Automated Classification of Whole Body Plethysmography Waveforms to Quantify Breathing Patterns

An update on spinal cord injury and diaphragm neuromotor control

INTRODUCTION

Understanding neuromotor control of the diaphragm muscle (DIAm) is the foundation for developing therapeutic approaches for functional recovery of ventilatory and non-ventilatory behaviors. Although the DIAm is the primary inspiratory pump, it plays a vital role in a wide variety of higher-force behaviors including airway clearance activities. After spinal cord injury (SCI), higher-force behaviors experience the greatest deficits. A classification scheme for SCI that incorporates this information would be clinically valuable.

AREAS COVERED

We begin by presenting foundational information about DIAm motor units. In addition, we introduce a classification scheme of SCI based on the impact it has on neural circuitry involved in breathing and other functions of the DIAm. Finally, we consider various promising therapeutic options available to improve DIAm motor function. Relevant literature was identified by searching PubMed and Google Scholar without specific limits on the dates.

EXPERT OPINION

Classification of SCI based on its impact on the neural circuitry involved in DIAm motor behaviors is an important part of developing effective therapeutics. An approach that considers the specific type of SCI and leverages a combination of interventions will likely yield the best outcomes for restoring both ventilatory and non-ventilatory functions.

Pharmacological modulation of respiratory control: Ampakines as a therapeutic strategy

Ampakines are a class of compounds that are positive allosteric modulators of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors and enhance glutamatergic neurotransmission. Glutamatergic synaptic transmission and AMPA receptor activation are fundamentally important to the genesis and propagation of the neural impulses driving breathing, including respiratory motoneuron depolarization. Ampakines therefore have the potential to modulate the neural control of breathing. In this paper, we describe the influence of ampakines on respiratory motor output in health and disease. We dissect the molecular mechanisms underlying ampakine action, delineate the diverse targets of ampakines along the respiratory neuraxis, survey the spectrum of respiratory disorders in which ampakines have been tested, and culminate with an examination of how ampakines modulate respiratory function after spinal cord injury. Collectively, the studies reviewed here indicate that ampakines may be a useful adjunctive strategy to pair with conventional respiratory rehabilitation approaches in conditions with impaired neural activation of the respiratory muscles.

Identification of eupneic breathing using machine learning

The diaphragm muscle (DIAm) is the primary inspiratory muscle in mammals. In awake animals, considerable heterogeneity in the electromyographic (EMG) activity of the DIAm reflects varied ventilatory and nonventilatory behaviors. Experiments in awake animals are an essential component to understanding the neuromotor control of breathing, which has especially begun to be appreciated within the last decade. However, insofar as the intent is to study the control of breathing, it is paramount to identify DIAm EMG activity that in fact reflects breathing. Current strategies for doing so in a reproducible, reliable, and efficient fashion are lacking. In the present article, we evaluated DIAm EMG from awake animals using hierarchical clustering across four-dimensional feature space to classify eupneic breathing. Our model, which can be implemented with automated threshold of the clustering dendrogram, successfully identified eupneic breathing with high F1 score (0.92), specificity (0.70), and accuracy (0.88), suggesting that it is a robust and reliable tool for investigating the neural control of breathing.NEW & NOTEWORTHY The heterogeneity of diaphragm muscle (DIAm) activity in awake animals reflects real motor behavior diversity but makes assessments of eupneic breathing challenging. The present article uses an unsupervised machine learning model to identify eupneic breathing amidst a deluge of different DIAm electromyography (EMG) burst patterns in awake rats. This technique offers a scalable and reliable tool that improves efficiency of DIAm EMG analysis and minimizes potential sources of bias.

Modeling Effects of Variable preBötzinger Complex Network Topology and Cellular Properties on Opioid-Induced Respiratory Depression and Recovery

The preBötzinger complex (preBötC), located in the medulla, is the essential rhythm-generating neural network for breathing. The actions of opioids on this network impair its ability to generate robust, rhythmic output, contributing to life-threatening opioid-induced respiratory depression (OIRD). The occurrence of OIRD varies across individuals and internal and external states, increasing the risk of opioid use, yet the mechanisms of this variability are largely unknown. In this study, we utilize a computational model of the preBötC to perform several in silico experiments exploring how differences in network topology and the intrinsic properties of preBötC neurons influence the sensitivity of the network rhythm to opioids. We find that rhythms produced by preBötC networks in silico exhibit variable responses to simulated opioids, similar to the preBötC network in vitro. This variability is primarily due to random differences in network topology and can be manipulated by imposed changes in network connectivity and intrinsic neuronal properties. Our results identify features of the preBötC network that may regulate its susceptibility to opioids.

