Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.

NDT flaw mapping of steel surfaces by continuous magnetic Barkhausen noise: Volumetric flaw detection case

This paper reports the use of a non-destructive, continuous magnetic Barkhausen noise (CMBN) technique to investigate the size and thickness of volumetric defects, in a 1070 steel. The magnetic behavior of the used probe was analyzed by numerical simulation, using the finite element method (FEM). Results indicated that the presence of a ferrite coil core in the probe favors MBN emissions. The samples were scanned with different speeds and probe configurations to determine the effect of the flaw on the CMBN signal amplitude. A moving smooth window, based on a second-order statistical moment, was used for analyzing the time signal. The results show the technique`s good repeatability, and high capacity for detection of this type of defect. (C) 2009 Elsevier Ltd. All rights reserved.

Genetic Diversity and a PCR-Based Method for Xanthomonas axonopodis Detection in Passion Fruit

Xanthomonas axonopodis pv. passiflorae causes bacterial spot in passion fruit. It attacks the purple and yellow passion fruit as well as the sweet passion fruit. The diversity of 87 isolates of pv. passiflorae collected from across 22 fruit orchards in Brazil was evaluated using molecular profiles and statistical procedures, including an unweighted pair-group method with arithmetical averages-based dendrogram, analysis of molecular variance (AMOVA), and an assigning test that provides information on genetic structure at the population level. Isolates from another eight pathovars were included in the molecular analyses and all were shown to have a distinct repetitive sequence-based polymerase chain reaction profile. Amplified fragment length polymorphism technique revealed considerable diversity among isolates of pv. passiflorae, and AMOVA showed that most of the variance (49.4%) was due to differences between localities. Cluster analysis revealed that most genotypic clusters were homogeneous and that variance was associated primarily with geographic origin. The disease adversely affects fruit production and may kill infected plants. A method for rapid diagnosis of the pathogen, even before the disease symptoms become evident, has value for producers. Here, a set of primers (Xapas) was designed by exploiting a single-nucleotide polymorphism between the sequences of the intergenic 16S-23S rRNA spacer region of the pathovars. Xapas was shown to effectively detect all pv. passiflorae isolates and is recommended for disease diagnosis in passion fruit orchards.

Cardiac MRI for Detection of Unrecognized Myocardial Infarction in Patients With End-Stage Renal Disease: Comparison With ECG and Scintigraphy

OBJECTIVE. The purposes of this study were to use the myocardial delayed enhancement technique of cardiac MRI to investigate the frequency of unrecognized myocardial infarction (MI) in patients with end-stage renal disease, to compare the findings with those of ECG and SPECT, and to examine factors that may influence the utility of these methods in the detection of MI. SUBJECTS AND METHODS. We prospectively performed cardiac MRI, ECG, and SPECT to detect unrecognized MI in 72 patients with end-stage renal disease at high risk of coronary artery disease but without a clinical history of MI. RESULTS. Fifty-six patients (78%) were men ( mean age, 56.2 +/- 9.4 years) and 16 (22%) were women ( mean age, 55.8 +/- 11.4). The mean left ventricular mass index was 103.4 +/- 27.3 g/m(2), and the mean ejection fraction was 60.6% +/- 15.5%. Myocardial delayed enhancement imaging depicted unrecognized MI in 18 patients (25%). ECG findings were abnormal in five patients (7%), and SPECT findings were abnormal in 19 patients (26%). ECG findings were false-negative in 14 cases and false-positive in one case. The accuracy, sensitivity, and specificity of ECG were 79.2%, 22.2%, and 98.1% (p = 0.002). SPECT findings were false-negative in six cases and false-positive in seven cases. The accuracy, sensitivity, and specificity of SPECT were 81.9%, 66.7%, and 87.0% ( not significant). During a period of 4.9-77.9 months, 19 cardiac deaths were documented, but no statistical significance was found in survival analysis. CONCLUSION. Cardiac MRI with myocardial delayed enhancement can depict unrecognized MI in patients with end-stage renal disease. ECG and SPECT had low sensitivity in detection of MI. Infarct size and left ventricular mass can influence the utility of these methods in the detection of MI.

