The pre-Bötzinger complex is necessary for the expression of inspiratory and post-inspiratory motor discharge of the vagus

The mammalian three-phase respiratory motor pattern of inspiration, post-inspiration and expiration is expressed in spinal and cranial motor nerve discharge and is generated by a distributed ponto-medullary respiratory pattern generating network. Respiratory motor pattern generation depends on a rhythmogenic kernel located within the pre-Bötzinger complex (pre-BötC). In the present study, we tested the effect of unilateral and bilateral inactivation of the pre-BötC after local microinjection of the GABAA receptor agonist isoguvacine (10 mM, 50 nl) on phrenic (PNA), hypoglossal (HNA) and vagal nerve (VNA) respiratory motor activities in an in situ perfused brainstem preparation of rats. Bilateral inactivation of the pre-BötC triggered cessation of phrenic (PNA), hypoglossal (HNA) and vagal (VNA) nerve activities for 15-20 min. Ipsilateral isoguvacine injections into the pre-BötC triggered transient (6-8 min) cessation of inspiratory and post-inspiratory VNA (p < 0.001) and suppressed inspiratory HNA by - 70 ± 15% (p < 0.01), while inspiratory PNA burst frequency increased by 46 ± 30% (p < 0.01). Taken together, these observations confirm the role of the pre-BötC as the rhythmogenic kernel of the mammalian respiratory network in situ and highlight a significant role for the pre-BötC in the transmission of vagal inspiratory and post-inspiratory pre-motor drive to the nucleus ambiguus.

Temperature dependence of gas exchange patterns shift as diapause progresses in the butterfly Pieris napi

Insects have the capacity to significantly modify their metabolic rate according to environmental conditions and physiological requirement. Consequently, the respiratory patterns can range from continuous gas exchange (CGE) to discontinuous gas exchange (DGE). In the latter, spiracles are kept closed during much of the time, and gas exchange occurs only during short periods when spiracles are opened. While ultimate causes and benefits of DGE remain debated, it is often seen during insect diapause, a deep resting stage that insects induce to survive unfavourable environmental conditions, such as winter. The present study explores the shifts between CGE and DGE during diapause by performing long continuous respirometry measurements at multiple temperatures during key diapause stages in the green-veined white butterfly Pieris napi. The primary goal is to explore respiratory pattern as a non-invasive method to assess whether pupae are in diapause or have transitioned to post-diapause. Respiratory pattern can also provide insight into endogenous processes taking place during diapause, and the prolonged duration of diapause allows for the detailed study of the thermal dependence of the DGE pattern. Pupae change from CGE to DGE a few days after pupation, and this shift coincides with metabolic rate suppression during diapause initiation. Once in diapause, pupae maintain DGE even at elevated temperatures that significantly increase CO2 production. Instead of shifting respiratory pattern to CGE, pupae increase the frequency of DGE cycles. Since total CO2 released during a single open phase remains unchanged, our results suggest that P. napi pupae defend a maximum internal ρCO2 set point, even in their heavily suppressed diapause state. During post-diapause development, CO2 production increases as a function of development and changes to CGE during temperature conditions permissive for development. Taken together, the results show that respiratory patterns are highly regulated during diapause in P. napi and change predictably as diapause progresses.

Risk Factors and Age-Related Patterns of Asthma-Like Symptoms in Early Childhood

BACKGROUND

Episodes of asthma-like symptoms in young children are common, but little is known about risk factors and their patterns for the daily symptom burden.

OBJECTIVE

We investigated a variety of possible risk factors and their age-related impact on the number of asthma-like episodes during age 0 to 3 years.

METHODS

The study population included 700 children from the Copenhagen Prospective Studies on Asthma in Childhood2010 mother-child cohort followed prospectively from birth. Asthma-like symptoms were recorded until age 3 by daily diaries. Risk factors were analyzed by quasi-Poisson regressions, and interaction with age was explored.

RESULTS

Diary data were available in 662 children. Male sex, maternal asthma, low birth weight, maternal antibiotic use, high asthma exacerbation polygenic risk score, and high airway immune score were associated with a higher number of episodes in a multivariable analysis. Maternal asthma, preterm birth, caesarean section, and low birth weight showed an increasing impact with age, whereas sibling(s) at birth showed a decreased association with age. The remaining risk factors had a stable pattern during age 0 to 3 years. For every additional clinical risk factor (male sex, low birth weight, and maternal asthma) a child had, we found 34% more episodes (incidence rate ratio: 1.34, 95% confidence interval: 1.21-1.48; P < .001).

