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Objective: Intermittent hypoxia (IH)—a hallmark of obstructive sleep apnea (OSA)—enhances lung cancer progression in mice via altered host immune responses that are also age and sex-dependent. However, the interactions of menopause with IH on tumor malignant properties remain unexplored. Here, we aimed to investigate lung cancer outcomes in the context of ovariectomy (OVX)-induced menopause in a murine model of OSA. Methods: Thirty-four female mice (C57BL/6, 12-week-old) were subjected to bilateral OVX or to Sham intervention. Six months after surgery, mice were pre-exposed to either IH or room air (RA) for 2 weeks. Then, 105 lung carcinoma (LLC1) cells were injected subcutaneously in the left flank, with IH or RA exposures continued for 4 weeks. Tumor weight, tumor invasion, and spontaneous lung metastases were assessed. Tumor-associated macrophages (TAMs) were isolated and subjected to flow cytometry polarity evaluation along with assessment of TAMs modulation of LLC1 proliferation in vitro. To determine the effect of IH and OVX on each experimental variable, a two-way analysis of variance was performed. Results: IH and OVX promoted a similar increase in tumor growth (2-fold; P = 0.05 and 1.74-fold; P < 0.05, respectively), and OVX-IH further increased it. Regarding lung metastasis, the concurrence of OVX in mice exposed to IH enhanced the number of metastases (23.7 ± 8.0) in comparison to those without OVX (7.9 ± 2.8; P < 0.05). The pro-tumoral phenotype of TAMS, assessed as M2/M1 ratio, was increased in OVX (0.06 ± 0.01; P < 0.01) and IH (0.06 ± 0.01; P < 0.01) compared with sham/RA conditions (0.14 ± 0.03). The co-culture of TAMS with naive LLC1 cells enhanced their proliferation only under IH. Conclusion: In female mice, both the IH that is characteristically present in OSA and OVX as a menopause model emerge as independent contributors that promote lung cancer aggressiveness and seemingly operate through alterations in the host immune response.

JTD Keywords: Animal models, Cancer progression, Intermittent hypoxia, Menopause, Obstructive sleep apnea, Ovariectomy

The relationship between surface diaphragm mechanomyography (sMMGdi), as a noninvasive measure of inspiratory muscle mechanical activation, and crural diaphragm electromyography (oesEMGdi), as the invasive gold standard measure of diaphragm electrical activation, had not previously been examined. To investigate this relationship, oesEMGdi and sMMGdi were measured simultaneously in 6 healthy subjects during an incremental inspiratory threshold loading protocol, and analyzed using fixed sample entropy (fSampEn). A positive curvilinear relationship was observed between mean fSampEn sMMGdi and oesEMGdi (r = 0.67). Accordingly, an increasing electromechanical ratio was also observed with increasing inspiratory load. These findings suggest that sMMGdi could provide useful noninvasive measures of inspiratory muscle mechanical activation.

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Background A thorough analysis of continuous adventitious sounds (CAS) can provide distinct and complementary information about bronchodilator response (BDR), beyond that provided by spirometry. Nevertheless, previous approaches to CAS analysis were limited by certain methodology issues. The aim of this study is to propose a new integrated approach to CAS analysis that contributes to improving the assessment of BDR in clinical practice for asthma patients. Methods Respiratory sounds and flow were recorded in 25 subjects, including 7 asthma patients with positive BDR (BDR+), assessed by spirometry, 13 asthma patients with negative BDR (BDR-), and 5 controls. A total of 5149 acoustic components were characterized using the Hilbert spectrum, and used to train and validate a support vector machine classifier, which distinguished acoustic components corresponding to CAS from those corresponding to other sounds. Once the method was validated, BDR was assessed in all participants by CAS analysis, and compared to BDR assessed by spirometry. Results BDR+ patients had a homogenous high change in the number of CAS after bronchodilation, which agreed with the positive BDR by spirometry, indicating high reversibility of airway obstruction. Nevertheless, we also found an appreciable change in the number of CAS in many BDR- patients, revealing alterations in airway obstruction that were not detected by spirometry. We propose a categorization for the change in the number of CAS, which allowed us to stratify BDR- patients into three consistent groups. From the 13 BDR- patients, 6 had a high response, similar to BDR+ patients, 4 had a noteworthy medium response, and 1 had a low response.Conclusions In this study, a new non-invasive and integrated approach to CAS analysis is proposed as a high-sensitive tool for assessing BDR in terms of acoustic parameters which, together with spirometry parameters, contribute to improving the stratification of BDR levels in patients with obstructive pulmonary diseases.

