80 research outputs found
Efficient and Robust Approaches for Analysis of SMARTs: Illustration using the ADAPT-R Trial
Personalized intervention strategies, in particular those that modify
treatment based on a participant's own response, are a core component of
precision medicine approaches. Sequential Multiple Assignment Randomized Trials
(SMARTs) are growing in popularity and are specifically designed to facilitate
the evaluation of sequential adaptive strategies, in particular those embedded
within the SMART. Advances in efficient estimation approaches that are able to
incorporate machine learning while retaining valid inference can allow for more
precise estimates of the effectiveness of these embedded regimes. However, to
the best of our knowledge, such approaches have not yet been applied as the
primary analysis in SMART trials. In this paper, we present a robust and
efficient approach using Targeted Maximum Likelihood Estimation (TMLE) for
estimating and contrasting expected outcomes under the dynamic regimes embedded
in a SMART, together with generating simultaneous confidence intervals for the
resulting estimates. We contrast this method with two alternatives
(G-computation and Inverse Probability Weighting estimators). The precision
gains and robust inference achievable through the use of TMLE to evaluate the
effects of embedded regimes are illustrated using both outcome-blind
simulations and a real data analysis from the Adaptive Strategies for
Preventing and Treating Lapses of Retention in HIV Care (ADAPT-R) trial
(NCT02338739), a SMART with a primary aim of identifying strategies to improve
retention in HIV care among people living with HIV in sub-Saharan Africa
An Approach to Nonparametric Inference on the Causal Dose Response Function
The causal dose response curve is commonly selected as the statistical
parameter of interest in studies where the goal is to understand the effect of
a continuous exposure on an outcome.Most of the available methodology for
statistical inference on the dose-response function in the continuous exposure
setting requires strong parametric assumptions on the probability distribution.
Such parametric assumptions are typically untenable in practice and lead to
invalid inference. It is often preferable to instead use nonparametric methods
for inference, which only make mild assumptions about the data-generating
mechanism. We propose a nonparametric test of the null hypothesis that the
dose-response function is equal to a constant function. We argue that when the
null hypothesis holds, the dose-response function has zero variance. Thus, one
can test the null hypothesis by assessing whether there is sufficient evidence
to claim that the variance is positive. We construct a novel estimator for the
variance of the dose-response function, for which we can fully characterize the
null limiting distribution and thus perform well-calibrated tests of the null
hypothesis. We also present an approach for constructing simultaneous
confidence bands for the dose-response function by inverting our proposed
hypothesis test. We assess the validity of our proposal in a simulation study.
In a data example, we study, in a population of patients who have initiated
treatment for HIV, how the distance required to travel to an HIV clinic affects
retention in care.Comment: 39 pages, 5 figure
Morphological Characterization and Selection of Spider Plant (Cleome Gynandra) Accessions from Kenya and South Africa
Characterization of selected spider plant accessions from Kenya and South Africa was performed in order
to individuate those with distinct morphological traits for future improvement programs. For this purpose, thirty two
accessions of spider plant, 23 sourced from Kenyan genebank and nine sourced from South African genebank, were
planted at the University of Nairobi’s Kabete field station, in a randomized complete block design with 3
replications. Eleven morphological traits based on modified FAO (1995) spider plant descriptors were used in
characterization. Traits evaluated were growth habit, flower colour, stem colour, stem hairiness, petiole colour,
petiole hairiness, leaf colour, leaf pubescence, leaf shape, leaf blade tip shape, and number of leaflets per leaf. The
scored data were analyzed using DARwin software v6 and Genstat v14. Shannon diversity index (H’), multivariate
methods of principal component analysis and hierarchical clustering analyses of unweighted pair group method of
arithmetic mean were assessed for all the traits. Estimates of Shannon-Weaver diversity index (H’) for the
morphological traits were generally high (H’>0.500). The H' index indicated inter-country diversity to be greater
than the intra-country diversity. Principal component analysis identified seven important morphological traits (stem
colour, stem hairiness, petiole colour, petiole hairiness, leaf hairiness, leaf shape and number of leaflets per leaf) for
characterizing spider plant accessions. The hierarchical cluster analysis revealed two major clusters (Cluster I and II)
for the 32 accessions grown, with clustering of accessions occurring along regional basis. Cluster I consisted of
South African accessions only while cluster II had mainly Kenyan accessions and two South African accessions.
