Inclusion of exogenous enzymes in feedlot cattle diets: Impacts on physiology, rumen fermentation, digestibility and fatty acid profile in rumen and meat.

The objective of this study was to evaluate if the inclusion of a blend composed of exogenous enzymes (amylase, protease, cellulase, xylanase and beta glucanase) in the individual and combined form in the feedlot steers diet has benefits on the physiology, rumen fermentation, digestibility and fatty acid profile in rumen and meat. The experiment used 24 animals, divided into 4 treatments, described as: T1-CON, T2-BLEND (0.5 g mixture of enzyme), T3-AMIL (0.5 g alpha-amylase), T4-BLEND+AMIL (0.5 g enzyme blend+ 0.5 g amylase). The concentration of mineral matter was higher in the meat of cattle of T4-BLEND+AMIL. A higher proportion of monounsaturated fatty acids was observed in the T3-AMIL group when compared to the others. The percentage of polyunsaturated fatty acids was higher in the T2-BLEND and T4-BLEND+AMIL compared to the T1-CON. The combination of exogenous enzymes in the diet positively modulate nutritional biomarkers, in addition to benefits in the lipid and oxidative profile meat.

Potential of NIR spectroscopy for predicting cellulose nanofibril quality in commercial bleached Kraft pulp of Eucalyptus.

Multivariate models were developed to classify cellulose nanofibril (CNF) fibrillation by a quality index from near infrared (NIR) spectra. Commercial pulps of Eucalyptus spp. were used to produce cellulose nanofibrils by means of a fibrillator mill. After each of the five passes through the mill, samples were collected and analyzed for energy consumption and fiber classification. As a standard, pulps were oxidized with TEMPO reagent followed by a single pass through the mill to compare the resulting quality of CNFs produced by each method. NIR spectra of CNFs were associated with quality indices determined by conventional laboratory analyses that included morphology, turbidity, mechanical properties, X-ray diffraction and quality index measurements. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were applied to the spectral and experimental data. Fibrillator milling to obtain CNFs was efficient and resulted in gel formation following the third pass through the mill. NIR spectroscopy combined with PLS-DA was used successfully to create a model to classify quality of CNFs with 96 % certainty in 3 wt% solutions. These findings suggest that NIR spectroscopy holds promise for estimating CNF quality in suspension, particularly in real-time industrial applications where reliable estimates are crucial.

Prediction of Return of Spontaneous Circulation in a Pediatric Swine Model of Cardiac Arrest Using Low-Resolution Multimodal Physiological Waveforms.

Monitoring physiological waveforms, specifically hemodynamic variables (e.g., blood pressure waveforms) and end-tidal CO2 (EtCO2), during pediatric cardiopulmonary resuscitation (CPR) has been demonstrated to improve survival rates and outcomes when compared to standard depth-guided CPR. However, waveform guidance has largely been based on thresholds for single parameters and therefore does not leverage all the information contained in multimodal data. We hypothesize that the combination of multimodal physiological features improves the prediction of the return of spontaneous circulation (ROSC), the clinical indicator of short-term CPR success. We used machine learning algorithms to evaluate features extracted from eight low-resolution (4 samples per minute) physiological waveforms to predict ROSC. The waveforms were acquired from the 2nd to 10th minute of CPR in pediatric swine models of cardiac arrest (N = 89, 8-12 kg). The waveforms were divided into segments with increasing length (both forward and backward) for feature extraction, and machine learning algorithms were trained for ROSC prediction. For the full CPR period (2nd to 10th minute), the area under the receiver operating characteristics curve (AUC) was 0.93 (95% CI: 0.87-0.99) for the multivariate model, 0.70 (0.55-0.85) for EtCO2 and 0.80 (0.67-0.93) for coronary perfusion pressure. The best prediction performances were achieved when the period from the 6th to the 10th minute was included. Poor predictions were observed for some individual waveforms, e.g., right atrial pressure. In conclusion, multimodal waveform features carry relevant information for ROSC prediction. Using multimodal waveform features in CPR guidance has the potential to improve resuscitation success and reduce mortality.

Heart rate variability as a biomarker in patients with Chronic Chagas Cardiomyopathy with or without concomitant digestive involvement and its relationship with the Rassi score.