Pattern sensitivity of ampakine-hypoxia interactions for evoking phrenic motor facilitation in anesthetized rat

Repeated hypoxic episodes can produce a sustained (>60 min) increase in neural drive to the diaphragm. The requirement of repeated hypoxic episodes (vs. a single episode) to produce phrenic motor facilitation (pMF) can be removed by allosteric modulation of α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid receptors using ampakines. We hypothesized that the ampakine-hypoxia interaction resulting in pMF requires that ampakine dosing precedes the onset of hypoxia. Phrenic nerve recordings were made from urethane-anesthetized, mechanically ventilated, and vagotomized adult male Sprague-Dawley rats during isocapnic conditions. Ampakine CX717 (15 mg/kg iv) was given immediately before (n = 8), during (n = 8), or immediately after (n = 8) a 5-min hypoxic episode (arterial oxygen partial pressure 40-45 mmHg). Ampakine before hypoxia (Aprior) resulted in a sustained increase in inspiratory phrenic burst amplitude (i.e., pMF) reaching +70 ± 21% above baseline (BL) after 60 min. This was considerably greater than corresponding values in the groups receiving ampakine during hypoxia (+28 ± 47% above BL, P = 0.005 vs. Aprior) or after hypoxia (+23 ± 40% above BL, P = 0.005 vs. Aprior). Phrenic inspiratory burst rate, heart rate, and systolic, diastolic, and mean arterial pressure (mmHg) were similar across the three treatment groups (all P > 0.3, treatment effect). We conclude that the presentation order of ampakine and hypoxia impacts the magnitude of pMF, with ampakine pretreatment evoking the strongest response. Ampakine pretreatment may have value in the context of hypoxia-based neurorehabilitation strategies.NEW & NOTEWORTHY Phrenic motor facilitation (pMF) is evoked after repeated episodes of brief hypoxia. pMF can also be induced when an allosteric modulator of AMPA receptors (ampakine) is intravenously delivered immediately before a single brief hypoxic episode. Here we show that ampakine delivery before hypoxia (vs. during or after hypoxia) evokes the largest pMF with minimal impact on arterial blood pressure and heart rate. Ampakine pretreatment may have value in the context of hypoxia-based neurorehabilitation strategies.

Oxygen therapy attenuates neuroinflammation after spinal cord injury

Acute hyperbaric O2 (HBO) therapy after spinal cord injury (SCI) can reduce inflammation and increase neuronal survival. To our knowledge, it is unknown if these benefits of HBO require hyperbaric vs. normobaric hyperoxia. We used a C4 lateralized contusion SCI in adult male and female rats to test the hypothesis that the combination of hyperbaria and 100% O2 (i.e. HBO) more effectively mitigates spinal inflammation and neuronal loss, and enhances respiratory recovery, as compared to normobaric 100% O2. Experimental groups included spinal intact, SCI no O2 therapy, and SCI + 100% O2 delivered at normobaric pressure (1 atmosphere, ATA), or at 2- or 3 ATA. O2 treatments lasted 1-h, commenced within 2-h of SCI, and were repeated for 10 days. The spinal inflammatory response was assessed with transcriptomics (RNAseq) and immunohistochemistry. Gene co-expression network analysis showed that the strong inflammatory response to SCI was dramatically diminished by both hyper- and normobaric O2 therapy. Similarly, both HBO and normobaric O2 treatments reduced the prevalence of immunohistological markers for astrocytes (glial fibrillary acidic protein) and microglia (ionized calcium binding adaptor molecule) in the injured spinal cord. However, HBO treatment also had unique impacts not detected in the normobaric group including upregulation of an anti-inflammatory cytokine (interleukin-4) in the plasma, and larger inspiratory tidal volumes at 10-days (whole body-plethysmography measurements). We conclude that normobaric O2 treatment can reduce the spinal inflammatory response after SCI, but pressured O2 (i.e., HBO) provides further benefit.

Neuromotor control of spontaneous quiet breathing in awake rats evaluated by assessments of diaphragm EMG stationarity