The relatively high levels of dissimilarity revealed in this study among the accessions for traits evaluated, especially
accessions from the two different countries, indicates high prospects for genetic improvement of the crop through
cross breeding by using materials from different geographical origins
Response of elite Kenyan finger millet (Eleusine coracana, L. Gaertn) genotypes to Ethrel application
Finger millet is a staple food crop of many communities in Africa. The crop is highly nutritious and has incredible grain storage quality. Limited research investment in finger millet in the past has resulted in poor yields and there are currently no commercial hybrids. We investigated the response of different finger millet genotypes (Okhale-1, Gulu-E, KACCIMMI-72, IE 2872, IE 4115 and U-15) to the application of a plant growth regulator hormone (Ethrel). Six elite Kenyan finger millet varieties with contrasting agronomic traits were crossed in a 6 x 6 diallel pattern. To enhance male sterility across female parents, we subjected the plants to Ethrel at concentrations of 1,500ppm, 1,750ppm and 2,000ppm against a 0ppm check. Dwarfing of sprayed plants that resulted in less lodging and ultimately higher yields were observed among plants sprayed with Ethrel at different concentrations. Ethrel application at 2,000ppm had the most dwarfing effect on plants while spraying plants with 1,500ppm of Ethrel resulted in increased grain weight. Although our results demonstrate overall positive effect of Ethrel on finger millet production, the optimum concentrations for more efficient hybridization will still need to be determined
Evaluation of the impact of a mobile health system on adherence to antenatal and postnatal care and prevention of mother-to-child transmission of HIV programs in Kenya
Assessing the feasibility of eHealth and mHealth: a systematic review and analysis of initiatives implemented in Kenya
Climate change challenges, plant science solutions
Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community
Defining the Transcriptome Assembly and Its Use for Genome Dynamics and Transcriptome Profiling Studies in Pigeonpea (Cajanus cajan L.)
This study reports generation of large-scale genomic resources for pigeonpea, a so-called ‘orphan crop species’ of the semi-arid tropic regions. FLX/454 sequencing carried out on a normalized cDNA pool prepared from 31 tissues produced 494 353 short transcript reads (STRs). Cluster analysis of these STRs, together with 10 817 Sanger ESTs, resulted in a pigeonpea trancriptome assembly (CcTA) comprising of 127 754 tentative unique sequences (TUSs). Functional analysis of these TUSs highlights several active pathways and processes in the sampled tissues. Comparison of the CcTA with the soybean genome showed similarity to 10 857 and 16 367 soybean gene models (depending on alignment methods). Additionally, Illumina 1G sequencing was performed on Fusarium wilt (FW)- and sterility mosaic disease (SMD)-challenged root tissues of 10 resistant and susceptible genotypes. More than 160 million sequence tags were used to identify FW- and SMD-responsive genes. Sequence analysis of CcTA and the Illumina tags identified a large new set of markers for use in genetics and breeding, including 8137 simple sequence repeats, 12 141 single-nucleotide polymorphisms and 5845 intron-spanning regions. Genomic resources developed in this study should be useful for basic and applied research, not only for pigeonpea improvement but also for other related, agronomically important legumes
Comparison of the microbial composition of African fermented foods using amplicon sequencing
Fermented foods play a major role in the diet of people in Africa, where a wide variety of raw materials
are fermented. Understanding the microbial populations of these products would help in the design of
specific starter cultures to produce standardized and safer foods. In this study, the bacterial diversity of
African fermented foods produced from several raw materials (cereals, milk, cassava, honey, palm sap,
and locust beans) under different conditions (household, small commercial producers or laboratory) in 8
African countries was analysed by 16S rRNA gene amplicon sequencing during the Workshop “Analysis
of the Microbiomes of Naturally Fermented Foods Training Course”. Results show that lactobacilli
were less abundant in fermentations performed under laboratory conditions compared to artisanal or
commercial fermentations. Excluding the samples produced under laboratory conditions, lactobacilli
is one of the dominant groups in all the remaining samples. Genera within the order Lactobacillales
dominated dairy, cereal and cassava fermentations. Genera within the order Lactobacillales, and genera
Zymomonas and Bacillus were predominant in alcoholic beverages, whereas Bacillus and Lactobacillus
were the dominant genera in the locust bean sample. The genus Zymomonas was reported for the first
time in dairy, cereal, cassava and locust bean fermentations
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