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Differentiating normal from adventitious respiratory sounds (RS) is a major challenge in the diagnosis of pulmonary diseases. Particularly, continuous adventitious sounds (CAS) are of clinical interest because they reflect the severity of certain diseases. This study presents a new classifier that automatically distinguishes normal sounds from CAS. It is based on the multi-scale analysis of instantaneous frequency (IF) and envelope (IE) calculated after ensemble empirical mode decomposition (EEMD). These techniques have two major advantages over previous techniques: high temporal resolution is achieved by calculating IF-IE and a priori knowledge of signal characteristics is not required for EEMD. The classifier is based on the fact that the IF dispersion of RS signals markedly decreases when CAS appear in respiratory cycles. Therefore, CAS were detected by using a moving window to calculate the dispersion of IF sequences. The study dataset contained 1494 RS segments extracted from 870 inspiratory cycles recorded from 30 patients with asthma. All cycles and their RS segments were previously classified as containing normal sounds or CAS by a highly experienced physician to obtain a gold standard classification. A support vector machine classifier was trained and tested using an iterative procedure in which the dataset was randomly divided into training (65%) and testing (35%) sets inside a loop. The SVM classifier was also tested on 4592 simulated CAS cycles. High total accuracy was obtained with both recorded (94.6% ± 0.3%) and simulated (92.8% ± 3.6%) signals. We conclude that the proposed method is promising for RS analysis and classification.

JTD Keywords: Diseases, Dispersion, Empirical mode decomposition, Feature extraction, Informatics, Support vector machines

Abstract The use of the Hilbert–Huang transform in the analysis of biomedical signals has increased during the past few years, but its use for respiratory sound (RS) analysis is still limited. The technique includes two steps: empirical mode decomposition (EMD) and instantaneous frequency (IF) estimation. Although the mode mixing (MM) problem of EMD has been widely discussed, this technique continues to be used in many RS analysis algorithms. In this study, we analyzed the MM effect in RS signals recorded from 30 asthmatic patients, and studied the performance of ensemble EMD (EEMD) and noise-assisted multivariate EMD (NA-MEMD) as means for preventing this effect. We propose quantitative parameters for measuring the size, reduction of MM, and residual noise level of each method. These parameters showed that EEMD is a good solution for MM, thus outperforming NA-MEMD. After testing different IF estimators, we propose Kay׳s method to calculate an EEMD-Kay-based Hilbert spectrum that offers high energy concentrations and high time and high frequency resolutions. We also propose an algorithm for the automatic characterization of continuous adventitious sounds (CAS). The tests performed showed that the proposed EEMD-Kay-based Hilbert spectrum makes it possible to determine CAS more precisely than other conventional time-frequency techniques.

JTD Keywords: Hilbert–Huang transform, Ensemble empirical mode decomposition, Instantaneous frequency, Respiratory sounds, Continuous adventitious sounds

Los sonidos adventicios continuos (CAS) son uno de los principales síntomas del asma. Dada su importancia clínica, el análisis de estas señales requiere del uso de técnicas que permitan segmentarlas y caracterizarlas con una precisión alta. Sin embargo, la mayoría de técnicas propuestas anteriormente estaban basadas en el análisis de Fourier o wavelet, técnicas que tienen una resolución limitada a priori y son altamente dependientes de la amplitud de los CAS. En este estudio se presenta una técnica alternativa para el análisis de CAS basada en el espectro de Hilbert. El método presentado combina la descomposición empírica en modos por conjuntos con el estimador de Kay de la frecuencia instantánea, para obtener una representación tiempo-frecuencia con una alta concentración de energía y una resolución temporal y frecuencial elevada. Con el fin de mostrar las ventajas que ofrece el método presentado, se ha aplicado a cuatro señales de sonidos respiratorios registradas en pacientes asmáticos que contienen distintos tipos de CAS, reforzando la hipótesis confirmada en nuestro estudio previo de que el espectro de Hilbert permite segmentar y caracterizar los CAS con mayor precisión que otras técnicas tradicionales ampliamente utilizadas, como el espectrograma.