Detection of nosocomial malnutrition is improved in Amazon region by a standard clinical nutrition education program

Background: In Brazil hospital malnutrition is highly prevalent. physician awareness of malnutrition is low, and nutrition therapy is underprescribed. One alternative to approach this problem is to educate health care providers in clinical nutrition. The present study aims to evaluate the effect of an intensive education course given to health care professionals and students on the diagnosis ability concerning to hospital malnutrition. Materials and methods: An intervention study based on a clinical nutrition educational program, offered to medical and nursing students and professionals, was held in a hospital of the Amazon region. Participants were evaluated through improvement of diagnostic ability, according to agreement of malnutrition diagnosis using Subjective Global Assessment before and after the workshop, as compared to independent evaluations (Kappa Index, k). To evaluate the impact of the educational intervention on the hospital malnutrition diagnosis, medical records were reviewed for documentation of parameters associated with nutritional status of in-patients. The SPSS statistical software package was used for data analysis. Results: A total of 165 participants concluded the program. The majority (76.4%) were medical and nursing students. Malnutrition diagnosis improved after the course (before k = 0.5; after k = 0.64; p < 0.05). A reduction of false negatives from 50% to 33.3% was observed. During the course, concern of nutritional diagnosis was increased W = 17.57; p < 0.001) and even after the course, improvement on the height measurement was detected chi(2) 12.87;p < 0.001). Conclusions: Clinical nutrition education improved the ability of diagnosing malnutrition; however the primary impact was on medical and nursing students. To sustain diagnostic capacity a clinical nutrition program should be part of health professional curricula and be coupled with continuing education for health care providers.

Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

Detection of Mycoplasma pulmonis in laboratory rats and technicians

Five species of mycoplasma are associated with several rat diseases. Mycoplasma pulmonis is the most important and most studied, possibly causing disease in rats and undermining the validity of laboratory experiments. M. pulmonis was isolated in 144/240 laboratory rats and identified by PCR in 155/240. This species was also detected in 12 human individuals (technicians of a laboratory animal house hold) in contact with these rats. The results were confirmed by sequencing of DNA products. Mycoplasma species are host specific; however, M. pulmonis was identified in humans, suggesting a case of unspecific colonization. Statistical analysis shows a greater risk for M. pulmonis colonizing individuals who are exposed to infected rats in animal facilities than individuals who do not. The detection of M. pulmonis in humans indicates a new status for this mollicute mycoplasmas in animal-holding facilities.

Statistical analysis of the Doppler broadening coincidence spectrum of electron-positron annihilation radiation in silicon

We report a statistical analysis of Doppler broadening coincidence data of electron-positron annihilation radiation in silicon using a (22)Na source. The Doppler broadening coincidence spectrum was fit using a model function that included positron annihilation at rest with 1s, 2s, 2p, and valence band electrons. In-flight positron annihilation was also fit. The response functions of the detectors accounted for backscattering, combinations of Compton effects, pileup, ballistic deficit, and pulse-shaping problems. The procedure allows the quantitative determination of positron annihilation with core and valence electron intensities as well as their standard deviations directly from the experimental spectrum. The results obtained for the core and valence band electron annihilation intensities were 2.56(9)% and 97.44(9)%, respectively. These intensities are consistent with published experimental data treated by conventional analysis methods. This new procedure has the advantage of allowing one to distinguish additional effects from those associated with the detection system response function. (C) 2009 Elsevier B.V. All rights reserved.

Evaluation of simulated bone lesion in the head of the mandible by using multislice computed tomography

Conventional radiography has shown limitation in acquiring image of the ATM region, thus, computed tomography (CT) scanning has been the best option to the present date for diagnosis, surgical planning and treatment of bone lesions, owing to its specific properties. OBJECTIVE: The aim of the study was to evaluate images of simulated bone lesions at the head of the mandible by multislice CT. MATERIAL AND METHODS: Spherical lesions were made with dental spherical drills (sizes 1, 3, and 6) and were evaluated by using multislice CT (64 rows), by two observers in two different occasions, deploying two protocols: axial, coronal, and sagittal images, and parasagittal images for pole visualization (anterior, lateral, posterior, medial and superior). Acquired images were then compared with those lesions in the dry mandible (gold standard) to evaluate the specificity and sensibility of both protocols. Statistical methods included: Kappa statistics, validity test and chi-square test. Results demonstrated the advantage of associating axial, coronal, and sagittal slices with parasagittal slices for lesion detection at the head of the mandible. RESULTS: There was no statistically significant difference between the types of protocols regarding a particular localization of lesions at the poles. CONCLUSIONS: Protocols for the assessment of the head of the mandible were established to improve the visualization of alterations of each of the poles of the mandible's head. The anterior and posterior poles were better visualized in lateral-medial planes while lateral, medial and superior poles were better visualized in the anterior-posterior plane.

Detection of human cytomegalovirus and Epstein-Barr virus in coronary atherosclerotic tissue

Previous studies indicated that patients with atherosclerosis are predominantly infected by human cytomegalovirus (HCMV), but rarely infected by type 1 Epstein-Barr virus (EBV-1). In this study, atheromas of 30 patients who underwent aortocoronary bypass surgery with coronary endartherectomy were tested for the presence of these two viruses. HCMV occurred in 93.3% of the samples and EBV-1 was present in 50% of them. Concurrent presence of both pathogens was detected in 43.3% of the samples.

