Combination of linkage and association mapping with genomic prediction to infer QTL regions associated with gray leaf spot and northern corn leaf blight resistance in tropical maize.

Among the diseases threatening maize production in Africa are gray leaf spot (GLS) caused by Cercospora zeina and northern corn leaf blight (NCLB) caused by Exserohilum turcicum. The two pathogens, which have high genetic diversity, reduce the photosynthesizing ability of susceptible genotypes and, hence, reduce the grain yield. To identify population-based quantitative trait loci (QTLs) for GLS and NCLB resistance, a biparental population of 230 lines derived from the tropical maize parents CML511 and CML546 and an association mapping panel of 239 tropical and sub-tropical inbred lines were phenotyped across multi-environments in western Kenya. Based on 1,264 high-quality polymorphic single-nucleotide polymorphisms (SNPs) in the biparental population, we identified 10 and 18 QTLs, which explained 64.2% and 64.9% of the total phenotypic variance for GLS and NCLB resistance, respectively. A major QTL for GLS, qGLS1_186 accounted for 15.2% of the phenotypic variance, while qNCLB3_50 explained the most phenotypic variance at 8.8% for NCLB resistance. Association mapping with 230,743 markers revealed 11 and 16 SNPs significantly associated with GLS and NCLB resistance, respectively. Several of the SNPs detected in the association panel were co-localized with QTLs identified in the biparental population, suggesting some consistent genomic regions across genetic backgrounds. These would be more relevant to use in field breeding to improve resistance to both diseases. Genomic prediction models trained on the biparental population data yielded average prediction accuracies of 0.66-0.75 for the disease traits when validated in the same population. Applying these prediction models to the association panel produced accuracies of 0.49 and 0.75 for GLS and NCLB, respectively. This research conducted in maize fields relevant to farmers in western Kenya has combined linkage and association mapping to identify new QTLs and confirm previous QTLs for GLS and NCLB resistance. Overall, our findings imply that genetic gain can be improved in maize breeding for resistance to multiple diseases including GLS and NCLB by using genomic selection.

Genome analyses reveal population structure and a purple stigma color gene candidate in finger millet.

Finger millet is a key food security crop widely grown in eastern Africa, India and Nepal. Long considered a 'poor man's crop', finger millet has regained attention over the past decade for its climate resilience and the nutritional qualities of its grain. To bring finger millet breeding into the 21st century, here we present the assembly and annotation of a chromosome-scale reference genome. We show that this ~1.3 million years old allotetraploid has a high level of homoeologous gene retention and lacks subgenome dominance. Population structure is mainly driven by the differential presence of large wild segments in the pericentromeric regions of several chromosomes. Trait mapping, followed by variant analysis of gene candidates, reveals that loss of purple coloration of anthers and stigma is associated with loss-of-function mutations in the finger millet orthologs of the maize R1/B1 and Arabidopsis GL3/EGL3 anthocyanin regulatory genes. Proanthocyanidin production in seed is not affected by these gene knockouts.

RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms.

There exists a gap in terms of the signals provided by pacemakers (i.e., intracardiac electrogram (EGM)) and the signals doctors use (i.e., 12-lead electrocardiogram (ECG)) to diagnose abnormal rhythms. Therefore, the former, even if remotely transmitted, are not sufficient for doctors to provide a precise diagnosis, let alone make a timely intervention. To close this gap and make a heuristic step towards real-time critical intervention in instant response to irregular and infrequent ventricular rhythms, we propose a new framework dubbed RT-RCG to automatically search for (1) efficient Deep Neural Network (DNN) structures and then (2) corresponding accelerators, to enable Real-Time and high-quality Reconstruction of ECG signals from EGM signals. Specifically, RT-RCG proposes a new DNN search space tailored for ECG reconstruction from EGM signals, and incorporates a differentiable acceleration search (DAS) engine to efficiently navigate over the large and discrete accelerator design space to generate optimized accelerators. Extensive experiments and ablation studies under various settings consistently validate the effectiveness of our RT-RCG. To the best of our knowledge, RT-RCG is the first to leverage neural architecture search (NAS) to simultaneously tackle both reconstruction efficacy and efficiency.

