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.

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.

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.

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.

Characterization of PM10 samples from Vanderbijlpark in South Africa.

In this study, mass concentrations and physico-chemical characteristics of suspended particulates of aerodynamic size 10 µm (PM10) were evaluated. A dual E-Sampler which combines the light scatter and the gravimetric filter methods was used. Sampling occurred between August and December 2009. Scanning Electron Microscope - Energy Dispersive Spectrometry (SEM-EDS) and Inductively Coupled Plasma 6000 were used for elemental and physical characterization. The highest daily average mass concentration measured was 0.03543 mg/m(3) and was below the international and national daily limit of 0.150 mg/m(3), as well as the strict Vaal Triangle regional standard of 0.075 µg/m(3). Relatively high daily average mass concentrations were obtained during the winter period. Concentrations of evaluated heavy metals decreased in the following order: iron (Fe) > manganese (Mn) > zinc (Zn) > copper (Cu) > vanadium (V) > titanium (Ti) > nickel (Ni) > lead (Pb). Positive correlations were established between Zn and Pb (r = 0.916); Zn and Mn (r = 0.883); Zn and V (0.984); Zn and Ni (r = 0.877); Zn and Fe (r = 0.914), which suggests common sources. However, Zn and Ti (r = 0.522); Zn and Cu (0.781) were poorly correlated.

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.

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.

Complex regional pain syndrome following protracted labour*.

Obstetric nerve palsies are common and long-term sequelae are fortunately rare. The development of a complex regional pain syndrome is an unusual and less reported complication of labour-related neuropathy. A 28-year-old primigravida who experienced prolonged labour and instrumental delivery under spinal anaesthesia complained of persisting weakness and numbness postpartum, affecting the left lower limb. Urgent magnetic resonance imaging demonstrated no abnormality and a common peroneal nerve injury was later confirmed by nerve conduction studies. Unfortunately, the neuropathy did not resolve as expected and oedema, burning paraesthesia and allodynia affecting the left foot developed within two weeks. She was treated with gabapentin, ibuprofen, topical capsaicin and regular physiotherapy. After six months, the foot drop had resolved and the chronic pain element was significantly diminished.

Generational differences in factors influencing physicians to choose a work location.

INTRODUCTION: Canadian medical schools have increased enrolment and recruited more rural students in an effort to address general and rural physician shortages. The success of this approach depends on the recruitment of these newly trained physicians to under-serviced areas. Studies from North America suggest that the career expectations and practice patterns of younger, more recently graduated physicians differ from those of their older counterparts. This study explored the factors that influenced the work location choices of physicians of differing generations, who trained at universities in Saskatchewan, and Newfoundland and Labrador, two Canadian provinces with large rural populations and no community larger than 235 000 population. METHODS: Semi-structured, qualitative interviews were conducted with physicians who graduated from either the Memorial University of Newfoundland or the University of Saskatchewan. Generation definitions were based on the graduation year. Early-career physicians graduated between 1995 and 1999; mid-career physician graduated between 1985 and 1989; late-career physicians graduated between 1975 and 1979; and end-career physicians graduated between 1965 and 1969. Each physician was asked questions about the number and nature of work location changes over the course of their careers and the factors related to their decision to choose each location. Interview transcripts and notes were analyzed using a thematic analysis approach. Although the study focus was on generational differences, similarities and differences between universities, sexes and specialties (family physicians/GPs vs specialists) were also examined. Recruitment to the provinces was focused on as a whole, because the largest communities in the provinces are small compared with most urban communities. RESULTS: Forty-eight physicians were interviewed, five to nine physicians who graduated in each decade and from each university. The desire to be near family and friends was cited as the primary consideration when choosing a work location, regardless of generation. Likewise, residency training location, the ability to use their skills and knowledge fully, and the quality of recruitment efforts were important considerations in choosing a work location for all physicians. For some, remuneration was very influential in their work location decision; however, many physicians who chose to remain in their smaller 'home' provinces noted the lower cost of living in these provinces. Physicians who graduated in the 1980s and 1990s placed greater emphasis on work-life balance and spouse's employment opportunities than their older generation counterparts. In contrast, physicians who graduated in the 1960s and 1070s highlighted the medical need of the community, and the desire for adventure and to see new places as important. CONCLUSIONS: While many factors for choosing a work location appear to be stable over generations, a number of generational differences were found. Younger physicians placed greater emphasis on work-life balance and spouse's employment than older generation physicians. These differences may have important implications for small population regions which may not be able to support physician-spouse pairs or certain subspecialties. Although economic factors have largely been the focus of recruitment and retention initiatives in these provinces, the findings highlight the importance of addressing the needs and expectations of younger generation physicians in order to attract these physicians.

