Breathing Cycle Research Articles

Electric impedance tomography and protective mechanical ventilation in elective robotic-assisted laparoscopy surgery with steep Trendelenburg position: a randomized controlled study

Electrical impedance tomography (EIT) reconstructs functional lung images and evaluates the variations of impedance during the breathing cycle. The aim of this study was to evaluate the effect of protective mechanical ventilation on ventilation distributions recorded by the EIT during elective robotic-assisted laparoscopy surgery with steep Trendelenburg position. This prospective, randomized single center study included patients with healthy lungs undergoing elective robot-assisted laparoscopic urological surgery in general anesthesia. Patients were randomly assigned to either protective lung ventilation or conventional ventilation. In the protective ventilation group, tidal volume (TV) was set at 6 ml/Kg predicted body weight (PBW), with PEEP 6 cmH2O, and recruitment maneuvers (RM) as needed. In the conventional ventilation group, TV was set at 9 ml/Kg PBW, with PEEP 2 cmH2O and RM only as needed. Ventilation distribution was assessed using an EIT device. This study included 40 patients in the functional image analysis. Significant differences were found in ventilation distribution in the region of interest (p < 0.05). Driving pressure was significantly lower in protective ventilation group (p < 0.05). Peak and plateau pressures were not different between the groups while statical significance was found in tidal volume and respiratory rate. EIT may be a valuable tool for monitoring lung function during general anesthesia. During elective robotic-assisted laparoscopy surgery with steep Trendelenburg position, protective mechanical ventilation may have a more homogenous distribution of intraoperative and postoperative ventilation. Larger sample size and long-term evaluation are needed in future studies to assess the benefit of EIT monitoring in operation room.Clinical trial registration ClinicalTrials.gov Identifier: NCT04194177 registered at 11th December 2019.

Highly accelerated dynamic acquisition of 3D grid-tagged hyperpolarized-gas lung images using compressed sensing.

To develop and test compressed sensing-based multiframe 3D MRI of grid-tagged hyperpolarized gas in the lung. Applying grid-tagging RF pulses to inhaled hyperpolarized gas results in images in which signal intensity is predictably and sparsely distributed. In the present work, this phenomenon was used to produce a sampling pattern in which k-space is undersampled by a factor of approximately seven, yet regions of high k-space energy remain densely sampled. Three healthy subjects received multiframe 3D 3 He tagging MRI using this undersampling method. Images were collected during a single exhalation at eight timepoints spanning the breathing cycle from end-of-inhalation to end-of-exhalation. Grid-tagged images were used to generate 3D displacement maps of the lung during exhalation, and time-resolved maps of principal strains and fractional volume change were generated from these displacement maps using finite-element analysis. Tags remained clearly resolvable for 4-6 timepoints (5-8s) in each subject. Displacement maps revealed noteworthy temporal and spatial nonlinearities in lung motion during exhalation. Compressive normal strains occurred along all three principal directions but were primarily oriented in the head-foot direction. Fractional volume changes displayed clear bilateral symmetry, but with the lower lobes displaying slightly higher change than the upper lobes in 2 of the 3 subjects. We developed a compressed sensing-based method for multiframe 3D MRI of grid-tagged hyperpolarized gas in the lung during exhalation. This method successfully overcomes previous challenges for 3D dynamic grid-tagging, allowing time-resolved biomechanical readouts of lung function to be generated.

Observation of respiration-entrained brain oscillations with scalp EEG

In animal models, oscillations of local field potentials are entrained by nasal respiration at the frequency of breathing cycle in olfactory brain regions, such as the olfactory bulb and piriform cortex, as well as in the other brain regions. Studies in humans also confirmed these respiration-entrained oscillations in several brain regions using intracranial electroencephalogram (EEG). Here we extend these findings by analyzing coherence between cortical activity and respiration using high-density scalp EEG in twenty-seven healthy human subjects. Results indicated the occurrence of significant coherence between scalp EEG and respiration signals, although the number and locations of electrodes showing significant coherence were different among subjects. These findings suggest that scalp EEG can detect respiration-entrained oscillations. It remained to be determined whether these oscillations are volume conducted from the olfactory brain regions or reflect the local cortical activity.

Pressure Prediction on Mechanical Ventilation Control Using Bidirectional Long-Short Term Memory Neural Networks.