Manifold Approximating Graph Interpolation of Cardiac Local Activation Time.

OBJECTIVE: Local activation time (LAT) mapping of cardiac chambers is vital for targeted treatment of cardiac arrhythmias in catheter ablation procedures. Current methods require too many LAT observations for an accurate interpolation of the necessarily sparse LAT signal extracted from intracardiac electrograms (EGMs). Additionally, conventional performance metrics for LAT interpolation algorithms do not accurately measure the quality of interpolated maps. We propose, first, a novel method for spatial interpolation of the LAT signal which requires relatively few observations; second, a realistic sub-sampling protocol for LAT interpolation testing; and third, a new color-based metric for evaluation of interpolation quality that quantifies perceived differences in LAT maps. METHODS: We utilize a graph signal processing framework to reformulate the irregular spatial interpolation problem into a semi-supervised learning problem on the manifold with a closed-form solution. The metric proposed uses a color difference equation and color theory to quantify visual differences in generated LAT maps. RESULTS: We evaluate our approach on a dataset consisting of seven LAT maps from four patients obtained by the CARTO electroanatomic mapping system during premature ventricular complex (PVC) ablation procedures. Random sub-sampling and re-interpolation of the LAT observations show excellent accuracy for relatively few observations, achieving on average 6% lower error than state-of-the-art techniques for only 100 observations. CONCLUSION: Our study suggests that graph signal processing methods can improve LAT mapping for cardiac ablation procedures. SIGNIFICANCE: The proposed method can reduce patient time in surgery by decreasing the number of LAT observations needed for an accurate LAT map.

Artificial Intelligence and Machine Learning in Cardiac Electrophysiology.

Cardiac electrophysiology requires the processing of several patient-specific data points in real time to provide an accurate diagnosis and determine an optimal therapy. Expanding beyond the traditional tools that have been used to extract information from patient-specific data, machine learning offers a new set of advanced tools capable of revealing previously unknown data patterns and features. This new tool set can substantially improve the speed and level of confidence with which electrophysiologists can determine patient-specific diagnoses and therapies. The ability to process substantial amounts of data in real time also paves the way to novel techniques for data collection and visualization. Extended realities such as virtual and augmented reality can now enable the real-time visualization of 3-dimensional images in space. This enables improved preprocedural planning and intraprocedural interventions. Machine learning supplemented with novel visualization technologies could substantially improve patient care and outcomes by helping physicians to make more informed patient-specific decisions. This article presents current applications of machine learning and their use in cardiac electrophysiology.

A high-density linkage map of finger millet provides QTL for blast resistance and other agronomic traits.

Finger millet [Eleusine coracana (L.) Gaertn.] is a critical subsistence crop in eastern Africa and southern Asia but has few genomic resources and modern breeding programs. To aid in the understanding of finger millet genomic organization and genes underlying disease resistance and agronomically important traits, we generated a F2:3 population from a cross between E. coracana (L.) Gaertn. subsp. coracana accession ACC 100007 and E. coracana (L.) Gaertn. subsp. africana , accession GBK 030647. Phenotypic data on morphology, yield, and blast (Magnaporthe oryzae) resistance traits were taken on a subset of the F2:3 population in a Kenyan field trial. The F2:3 population was genotyped via genotyping-by-sequencing (GBS) and the UGbS-Flex pipeline was used for sequence alignment, nucleotide polymorphism calling, and genetic map construction. An 18-linkage-group genetic map consisting of 5,422 markers was generated that enabled comparative genomic analyses with rice (Oryza sativa L.), foxtail millet [Setaria italica (L.) P. Beauv.], and sorghum [Sorghum bicolor (L.) Moench]. Notably, we identified conserved acrocentric homoeologous chromosomes (4A and 4B in finger millet) across all species. Significant quantitative trait loci (QTL) were discovered for flowering date, plant height, panicle number, and blast incidence and severity. Sixteen putative candidate genes that may underlie trait variation were identified. Seven LEUCINE-RICH REPEAT-CONTAINING PROTEIN genes, with homology to nucleotide-binding site leucine-rich repeat (NBS-LRR) disease resistance proteins, were found on three chromosomes under blast resistance QTL. This high-marker-density genetic map provides an important tool for plant breeding programs and identifies genomic regions and genes of critical interest for agronomic traits and blast resistance.

