Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images

The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

Statistical analysis of event-related potential elicited by verb-complement merge in Brazilian Portuguese

An interesting fact about language cognition is that stimulation involving incongruence in the merge operation between verb and complement has often been related to a negative event-related potential (ERP) of augmented amplitude and latency of ca. 400 ms - the N400. Using an automatic ERP latency and amplitude estimator to facilitate the recognition of waves with a low signal-to-noise ratio, the objective of the present study was to study the N400 statistically in 24 volunteers. Stimulation consisted of 80 experimental sentences (40 congruous and 40 incongruous), generated in Brazilian Portuguese, involving two distinct local verb-argument combinations (nominal object and pronominal object series). For each volunteer, the EEG was simultaneously acquired at 20 derivations, topographically localized according to the 10-20 International System. A computerized routine for automatic N400-peak marking (based on the ascendant zero-cross of the first waveform derivative) was applied to the estimated individual ERP waveform for congruous and incongruous sentences in both series for all ERP topographic derivations. Peak-to-peak N400 amplitude was significantly augmented (P < 0.05; one-sided Wilcoxon signed-rank test) due to incongruence in derivations F3, T3, C3, Cz, T5, P3, Pz, and P4 for nominal object series and in P3, Pz and P4 for pronominal object series. The results also indicated high inter-individual variability in ERP waveforms, suggesting that the usual procedure of grand averaging might not be considered a generally adequate approach. Hence, signal processing statistical techniques should be applied in neurolinguistic ERP studies allowing waveform analysis with low signal-to-noise ratio.

Participation of endogenous opioids in the antinociception induced by resistance exercise in rats

Exercise is a low-cost intervention that promotes health and contributes to the maintenance of the quality of life. The present study was designed to investigate the influence of different resistance exercise protocols on the nociceptive threshold of rats. Female Wistar rats were used to perform exercises in a weight-lifting exercise model. The following groups were examined (N = 6 per group): untrained rats (control group); an acute protocol group consisting of rats submitted to 15 sets of 15 repetitions of resistance exercise (acute group); rats exercised with 3 sets of 10 repetitions, three times per week for 12 weeks (trained group), and a group consisting of trained rats that were further submitted to the acute protocol (trained-acute group). The nociceptive threshold was measured by the paw-withdrawal test, in which the withdrawal threshold (escape reaction) was measured by an apparatus applying force to the plantar surface of the animal paw. The opioid antagonist naloxone (2 mg/kg) was administered subcutaneously 10 min before the exercise protocols. The trained group demonstrated antinociception only up to day 45 of the 12-week training period. A significant increase (37%, P < 0.05) in the nociceptive threshold was produced immediately after exercise, decreasing to 15% after 15 min, when the acute exercise protocol was used. Naloxone reversed this effect. These data show that the acute resistance exercise protocol was effective in producing antinociception for 15 min. This antinociceptive effect is mediated by the activation of opioid receptors.

Do whole-body vibration exercise and resistance exercise modify concentrations of salivary cortisol and immunoglobulin A?

A single bout of resistance exercise (RE) induces hormonal and immune responses, playing an important role in a long-term adaptive process. Whole-body vibration (WBV) has also been shown to affect hormonal responses. Evidence suggests that combining WBV with RE may amplify hormonal and immune responses due to the increased neuromuscular load. Therefore, the aim of this study was to evaluate salivary cortisol (Scortisol) and salivary IgA (SIgA) concentrations following a RE session combined or not with WBV. Nine university students (22.9 ± 5.1 years, 175.8 ± 5.2 cm, and 69.2 ± 7.3 kg) performed five sets of squat exercise (70% one-repetition-maximum) combined (R+V30) or not (R) with WBV at 30 Hz. Saliva samples were obtained before and after exercise. Subjects also rated their effort according to the Borg CR-10 scale (RPE). Data were analyzed by a mixed model. RPE was higher after R+V30 (8.3 ± 0.7) compared to R (6.2 ± 0.7). However, Scortisol (pre: 10.6 ± 7.6 and 11.7 ± 7.6, post: 8.3 ± 6.3 and 10.2 ± 7.2 ng/mL for R and R+V30, respectively) and SIgA concentrations (pre: 98.3 ± 22.6 and 116.1 ± 51.2, post: 116.6 ± 64.7 and 143.6 ± 80.5 µg/mL for R and R+V30, respectively) were unaffected. No significant correlations were observed between Scortisol and RPE (r = 0.45, P = 0.22; r = 0.30, P = 0.42, for R and R+V30, respectively). On the basis of these data, neither protocol modified salivary cortisol or IgA, although RPE was higher after R+V30 than R.