BACKGROUND: Dysautonomia plays an ancillary role in the pathogenesis of Chronic Chagas Cardiomyopathy (CCC), but is the key factor causing digestive organic involvement. We investigated the ability of heart rate variability (HRV) for death risk stratification in CCC and compared alterations of HRV in patients with isolated CCC and in those with the mixed form (CCC + digestive involvement). Thirty-one patients with CCC were classified into three risk groups (low, intermediate and high) according to their Rassi score. A single-lead ECG was recorded for a period of 10-20 min, RR series were generated and 31 HRV indices were calculated. The HRV was compared among the three risk groups and regarding the associated digestive involvement. Four machine learning models were created to predict the risk class of patients. RESULTS: Phase entropy is decreased and the percentage of inflection points is increased in patients from the high-, compared to the low-risk group. Fourteen patients had the mixed form, showing decreased triangular interpolation of the RR histogram and absolute power at the low-frequency band. The best predictive risk model was obtained by the support vector machine algorithm (overall F1-score of 0.61). CONCLUSIONS: The mixed form of Chagas' disease showed a decrease in the slow HRV components. The worst prognosis in CCC is associated with increased heart rate fragmentation. The combination of HRV indices enhanced the accuracy of risk stratification. In patients with the mixed form of Chagas disease, a higher degree of sympathetic autonomic denervation may be associated with parasympathetic impairment.

Idiopathic musculoskeletal pain, musculoskeletal pain syndromes, and use of electronic devices in adolescents with asthma

Abstract Objective: To evaluate idiopathic musculoskeletal pain, musculoskeletal pain syndromes, and use of electronic devices in adolescents with asthma and healthy controls. Methods: Cross-sectional study was conducted on 150 asthmatic adolescents and 300 controls. Adolescents completed a self-administered questionnaire regarding painful symptoms, use of electronic devices, and physical activity. Seven musculoskeletal pain syndromes were evaluated, and Asthma Control Test (ACT) was assessed. Results: Musculoskeletal pain (42% vs. 61%, p = 0.0002) and musculoskeletal pain syndromes (2.7% vs. 15.7%, p = 0.0006) were significantly lower in asthmatic adolescents than in controls. The frequency of pain in the hands and wrists was reduced in asthmatic than in controls (12.6% vs. 31.1%, p = 0.004), in addition to cell phone use (80% vs. 93%, p < 0.0001), simultaneous use of at least two electronic media (47% vs. 91%, p < 0.0001), myofascial syndrome (0% vs. 7.1%, p = 0.043), and tendinitis (0% vs. 9.2%, p = 0.008). Logistic regression analysis, including asthma with musculoskeletal pain as the dependent variable, and female sex, ACT > 20, simultaneous use of at least two electronic devices, cell phone use, and weekends and weekdays of cell phone use, as independent variables, showed that female sex (odds ratio [OR], 2.06; 95% confidence interval [CI], 1.929-6.316; p = 0.0009) and ACT ≥ 20 (OR, 0.194; 95% CI, 0.039-0.967; p = 0.045) were associated with asthma and musculoskeletal pain (Nagelkerke R2 = 0.206). Conclusion: Musculoskeletal pain and musculoskeletal pain syndromes were lower in adolescents with asthma. Female sex was associated with musculoskeletal pain in asthmatic, whereas patients with asthma symptoms and well-controlled disease reported a lower prevalence of musculoskeletal pain.

Aryl hydrocarbon receptor (AhR) activation contributes to high-fat diet-induced vascular dysfunction.