A novel convolutional neural network for reconstructing surface electrocardiograms from intracardiac electrograms and vice versa.

We propose a novel convolutional neural network framework for mapping a multivariate input to a multivariate output. In particular, we implement our algorithm within the scope of 12-lead surface electrocardiogram (ECG) reconstruction from intracardiac electrograms (EGM) and vice versa. The goal of performing this task is to allow for improved point-of-care monitoring of patients with an implanted device to treat cardiac pathologies. We will achieve this goal with 12-lead ECG reconstruction and by providing a new diagnostic tool for classifying five different ECG types. The algorithm is evaluated on a dataset retroactively collected from 14 patients. Correlation coefficients calculated between the reconstructed and the actual ECG show that the proposed convolutional neural network model represents an efficient, accurate, and superior way to synthesize a 12-lead ECG when compared to previous methods. We can also achieve the same reconstruction accuracy with only one EGM lead as input. We also tested the model in a non-patient specific way and saw a reasonable correlation coefficient. The model was also executed in the reverse direction to produce EGM signals from a 12-lead ECG and found that the correlation was comparable to the forward direction. Lastly, we analyzed the features learned in the model and determined that the model learns an overcomplete basis of our 12-lead ECG space. We then use this basis of features to create a new diagnostic tool for classifying different ECG arrhythmia's on the MIT-BIH arrhythmia database with an average accuracy of 0.98.

Population genetic structure and migration patterns of the maize pathogenic fungus, Cercospora zeina in East and Southern Africa.

Cercospora zeina is a causal pathogen of gray leaf spot (GLS) disease of maize in Africa. This fungal pathogen exhibits a high genetic diversity in South Africa. However, little is known about the pathogen's population structure in the rest of Africa. In this study, we aimed to assess the diversity and gene flow of the pathogen between major maize producing countries in East and Southern Africa (Kenya, Uganda, Zambia, Zimbabwe, and South Africa). A total of 964 single-spore isolates were made from GLS lesions and confirmed as C.zeina using PCR diagnostics. The other causal agent of GLS, Cercospora zeae-maydis, was absent. Genotyping all the C.zeina isolates with 11 microsatellite markers and a mating-type gene diagnostic revealed (i) high genetic diversity with some population structure between the five African countries, (ii) cryptic sexual recombination, (iii) that South Africa and Kenya were the greatest donors of migrants, and (iv) that Zambia had a distinct population. We noted evidence of human-mediated long-distance dispersal, since four haplotypes from one South African site were also present at five sites in Kenya and Uganda. There was no evidence for a single-entry point of the pathogen into Africa. South Africa was the most probable origin of the populations in Kenya, Uganda, and Zimbabwe. Continuous annual maize production in the tropics (Kenya and Uganda) did not result in greater genetic diversity than a single maize season (Southern Africa). Our results will underpin future management of GLS in Africa through effective monitoring of virulent C.zeina strains.

Morphological and Molecular Characterization of Toxigenic Aspergillus flavus from Groundnut Kernels in Kenya.

