in climate smart cassava innovations. Data were subjected to cross-tabulation to generate frequencies used to compute weighted index scores. This revealed increasing magnitude and was a preferred fair comparison of a sample of fewer positive deviants (n=6) with large number of typical (n=144) farmers. Results revealed substantial differences in the attained triple win gains from climate smart cassava innovations between typical and positive deviant farmers. The weighted index scores showed that positive deviant farmers had attained higher adaptability, production diversification, farm productivity and intensification, food security and were implementing more mitigation practices for climate change. This empirical evidence demonstrates potential gains from climate smart cassava innovations when deployed effectively. This is because innovative management practices distinguish positive deviant farmers from typical farmers. These typical farmers would benefit more by learning from positive deviant farmers about effective deployment of climate smart cassava innovations. The study recommends strengthening extension services linked to farmer platforms in order to grow capacity for more effective deployment of climate smart cassava innovations for realising the CSA triple wins