BACKGROUND AND PURPOSE: Metabolic and vascular dysfunction are common features of obesity. Aryl hydrocarbon receptor (AhR) regulates lipid metabolism and vascular homeostasis, but whether vascular AhR are activated in obesity or have a protective and/or harmful effects on vascular function in obesity are unknown. Our study addresses whether AhR activation contributes to obesity-associated vascular dysfunction and the mechanisms involved in these AhR effects. EXPERIMENTAL APPROACH: Male AhR KO (Ahr-/- ) and WT mice were fed either control or a HF (high-fat) diet for 10 weeks. Metabolic and inflammatory parameters were measured in serum and adipose tissue. Vascular reactivity (isometric force) was evaluated using a myography. Endothelial NOS (eNOS) and AhR protein expression was determined by western blot, Cyp1A1 and Nos3 gene expression by RT-PCR and.NO production was quantified by DAF fluorescence. KEY RESULTS: HF diet increased total serum HDL and LDL, as well as vascular AhR protein expression and proinflammatory cytokines in the adipose tissue. HF diet decreased endothelium-dependent vasodilation. AhR deletion protected mice from HF diet-induced dyslipidaemia, weight gain and inflammatory processes. HF diet-induced endothelial dysfunction was attenuated in Ahr-/- mice. Vessels from Ahr-/- mice exhibited a greater NO reserve. In cultured endothelial cells, lysophosphatidylcholine (LPC) a major component of LDL and oxidized LDL [oxLDL]) reduced Nos3 gene expression and NO production. Antagonism of the AhR inhibited LPC effects on endothelial cells and induced decreased endothelium-dependent vasodilation. CONCLUSION AND IMPLICATIONS: AhR deletion attenuates HF diet-induced dyslipidaemia and vascular dysfunction by improving eNOS/NO signalling. Targeting AhRs may prevent obesity-associated vascular dysfunction.

Correlation between heart rate variability and polysomnography-derived scores of obstructive sleep apnea.

Obstructive sleep apnea (OSA) is one of the most common sleep disorders and affects nearly a billion people worldwide. Furthermore, it is estimated that many patients with OSA are underdiagnosed, which contributes to the development of comorbidities, such as cardiac autonomic imbalance, leading to high cardiac risk. Heart rate variability (HRV) is a non-invasive, widely used approach to evaluating neural control of the heart. This study evaluates the relationship between HRV indices and the presence and severity of OSA. We hypothesize that HRV, especially the nonlinear methods, can serve as an easy-to-collect marker for OSA early risk stratification. Polysomnography (PSG) exams of 157 patients were classified into four groups: OSA-free (N = 26), OSA-mild (N = 39), OSA-moderate (N = 37), and OSA-severe (N = 55). The electrocardiogram was extracted from the PSG recordings, and a 15-min beat-by-beat series of RR intervals were generated every hour during the first 6 h of sleep. Linear and nonlinear HRV approaches were employed to calculate 32 indices of HRV. Specifically, time- and frequency-domain, symbolic analysis, entropy measures, heart rate fragmentation, acceleration and deceleration capacities, asymmetry measures, and fractal analysis. Results with indices of sympathovagal balance provided support to reinforce previous knowledge that patients with OSA have sympathetic overactivity. Nonlinear indices showed that HRV dynamics of patients with OSA display a loss of physiologic complexity that could contribute to their higher risk of development of cardiovascular disease. Moreover, many HRV indices were found to be linked with clinical scores of PSG. Therefore, a complete set of HRV indices, especially the ones obtained by the nonlinear approaches, can bring valuable information about the presence and severity of OSA, suggesting that HRV can be helpful for in a quick diagnosis of OSA, and supporting early interventions that could potentially reduce the development of comorbidities.

Idiopathic musculoskeletal pain, musculoskeletal pain syndromes, and use of electronic devices in adolescents with asthma.

OBJECTIVE: To evaluate idiopathic musculoskeletal pain, musculoskeletal pain syndromes, and use of electronic devices in adolescents with asthma and healthy controls. METHODS: Cross-sectional study was conducted on 150 asthmatic adolescents and 300 controls. Adolescents completed a self-administered questionnaire regarding painful symptoms, use of electronic devices, and physical activity. Seven musculoskeletal pain syndromes were evaluated, and Asthma Control Test (ACT) was assessed. RESULTS: Musculoskeletal pain (42% vs. 61%, p = 0.0002) and musculoskeletal pain syndromes (2.7% vs. 15.7%, p = 0.0006) were significantly lower in asthmatic adolescents than in controls. The frequency of pain in the hands and wrists was reduced in asthmatic than in controls (12.6% vs. 31.1%, p = 0.004), in addition to cell phone use (80% vs. 93%, p < 0.0001), simultaneous use of at least two electronic media (47% vs. 91%, p < 0.0001), myofascial syndrome (0% vs. 7.1%, p = 0.043), and tendinitis (0% vs. 9.2%, p = 0.008). Logistic regression analysis, including asthma with musculoskeletal pain as the dependent variable, and female sex, ACT > 20, simultaneous use of at least two electronic devices, cell phone use, and weekends and weekdays of cell phone use, as independent variables, showed that female sex (odds ratio [OR], 2.06; 95% confidence interval [CI], 1.929-6.316; p = 0.0009) and ACT ≥ 20 (OR, 0.194; 95% CI, 0.039-0.967; p = 0.045) were associated with asthma and musculoskeletal pain (Nagelkerke R2 = 0.206). CONCLUSIONS: Musculoskeletal pain and musculoskeletal pain syndromes were lower in adolescents with asthma. Female sex was associated with musculoskeletal pain in asthmatic, whereas patients with asthma symptoms and well-controlled disease reported a lower prevalence of musculoskeletal pain.