CONCLUSION

Using unique day-to-day diary recordings, we identified risk factors for the burden of asthma-like symptoms in the first 3 years of life and described their unique age-related patterns. This provides novel insight into the origin of asthma-like symptoms in early childhood that potentially pave a path for personalized prognostics and treatment.

Intercostal muscle oxygenation and expiratory loaded breathing at rest: Respiratory pattern effect

In patients with airway obstruction, an increase in breathing frequency at rest is commonly associated with a dynamic hyperinflation (DH). In such a situation, intercostal muscle oxygenation may be disturbed. This hypothesis was examined in a context of simulated airway obstruction in healthy subjects. After a control period of 5 min, twelve participants (20 ± 2 years) breathed at rest through a 20-cmH₂O expiratory threshold load, either by increasing or reducing their respiratory rate (_ETLF⁺ or _ETLF). Tissue saturation index (TSI) and concentration changes in oxyhaemoglobin (oxy[Hb+Mb]) were measured as well as cardiorespiratory variables. Inspiratory capacity was decreased in _ETLF⁺ (p < 0.001) and correlated with dyspnea. An increase in oxy[Hb+Mb] occurred in _ETLF⁺ that was higher than in _ETLF (p < 0.01). TSI was not different between conditions. In healthy subjects at rest, an increase in respiratory rate during a simulated obstruction with an expiratory threshold load resulted in paradoxical response with DH emergence while intercostal muscle oxygenation was preserved.

Respiratory pattern complexity in newly-diagnosed asthmatic patients

BACKGROUND

The intensity of respiratory symptoms and expiratory airflow limitations in asthma fluctuate over time. Some studies have reported variable complexity of the respiratory patterns in asthmatic patients. Thus, we conducted a novel study to assess the correlation between asthma severity and breathing pattern dynamics in newly-diagnosed asthmatic patients.

METHODS

A total of 20 newly-diagnosed asthmatic patients (7 male, 13 female) and 20 healthy cases (11 male, 9 female) were included. The respiratory patterns of all participants and the asthma severity for asthmatic patients were measured using a spirometer (before and after a bronchodilator exposure) and airflow recorder, respectively. The peak-to-peak intervals and the amplitude of peaks were considered as the inter-breath interval (IBI) and lung volume (LV) series. The Detrended Fluctuation Analysis (DFA), Sample Entropy (SampEn), Multi-scale Entropy (MSE), short-term (SD1) and long-term (SD2) variability, and IBI and LV Cross-Sample Entropy of the respiratory pattern dynamics were calculated using MATLAB (Mathwork, USA).

RESULTS

Asthma patients showed notable increase in the average of sample entropy in both IBI and LV parameters (p = 0.025 and p = 0.018, respectively) and also decreased synchronization between IBI and LV (p = 0.042). The multi-scale sample entropy of both IBI and LV was significantly higher in asthmatic patients (p < 0.05). Furthermore, SD1 and SD2 were higher in the patients with asthma (p < 0.05). Significant correlations were detected between spirometric (forced expiratory flow (FEF) change, pre FEF, pre forced expiratory volume in one second (FEV1) / forced vital capacity (FVC), FVC change) and respiratory pattern (mean-IBI, mean-LV, mean-respiratory rate (RR), coefficient of variation (CV)-IBI, CV-LV, cross-sample entropy) parameters (p < 0.05). Furthermore, we identified a negative correlation between CV of IBI and asthma severity (r = -0.52, p = 0.021).

CONCLUSION

Here, we took a novel approach and observed increased irregularity (more complexity) in the breathing pattern of patients newly-diagnosed with asthma. Remarkable correlations were detected between breathing complexity markers and spirometric indices along with disease severity in asthmatic patients. Thus, our data suggests respiratory pattern indices could be utilized as an indicator of asthma and its severity. However, more clinical data are required to support this conclusion.