The neuromotor control of the diaphragm muscle (DIAm) is dynamic. The activity of the DIAm can be recorded via electromyography (EMG), which represents the temporal summation of motor unit action potentials. Our goal in the present study was to investigate DIAm neuromotor control during quiet spontaneous breathing (eupnea) in awake rats by evaluating DIAm EMG at specific temporal locations defined by motor unit recruitment and derecruitment. We evaluated the nonstationarity of DIAm EMG activity to identify DIAm motor unit recruitment and derecruitment durations. Combined with assessments of root mean square (RMS) and sum of squares (SS) EMG, the durations of these phases provide physiological information about the temporal aspects of motor control. During eupnea in awake rats (n = 10), the duration of motor unit recruitment comprised 61 ± 19 ms of the onset-to-peak duration (214 ± 62 ms) of the DIAm RMS EMG. The peak-to-offset duration of DIAm EMG activity was 453 ± 96 ms, with a terminating period of derecruitment of 161 ± 44 ms. The burst duration was 673 ± 128 ms. Both the RMS EMG amplitude and the SS EMG were higher at the completion of motor unit recruitment than at the start of motor unit derecruitment, suggesting that offset discharge rates were lower than onset discharge rates. Our analyses provide novel insights into the time domain aspects of DIAm neuromotor control and allow indirect estimates of the contribution of recruitment and frequency to RMS EMG amplitude during eupnea in awake rats.NEW & NOTEWORTHY We characterized three phases of neuromotor control-motor unit recruitment, sustained activity, and derecruitment-based on statistical assessments of stationarity of the diaphragm muscle (DIAm) EMG activity in awake rats. Our findings may allow indirect estimates of the contribution of motor unit recruitment and frequency coding toward generating force and provide novel insights about the temporal aspects of DIAm neuromotor control and descending respiratory drive in unanesthetized animals.

An automated respiratory data pipeline for waveform characteristic analysis

Comprehensive and accurate analysis of respiratory and metabolic data is crucial to modelling congenital, pathogenic and degenerative diseases converging on autonomic control failure. A lack of tools for high-throughput analysis of respiratory datasets remains a major challenge. We present Breathe Easy, a novel open-source pipeline for processing raw recordings and associated metadata into operative outcomes, publication-worthy graphs and robust statistical analyses including QQ and residual plots for assumption queries and data transformations. This pipeline uses a facile graphical user interface for uploading data files, setting waveform feature thresholds and defining experimental variables. Breathe Easy was validated against manual selection by experts, which represents the current standard in the field. We demonstrate Breathe Easy's utility by examining a 2-year longitudinal study of an Alzheimer's disease mouse model to assess contributions of forebrain pathology in disordered breathing. Whole body plethysmography has become an important experimental outcome measure for a variety of diseases with primary and secondary respiratory indications. Respiratory dysfunction, while not an initial symptom in many of these disorders, often drives disability or death in patient outcomes. Breathe Easy provides an open-source respiratory analysis tool for all respiratory datasets and represents a necessary improvement upon current analytical methods in the field. KEY POINTS: Respiratory dysfunction is a common endpoint for disability and mortality in many disorders throughout life. Whole body plethysmography in rodents represents a high face-value method for measuring respiratory outcomes in rodent models of these diseases and disorders. Analysis of key respiratory variables remains hindered by manual annotation and analysis that leads to low throughput results that often exclude a majority of the recorded data. Here we present a software suite, Breathe Easy, that automates the process of data selection from raw recordings derived from plethysmography experiments and the analysis of these data into operative outcomes and publication-worthy graphs with statistics. We validate Breathe Easy with a terabyte-scale Alzheimer's dataset that examines the effects of forebrain pathology on respiratory function over 2 years of degeneration.

Alpha-1 antitrypsin protects against phosgene-induced acute lung injury by activating the ID1-dependent anti-inflammatory response

Phosgene is widely used as an industrial chemical, and phosgene inhalation causes acute lung injury (ALI), which may further progress into pulmonary edema. Currently, an antidote for phosgene poisoning is not known. Alpha-1 antitrypsin (α1-AT) is a protease inhibitor used to treat patients with emphysema who are deficient in α1-AT. Recent studies have revealed that α1-AT has both anti-inflammatory and anti-SARS-CoV-2 effects. Herein, we aimed to investigate the role of α1-AT in phosgene-induced ALI. We observed a time-dependent increase in α1-AT expression and secretion in the lungs of rats exposed to phosgene. Notably, α1-AT was derived from neutrophils but not from macrophages or alveolar type II cells. Moreover, α1-AT knockdown aggravated phosgene- and lipopolysaccharide (LPS)-induced inflammation and cell death in human bronchial epithelial cells (BEAS-2B). Conversely, α1-AT administration suppressed the inflammatory response and prevented death in LPS- and phosgene-exposed BEAS-2B cells. Furthermore, α1-AT treatment increased the inhibitor of DNA binding 1 (ID1) gene expression, which suppressed NF-κB pathway activation, reduced inflammation, and inhibited cell death. These data demonstrate that neutrophil-derived α1-AT acts as a self-protective mechanism, which protects against phosgene-induced ALI by activating the ID1-dependent anti-inflammatory response. This study may provide novel strategies for the treatment of patients with phosgene-induced ALI.

