Effects of akidi (Vigna unguiculata sub spp. Sesquipedalis) planting density on growth, yields and land use efficiency of akidi/cassava intercrop

Field experiment was conducted at the Teaching and Research Farm, College of Education, Afaha Nsit, Akwa Ibom State, Nigeria to determine the effects of akidi (vegetable cowpea) planting density on growth, yields and productivity of akidi /cassava intercropping system in 2008 and 2009 planting seasons. The experiment was laid out in randomized complete block design with three replicates. Treatments were seven akidi populations of 20,000, 30,000, 40,000, 50,000, 60,000, 70,000 plants/ha and a sole cassava. Akidi was also planted sole and in intercropped with cassava. Results indicated that the average plant height of 180.66 and 180.74 cm obtained from the akidi plots at 60,000 and 70,000 plants/ha was significantly (P<0.05) higher than the average of 170.12cm obtained from sole cassava. Similar trend was also observed in cassava leaf area index. A significantly (P<0.05) lowest number of pods/plant (7.37) was obtained from the intercropped plots of akidi (70,000 plants/ha). Dry seed yield of 313.00 kg/ha obtained from the sole plots of akidi (60,000 plants/ha) was significantly higher than 284.97 kg/ha obtained from intercropping akidi at the same planting density. Akidi plots at 60,000 and 70,000 plants/ha produced significantly higher cassava tuberous root yields than the yields obtained from sole cassava and from the plots of other akidi densities in the intercrop. Although akidi at 70,000 plants/ha produced the highest cassava tuberous root yield advantage by 30.1 % over sole cassava; the highest land equivalent ratio (2.34) was however obtained from akidi plots at 60,000 plants/ha. From this study, it appears that integration of optimum akidi density (60,000 plants/ha) in cassava intercrop can enhance cassava growth, tuberous root yield and increased land use efficiency. Keywords: Akidi, Cassava, Intercrop, planting density, yields, land use efficiency

Extracts of Pterocarpus osun as a histological stain for collagen fibres

The staining ability of Pterocarpus osun extract on tissue sections was determined. 2 kg of P. osun stem was dried, milled to obtain a fine powder and a red pigment extracted from the powder with 1 L of 70% ethanol at 78°C for 24 h. The alcoholic and acidic extracts were used to stain tissue sections. Collagen fibres, red blood cells and muscles were stained in shades of reddish brown. Preliminary phytochemical screening of this extract revealed that it contained alkaloids, steroid ring, cardiac glycosides and reducing sugar.African Journal of Biotechnology Vol. 4 (5), pp. 460-462, 200

PREVALENCE AND FACTORS ASSOCIATED WITH URINARY SCHISTOSOMIASIS AMONG INFANTS AND PRESCHOOL-AGED CHILDREN IN SETTLEMENTS AROUND OYAN RESERVOIR IN OGUN STATE, NIGERIA

The need for more information on the risk factors for schistosomiasis among infants and preschool-aged children as become important for the development of health education programme since this age group is currently excluded in preventive chemotherapy programmes.  Therefore, the prevalence and intensity of, and risk factors for, infant and preschool-aged children infection with Schistosoma haematobium were explored in two endemic settlements around Oyan Reservior in Ogun State, Nigeria. Mothers and caregivers’ knowledge of the disease, water contact activities of their preschooler, age at first exposure and control measures were recorded using a structured questionnaire. Of the 86 preschooler screened from the two settlements 46 (53.5%) were infected, with an overall geometric mean intensity of 0.36 eggs/10 ml urine. The prevalence of egg-patent S. haematobium infection was 27.8% in Ibaro and 72.0% in Imala-Odo respectively. There were significant differences in prevalence (P=0.0005) and intensity (P=0.0006) of infection between the two communities, however, these did not increase significantly with age in both communities.  Interviews revealed that preschoolers were exposed to infected reservoir water as early as after birth, while older preschoolers frequently visited water bodies on their own to play, bath and wash cloth. There was significant reduction in prevalence of schistosomiasis among preschool-aged children in Ibaro community compared to Imala-Odo community; this could be attributed to awareness about the disease, and its mode of transmission.  Intensive health education still remains the alternative for reducing transmission in preschoolers in the absence of standardized treatment dosage for them.Â

Cross-Location Analysis of the Impact of Household Socioeconomic Status on Participation in Urban and Peri-Urban Agriculture in West Africa

This study explores the relation between household socioeconomic status (SES) and participation in urban and periurban agriculture (UPA) in three West African cities. We used a structured questionnaire to survey 700 randomly selected households: 250 in Kano, Nigeria, 250 in Bobo Dioulasso, Burkina Faso, and 200 in Sikasso, Mali. Multiple correspondence analysis was applied on household asset variables to create an index of assets which was used as a proxy for household SES. The results showed no significant differences in households’ rate of participation in UPA across socioeconomic groups. Participation in UPA was rather significantly (P < 0.001) and positively related to household size. Interestingly, the analysis revealed that field crop cultivation and gardening were more common among households in the low and medium SES groups while those in the high SES group were more likely to keep livestock

Emergence and spread of two SARS-CoV-2 variants of interest in Nigeria.

Identifying the dissemination patterns and impacts of a virus of economic or health importance during a pandemic is crucial, as it informs the public on policies for containment in order to reduce the spread of the virus. In this study, we integrated genomic and travel data to investigate the emergence and spread of the SARS-CoV-2 B.1.1.318 and B.1.525 (Eta) variants of interest in Nigeria and the wider Africa region. By integrating travel data and phylogeographic reconstructions, we find that these two variants that arose during the second wave in Nigeria emerged from within Africa, with the B.1.525 from Nigeria, and then spread to other parts of the world. Data from this study show how regional connectivity of Nigeria drove the spread of these variants of interest to surrounding countries and those connected by air-traffic. Our findings demonstrate the power of genomic analysis when combined with mobility and epidemiological data to identify the drivers of transmission, as bidirectional transmission within and between African nations are grossly underestimated as seen in our import risk index estimates

A machine learning model based on readers' characteristics to predict their performances in reading screening mammograms

Objectives: Proposing a machine learning model to predict readers’ performances, as measured by the area under the receiver operating characteristics curve (AUC) and lesion sensitivity, using the readers’ characteristics. Methods: Data were collected from 905 radiologists and breast physicians who completed at least one case-set of 60 mammographic images containing 40 normal and 20 biopsy-proven cancer cases. Nine different case-sets were available. Using a questionnaire, we collected radiologists’ demographic details, such as reading volume and years of experience. These characteristics along with a case set difficulty measure were fed into two ensemble of regression trees to predict the readers’ AUCs and lesion sensitivities. We calculated the Pearson correlation coefficient between the predicted values by the model and the actual AUC and lesion sensitivity. The usefulness of the model to categorize readers as low and high performers based on different criteria was also evaluated. The performances of the models were evaluated using leave-one-out cross-validation. Results: The Pearson correlation coefficient between the predicted AUC and actual one was 0.60 (p < 0.001). The model’s performance for differentiating the reader in the first and fourth quartile based on the AUC values was 0.86 (95% CI 0.83–0.89). The model reached an AUC of 0.91 (95% CI 0.88–0.93) for distinguishing the readers in the first quartile from the fourth one based on the lesion sensitivity. Conclusion: A machine learning model can be used to categorize readers as high- or low-performing. Such model could be useful for screening programs for designing a targeted quality assurance and optimizing the double reading practice