Validity and reliability of methods for the detection of secondary caries around amalgam restorations in primary teeth

Secondary caries has been reported as the main reason for restoration replacement. The aim of this in vitro study was to evaluate the performance of different methods - visual inspection, laser fluorescence (DIAGNOdent), radiography and tactile examination - for secondary caries detection in primary molars restored with amalgam. Fifty-four primary molars were photographed and 73 suspect sites adjacent to amalgam restorations were selected. Two examiners evaluated independently these sites using all methods. Agreement between examiners was assessed by the Kappa test. To validate the methods, a caries-detector dye was used after restoration removal. The best cut-off points for the sample were found by a Receiver Operator Characteristic (ROC) analysis, and the area under the ROC curve (Az), and the sensitivity, specificity and accuracy of the methods were calculated for enamel (D2) and dentine (D3) thresholds. These parameters were found for each method and then compared by the McNemar test. The tactile examination and visual inspection presented the highest inter-examiner agreement for the D2 and D3 thresholds, respectively. The visual inspection also showed better performance than the other methods for both thresholds (Az = 0.861 and Az = 0.841, respectively). In conclusion, the visual inspection presented the best performance for detecting enamel and dentin secondary caries in primary teeth restored with amalgam.

Detection of Brucella ovis in ovine from Paraíba State, in the Northeast region of Brazil

To determine the presence of Brucella ovis in ovine from Paraíba State, in the Northeast region of Brazil, 80 animals slaughtered in the public slaughterhouse of Patos city were used. Before slaughter, blood samples were collected by jugular venopuncture from each animal, and after slaughter, testicles, epidydimus and uterus were aseptically collected. For the serological diagnosis of B. ovis and B. abortus infections, the agar gel immunodiffusion (AGID) and Rose Bengal (RBT) tests were carried out, respectively. In addition, microbiological culture and polymerase chain reaction (PCR) were performed on testicle, epidydimus and uterus samples. Six animals (7.5%) tested positive for the presence of B. ovis antibodies and all animals tested negative for the presence of B. abortus antibodies. One AGID-positive animal tested positive at uterine swab culture. PCR was able to amplify DNA of Brucella spp. from the pool of testicle, epidydimus and uterus samples from AGID-positive animals. This is the first report of isolation and detection of B. ovis DNA by PCR in ovine from the Northeast region of Brazil.

Evaluation of DNA extraction protocols for Brucella abortus pcr detection in aborted fetuses or calves born from cows experimentally infected with strain 2308

The objective of the present study was to improve the detection of B. abortus by PCR in organs of aborted fetuses from infected cows, an important mechanism to find infected herds on the eradication phase of the program. So, different DNA extraction protocols were compared, focusing the PCR detection of B. abortus in clinical samples collected from aborted fetuses or calves born from cows challenged with the 2308 B. abortus strain. Therefore, two gold standard groups were built based on classical bacteriology, formed from: 32 lungs (17 positives), 26 spleens (11 positives), 23 livers (8 positives) and 22 bronchial lymph nodes (7 positives). All samples were submitted to three DNA extraction protocols, followed by the same amplification process with the primers B4 and B5. From the accumulated results for organ, the proportion of positives for the lungs was higher than the livers (p=0.04) or bronchial lymph nodes (p=0.004) and equal to the spleens (p=0.18). From the accumulated results for DNA extraction protocol, the proportion of positives for the Boom protocol was bigger than the PK (p<0.0001) and GT (p=0.0004). There was no difference between the PK and GT protocols (p=0.5). Some positive samples from the classical bacteriology were negative to the PCR and viceversa. Therefore, the best strategy for B. abortus detection in the organs of aborted fetuses or calves born from infected cows is the use, in parallel, of isolation by classical bacteriology and the PCR, with the DNA extraction performed by the Boom protocol.

A closer look at multiple-clone Plasmodium vivax infections: detection methods, prevalence and consequences

The naturally occurring clonal diversity among field isolates of the major human malaria parasite Plasmodium vivax remained unexplored until the early 1990s, when improved molecular methods allowed the use of blood samples obtained directly from patients, without prior in vitro culture, for genotyping purposes. Here we briefly review the molecular strategies currently used to detect genetically distinct clones in patient-derived P. vivax samples, present evidence that multiple-clone P. vivax infections are commonly detected in areas with different levels of malaria transmission and discuss possible evolutionary and epidemiological consequences of the competition between genetically distinct clones in natural human infections. We suggest that, when two or more genetically distinct clones are present in the same host, intra-host competition for limited resources may select for P. vivax traits that represent major public health challenges, such as increased virulence, increased transmissibility and antimalarial drug resistance.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.