Spinopelvic parameters after posterior lumbar arthrodesis in degenerative spinal diseases / Parâmetros espinopélvicos após artrodese lombar posterior em doenças degenerativas da coluna vertebral / Parámetros espinopélvicos tras artrodesis lumbar posterior en enfermedades degenerativas de la coluna vertebral

ABSTRACT Introduction: Spinopelvic parameters related to sagittal balance have become increasinglyimportantamong spine surgeons due to their correlation with patient satisfaction rates. Objective: The goal of this study was to evaluate changes in spinal sagittal balance after lumbar spine surgery using PLIF, the posterior lumbar interbody fusion technique. Methods: The sample consisted of adult patients with degenerative spinal disease submitted to posterior lumbar arthrodesis. Patients between 18 and 70 years of agewho underwent surgeryfrom 2015 to 2017 were included in the study and divided into short (1 level) and long arthrodesis (2 to 4 levels) groups. Radiographic analysis of the spinopelvic parameters, measured before and after lumbar arthrodesis, was conducted using the SURGIMAP software. Then we evaluated the variation between pre- and postoperative measurements and performed correlation and linear regression analyses between the parameters. Results: The sample was composed of 80 patients (48 men). The mean age was lower in the short arthrodesis group than in the long arthrodesis group (52.67 ± 9.66 years versus 59.37 ± 9.30 years, respectively; p<0.0025). Significant variations in lumbar lordosis, pelvic tilt, sagittal vertical axis, T1 pelvic angle, and pelvic incidence minus lumbar lordosis were found in both short and long arthrodesis groups. The variation was significantly larger in the long than in the short arthrodesis group. Conclusion: In adult degenerative spine disease, short and long arthrodesis of the lumbar spine by PLIF allows correction of the spinopelvic parameters. Level of evidence III; Retrospective, comparative study.

RESUMO: Introdução: Os parâmetros espinopélvicos relacionados ao equilíbrio sagital vêm ganhando cada vez mais importância devido a sua correlação com as taxas de satisfação dos pacientes. Objetivo: O objetivo do estudo foi avaliar as alterações no equilíbrio sagital após cirurgia da coluna lombar com a técnica PLIF, fusão intersomática lombar posterior. Métodos: A população do estudo foi composta por pacientes adultos com doença degenerativa da coluna submetidos a artrodese da coluna lombar por via posterior. Foram incluídos pacientes com idade entre 18 e 70 anos, submetidos àcirurgia no período de 2015 a 2017, divididos em grupo de artrodese curta (1 nível) e grupo de artrodese longa (2 a 4 níveis). Foi realizada análise radiográfica dos parâmetros espinopélvicos, medidos antes e após a artrodese lombar, utilizando o softwareSURGIMAP. Em seguida, a variação entre as medidas pré e pós-operatórias foi avaliada e foram realizadas análises de correlação e regressão linear entre os parâmetros. Resultados: A amostra foi composta por 80 pacientes (48 homens). A média de idade dos pacientes do grupo artrodese curta foi inferior à do grupo artrodese longa (52,67 ± 9,66 anos versus 59,37 ± 9,30, respectivamente; p<0,0025). Foram identificadas variações significativas na lordose lombar, inclinação pélvica, eixo vertical sagital, ângulo pélvico T1 e incidência pélvica menos lordose lombar tanto no grupo de artrodese curta e como de artrodese longa. A variação foi significativamente maior no grupo de artrodese longa do que no grupo de artrodese curta. Conclusão: Em adultos com doença degenerativa da coluna lombar, a artrodese curta e longa usando atécnica PLIF permite a correção dos parâmetros espinopélvicos. Nível de evidência III; Estudo retrospectivo comparativo.