Pathogenesis of Aspergillus flavus on important agricultural products is a key concern on human health due to the synthesis and secretion of the hazardous secondary metabolite, aflatoxin. This study identified and further characterized aflatoxigenic A. flavus from groundnuts sampled from sundry shops in Kenya using integrated morphological and molecular approaches. The groundnuts were plated on potato dextrose agar for isolation and morphological observation of A. flavus based on macroscopic and microscopic features. Molecular characterization was done through amplification and comparison of the partial sequence of the ITS1-5.8S-ITS2 region. The expression analysis of aflR, aflS, aflD, aflP, and aflQ genes in the aflatoxin biosynthesis pathways was conducted to confirm the positive identification of A. flavus. The gene expression also aided to delineate toxigenic isolates of A. flavus from atoxigenic ones. Morphologically, 18 isolates suspected to be A. flavus were identified. Out of these, 14 isolates successfully amplified the 500 bp ITS region of A. flavus or Aspergillus oryzae, while 4 isolates were not amplified. All the remaining 14 isolates expressed at least one of the aflatoxigenic genes but only 5 had all the genes expressed. Partial sequencing revealed that isolates 5, 11, 12, 13, and 15 had 99.2%, 97.6%, 98.4%, 97.5%, and 100% homology, respectively, to the A. flavus isolate LUOHE, ITS-5.8S-ITS2, obtained from the NCBI database. The five isolates were accurate identification of atoxigenic A. flavus. Precise identification of toxigenic strains of A. flavus will be useful in establishing control strategies of the fungus in food products.

Alcohol Ablation of Cardiac Tissues Quantified and Evaluated Using CIELAB Euclidean Distances.

Ethanol solubilizes cell membranes, making it useful for various ablation applications. We examined the effect of time and alcohol type on the extent of ablation, quantified as Euclidean distances between color coordinates. We obtained biopsy punch samples (diameter, 6 mm) of left atrial appendage, atrial, ventricular, and septal tissue from porcine hearts and placed them in transwell plates filled with ethanol or methanol for 10, 20, 30, 40, 50, or 60 min. Control samples were taken for each time point. At each time point, samples were collected, cut transversely, and photographed. With use of a custom MATLAB program, all images were analyzed in the CIELAB color space, which is more perceptually uniform than the red-green-blue color space. Euclidean distances were calculated from CIELAB coordinates. The mean and standard error of these distances were analyzed. Two-way analysis of variance was used to test for differences among time points, and 2-tailed t tests, for differences between the alcohol datasets at each time point. Generally, Euclidean distances differed significantly between all time points, except for those immediately adjacent, and methanol produced larger Euclidean distances than ethanol did. Some tissue showed a plateauing effect, potentially indicating transmurality. Mean Euclidean distances effectively indexed alcohol ablation in cardiac tissue. Furthermore, we found that methanol ablated tissue more effectively than ethanol did. With ethanol, the extent of ablation for atrial tissue was largest at 60 min. We conclude that to achieve full transmurality in clinical applications, ethanol must remain in contact with atrial tissue for at least one hour.

UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study.

BACKGROUND: Research on orphan crops is often hindered by a lack of genomic resources. With the advent of affordable sequencing technologies, genotyping an entire genome or, for large-genome species, a representative fraction of the genome has become feasible for any crop. Nevertheless, most genotyping-by-sequencing (GBS) methods are geared towards obtaining large numbers of markers at low sequence depth, which excludes their application in heterozygous individuals. Furthermore, bioinformatics pipelines often lack the flexibility to deal with paired-end reads or to be applied in polyploid species. RESULTS: UGbS-Flex combines publicly available software with in-house python and perl scripts to efficiently call SNPs from genotyping-by-sequencing reads irrespective of the species' ploidy level, breeding system and availability of a reference genome. Noteworthy features of the UGbS-Flex pipeline are an ability to use paired-end reads as input, an effective approach to cluster reads across samples with enhanced outputs, and maximization of SNP calling. We demonstrate use of the pipeline for the identification of several thousand high-confidence SNPs with high representation across samples in an F3-derived F2 population in the allotetraploid finger millet. Robust high-density genetic maps were constructed using the time-tested mapping program MAPMAKER which we upgraded to run efficiently and in a semi-automated manner in a Windows Command Prompt Environment. We exploited comparative GBS with one of the diploid ancestors of finger millet to assign linkage groups to subgenomes and demonstrate the presence of chromosomal rearrangements. CONCLUSIONS: The paper combines GBS protocol modifications, a novel flexible GBS analysis pipeline, UGbS-Flex, recommendations to maximize SNP identification, updated genetic mapping software, and the first high-density maps of finger millet. The modules used in the UGbS-Flex pipeline and for genetic mapping were applied to finger millet, an allotetraploid selfing species without a reference genome, as a case study. The UGbS-Flex modules, which can be run independently, are easily transferable to species with other breeding systems or ploidy levels.