Unsupervised classification of plethysmography signals with advanced visual representations

Ventilation is a simple physiological function that ensures the vital supply of oxygen and the elimination of CO₂. The recording of the airflow through the nostrils of a mouse over time makes it possible to calculate the position of critical points, based on the shape of the signals, to compute the respiratory frequency and the volume of air exchanged. These descriptors only account for a part of the dynamics of respiratory exchanges. In this work we present a new algorithm that directly compares the shapes of signals and considers meaningful information about the breathing dynamics omitted by the previous descriptors. The algorithm leads to a new classification of inspiration and expiration, which reveals that mice respond and adapt differently to inhibition of cholinesterases, enzymes targeted by nerve gas, pesticide, or drug intoxication.

Parabrachial tachykinin1-expressing neurons involved in state-dependent breathing control

Breathing is regulated automatically by neural circuits in the medulla to maintain homeostasis, but breathing is also modified by behavior and emotion. Mice have rapid breathing patterns that are unique to the awake state and distinct from those driven by automatic reflexes. Activation of medullary neurons that control automatic breathing does not reproduce these rapid breathing patterns. By manipulating transcriptionally defined neurons in the parabrachial nucleus, we identify a subset of neurons that express the Tac1, but not Calca, gene that exerts potent and precise conditional control of breathing in the awake, but not anesthetized, state via projections to the ventral intermediate reticular zone of the medulla. Activating these neurons drives breathing to frequencies that match the physiological maximum through mechanisms that differ from those that underlie the automatic control of breathing. We postulate that this circuit is important for the integration of breathing with state-dependent behaviors and emotions.

Cholinergic basal forebrain degeneration due to sleep-disordered breathing exacerbates pathology in a mouse model of Alzheimer's disease

Although epidemiological studies indicate that sleep-disordered breathing (SDB) such as obstructive sleep apnea is a strong risk factor for the development of Alzheimer's disease (AD), the mechanisms of the risk remain unclear. Here we developed a method of modeling SDB in mice that replicates key features of the human condition: altered breathing during sleep, sleep disruption, moderate hypoxemia, and cognitive impairment. When we induced SDB in a familial AD model, the mice displayed exacerbation of cognitive impairment and the pathological features of AD, including increased levels of amyloid-beta and inflammatory markers, as well as selective degeneration of cholinergic basal forebrain neurons. These pathological features were not induced by chronic hypoxia or sleep disruption alone. Our results also revealed that the cholinergic neurodegeneration was mediated by the accumulation of nuclear hypoxia inducible factor 1 alpha. Furthermore, restoring blood oxygen levels during sleep to prevent hypoxia prevented the pathological changes induced by the SDB. These findings suggest a signaling mechanism whereby SDB induces cholinergic basal forebrain degeneration.

Unsupervised study of plethysmography signals through DTW clustering

The study of plethysmography time series is crucial to better understand the breathing behavior of mice, in particular the influence of neurotoxins on the respiratory system. Current approaches rely on a few respiratory descriptors computed on individual breathing cycles that fail to account for the variety of breathing habits and their evolution with time. In this paper we introduce a new procedure for the automatic analysis of plethysmography signals. Our method relies on a new and robust segmentation of respiratory cycles and a DTW-based clustering algorithm to extract the most typical respiratory cycles (called reference sequences). We can then create a symbolic representation of any new recording by matching respiratory cycles to their closest reference sequence. This new representation is a visual and quantitative tool to assess the breathing behavior of mice and its evolution with time. Our method is applied to plethysmography signals collected on mice with two different genotypes and exposed to a neurotoxin. Clinical relevance This article proposes a novel approach to study plethysmography data. Our algorithm is able to accurately extract clinically meaningful respiratory cycles and the associated ventilation patterns descriptors such as tidal volume and inhalation/exhalation duration. In addition, thanks to the associated symbolic representation of signals, the temporal evolution of respiration is easily quantified. This opens a new research path to study the often slowly evolving and subtle influence of neurotoxins on the respiratory system.

Automated evaluation of respiratory signals to provide insight into respiratory drive

The diaphragm muscle (DIAm) is the primary inspiratory muscle in mammals and is highly active throughout life displaying rhythmic activity. The repetitive activation of the DIAm (and of other muscles driven by central pattern generator activity) presents an opportunity to analyze these physiological data on a per-event basis rather than pooled on a per-subject basis. The present study highlights the development and implementation of a graphical user interface-based algorithm using an analysis of critical points to detect the onsets and offsets of individual respiratory events across a range of motor behaviors, thus facilitating analyses of within-subject variability. The algorithm is designed to be robust regardless of the signal type (e.g., EMG or transdiaphragmatic pressure). Our findings suggest that this approach may be particularly beneficial in reducing animal numbers in certain types of studies, for assessments of perturbation studies where the effects are relatively small but potentially physiologically meaningful, and for analyses of respiratory variability.