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.

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.

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.

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.

Terrestrial toxicity evaluation of decabromodiphenyl ethane on organisms from three trophic levels.

Decabromodiphenyl ethane (DBDP-Ethane) was evaluated for its potential to effect sewage sludge respiration, soil nitrification, survival and reproduction in Eisenia fetida, and seedling emergence and growth in Zea mays, Lolium perenne, Glycine max, Allium cepa, Lycopersicon esculentum, and Cucumis sativa. The no observed effect concentrations (NOECs) were identified at the limit concentration level for sewage sludge respiration (>10 mg DBDP-Ethane/kg dry soil), >2500 mg/kg dry soil for soil nitrification, >3720 mg/kg dry soil for earthworm survival, and >6250 mg/kg dry soil for seedling emergence and growth in Z. mays, L. perenne, and G. max . Treatment-related effects were identified for E. fetida reproduction, C. sativa survival, and L. esculentum and A. cepa height and dry weight. The most sensitive endpoints were decreased height and dry weight for A. cepa and decreased reproduction for E. fetida with NOECs of 1563(nominal) (1540(measured)) and 2210(nominal) (1907(mean measured)) mg/kg dry soil. The NOEC for soil nitrification and the lowest NOEC identified for soil (i.e., A. cepa) were used to derive predicted no effect concentrations (PNEC) values of 2500 mg/kg for sewage sludge and 156 mg/kg for soil. The calculated PNECs indicate DBDP-Ethane presents little risk to organisms in the sewage sludge and soil compartments.

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.

Autoantibodies against alanyl-tRNA synthetase and tRNAAla coexist and are associated with myositis.

The sera of six patients with autoimmune disease, predominantly myositis with pulmonary fibrosis, contain antibodies of the PL-12 specificity. These autoantibodies react with both protein and RNA components of human cells. The protein has a subunit molecular mass of 110 kD, and the RNA comprises a group of bands in the tRNA size class. Aminoacylation experiments identify the antigens as alanyl-tRNA synthetase and its corresponding tRNAs, tRNAAla. Anti-tRNA antibody can be absorbed out without depleting antisynthetase activity, showing that the antigens are recognized independently by separable antibodies that coexist in these sera. The concurrence of separate antibodies to the two components suggests that the autoimmune response may be mounted against the charging enzyme-tRNA complex. However, the antisynthetase antibody fails to coprecipitate tRNA with the enzyme, suggesting that the antibody reacts with its target only when it is not complexed with tRNA.

Anti-threonyl-tRNA synthetase, a second myositis-related autoantibody.

An autoantibody known as PL-7 was found in the serum of four patients with myositis and one with a systemic lupus erythematosus-like syndrome. The PL-7 antigen is an 80,000 dalton polypeptide that coprecipitates with transfer RNA. In aminoacylation reactions, PL-7 IgG inhibited the charging of tRNA with threonine but had little or no effect on charging with other amino acids. Experimental antibodies raised against purified threonyl-tRNA synthetase recognized the same 80,000 dalton polypeptide, but tRNA was not coprecipitated. We conclude that PL-7 antibody is directed at threonyl-tRNA synthetase, and that different antigenic sites are recognized by the human and experimental autoantibodies. Our findings emphasize the link between myositis and autoimmunity to tRNA-related structures.

Survey of a salivary effector in caterpillars: glucose oxidase variation and correlation with host range.

Salivary glucose oxidase (GOX) has been reported in a few insect species where it plays a role in protection against infectious disease. Our recent research has focused on the role of this salivary enzyme in the noctuid Helicoverpa zea, where it functions as an effector to suppress the induced defenses of the host plant Nicotiana tabacum. In this study, we examined the labial gland GOX activities in 23 families of Lepidoptera (85 species) and two families of plant-feeding Hymenoptera (three species). We analyzed the relationship between host breadth and GOX activities, and we found a significant relationship, where highly polyphagous species were more likely to possess relatively high levels of GOX compared to species with more limited host range. We also examined the effect of diet on GOX activity and found that the host plant had a significant effect on enzyme activity. The significance of these findings is discussed in relation to caterpillar host breadth.

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.