The role of Kenya in the trans-African spread of maize streak virus strain A.

Maize streak virus (MSV), the causal agent of maize streak disease (MSD), is the most important viral pathogen of Africa's staple food crop, maize. Previous phylogeographic analyses have revealed that the most widely-distributed and common MSV variant, MSV-A1, has been repeatedly traversing Africa over the past fifty years with long-range movements departing from either the Lake Victoria region of East Africa, or the region around the convergence of Zimbabwe, South Africa and Mozambique in southern Africa. Despite Kenya being the second most important maize producing country in East Africa, little is known about the Kenyan MSV population and its contribution to the ongoing diversification and trans-continental dissemination of MSV-A1. We therefore undertook a sampling survey in this country between 2008 and 2011, collecting MSD prevalence data in 119 farmers' fields, symptom severity data for 170 maize plants and complete MSV genome sequence data for 159 MSV isolates. We then used phylogenetic and phylogeographic analyses to show that whereas the Kenyan MSV population is likely primarily derived from the MSV population in neighbouring Uganda, it displays considerably more geographical structure than the Ugandan population. Further, this geographical structure likely confounds apparent associations between virus genotypes and both symptom severity and MSD prevalence in Kenya. Finally, we find that Kenya is probably a sink rather than a source of MSV diversification and movement, and therefore, unlike Uganda, Kenya probably does not play a major role in the trans-continental dissemination of MSV-A1.

The integrated effect of moderate exercise on coronary heart disease

Background: Moderate exercise is associated with a lower risk for coronary heart disease (CHD). A suitable integrated model of the CHD pathogenetic pathways relevant to moderate exercise may help to elucidate this association. Such a model is currently not available in the literature.Methods: An integrated model of CHD was developed and used to investigate pathogenetic pathways of importance between exercise and CHD. Using biomarker relative-risk data, the pathogenetic effects are representable as measurable effects based on changes in biomarkers.Results: The integrated model provides insight into higherorder interactions underlying the associations between CHD and moderate exercise. A novel 'connection graph' was developed, which simplifies these interactions. It quantitatively illustrates the relationship between moderate exercise and various serological biomarkers of CHD. The connection graph of moderate exercise elucidates all the possible integrated actions through which risk reduction may occur.Conclusion: An integrated model of CHD provides a summary of the effects of moderate exercise on CHD. It also shows the importance of each CHD pathway that moderate exercise influences. The CHD risk-reducing effects of exercise appear to be primarily driven by decreased inflammation and altered metabolism

Identification of SNP and SSR Markers in Finger Millet Using Next Generation Sequencing Technologies.

Finger millet is an important cereal crop in eastern Africa and southern India with excellent grain storage quality and unique ability to thrive in extreme environmental conditions. Since negligible attention has been paid to improving this crop to date, the current study used Next Generation Sequencing (NGS) technologies to develop both Simple Sequence Repeat (SSR) and Single Nucleotide Polymorphism (SNP) markers. Genomic DNA from cultivated finger millet genotypes KNE755 and KNE796 was sequenced using both Roche 454 and Illumina technologies. Non-organelle sequencing reads were assembled into 207 Mbp representing approximately 13% of the finger millet genome. We identified 10,327 SSRs and 23,285 non-homeologous SNPs and tested 101 of each for polymorphism across a diverse set of wild and cultivated finger millet germplasm. For the 49 polymorphic SSRs, the mean polymorphism information content (PIC) was 0.42, ranging from 0.16 to 0.77. We also validated 92 SNP markers, 80 of which were polymorphic with a mean PIC of 0.29 across 30 wild and 59 cultivated accessions. Seventy-six of the 80 SNPs were polymorphic across 30 wild germplasm with a mean PIC of 0.30 while only 22 of the SNP markers showed polymorphism among the 59 cultivated accessions with an average PIC value of 0.15. Genetic diversity analysis using the polymorphic SNP markers revealed two major clusters; one of wild and another of cultivated accessions. Detailed STRUCTURE analysis confirmed this grouping pattern and further revealed 2 sub-populations within wild E. coracana subsp. africana. Both STRUCTURE and genetic diversity analysis assisted with the correct identification of the new germplasm collections. These polymorphic SSR and SNP markers are a significant addition to the existing 82 published SSRs, especially with regard to the previously reported low polymorphism levels in finger millet. Our results also reveal an unexploited finger millet genetic resource that can be included in the regional breeding programs in order to efficiently optimize productivity.