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Study Objectives: To test the hypotheses that brain oxygen partial pressure (PtO2) in response to obstructive apneas changes with age and that it might lead to different levels of cerebral tissue oxidative stress. Design: Prospective controlled animal study. Setting: University laboratory. Participants: Sixty-four male Wistar rats: 32 young (3 mo old) and 32 aged (18 mo). Interventions: Protocol 1: Twenty-four animals were subjected to obstructive apneas (50 apneas/h, lasting 15 sec each) or to sham procedure for 50 min. Protocol 2: Forty rats were subjected to obstructive apneas or sham procedure for 4 h. Measurements and Results: Protocol 1: Real-time PtO2 measurements were performed using a fast-response oxygen microelectrode. During successive apneas cerebral cortex PtO2 presented a different pattern in the two age groups; there was a fast increase in young rats, whereas it remained without significant changes between the beginning and the end of the protocol in the aged group. Protocol 2: Brain oxidative stress assessed by lipid peroxidation increased after apneas in young rats (1.34 ± 0.17 nmol/mg of protein) compared to old ones (0.63 ± 0.03 nmol/mg), where a higher expression of antioxidant enzymes was observed. Conclusions: The results suggest that brain oxidative stress in aged rats is lower than in young rats in response to recurrent apneas, mimicking obstructive sleep apnea. This could be due to the different PtO2 response observed between age groups and the increased antioxidant expression in aged rats.

JTD Keywords: Aging, Animal model, Obstructive apnea, Oxidative stress, Tissue oxygenation, antioxidant, glutathione disulfide, aged, animal experiment, animal model, animal tissue, apnea, arterial oxygen saturation, article, brain cortex, brain oxygen tension, brain tissue, controlled study, groups by age, hypoxia, lipid peroxidation, male, nonhuman, oxidative stress, pressure, priority journal, rat

The consequences of phrenic nerve paralysis vary from a considerable reduction in respiratory function to an apparently normal state. Acoustic analysis of lung sound intensity (LSI) could be an indirect non-invasive measurement of respiratory muscle function, comparing activity on the two sides of the thoracic cage. Lung sounds and airflow were recorded in ten males with unilateral phrenic paralysis and ten healthy subjects (5 men/5 women), during progressive increasing airflow maneuvers. Subjects were in sitting position and two acoustic sensors were placed on their back, on the left and right sides. LSI was determined from 1.2 to 2.4 L/s between 70 and 2000 Hz. LSI was significantly greater on the normal (19.3±4.0 dB) than the affected (5.7±3.5 dB) side in all patients (p = 0.0002), differences ranging from 9.9 to 21.3 dB (13.5±3.5 dB). In the healthy subjects, the LSI was similar on both left (15.1±6.3 dB) and right (17.4±5.7 dB) sides (p = 0.2730), differences ranging from 0.4 to 4.6 dB (2.3±1.6 dB). There was a positive linear relationship between the LSI and the airflow, with clear differences between the slope of patients (about 5 dB/L/s) and healthy subjects (about 10 dB/L/s). Furthermore, the LSI from the affected side of patients was close to the background noise level, at low airflows. As the airflow increases, the LSI from the affected side did also increase, but never reached the levels seen in healthy subjects. Moreover, the difference in LSI between healthy and paralyzed sides was higher in patients with lower FEV1 (%). The acoustic analysis of LSI is a relevant non-invasive technique to assess respiratory function. This method could reinforce the reliability of the diagnosis of unilateral phrenic paralysis, as well as the monitoring of these patients.

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(ISR) es una medida indirecta y no invasiva de la función respiratoria, que permite comparar la actividad en los dos hemitórax de los pacientes con parálisis frénica unilateral. Se registraron los sonidos y el flujo respiratorio en 10 hombres con parálisis frénica unilateral y 10 sujetos sanos (5 hombres/5 mujeres) en posición sentada. Se colocaron 2 micrófonos de contacto en la espalda, uno a cada lado de la columna. La ISR se calculó en el rango frecuencial 70-2000 Hz a partir de la densidad espectral de potencia y para flujos entre 1,2 y 2,4 l/s. Se encontró que las diferencias en la ISR media de los dos hemitórax era significativamente mayor en los pacientes (13.5 dB) que en los sujetos sanos (2.3 dB). Además, se comprobó que esa diferencia era mayor en pacientes con un volumen espiratorio forzado en el primer segundo menor. Por lo tanto, el análisis acústico de la ISR es una técnica no invasiva muy útil para valorar la función respiratoria. Esta técnica puede mejorar la fiabilidad en el diagnóstico de la parálisis frénica unilateral así como la monitorización a largo plazo de estos pacientes.