Development and validation of a genotype 3 recombinant protein-based immunoassay for hepatitis E virus serology in swine

Hepatitis E virus (HEV) is classified within the family Hepeviridae, genus Hepevirus. HEV genotype 3 (Gt3) infections are endemic in pigs in Western Europe and in North and South America and cause zoonotic infections in humans. Several serological assays to detect HEV antibodies in pigs have been developed, at first mainly based on HEV genotype 1 (Gt1) antigens. To develop a sensitive HEV Gt3 ELISA, a recombinant baculovirus expression product of HEV Gt3 open reading frame-2 was produced and coated onto polystyrene ELISA plates. After incubation of porcine sera, bound HEV antibodies were detected with anti-porcine anti-IgG and anti-IgM conjugates. For primary estimation of sensitivity and specificity of the assay, sets of sera were used from pigs experimentally infected with HEV Gt3. For further validation of the assay and to set the cutoff value, a batch of 1100 pig sera was used. All pig sera were tested using the developed HEV Gt3 assay and two other serologic assays based on HEV Gt1 antigens. Since there is no gold standard available for HEV antibody testing, further validation and a definite setting of the cutoff of the developed HEV Gt3 assay were performed using a statistical approach based on Bayes' theorem. The developed and validated HEV antibody assay showed effective detection of HEV-specific antibodies. This assay can contribute to an improved detection of HEV antibodies and enable more reliable estimates of the prevalence of HEV Gt3 in swine in different regions.

Global microRNA profiles and signaling pathways in the development of cardiac hypertrophy

Hypertrophy is a major predictor of progressive heart disease and has an adverse prognosis. MicroRNAs (miRNAs) that accumulate during the course of cardiac hypertrophy may participate in the process. However, the nature of any interaction between a hypertrophy-specific signaling pathway and aberrant expression of miRNAs remains unclear. In this study, Spague Dawley male rats were treated with transverse aortic constriction (TAC) surgery to mimic pathological hypertrophy. Hearts were isolated from TAC and sham operated rats (n=5 for each group at 5, 10, 15, and 20 days after surgery) for miRNA microarray assay. The miRNAs dysexpressed during hypertrophy were further analyzed using a combination of bioinformatics algorithms in order to predict possible targets. Increased expression of the target genes identified in diverse signaling pathways was also analyzed. Two sets of miRNAs were identified, showing different expression patterns during hypertrophy. Bioinformatics analysis suggested the miRNAs may regulate multiple hypertrophy-specific signaling pathways by targeting the member genes and the interaction of miRNA and mRNA might form a network that leads to cardiac hypertrophy. In addition, the multifold changes in several miRNAs suggested that upregulation of rno-miR-331*, rno-miR-3596b, rno-miR-3557-5p and downregulation of rno-miR-10a, miR-221, miR-190, miR-451 could be seen as biomarkers of prognosis in clinical therapy of heart failure. This study described, for the first time, a potential mechanism of cardiac hypertrophy involving multiple signaling pathways that control up- and downregulation of miRNAs. It represents a first step in the systematic discovery of miRNA function in cardiovascular hypertrophy.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Mathematical modeling of microbial growth in milk

A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.