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.

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.

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.

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.

Heart failure developed after myocardial infarction does not affect gut microbiota composition in the rat.

There is a body of evidence that supports the notion that gut dysbiosis plays a role in the pathogenesis of cardiovascular diseases. Decreased cardiac function can reduce intestinal perfusion, resulting in morphological alterations, which may contribute to changes in the gut microbiota composition in patients with heart failure (HF). In this regard, a germane question is whether changes in gut microbiota composition are a cause or consequence of the cardiovascular disturbance. We tested the hypothesis that the development of HF, after myocardial infarction, would cause gut dysbiosis. Fecal samples were collected before and 6 wk after myocardial infarction or sham surgery. Gut microbiota were characterized by sequencing the bacterial 16S ribosomal DNA. The composition of bacterial communities in the fecal samples was evaluated by calculating three major ecological parameters: 1) the Chao 1 richness, 2) the Pielou evenness, and 3) the Shannon index. None of these indices was changed in either sham or HF rats. The Firmicutes/Bacteroidetes ratio was not altered in HF rats. The number of species in each phylum was also not different between sham and HF rats. ß-Diversity analysis showed that the composition of gut microbiota was not changed with the development of HF. Bacterial genera were grouped according to their major metabolic end-products (acetate, butyrate, and lactate), but no differences were observed in HF rats. Therefore, we conclude that HF induced by myocardial infarction does not affect gut microbiota composition, at least in rats, indicating that the dysbiosis observed in patients with HF may precede cardiovascular disturbance.NEW & NOTEWORTHY Our study demonstrated that, following myocardial infarction in rats, heart failure (HF) development did not affect the intestinal microbiota despite distinct differences reported in the gut microbiota of humans with HF. Our finding is consistent with the notion that dysbiosis observed in patients with HF may precede cardiovascular dysfunction and therefore offers potential for early diagnosis and treatment.

Changes in the Complexity of Heart Rate Variability with Exercise Training Measured by Multiscale Entropy-Based Measurements.

Quantifying complexity from heart rate variability (HRV) series is a challenging task, and multiscale entropy (MSE), along with its variants, has been demonstrated to be one of the most robust approaches to achieve this goal. Although physical training is known to be beneficial, there is little information about the long-term complexity changes induced by the physical conditioning. The present study aimed to quantify the changes in physiological complexity elicited by physical training through multiscale entropy-based complexity measurements. Rats were subject to a protocol of medium intensity training ( n = 13 ) or a sedentary protocol ( n = 12 ). One-hour HRV series were obtained from all conscious rats five days after the experimental protocol. We estimated MSE, multiscale dispersion entropy (MDE) and multiscale SDiff q from HRV series. Multiscale SDiff q is a recent approach that accounts for entropy differences between a given time series and its shuffled dynamics. From SDiff q , three attributes (q-attributes) were derived, namely SDiff q m a x , q m a x and q z e r o . MSE, MDE and multiscale q-attributes presented similar profiles, except for SDiff q m a x . q m a x showed significant differences between trained and sedentary groups on Time Scales 6 to 20. Results suggest that physical training increases the system complexity and that multiscale q-attributes provide valuable information about the physiological complexity.

Baroreflex control of renal sympathetic nerve activity in early heart failure assessed by the sequence method.

KEY POINTS: The integrity of the baroreflex control of sympathetic activity in heart failure (HF) remains under debate. We proposed the use of the sequence method to assess the baroreflex control of renal sympathetic nerve activity (RSNA). The sequence method assesses the spontaneous arterial pressure (AP) fluctuations and their related changes in heart rate (or other efferent responses), providing the sensitivity and the effectiveness of the baroreflex. Effectiveness refers to the fraction of spontaneous AP changes that elicits baroreflex-mediated variations in the efferent response. Using three different approaches, we showed that the baroreflex sensitivity between AP and RSNA is not altered in early HF rats. However, the sequence method provided evidence that the effectiveness of baroreflex in changing RSNA in response to AP changes is markedly decreased in HF. The results help us better understand the baroreflex control of the sympathetic nerve activity. ABSTRACT: In heart failure (HF), the reflex control of the heart rate is known to be markedly impaired; however, the baroreceptor control of the sympathetic drive remains under debate. Applying the sequence method to a series of arterial pressure (AP) and renal sympathetic nerve activity (RSNA), we demonstrated a clear dysfunction in the baroreflex control of sympathetic activity in rats with early HF. We analysed the baroreflex control of the sympathetic drive using three different approaches: AP vs. RSNA curve, cross-spectral analysis and sequence method between AP and RSNA. The sequence method also provides the baroreflex effectiveness index (BEI), which represents the percentage of AP ramps that actually produce a reflex response. The methods were applied to control rats and rats with HF induced by myocardial infarction. None of the methods employed to assess the sympathetic baroreflex gain were able to detect any differences between the control and the HF group. However, rats with HF exhibited a lower BEI compared to the controls. Moreover, an optimum delay of 1 beat was observed, i.e. 1 beat is required for the RSNA to respond after AP changing, which corroborates with the findings related to the timing between these two variables. For delay 1, the BEI of the controls was 0.45 ± 0.03, whereas the BEI of rats with HF was 0.29 ± 0.09 (P < 0.05). These data demonstrate that while the gain of the baroreflex is not affected in early HF, its effectiveness is markedly decreased. The analysis of the spontaneous changes in AP and RSNA using the sequence method provides novel insights into arterial baroreceptor reflex function.

