Temperature-dependent Development of Four Egg Parasitoid Trichogramma Species (Hymenoptera: Trichogrammatidae)

Trichogramma species have been successfully utilized for biocontrol of several lepidopteran pests worldwide. The development, survival and progeny production of two Kenyan species' Trichogramma bournieri Pintureau & Babault and Trichogramma sp. nr. mwanzai Schulten & Feijen (collected from Kenya), Trichogramma evanescens Westwood (Germany) and Trichogramma chilonis Ishii (India) was studied at four constant temperatures (13, 18, 25 and 34°C) with the 011 aim of assessing the relative biotic potential of the two native species for 011 biocontrol of Helicoverpa armigera and Plutella xylostella in Kenya. The study was conducted at the Institute 011 for Biological Control (BBA), Darmstadt, Germany. The Trichogramma species tested showed variations 011 in fertility, developmental time, percent emergence, progeny production and sex ratio 011 at the four temperature regimes. Fertility decreased as temperature increased from 25 to 34°C. 011 T. chilonis and T. evanescens completed development at all temperatures tested, but T. 011 bournieri and T. sp. nr. mwanzai failed to complete development at 13°C. The developmental 011 period for all the species decreased as the temperature increased. The duration of development from 011 oviposition to adult emergence varied from 8 days to 12 weeks shorter at 34°C than at 011 13°C for T. chilonis and T. evanescens . For the various temperatures tested, a linear model was 011 satisfactory for egg to adult development at P = 0.05 for T. chilonis and T. evanescens . The 011 lower temperature thresholds for development and duration in degree-days were 8.83°C and 188 for 011 T. chilonis and 9.23°C and 192 for T. evanescens , respectively. For all temperatures tested, 011 T. sp. nr. mwanzai had the highest preimaginal survivorship. Adult emergence was lower at 13°C and 34°C than at 011 18 and 25°C. The highest fertility (mean ±SE) (50.37 ±2.32 adult 011 female -1 ) and progeny production (44.03 ±2.02 adult female -1 ) was recorded at 25°C for 011 T. evanescens . Sex ratio was biased towards female at all temperatures in T. bournieri and T. chilonis . 011 At all temperatures tested, T . sp. nr. mwanzai produced more males than females. For all species tested, 011 favourable parasitism was between 18 and 25°C. The results from this study will be useful for mass rearing purposes as well as for future field release programmes.     

Access to Water Source,Latrine Facilities and Other Risk Factors of Active Trachoma in Ankober,Ethiopia

Objective

This study aims to determine the prevalence and correlates of active trachoma in Ankober, Ethiopia.

Methods

A cross-sectional community-based study was conducted during July 2007. A total of 507 children (ages 1–9 years), from 232 households were included in the study. All children were examined for trachoma by ophthalmic nurses using the WHO simplified clinical grading system. Interviews and observations were used to assess risk factors. Logistic regression procedures were used to determine associations between potential risk factors and signs of active trachoma.

Results

Overall, the prevalence of active trachoma was found to be 53.9% (95%CI 49.6%–58.2%). Presence of fly-eye (fly contact with the eyelid margin during eye examination) (Odds Ratio (OR) = 4.03 95% CI 1.40–11.59), absence of facial cleanliness (OR = 7.59; 95%CI 4.60–12.52), an illiterate mother (OR = 5.88; 95%CI 2.10–15.95), lack of access to piped water (OR = 2.19; 95%CI 1.14–6.08), and lack of access to latrine facilities (OR = 4.36; 95%CI 1.49–12.74) were statistically significantly associated with increased risk of active trachoma.

Conclusion

Active trachoma among children 1–9 years of age in Ankober is highly prevalent and significantly associated with a number of risk factors including access to water and latrine facilities. Trachoma prevention programs that include improved access to water and sanitation, active fly control, and hygiene education are recommended to lower the burden of trachoma in Ankober, Ethiopia.     

Effect of Brassica carinata (L.) biofumigants (seed meal) on chickpea wilt (Fusarium oxysporum f.sp. ciceris), growth,yield and yield component in Ethiopia