Life support systems are playing a critical role on keeping a patient alive when admitted in ICU bed. One of the most popular life support system is Mechanical Ventilation which helps a patient to breath when breathing is inadequate to maintain life. Despite its important role during ICU admission, the technology for Mechanical Ventilation hasn't change a lot for several years. In this paper, we developed a model using artificial neural networks, in an attempt to make ventilators more intelligent and personalized to each patient's needs. We used artificial data to train a deep learning model that predicts the correct pressure to be applied on patient's lungs every timepoint within a breath cycle. Our model was evaluated using cross-validation and achieved a Mean Absolute Error of 0.19 and a Mean Absolute Percentage Error of 2%.

Heart Rate Variability Biofeedback Psychophysiological Rehabilitation in Coronary Artery Disease Patients: State of Heart as the State of Brain

Introduction: Psychological therapies in cardiac rehabilitation programs were found to be effective for patients with Coronary Artery Disease (CAD). Heart Rate Variability Biofeedback (HRVBF) is a behavioural neuro-cardiac intervention designed as a natural oscillation between the breathing cycle and Heart Rate (HR), also known as refractory sinus rhythm biofeedback. Aim: To find the potential effects of heart rate variability biofeedback for psychophysiological rehabilitation in coronary artery disease patients. Materials and Methods: In this systematic review included five databases (PubMed, Scopus, web of science, and Google Scholar) were searched for publications between January 2011 and December 2021. Randomised control trials published in the English language, done on the effect of HRV-BF on psychophysiological rehabilitation in CAD, were included. High-quality experimental trials were chosen for the study, using Arksey and O’Malley framework. The records were screened against eligibility criteria and methodological quality analysis was done using Downs and black checklist. Results: Overall, 11,048 articles were extracted, from which 56 records were screened, and three randomised control trials were included in the study. All the three studies scored within a range of 20 to 25, with good methodological quality. They demonstrate practical feasibility of heart rate variability biofeedback device with both short-term and long-term effect on psychophysiological rehabilitation in CAD patients. Conclusion: This systematic review showed the potential effects of HRV-BF for psychophysiological rehabilitation in CAD patients. Patients have reported the benefits of HRV-BF therapies by patient-reported as well as therapies reported outcome measures.

Project of a psychocorrection program to athletes of wheelchair curling

The article describes a correctional program for athletes of the Russian national wheelchair curling team, aimed at improving the indicators of higher mental functions and stress resistance. At the 2021 World Cup, the team took 3rd place, losing in the semifinals, because they could not cope with tension and psychological instability at a crucial moment. At the Winter Paralympic Games held in March 2022, the athletes of the Russian wheelchair curling team had to be emotionally stable, able to maintain high concentration of attention and an unmistakable figurative memory throughout the tournament. To achieve this goal, the coaching staff of the Russian national team proposed the idea of developing a program of psychological correction. This study is a continuation of the diagnosis of the characteristics of the psycho-emotional states of athletes, which was conducted in 2021. Based on the results of the diagnosis, a sports psychologist developed a correctional program. The program is based on breathing control techniques, visualization, ways to control muscle tone, as well as the formation of grounding skills to reduce anxiety levels before competitions. To mobilize the condition, athletes are offered exercises for upper breathing, and for calm and concentration – 4 stages of a single cycle of lower breathing. Athletes are also recommended to prevent muscle clamps by performing exercises for 3 phases "strain – feel – relax". In 2021, a pedagogical experiment lasting ten months was conducted to evaluate the effectiveness of the developed methodology. The study involved 9 athletes – members of the main and extended squads of the Russian wheelchair curling team aged 28 to 49 years: 6 men and 3 women.

Bidirectional airflow in lung airway-on-a-chip with matrix-derived membrane elicits epithelial glycocalyx formation.

Organ-on-a-chip systems are rapidly advancing as a viable alternative to existing experimental models in respiratory research. To date, however, epithelial cell cultures within lung airway-on-a-chip devices have yet to demonstrate the presence of an epithelial glycocalyx, a thin layer of proteoglycans, glycoproteins, and glycolipids known to play an important role in regulating epithelial function. Here, we demonstrate that an airway-on-a-chip device that incorporates bidirectional flow mimicking breathing cycles in combination with an ultra-thin matrix-derived membrane (UMM) layer can generate a glycocalyx layer comprised of heparan sulfate. Results with this device and airflow system showed dramatic differences of airway epithelial cell viability and expression of tight junctions, cilia, and mucus over a wide range of flow rates when cultured under oscillatory flow. More importantly, for the first time in a microfluidic organ-on-a-chip setting, we achieved the visualization of an airflow-induced epithelial glycocalyx layer. Our experiments highlight the importance of physiological mimicry in developing in vitro models, as bidirectional airflow showed more representative mucociliary differentiation compared to continuous unidirectional airflow. Thus, the lung airway-on-a-chip platform demonstrated in this study holds great potential as a lung epithelial barrier model for studying the mechanisms of various respiratory diseases and for testing the efficacy of therapeutic candidates in the presence of bidirectional airflow and the glycocalyx.