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Assessment of asthma is a difficult procedure which is based on the correlation of multiple factors. A major component in the diagnosis of asthma is the assessment of BD response, which is performed by traditional spirometry. In this context, the analysis of respiratory sounds (RS) provides relevant and complementary information about the function of the respiratory system. In particular, continuous adventitious sounds (CAS), such as wheezes, contribute to assess the severity of patients with obstructive diseases. On the other hand, the intensity of normal RS is dependent on airflow level and, therefore, it changes depending on the level of obstruction. This study proposes a new approach to RS analysis for the assessment of asthmatic patients, by combining the quantification of CAS and the analysis of the changes in the normal sound intensity-airflow relationship. According to results obtained from three patients with different characteristics, the proposed technique seems more sensitive and promising for the assessment of asthma.

JTD Keywords: Asthma, Bronchodilator response, Continuous adventitious sound, Respiratory sound intensity, Wheezes

Instantaneous frequency (IF) calculated by empirical mode decomposition (EMD) provides a novel approach to analyze respiratory sounds (RS). Traditionally, RS have been analyzed using classical time-frequency distributions, such as short-time Fourier transform (STFT) or wavelet transform (WT). However, EMD has become a powerful tool for nonlinear and non-stationary data analysis. IF estimated by EMD has two major advantages: its high temporal resolution and the fact that a priori knowledge of the signal characteristics is not required. In this study, we have estimated IF by EMD on real RS signals in order to identify continuous adventitious sounds (CAS), such as wheezes, within inspiratory sounds cycles. We show that there are differences in IF distribution among frequency scales of RS signal when CAS are within RS. Therefore, a new method for RS analysis and classification may be developed by combining both EMD and IF.

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En este trabajo se ha visto que la evaluación de la potencia media de las señales de sonidos respiratorios antes y después de aplicar un fármaco broncodilatador puede reportar información importante sobre el estado y los cambios producidos en el sistema respiratorio. Se ha realizado y puesto a punto un protocolo de registro multicanal de acústica pulmonar mediante la colocación de 5 micrófonos de contacto: uno traqueal y cuatro micrófonos colocados en el tórax posterior. Mediante el análisis de las curvas intensidad-flujo respiratorio se han observado cambios significativos de intensidad a niveles de flujo elevados y en pacientes con una PBD negativa. Es en este grupo de pacientes, no respondedores, donde la técnica propuesta puede aportar información de interés clínico complementaria a la proporcionada por la espirometría clásica.

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Objectives/Hypothesis: We used a new automatic snoring detection and analysis system to monitor snoring during full-night polysomnography to assess whether the acoustic characteristics of snores differ in relation to the apnea-hypopnea index (AHI) and to classify subjects according to their AHI Study Design: Individual Case-Control Study. Methods: Thirty-seven snorers (12 females and 25 males, ages 40-65 years; body mass index (BMI), 29.65 +/- 4.7 kg/m(2)) participated Subjects were divided into three groups: G1 (AHI <5), G2 (AHI >= 5, <15) and G3 (AHI >= 15) Snore and breathing sounds were : recorded with a tracheal microphone throughout 6 hours of nighttime polysomnography The snoring episodes identified were automatically and continuously analyzed with a previously trained 2-layer feed-forward neural network. Snore number, average intensity, and power spectral density parameters were computed for every subject and compared among AHI groups. Subjects were classified using different AHI thresholds by means of a logistic regression model. Results: There were significant differences in supine position between G1 and G3 in sound intensity, number of snores; standard deviation of the spectrum, power ratio in bands 0-500, 100-500, and 0-800 Hz, and the symmetry coefficient (P < .03); Patients were classified with thresholds AHI = 5 and AHI = 15 with a sensitivity (specificity) of 87% (71%) and 80% (90%), respectively. Conclusions: A new system for automatic monitoring and analysis of snores during the night is presented. Sound intensity and several snore frequency parameters allow differentiation of snorers according to obstructive sleep apnea syndrome severity (OSAS). Automatic snore intensity and frequency monitoring and analysis could be a promising tool for screening OSAS patients, significantly improving the managing of this pathology.

JTD Keywords: Breathing sounds, Signal interpretation, Sleep apnea syndromes, Snoring