RESUMEN: Introducción: Los parámetros espinopélvicos relacionados con el equilibrio sagital han ido ganando cada vez más importancia debido a su correlación con los índices de satisfacción de los pacientes. Objetivo: El objetivo del estudio fue evaluar los cambios en el equilibrio sagital después de la cirugía de columna lumbar con la técnica PLIF, fusión intersomática lumbar posterior. Métodos: La población de estudio fue compuesta por pacientes adultos con enfermedad degenerativa de la columna sometidos a artrodesis de columna lumbar por vía posterior. Se incluyeron pacientes entre 18 y 70 años, sometidos a cirugíaentre 2015 y 2017, divididos en grupos de artrodesis corta (1 nivel) y grupo de artrodesis larga (2 a 4 niveles). El análisis radiográfico de los parámetros espinopélvicos, medidos antes y después de la artrodesis lumbar,se realizó utilizando el software SURGIMAP. A continuación, se evaluó la variación entre las mediciones pre y postoperatorias y se realizaron análisis de correlación y regresión entre los parámetros. Resultados: La muestra estabacompuesta por 80 pacientes (48 hombres). La edad media de los pacientes del grupo de artrodesis corta era inferior a la del grupo de artrodesis larga (52,67 ± 9,66 años frente a 59,37 ± 9,30, respectivamente; p<0,0025). Se identificaron variaciones significativas en cuanto a lordosis lumbar, inclinación pélvica, eje vertical sagital, ángulo pélvico T1 e incidencia pélvica menos lordosis lumbar en los grupos de artrodesis corta y larga. La variación fue significativamente mayor en el grupo de artrodesis larga que en el de artrodesis corta.. Conclusión: En adultos con enfermedad degenerativa de la columna lumbar, la artrodesis corta y larga mediante la técnica PLIF permite corregir los parámetros espinopélvicos. Nivel de evidencia III; Estudio retrospectivo comparativo.

Multiscale Entropy Analysis of Short Signals: The Robustness of Fuzzy Entropy-Based Variants Compared to Full-Length Long Signals.

Multiscale entropy (MSE) analysis is a fundamental approach to access the complexity of a time series by estimating its information creation over a range of temporal scales. However, MSE may not be accurate or valid for short time series. This is why previous studies applied different kinds of algorithm derivations to short-term time series. However, no study has systematically analyzed and compared their reliabilities. This study compares the MSE algorithm variations adapted to short time series on both human and rat heart rate variability (HRV) time series using long-term MSE as reference. The most used variations of MSE are studied: composite MSE (CMSE), refined composite MSE (RCMSE), modified MSE (MMSE), and their fuzzy versions. We also analyze the errors in MSE estimations for a range of incorporated fuzzy exponents. The results show that fuzzy MSE versions-as a function of time series length-present minimal errors compared to the non-fuzzy algorithms. The traditional multiscale entropy algorithm with fuzzy counting (MFE) has similar accuracy to alternative algorithms with better computing performance. For the best accuracy, the findings suggest different fuzzy exponents according to the time series length.

An Ultrasonic-Capacitive System for Online Characterization of Fuel Oils in Thermal Power Plants.

This paper presents a ultrasonic-capacitive system for online analysis of the quality of fuel oils (FO), which are widely used to produce electric energy in Thermal Power Plants (TPP) due to their elevated heating value. The heating value, in turn, is linked to the quality of the fuel (i.e., the density and the amount of contaminants, such as water). Therefore, the analysis of the quality is of great importance for TPPs, either in order to avoid a decrease in generated power or in order to avoid damage to the TPP equipment. The proposed system is composed of two main strategies: a capacitive system (in order to estimate the water content in the fuel) and an ultrasonic system (in order to estimate the density). The conjunction of the two strategies is used in order to estimate the heating value of the fuel, online, as it passes through the pipeline and is an important tool for the TPP in order to detect counterfeit fuel. In addition, the ultrasonic system allows the estimation of the flow rate through the pipeline, hence estimating the amount of oil transferred and obtaining the total mass transferred as a feature of the system. Experimental results are provided for both sensors installed in a TPP in Brazil.