Machine-learning based feature selection for a non-invasive breathing change detection

Background

Chronic Obstructive Pulmonary Disease (COPD) is one of the top 10 causes of death worldwide, representing a major public health problem. Researchers have been looking for new technologies and methods for patient monitoring with the intention of an early identification of acute exacerbation events. Many of these works have been focusing in breathing rate variation, while achieving unsatisfactory sensitivity and/or specificity. This study aims to identify breathing features that better describe respiratory pattern changes in a short-term adjustment of the load-capacity-drive balance, using exercising data.

Results

Under any tested circumstances, breathing rate alone leads to poor capability of classifying rest and effort periods. The best performances were achieved when using Fourier coefficients or when combining breathing rate with the signal amplitude and/or ARIMA coefficients.

Conclusions

Breathing rate alone is a quite poor feature in terms of prediction of breathing change and the addition of any of the other proposed features improves the classification power. Thus, the combination of features may be considered for enhancing exacerbation prediction methods based in the breathing signal.Trial Registration : ClinicalTrials NCT03753386. Registered 27 November 2018, https://clinicaltrials.gov/show/NCT03753386

The pontine Kölliker-Fuse nucleus gates facial, hypoglossal, and vagal upper airway related motor activity

The pontine Kölliker-Fuse nucleus (KFn) is a core nucleus of respiratory network that mediates the inspiratory-expiratory phase transition and gates eupneic motor discharges in the vagal and hypoglossal nerves. In the present study, we investigated whether the same KFn circuit may also gate motor activities that control the resistance of the nasal airway, which is of particular importance in rodents. To do so, we simultaneously recorded phrenic, facial, vagal and hypoglossal cranial nerve activity in an in situ perfused brainstem preparation before and after bilateral injection of the GABA-receptor agonist isoguvacine (50-70 nl, 10 mM) into the KFn (n = 11). Our results show that bilateral inhibition of the KFn triggers apneusis (prolonged inspiration) and abolished pre-inspiratory discharge of facial, vagal and hypoglossal nerves as well as post-inspiratory discharge in the vagus. We conclude that the KFn plays a critical role for the eupneic regulation of naso-pharyngeal airway patency and the potential functions of the KFn in regulating airway patency and orofacial behavior is discussed.

Information conveyed by electrical diaphragmatic activity during unstressed, stressed and assisted spontaneous breathing: a physiological study

Background

The electrical activity of the crural diaphragm (Eadi), a surrogate of respiratory drive, can now be measured at the bedside in mechanically ventilated patients with a specific catheter. The expected range of Eadi values under stressed or assisted spontaneous breathing is unknown. This study explored Eadi values in healthy subjects during unstressed (baseline), stressed (with a resistance) and assisted spontaneous breathing. The relation between Eadi and inspiratory effort was analyzed.

Methods

Thirteen healthy male volunteers were included in this randomized crossover study. Eadi and esophageal pressure (Peso) were recorded during unstressed and stressed spontaneous breathing and under assisted ventilation delivered in pressure support (PS) at low and high assist levels and in neurally adjusted ventilatory assist (NAVA). Overall eight different situations were assessed in each participant (randomized order). Peak, mean and integral of Eadi, breathing pattern, esophageal pressure–time product (PTPeso) and work of breathing (WOB) were calculated offline.

Results

Median [interquartile range] peak Eadi at baseline was 17 [13–22] μV and was above 10 μV in 92% of the cases. Eadi_max defined as Eadi measured at maximal inspiratory capacity reached 90 [63 to 99] μV. Median peak Eadi/Eadi_max ratio was 16.8 [15.6–27.9]%. Compared to baseline, respiratory rate and minute ventilation were decreased during stressed non-assisted breathing, whereas peak Eadi and PTPeso were increased. During unstressed assisted breathing, peak Eadi decreased during high-level PS compared to unstressed non-assisted breathing and to NAVA (p = 0.047). During stressed breathing, peak Eadi was lower during all assisted ventilation modalities compared to stressed non-assisted breathing. During assisted ventilation, across the different conditions, peak Eadi changed significantly, whereas PTPeso and WOB/min were not significantly modified. Finally, Eadi signal was still present even when Peso signal was suppressed due to high assist levels.

Conclusion

Eadi analysis provides complementary information compared to respiratory pattern and to Peso monitoring, particularly in the presence of high assist levels.