Pot experiments were carried out in the green house at Amhara Regional Agriculture Research Institute (ARARI) Bahirdar, Ethiopia to evaluate the potential of Brassica carinata cultivars namely; Holleta-l, S-67 and Yellow Dodola in 2007 and 2008. The treatment effects of B. carinata (L.) cultivars Holleta–1, S-67 and Yellow Dodola seed meals on chickpea fusarium wilt (Fusarium oxysporum f.sp. ciceris) were studied. Six rates of seed (0, 5, 10, 15, 20 and 25 g/kg of infested soil) were used. Infested soil without B.carinata cultivars amendments as a control and susceptible check variety JG-62 also without amendments were used in all the experiments. For each seed meal experiment, the treatments were arranged in factorial randomised complete block design in three replications. Data on seedling emergence, wilt incidence, fresh weight, dry weight, pod per plant, seed per pod, hundred seed weight and yield per hectare were collected. The amendments of infested soil with B.carinata cultivars seed meal reduced the incidence of chickpea fusarium wilt and increased yield per hectare. The interaction of the seed meal Holleta-1, S-67 and Yellow Dodola at 10–25 g/kg infested soil were effective in reducing wilt incidences on chickpea. However, the interaction of Yellow Dodola with 20 and 25 g seed meal per kg infested soil were the best combination in reducing significantly wilt incidence. The three cultivars incorporated at different level of doses significantly affected the influence of Fusarium wilt on the fresh weight, dry weight, pod per plant, seed per pod, hundred seed weight and yield per hectare. The highest yield kg/ha was recorded in combination of Yellow Dodola seed meal at 20 and 25 g followed by S-67 and Holleta-1 at 25 g /kg infested soil, respectively. The interaction of Holleta-1 at 5–25 infested soil significantly reduced disease incidence up to 16.7–43.3% and increased yield per hectare with mean by (30%) over the control. Seed meal amendment S-67 significantly reduce disease incidence 26.7–46.7% and increased yield kg/ha with mean by (36.7%) from the unamended control. Yellow dodola reduces disease incidence with 26.7–63.3% and increased yield kg/ha with mean by (45%) from the unamended control. The result indicates the potential of using Brassica crop seed meal amendment as useful component of integrated chickpea wilt management.     

The Outcome of Trachomatous Trichiasis Surgery in Ethiopia: Risk Factors for Recurrence

Background

Over 1.2 million people are blind from trachomatous trichiasis (TT). Lid rotation surgery is the mainstay of treatment, but recurrence rates can be high. We investigated the outcomes (recurrence rates and other complications) of posterior lamellar tarsal rotation (PLTR) surgery, one of the two most widely practised TT procedures in endemic settings.

Methodology/Principal Findings

We conducted a two-year follow-up study of 1300 participants who had PLTR surgery, conducted by one of five TT nurse surgeons. None had previously undergone TT surgery. All participants received a detailed trachoma eye examination at baseline and 6, 12, 18 and 24 months post-operatively. The study investigated the recurrence rates, other complications and factors associated with recurrence. Recurrence occurred in 207/635 (32.6%) and 108/641 (16.9%) of participants with pre-operative major (>5 trichiatic lashes) and minor (<5 lashes) TT respectively. Of the 315 recurrences, 42/315 (3.3% overall) had >5 lashes (major recurrence). Recurrence was greatest in the first six months after surgery: 172 cases (55%) occurring in this period. Recurrence was associated with major TT pre-operatively (OR 2.39, 95% CI 1.83–3.11), pre-operative entropic lashes compared to misdirected/metaplastic lashes (OR 1.99, 95% CI 1.23–3.20), age over 40 years (OR 1.59, 95% CI 1.14–2.20) and specific surgeons (surgeon recurrence risk range: 18%–53%). Granuloma occurred in 69 (5.7%) and notching in 156 (13.0%).

Conclusions/Significance

Risk of recurrence is high despite high volume, highly trained surgeons. However, the vast majority are minor recurrences, which may not have significant corneal or visual consequences. Inter-surgeon variation in recurrence is concerning; surgical technique, training and immediate post-operative lid position require further investigation.     

Machine learning-based risk factor analysis and prevalence prediction of intestinal parasitic infections using epidemiological survey data

BackgroundPrevious epidemiological studies have examined the prevalence and risk factors for a variety of parasitic illnesses, including protozoan and soil-transmitted helminth (STH, e.g., hookworms and roundworms) infections. Despite advancements in machine learning for data analysis, the majority of these studies use traditional logistic regression to identify significant risk factors.MethodsIn this study, we used data from a survey of 54 risk factors for intestinal parasitosis in 954 Ethiopian school children. We investigated whether machine learning approaches can supplement traditional logistic regression in identifying intestinal parasite infection risk factors. We used feature selection methods such as InfoGain (IG), ReliefF (ReF), Joint Mutual Information (JMI), and Minimum Redundancy Maximum Relevance (MRMR). Additionally, we predicted children’s parasitic infection status using classifiers such as Logistic Regression (LR), Support Vector Machines (SVM), Random Forests (RF) and XGBoost (XGB), and compared their accuracy and area under the receiver operating characteristic curve (AUROC) scores. For optimal model training, we performed tenfold cross-validation and tuned the classifier hyperparameters. We balanced our dataset using the Synthetic Minority Oversampling (SMOTE) method. Additionally, we used association rule learning to establish a link between risk factors and parasitic infections.Key findingsOur study demonstrated that machine learning could be used in conjunction with logistic regression. Using machine learning, we developed models that accurately predicted four parasitic infections: any parasitic infection at 79.9% accuracy, helminth infection at 84.9%, any STH infection at 95.9%, and protozoan infection at 94.2%. The Random Forests (RF) and Support Vector Machines (SVM) classifiers achieved the highest accuracy when top 20 risk factors were considered using Joint Mutual Information (JMI) or all features were used. The best predictors of infection were socioeconomic, demographic, and hematological characteristics.ConclusionsWe demonstrated that feature selection and association rule learning are useful strategies for detecting risk factors for parasite infection. Additionally, we showed that advanced classifiers might be utilized to predict children’s parasitic infection status. When combined with standard logistic regression models, machine learning techniques can identify novel risk factors and predict infection risk.