Patient-expressed perceptions of wait-time causes and wait-related satisfaction.

BACKGROUND: This study set out to identify patterns in the causes of waits and wait-related satisfaction. METHODS: We conducted qualitative interviews with urban, semi-urban, and rural patients (n = 60) to explore their perceptions of the waits they experienced in the detection and treatment of their breast, prostate, lung, or colorectal cancer. We asked participants to describe their experiences from the onset of symptoms to the start of treatment at the cancer clinic and their satisfaction with waits at various intervals. Interview transcripts were coded using a thematic approach. RESULTS: Patients identified five groups of wait-time causes: Patient-related (beliefs, preferences, and non-cancer health issues)Treatment-related (natural consequences of treatment)System-related (the organization or functioning of groups, workforce, institution, or infrastructure in the health care system)Physician-related (a single physician responsible for a specific element in the patient's care)Other causes (disruptions to normal operations of a city or community as a whole) With the limited exception of physician-related absences, the nature of the cause was not linked to overall satisfaction or dissatisfaction with waits. CONCLUSIONS: Causes in themselves do not explain wait-related satisfaction. Further work is needed to explore the underlying reasons for wait-related satisfaction or dissatisfaction. Although our findings shed light on patient experiences with the health system and identify where interventions could help to inform the expectations of patients and the public with respect to wait time, more research is needed to understand wait-related satisfaction among cancer patients.

Sensing the neuronal glycocalyx by glial sialic acid binding immunoglobulin-like lectins.

Sialic acid binding immunoglobulin-like lectins (Siglecs) are cell surface receptors of microglia and oligodendrocytes that recognize the sialic acid cap of healthy neurons and neighboring glial cells. Upon ligand binding, Siglecs typically signal through an immunoreceptor tyrosine-based inhibition motif (ITIM) to keep the cell in a homeostatic status and support healthy neighboring cells. Siglecs can be divided into two groups; the first, being conserved among different species. The conserved Siglec-4/myelin-associated glycoprotein is expressed on oligodendrocytes and Schwann cells. Siglec-4 protects neurons from acute toxicity via interaction with sialic acids bound to neuronal gangliosides. The second group of Siglecs, named CD33-related Siglecs, is almost exclusively expressed on immune cells and is highly variable among different species. Microglial expression of Siglec-11 is human lineage-specific and prevents neurotoxicity via interaction with α2.8-linked sialic acid oligomers exposed on the neuronal glycocalyx. Microglial Siglec-E is a mouse CD33-related Siglec member that prevents microglial phagocytosis and the associated oxidative burst. Mouse Siglec-E of microglia binds to α2.8- and α2.3-linked sialic acid residues of the healthy glycocalyx of neuronal and glial cells. Recently, polymorphisms of the human Siglec-3/CD33 were linked to late onset Alzheimer's disease by genome-wide association studies. Human Siglec-3 is expressed on microglia and produces inhibitory signaling that decreases uptake of particular molecules such as amyloid-ß aggregates. Thus, glial ITIM-signaling Siglecs recognize the intact glycocalyx of neurons and are involved in the modulation of neuron-glia interaction in healthy and diseased brain.

Use of screening tests, diagnosis wait times, and wait-related satisfaction in breast and prostate cancer.