Time-Synchronized MRI-Assessment of Respiratory Apparatus Subsystems—A Feasibility Study

The thorax (TH), the thoracic diaphragm (TD), and the abdominal wall (AW) are three sub-systems of the respiratory apparatus whose displacement motion has been well studied with the use of magnetic resonance imaging (MRI). Another sub-system, which has however received less research attention with respect to breathing, is the pelvic floor (PF). In particular, there is no study that has investigated the displacement of all four sub-systems simultaneously. Addressing this issue, it was the purpose of this feasibility study to establish a data acquisition paradigm for time-synchronous quantitative analysis of dynamic MRI data from these four major contributors to respiration and phonation (TH, TD, AW, and PF). Three healthy females were asked to breathe in and out forcefully while being recorded in a 1.5-Tesla whole body MR-scanner. Spanning a sequence of 15.12 seconds, 40 MRI data frames were acquired. Each data frame contained two slices, simultaneously documenting the mid-sagittal (TH, TD, PF) and transversal (AW) planes. The displacement motion of the four anatomical structures of interest was documented using kymographic analysis, resulting in time-varying calibrated structure displacement data. After computing the fundamental frequency of the cyclical breathing motion, the phase offsets of the TH, PF, and AW with respect to the TD were computed. Data analysis revealed three fundamentally different displacement patterns. Total structure displacement was in the range of 0.94 cm (TH) to 4.27cm (TD). Phase delays of up to 90∘ (i.e., a quarter of a breathing cycle) between different structures were found. Motion offsets in the range of -28.30∘ to 14.90∘ were computed for the PF with respect to the TD. The diversity of results in only three investigated participants suggests a variety of possible breathing strategies, warranting further research.

Reduced personal exposure to airborne cross-infection using wearable exhaust ventilation

This study aimed to explore an alternative solution for protection against cross-infection. Exposure reduction to exhaled airborne contaminants by wearing an exhaust nozzle was studied. Experiments were performed in a full-scale test room (64.8 m3) equipped with a small section of a stadium tribune with six seats. Two breathing thermal manikins and four heated dummies were placed on the tribune. The manikins were equipped with artificial lungs simulating a realistic breathing cycle and respiratory flow. One of the breathing manikins was used to mimic a sick person having an infectious respiratory disease. The exhaled air of the “infecting person” was mixed with tracer gas to imitate pathogens. Four types of air exhaust nozzles were studied for their efficiency to reduce exposure to exhaled contaminants. The nozzle was positioned in front of the mouth of the infecting person. The test room was ventilated with mixing background ventilation. The use of the exhaust nozzle resulted in cleaner air in the room and at the breathing zone of the simulated occupants compared to only using dilution by the background ventilation. The novel device has the potential to capture exhaled air and reduce airborne cross-infection in densely occupied sitting areas.

Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring.

Breathing can be measured in a non-contact method using a thermal camera. The objective of this study investigates non-contact breathing measurements using thermal cameras, which have previously been limited to measuring the nostril only from the front where it is clearly visible. The previous method is challenging to use for other angles and frontal views, where the nostril is not well-represented. In this paper, we defined a new region called the breathing-associated-facial-region (BAFR) that reflects the physiological characteristics of breathing, and extract breathing signals from views of 45 and 90 degrees, including the frontal view where the nostril is not clearly visible. Experiments were conducted on fifteen healthy subjects in different views, including frontal with and without nostril, 45-degree, and 90-degree views. A thermal camera (A655sc model, FLIR systems) was used for non-contact measurement, and biopac (MP150, Biopac-systems-Inc) was used as a chest breathing reference. The results showed that the proposed algorithm could extract stable breathing signals at various angles and views, achieving an average breathing cycle accuracy of 90.9% when applied compared to 65.6% without proposed algorithm. The average correlation value increases from 0.587 to 0.885. The proposed algorithm can be monitored in a variety of environments and extract the BAFR at diverse angles and views.

Monitoring of Sleep Breathing States Based on Audio Sensor Utilizing Mel-Scale Features in Home Healthcare.

Sleep-related breathing disorders (SBDs) will lead to poor sleep quality and increase the risk of cardiovascular and cerebrovascular diseases which may cause death in serious cases. This paper aims to detect breathing states related to SBDs by breathing sound signals. A moment waveform analysis is applied to locate and segment the breathing cycles. As the core of our study, a set of useful features of breathing signal is proposed based on Mel frequency cepstrum analysis. Finally, the normal and abnormal sleep breathing states can be distinguished by the extracted Mel-scale indexes. Young healthy testers and patients who suffered from obstructive sleep apnea are tested utilizing the proposed method. The average accuracy for detecting abnormal breathing states can reach 93.1%. It will be helpful to prevent SBDs and improve the sleep quality of home healthcare.