Heart rate fragmentation, a novel approach in heart rate variability analysis, is altered in rats 4 and 12 weeks after myocardial infarction.

An approach recently proposed to assess ultra-rapid patterns of heart rate variability, namely heart rate fragmentation (HRF), is increased in aging and coronary disease. We aimed to evaluate and to correlate HRF with cardiac functional parameters in a rat model of myocardial infarction (MI). Wistar rats were submitted to MI (n = 18) or sham operation (n = 20), and after 4 or 12 weeks, their arterial pressure was recorded. Subsequently, cardiac function was evaluated by echocardiography. From pulse interval series, HRF patterns with zero, one, two, or three inflection points were estimated, as well as the total percentage of inflection points (PIP). Cardiac function was reduced in MI rats. Ejection fraction was smaller 4 (28 ± 3 vs 68 ± 2%, p < 0.0001) and 12 weeks after MI (38 ± 3 vs 70 ± 3%, p < 0.0001). Fractional shortening was also smaller 4 (13 ± 2 vs 41 ± 2%, p < 0.0001) and 12 weeks after MI (20 ± 2 vs 41 ± 3%, p < 0.0001). PIP was increased in MI rats 4 (74 ± 2 vs 69 ± 1%, p = 0.03) and 12 weeks after surgery (70 ± 2 vs 63 ± 1%, p = 0.02). We found a significant negative correlation between cardiac functional parameters and HRF at both 4 and 12 weeks after MI. These findings reveal that MI increases HRF, reinforcing the importance of this approach to explore pathophysiological conditions. Evaluation of heart rate fragmentation (HRF) in a rat model of myocardial infarction (MI). Wistar rats were submitted to MI (n = 18) or sham operation (n = 20), and after 4 or 12 weeks, their arterial pressure was recorded. Cardiac function was evaluated by echocardiography. From pulse interval series, HRF patterns with zero (W0), one (W1), two (W3), or three (W3) inflection points were estimated, as well as the total percentage of inflection points (PIP). Cardiac function was reduced, while PIP was increased in all MI rats. Fluent patterns (W0 and W1) decreased in MI rats after 12 weeks. Altogether, the findings reveal that MI increases HRF, reinforcing the potential of this approach to explore pathophysiological conditions.

Redispersion and structural change evaluation of dried microfibrillated cellulose.

Commercializing dried microfibrillated cellulose (MFC) has always been a challenge mainly due to the tendency of MFC to aggregate. In this study MFC samples were submitted to drying/redispersion cycles at different temperatures. Morphology, crystallinity and mechanical performance of films were analyzed throughout the cycles. Microscopy images, particle size and stability in water showed that aggregation happens more severely with 5 drying/redispersion cycles and at drying temperatures of 75 and 100 °C. Particles once-dried at 20 °C formed the same size and web-like structure as the MFC-control. Crystallinity and crystallite sizes increased with drying/redispersion cycles especially when dried at 75 and 100 °C, however drying/redispersion cycles also led to a reduction in mechanical performance due to aggregation. While oven-drying is not the most suitable method, milder action at room temperature once-drying led to suspension stability in water, morphology and mechanical properties close to never-dried MFC, which makes this treatment a feasible option to maintain cellulose quality.

Intelligent System for Dispatch Ranking of Generating Units in Thermoelectric Power-Plants

Abstract The multicriteria decision-making process is still an open problem, especially when the decision criteria are not numerical or fully outlined. Several numerical, intelligent, or hybrid techniques have been developed, creating contributions to this problem's solution. This paper is another step in this direction. Based on the Modified Analytic Hierarchy Process (MAHP), a methodology for diagnosis and performance analysis is presented for the dispatch ranking of generating units in a thermoelectric plant. The problem is complex because it covers a power plant, where 99 generating units may be dispatched, according to 10 possible evaluation criteria, which should be used together. This article also presents details of the implementation of the sensors necessary to add to the supervisory system existing in the Palmeiras de Goias Thermal Power Plant.