BACKGROUND: Understanding factors relating to the perception of wait time by patients is key to improving the patient experience. METHODS: We surveyed 122 breast and 90 prostate cancer patients presenting at clinics or listed on the cancer registry in Newfoundland and Labrador and reviewed their charts. We compared the wait time (first visit to diagnosis) and the wait-related satisfaction for breast and prostate cancer patients who received regular screening tests and whose cancer was screening test-detected ("screen/screen"); who received regular screening tests and whose cancer was symptomatic ("screen/symptomatic"); who did not receive regular screening tests and whose cancer was screen test-detected ("no screen/screen"); and who did not receive regular screening tests and whose cancer was symptomatic ("no screen/symptomatic"). RESULTS: Although there were no group differences with respect to having a long wait (greater than the median of 47.5 days) for breast cancer patients (47.8% screen/screen, 54.7% screen/symptomatic, 50.0% no screen/ screen, 40.0% no screen/symptomatic; p = 0.814), a smaller proportion of the screen/symptomatic patients were satisfied with their wait (72.5% screen/ screen, 56.4% screen/symptomatic, 100% no screen/ screen, 90.9% no screen/symptomatic; p = 0.048). A larger proportion of screen/symptomatic prostate cancer patients had long waits (>104.5 days: 41.3% screen/screen, 92.0% screen/symptomatic, 46.0% no screen/screen, 40.0% no screen/symptomatic; p = 0.011) and a smaller proportion of screen/ symptomatic patients were satisfied with their wait (71.2% screen/screen, 30.8% screen/symptomatic, 76.9% no screen/screen, 90.9% no screen/symptomatic; p = 0.008). CONCLUSIONS: Diagnosis-related wait times and satisfaction were poorest among patients who received regular screening tests but whose cancer was not detected by those tests.

Symbiotic Efficiency of Native Rhizobia Nodulating Common Bean (Phaseolus vulgaris L.) in Soils of Western Kenya.

This study was conducted to determine the abundance and symbiotic efficiency of native rhizobia nodulating common bean in Kisumu and Kakamega, Kenya. Soil sampling was carried out in three farms that had been used for growing common bean for at least two seasons and one fallow land with no known history of growing common bean or inoculation. Abundance of soil rhizobia and symbiotic efficiency (SE) were determined in a greenhouse experiment. Native rhizobia populations ranged from 3.2 × 10(1) to 3.5 × 10(4) cells per gram of soil. Pure bacterial cultures isolated from fresh and healthy root nodules exhibited typical characteristics of Rhizobium sp. on yeast extract mannitol agar media supplemented with Congo red. Bean inoculation with the isolates significantly (p < 0.05) increased the shoot dry weight and nitrogen (N) concentration and content. The SE of all the native rhizobia were higher when compared to a reference strain, CIAT 899 (67%), and ranged from 74% to 170%. Four isolates had SE above a second reference strain, Strain 446 (110%). Our results demonstrate the presence of native rhizobia that are potentially superior to the commercial inoculants. These can be exploited to enhance bean inoculation programmes in the region.

Responses by breast and prostate cancer patients to out-of-pocket costs in Newfoundland and Labrador.