The role of sympathetic and vagal cardiac control on complexity of heart rate dynamics.

Analysis of heart rate variability (HRV) by nonlinear approaches has been gaining interest due to their ability to extract additional information from heart rate (HR) dynamics that are not detectable by traditional approaches. Nevertheless, the physiological interpretation of nonlinear approaches remains unclear. Therefore, we propose long-term (60 min) protocols involving selective blockade of cardiac autonomic receptors to investigate the contribution of sympathetic and parasympathetic function upon nonlinear dynamics of HRV. Conscious male Wistar rats had their electrocardiogram (ECG) recorded under three distinct conditions: basal, selective (atenolol or atropine), or combined (atenolol plus atropine) pharmacological blockade of autonomic muscarinic or ß1-adrenergic receptors. Time series of RR interval were assessed by multiscale entropy (MSE) and detrended fluctuation analysis (DFA). Entropy over short (1 to 5, MSE1-5) and long (6 to 30, MSE6-30) time scales was computed, as well as DFA scaling exponents at short (αshort, 5 ≤ n ≤ 15), mid (αmid, 30 ≤ n ≤ 200), and long (αlong, 200 ≤ n ≤ 1,700) window sizes. The results show that MSE1-5 is reduced under atropine blockade and MSE6-30 is reduced under atropine, atenolol, or combined blockade. In addition, while atropine expressed its maximal effect at scale six, the effect of atenolol on MSE increased with scale. For DFA, αshort decreased during atenolol blockade, while the αmid increased under atropine blockade. Double blockade decreased αshort and increased αlong Results with surrogate data show that the dynamics during combined blockade is not random. In summary, sympathetic and vagal control differently affect entropy (MSE) and fractal properties (DFA) of HRV. These findings are important to guide future studies.NEW & NOTEWORTHY Although multiscale entropy (MSE) and detrended fluctuation analysis (DFA) are recognizably useful prognostic/diagnostic methods, their physiological interpretation remains unclear. The present study clarifies the effect of the cardiac autonomic control on MSE and DFA, assessed during long periods (1 h). These findings are important to help the interpretation of future studies.

Multiscale entropy analysis of heart rate variability in heart failure, hypertensive, and sinoaortic-denervated rats: classical and refined approaches.

The analysis of heart rate variability (HRV) by nonlinear methods has been gaining increasing interest due to their ability to quantify the complexity of cardiovascular regulation. In this study, multiscale entropy (MSE) and refined MSE (RMSE) were applied to track the complexity of HRV as a function of time scale in three pathological conscious animal models: rats with heart failure (HF), spontaneously hypertensive rats (SHR), and rats with sinoaortic denervation (SAD). Results showed that HF did not change HRV complexity, although there was a tendency to decrease the entropy in HF animals. On the other hand, SHR group was characterized by reduced complexity at long time scales, whereas SAD animals exhibited a smaller short- and long-term irregularity. We propose that short time scales (1 to 4), accounting for fast oscillations, are more related to vagal and respiratory control, whereas long time scales (5 to 20), accounting for slow oscillations, are more related to sympathetic control. The increased sympathetic modulation is probably the main reason for the lower entropy observed at high scales for both SHR and SAD groups, acting as a negative factor for the cardiovascular complexity. This study highlights the contribution of the multiscale complexity analysis of HRV for understanding the physiological mechanisms involved in cardiovascular regulation.

Toll-like receptor 9 plays a key role in the autonomic cardiac and baroreflex control of arterial pressure.