Diferenciação oxidativa em dispositivos temporários de ancoragem de Ti6Al4V e aço 316L ­ estudo piloto / Oxidative differentiation in temporary anchoring devices made by Ti6Al4V and 316L steel ­ a pilot study

Resumo Este estudo piloto testou a hipótese de que os dispositivos temporários de ancoragem (DATs) fabricados de Aço 316L são mais resistentes à corrosão, mesmo em meio com flúor, do que os DATs fabricados a partir de ligas de titânio, para tanto foram realizadas medições eletroquímicas em Potenciostato. Materiais e Métodos: Quatro amostras de cada material foram testadas em cada conjunto de teste, a formulação artificial de saliva de Fusayama foi usada como eletrólito solução neste estudo de corrosão in vitro, sem flúor em sua composição e, em um segundo momento, com a concentração de 1500ppM de flúor em sua composição. No teste, uma polarização catódica foi então realizada aumentando essa voltagem por 5 minutos ou até que se obtivessem os pitins de corrosão. Em saliva artificial contendo até 1500ppmF- foi repetido esse teste com novas amostras de cada material em solução de saliva artificial sem a presença de flúor. Resultados: Os resultados de escala de corrente de indução foram inseridos no software OriginPro8 para confecção dos gráficos de valores. Tratando-se de um número reduzido de amostras, para não violar a confiabilidade do estudo, não se realizou teste estatístico. Dentre todas as ligas metálicas utilizadas atualmente, a liga de Ti6Al4V apresentou uma boa resistência à corrosão em saliva artificial. Entretanto a corrosão dessas ligas ocorre em contato com altas concentrações de flúor, diferentemente da liga de Aço 316L, que além da corrosão faz a passivação da superfície. (AU)

Abstract The aim of this pilot study was to test the hypothesis that temporary anchoring devices (TADs) made of 316L steel are more resistant to corrosion even in fluorine environment than DATs manufactured in addition to titanium alloys, for this Potentiostat electrochemical measurements were performed. Materials and Methods: Four pieces of each material were tested in each test set, an application of Fusayama artificial saliva was used as an electrolytic solution in this study of in vitro corrosion, without fluorine in its composition and in a second moment with 1500ppM of fluorine in its composition. In the test, a cathodic polarization was performed by increasing this voltage for 5 minutes or until the corrosion pins were obtained. In artificial saliva containing up to 1500ppmF- this test was repeated with new samples of each material in artificial saliva solution without fluorine. Results: The results of the induction current scale were inserted into OriginPro8 software for making value graphs. As there was a small number of samples, in order not to violate the study's reliability no statistical test was performed. Among all metal alloys currently used the Ti6Al4V alloy showed good resistance to corrosion in artificial saliva. However, the corrosion of these alloys occurs in contact with high fluorine concentration, unlike 316L steel alloy, which in addition to corrosion makes surface passivation. (AU)

Changes in Short-Term and Ultra-Short Term Heart Rate, Respiratory Rate, and Time-Domain Heart Rate Variability Parameters during Sympathetic Nervous System Activity Stimulation in Elite Modern Pentathlonists-A Pilot Study.

Monitoring of markers reflecting cardiac autonomic activity before and during stressful situations may be useful for identifying the physiological state of an athlete and may have medical or performance implications. The study aimed to determine group and individual changes in short-term (5 min) and ultra-short-term (1 min) heart rate (HR), respiratory rate (RespRate), and time-domain heart rate variability (HRV) parameters during sympathetic nervous system activity (SNSa) stimulation among professional endurance athletes. Electrocardiographic recordings were performed in stable measurement conditions (Baseline) and during SNSa stimulation via isometric handgrip in 12 elite modern pentathlonists. Significant increases in short-term HR and decreases in time-domain HRV parameters with no changes in RespRate were observed during SNSa stimulation. Significant differences were observed between Baseline (all minutes) and the last (i.e., 5th) minute of SNSa stimulation for ultra-short-term parameters. Analysis of intra-individual changes revealed some heterogeneity in responses. The study provides baseline responses of HR, RespRate, and time-domain HRV parameters to SNSa stimulation among elite pentathlonists, which may be useful for identifying abnormal responses among fatigued or injured (e.g., concussed) athletes. More attention to individual analysis seems to be necessary when assessing physiological responses to sympathetic stimuli in professional endurance athletes.