PURPOSE: Cancer patients face substantial care-related out-of-pocket (oop) costs that may influence treatment decisions, attitudes, and use of drug- or appointment-related cost-saving strategies. We examined the relationship between oop costs and care-related responses by patients. METHODS: We surveyed 170 prostate and 131 breast cancer patients presenting at clinics or support groups, or listed on the cancer registry in Newfoundland and Labrador. RESULTS: In the 3-month period before the survey, 18.8% of prostate and 25.2% of breast cancer patients had oop costs greater than $500. Those oop costs consumed more than 7.5% of quarterly household income for 15.9% of prostate and 19.1% of breast cancer patients. Few patients (8.8% prostate, 15.3% breast) ever adopted any drug- or appointment-related cost-saving strategy. Few patients (7.2% prostate, 9.6% breast) said oop costs influenced treatment decisions, told their physicians about their oop costs (27.0% prostate, 21.1% breast), or were aware of available financial assistance programs (27.3% prostate, 36.9% breast). Compared with patients having low or moderate oop costs (22.9% prostate, 16.7% breast, and 25.7% prostate, 58.3% breast respectively), a larger proportion of prostate (56.0%) and breast (58.3%) cancer patients with high oop costs said that those costs created stress. Among prostate cancer patients, a larger proportion of those having high oop costs (compared with low or moderate costs) used drug-related (22.2% vs. 3.3% and 9.6% respectively) and appointment-related (11.1% vs. 1.1% and 3.8% respectively) cost-saving strategies, said oop costs created an unusual amount of stress (48.0% vs. 18.4% and 10.4%), and had difficulty paying those costs (29.2% vs. 6.2% and 10.4%). CONCLUSIONS: For a small group of breast and prostate cancer patients, oop costs are high, but rarely lead to the use of care-related cost-saving strategies or influence care decisions.

A randomized controlled Alzheimer's disease prevention trial's evolution into an exposure trial: the PREADViSE Trial.

OBJECTIVES: To summarize the ongoing prevention of Alzheimer's disease (AD) by vitamin E and selenium (PREADViSE) trial as an ancillary study to SELECT (a large prostate cancer prevention trial) and to present the blinded results of the first year as an exposure study. DESIGN: PREADViSE was designed as a double blind randomized controlled trial (RCT). SETTING: SELECT terminated after median of 5.5 years of exposure to supplements due to a futility analysis. Both trials then converted into an exposure study. PARTICIPANTS: In the randomized component PREADViSE enrolled 7,547 men age 62 or older (60 if African American). Once the trial terminated 4,246 of these men volunteered for the exposure study. Demographics were similar for both groups with exposure volunteers having baseline mean age 67.3 ± 5.2 years, 15.3 ± 2.4 years of education, 9.8% African Americans, and 22.0% reporting a family history of dementia. INTERVENTION: In the RCT men were randomly assigned to either daily doses of 400 IU of vitamin E or placebo and 200 µg of selenium or placebo using a 2x2 factorial structure. MEASUREMENTS: In the RCT, participants completed the memory impairment screen (MIS), and if they failed, underwent a longer screening (based on an expanded Consortium to Establish a Registry in AD [CERAD] battery). CERAD failure resulted in visits to their clinician for medical examination with records of these examinations forwarded to the PREADViSE center for further review. In the exposure study, men are contacted by telephone and complete the telephone version of the memory impairment screen (MIS-T) screen. If they fail the MIS-T, a modified telephone interview of cognitive status (TICS-M) exam is given. A failed TICS-M exam also leads to a visit to their clinician for an in-depth examination and forwarding of records for a centralized consensus diagnosis by expert clinicians. A subgroup of the men who pass the MIS-T also take the TICS-M exam for validation purposes. RESULTS: While this ancillary trial was open to all 427 SELECT clinical sites, only 130 (30.0%) of the sites chose to participate in PREADViSE. Staff turnover at the sites presented challenges when training persons unfamiliar with cognitive testing procedures to conduct the memory screens. In the RCT few participants (1.6%) failed the MIS screen and among those who passed this screen a significant practice effect was encountered. In the exposure study 3,581 men were reached by phone in year 1, 15.7% could not be reached after 5 calls, and of those contacted 6.0% refused the screen even after consenting to the procedures at their clinical site. Most notable is that the failure rate for the MIS-T increased fourfold to 7.2%. Of the 257 men who took the TICS-M, 84.0% failed and were asked to contact their physicians for a more detailed memory assessment, and approximately half of these had some form of dementia or cognitive impairment. Several of these dementia cases are not AD. CONCLUSION: Partnering with SELECT led to an AD prevention trial conducted at a very reasonable cost by taking advantage of the experience and efficient clinical trial management found in a cancer cooperative group (Southwest Oncology Group or SWOG). Once unblinded, the RCT and exposure study data have the potential to yield new information on long term exposure to antioxidant supplements under controlled conditions.