The crosstalk between the immune and the autonomic nervous system may impact the cardiovascular function. Toll-like receptors are components of the innate immune system and play developmental and physiological roles. Toll-like receptor 9 (TLR9) is involved in the pathogenesis of cardiovascular diseases, such as hypertension and heart failure. Since such diseases are commonly accompanied by autonomic imbalance and lower baroreflex sensitivity, we hypothesized that TLR9 modulates cardiac autonomic and baroreflex control of arterial pressure (AP). Toll-like receptor 9 knockout (TLR9 KO) and wild-type (WT) mice were implanted with catheters into carotid artery and jugular vein and allowed to recover for 3 days. After basal recording of AP, mice received methyl-atropine or propranolol. AP and pulse interval (PI) variability were evaluated in the time and frequency domain (spectral analysis), as well as by multiscale entropy. Spontaneous baroreflex was studied by sequence technique. Behavioral and cardiovascular responses to fear-conditioning stress were also evaluated. AP was similar between groups, but TLR9 KO mice exhibited lower basal heart rate (HR). AP variability was not different, but PI variability was increased in TLR9 KO mice. The total entropy was higher in TLR9 KO mice. Moreover, baroreflex function was found higher in TLR9 KO mice. Atropine-induced tachycardia was increased in TLR9 KO mice, whereas the propranolol-induced bradycardia was similar to WT mice. TLR9 KO mice exhibit increased behavioral and decreased tachycardia responses to fear-conditioning stress. In conclusion, our findings suggest that TLR9 may negatively modulate cardiac vagal tone and baroreflex in mice.

Heart rate complexity in sinoaortic-denervated mice.

NEW FINDINGS: What is the central question of this study? New measurements for cardiovascular complexity, such as detrended fluctuation analysis (DFA) and multiscale entropy (MSE), have been shown to predict cardiovascular outcomes. Given that cardiovascular diseases are accompanied by autonomic imbalance and decreased baroreflex sensitivity, the central question is: do baroreceptors contribute to cardiovascular complexity? What is the main finding and its importance? Sinoaortic denervation altered both DFA scaling exponents and MSE, indicating that both short- and long-term mechanisms of complexity are altered in sinoaortic denervated mice, resulting in a loss of physiological complexity. These results suggest that the baroreflex is a key element in the complex structures involved in heart rate variability regulation. Recently, heart rate (HR) oscillations have been recognized as complex behaviours derived from non-linear processes. Physiological complexity theory is based on the idea that healthy systems present high complexity, i.e. non-linear, fractal variability at multiple scales, with long-range correlations. The loss of complexity in heart rate variability (HRV) has been shown to predict adverse cardiovascular outcomes. Based on the idea that most cardiovascular diseases are accompanied by autonomic imbalance and a decrease in baroreflex sensitivity, we hypothesize that the baroreflex plays an important role in complex cardiovascular behaviour. Mice that had been subjected to sinoaortic denervation (SAD) were implanted with catheters in the femoral artery and jugular vein 5 days prior to the experiment. After recording the baseline arterial pressure (AP), pulse interval time series were generated from the intervals between consecutive values of diastolic pressure. The complexity of the HRV was determined using detrended fluctuation analysis and multiscale entropy. The detrended fluctuation analysis α1 scaling exponent (a short-term index) was remarkably decreased in the SAD mice (0.79 ± 0.06 versus 1.13 ± 0.04 for the control mice), whereas SAD slightly increased the α2 scaling exponent (a long-term index; 1.12 ± 0.03 versus 1.04 ± 0.02 for control mice). In the SAD mice, the total multiscale entropy was decreased (13.2 ± 1.3) compared with the control mice (18.9 ± 1.4). In conclusion, fractal and regularity structures of HRV are altered in SAD mice, affecting both short- and long-term mechanisms of complexity, suggesting that the baroreceptors play a considerable role in the complex structure of HRV.

Cardiac autonomic modulation in non-frail, pre-frail and frail elderly women: a pilot study.

Frailty has been defined as a geriatric syndrome that results in high vulnerability to health adverse outcomes. This increased vulnerability state results from dysregulation of multiple physiological systems and its complex interactions. Thus, assessment of physiological systems integrity and of its dynamic interactions seems to be useful in the context of frailty management. Heart rate variability (HRV) analysis provides information about autonomic nervous system (ANS) function, which is responsible to control several physiologic functions. This study investigated the cardiac autonomic modulation by HRV analysis in community-dwelling elderly women classified as non-frail, pre-frail and frail. Twenty-three elderly women were assigned to the following groups: non-frail (n = 8), pre-frail (n = 8) and frail (n = 7). HRV assessment was performed through linear and non-linear analysis of cardiac interval variability. It was observed a higher sympathetic and lower parasympathetic modulation in frail when compared with non-frail and pre-frail groups (p < 0.05) as indicated by frequency domain indices. Additionally, frail group had a decreased 2LV % pattern (that reflects parasympathetic modulation) in the symbolic analysis in comparison with non-frail group. These findings suggest that frail elderly women present an autonomic imbalance characterized by a shift towards sympathetic predominance. Thus, monitoring ANS function in the context of frailty management may be an important strategy to prevention, diagnosis and treatment of this syndrome and its consequences.

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.

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.

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.

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.

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.