A Pilot Study of the Reliability and Agreement of Heart Rate, Respiratory Rate and Short-Term Heart Rate Variability in Elite Modern Pentathlon Athletes.

Research on reliability of heart rate variability (HRV) parameters in athletes has received increasing attention. The aims of this study were to examine the inter-day reliability of short-term (5 min) and ultra-short-term (1 min) heart rate (HR), respiratory rate (RespRate) and HRV parameters, agreement between short-term and ultra-short-term parameters, and association between differences in HR, RespRate and HRV parameters in elite modern pentathletes. Electrocardiographic recordings were performed in stable measurement conditions with a week interval between tests. Relative reliability was evaluated by intra-class correlation coefficients, absolute reliability was evaluated by within-subject coefficient of variation, and agreement was evaluated using Bland-Altman (BA) plot with limits of agreement and defined a priori maximum acceptable difference. Short-term HR, RespRate, log transformed (ln) root mean square of successive normal-to-normal interval differences (lnRMSSD), ln high frequency (lnHF) and SD2/SD1 HRV indices and ultra-short-term HR, RespRate and lnRMSSD presented acceptable, satisfactory inter-day reliability. Although there were no significant differences between short-term and ultra-short-term HR, RespRate and lnRMSSD, no parameter showed acceptable differences with BA plots. Differences in time-domain and non-linear HRV parameters were more correlated with differences in HR than with differences in RespRate. Inverse results were observed for frequency-domain parameters. Short-term HR, RespRate, lnRMSSD, lnHF, and SD2/SD1 and ultra-short-term HR, RespRate and lnRMSSD could be used as reliable parameters in endurance athletes. However, practitioners should interpret changes in HRV parameters with regard to concomitant differences in HR and RespRate and caution should be taken before considering 5 min and 1 min parameters as interchangeable.

Modified multiscale fuzzy entropy: A robust method for short-term physiologic signals.

The introduction of the multiscale entropy (MSE) method was a milestone in the field of complex physiological signal analysis. However, since MSE is inapplicable for short signals, several variants of MSE have been proposed. One of the most important variants of MSE is the modified multiscale entropy (MMSE), even though it can still produce biased estimates due to the hard similarity criteria of sample entropy. Taking the advantages of MMSE and the concept of fuzzy entropy, we propose the modified multiscale fuzzy entropy (MMFE). We evaluated the robustness of MMSE and MMFE using segmented stochastic noises and actual heart rate variability series and compared it with the classical MSE results obtained with the full signals. Results show that MMFE is much more robust than MMSE for short physiological time series, resembling MSE for series as shorter as 400 samples. We also show the existence of an exponential relationship between the MMFE fuzzy parameter and the signal size. We suggest the use of this relationship to choose the optimal MMFE parameter as part of the method.

PyBioS: A freeware computer software for analysis of cardiovascular signals.

BACKGROUND AND OBJECTIVE: Several software applications have been proposed in the past years as computational tools for assessing biomedical signals. Many of them are focused on heart rate variability series only, with their strengths and limitations depending on the necessity of the user and the scope of the application. Here, we introduce new software, named PyBioS, intended for the analysis of cardiovascular signals, even though any type of biomedical signal can be used. PyBioS has some functionalities that differentiate it from the other software. METHODS: PyBioS was developed in Python language with an intuitive, user-friendly graphical user interface. The basic steps for using PyBioS comprise the opening or creation (simulation) of signals, their visualization, preprocessing and analysis. Currently, PyBioS has 8 preprocessing tools and 15 analysis methods, the later providing more than 50 metrics for analysis of the signals' dynamics. RESULTS: The possibility to create simulated signals and save the preprocessed signals is a strength of PyBioS. Besides, the software allows batch processing of files, making the analysis of a large amount of data easy and fast. Finally, PyBioS has plenty of analysis methods implemented, with the focus on nonlinear and complexity analysis of signals and time series. CONCLUSIONS: Although PyBioS is not intended to overcome all the necessities from users, it has useful functionalities that may be helpful in many situations. Moreover, PyBioS is continuously under improvement and several simulated signals, tools and analysis methods are still to be implemented. Also, a new module is being implemented on it to provide machine learning algorithms for classification and regression of data extracted from the biomedical signals.