Trial registration The study was registered as NCT01818219 in clinicaltrial.gov. Registered 28 February 2013

Electronic supplementary material

The online version of this article (10.1186/s13613-019-0564-1) contains supplementary material, which is available to authorized users.

Effect of respiratory pattern on automated clinical blood pressure measurement: an observational study with normotensive subjects

BACKGROUND

It has been reported that deep breathing could reduce blood pressures (BP) in general. It is also known that BP is decreased during inhalation and increased during exhalation. Therefore, the measured BPs could be potentially different during deep breathing with different lengths of inhalation and exhalation. This study aimed to quantitatively investigate the effect of different respiratory patterns on BPs.

METHODS

Forty healthy subjects (20 males and 20 females, aged from 18 to 60 years) were recruited. Systolic and diastolic BPs (SBP and DBP) were measured using a clinically validated automated BP device. There were two repeated measurement sessions for each subject. Within each session, eight BP measurements were performed, including 4 measurements during deep breathing with different respiratory patterns (Pattern 1: 4.5 s vs 4.5 s; Patter 2: 6 s vs 2 s; Pattern 3: 2 s vs 6 s; and Pattern 4: 1.5 s vs 1.5 s, respectively for the durations of inhalation and exhalation) and additional 4 measurements from 1 min after the four different respiratory patterns. At the beginning and end of the two repeated measurement sessions, there were two baseline BP measurements under resting condition.

RESULTS

The key experimental results showed that overall automated SBP significantly decreased by 3.7 ± 5.7 mmHg, 3.9 ± 5.2 mmHg, 1.7 ± 5.9 mmHg and 3.3 ± 5.3 mmHg during deep breathing, respectively for Patterns 1, 2, 3 and 4 (all p < 0.001 except p < 0.05 for Pattern 3). Similarly, the automated DBPs during deep breathing in pattern 1, 2 and 4 decreased by 3.7 ± 5.0 mmHg, 3.7 ± 4.9 mmHg and 4.6 ± 3.9 mmHg respectively (all p < 0.001, except in Pattern 3 with a decrease of 1.0 ± 4.3 mmHg, p = 0.14). Correspondingly, after deep breathing, automated BPs recovered back to normal with no significant difference in comparison with baseline BP (all p > 0.05, except for SBP in Pattern 4).

CONCLUSIONS

In summary, this study has quantitatively demonstrated that the measured automated BPs decreased by different amounts with all the four deep breathing patterns, which recovered back quickly after these single short-term interventions, providing evidence of short-term BP decrease with deep breathing and that BP measurements should be performed under normal breathing condition.

Effect of physical training on ventilatory patterns during exercise in patients with heart disease

BACKGROUND

Exercise training is known to improve the shortness of breath experienced by patients with heart disease when the ventilatory pattern becomes abnormal during exercise. However, the precise relationship between breathing patterns and the effect of exercise training has not been elucidated to date. We evaluated the relationship between the effect of exercise training on exercise tolerance and the amelioration of the ventilatory response during exercise in such patients.

METHODS AND RESULTS

Patients with heart disease (n=170) underwent cardiopulmonary exercise testing twice (pre- and postexercise training for 3-6 months). They were divided into the exercise training group (Group E, n=123) and control group (Group C, n=47). Regression line relating tidal volume to respiratory rate (TV-RR slope) during a ramp protocol below the inflection point was regarded as an indicator of rapid ventilation. Tidal volume after the inflection point was regarded as an indicator of shallow ventilation (TV at plateau). The TV-RR slope and TV at plateau improved after exercise training from 94.8±45.9 to 129.9±69.5 (p<0.001) and from 1473.6±321.9mL to 1673.2±355.1mL (p<0.001), respectively, in Group E. In contrast, no improvement was evident in Group C. In total, %anaerobic threshold (%AT) [AT improving ratio=(post-AT-pre-AT)/pre-AT×100] was positively correlated with both %TV-RR slope [TV-RR slope improving ratio=(post-TV-RR slope-pre-TV-RR slope)/pre-TV-RR slope×100] (r=0.60) and %TV at plateau [TV at plateau improving ratio=(post-TV at plateau-pre-TV at plateau)/pre-TV at plateau×100] (r=0.51).

CONCLUSION

Exercise training improved the rapidness and depth of breathing during exercise. Therefore, improvement of abnormal ventilatory patterns is correlated with exercise tolerance.