Limitations of phase-sorting based pencil beam scanned 4D proton dose calculations under irregular motion

Objective. 4D dose calculation (4DDC) for pencil beam scanned (PBS) proton therapy is typically based on phase-sorting of individual pencil beams onto phases of a single breathing cycle 4DCT. Understanding the dosimetric limitations and uncertainties of this approach is essential, especially for the realistic treatment scenario with irregular free breathing motion. Approach. For three liver and three lung cancer patient CTs, the deformable multi-cycle motion from 4DMRIs was used to generate six synthetic 4DCT(MRI)s, providing irregular motion (11/15 cycles for liver/lung; tumor amplitudes ∼4–18 mm). 4DDCs for two-field plans were performed, with the temporal resolution of the pencil beam delivery (4–200 ms) or with 8 phases per breathing cycle (500–1000 ms). For the phase-sorting approach, the tumor center motion was used to determine the phase assignment of each spot. The dose was calculated either using the full free breathing motion or individually repeating each single cycle. Additionally, the use of an irregular surrogate signal prior to 4DDC on a repeated cycle was simulated. The CTV volume with absolute dose differences >5% (V dosediff>5%) and differences in CTV V 95% and D 5%–D 95% compared to the free breathing scenario were evaluated. Main results. Compared to 4DDC considering the full free breathing motion with finer spot-wise temporal resolution, 4DDC based on a repeated single 4DCT resulted in V dosediff>5% of on average 34%, which resulted in an overestimation of V 95% up to 24%. However, surrogate based phase-sorting prior to 4DDC on a single cycle 4DCT, reduced the average V dosediff>5% to 16% (overestimation V 95% up to 19%). The 4DDC results were greatly influenced by the choice of reference cycle (V dosediff>5% up to 55%) and differences due to temporal resolution were much smaller (V dosediff>5% up to 10%). Significance. It is important to properly consider motion irregularity in 4D dosimetric evaluations of PBS proton treatments, as 4DDC based on a single 4DCT can lead to an underestimation of motion effects.

Pulse respiration quotient as a measure sensitive to changes in dynamic behavior of cardiorespiratory coupling such as body posture and breathing regime.

Objective: In this research we explored the (homeo)dynamic character of cardiorespiratory coupling (CRC) under the influence of different body posture and breathing regimes. Our tool for it was the pulse respiration quotient (PRQ), representing the number of heartbeat intervals per breathing cycle. We obtained non-integer PRQ values using our advanced Matlab® algorithm and applied it on the signals of 20 healthy subjects in four conditions: supine position with spontaneous breathing (Supin), standing with spontaneous breathing (Stand), supine position with slow (0.1Hz) breathing (Supin01) and standing with slow (0.1Hz) breathing (Stand01). Main results: Linear features of CRC (in PRQ signals) were dynamically very sensitive to posture and breathing rhythm perturbations. There are obvious increases in PRQ mean level and variability under the separated and joined influence of orthostasis and slow (0.1Hz) breathing. This increase was most pronounced in Stand01 as the state of joint influences. Importantly, PRQ dynamic modification showed greater sensitivity to body posture and breathing regime changes than mean value and standard deviation of heart rhythm and breathing rhythm. In addition, as a consequence of prolonged supine position, we noticed the tendency to integer quantization of PRQ (especially after 14min), in which the most common quantization number was 4:1 (demonstrated in other research reports as well). In orthostasis and slow breathing, quantization can also be observed, but shifted to other values. We postulate that these results manifest resonance effects induced by coupling patterns from sympathetic and parasympathetic adjustments (with the second as dominant factor). Significance: Our research confirms that cardiorespiratory coupling adaptability could be profoundly explored by precisely calculated PRQ parameter since cardiorespiratory regulation in healthy subjects is characterized by a high level of autonomic adaptability (responsiveness) to posture and breathing regime, although comparisons with pathological states has yet to be performed. We found Stand01 to be the most provoking state for the dynamic modification of PRQ (cardiorespiratory inducement). As such, Stand01 has the potential of using for PRQ tuning by conditioning the cardiorespiratory autonomic neural networks, e.g., in the cases where PRQ is disturbed by environmental (i.e., microgravity) or pathologic conditions.

Preclinical MRI Using Hyperpolarized 129Xe

Although critical for development of novel therapies, understanding altered lung function in disease models is challenging because the transport and diffusion of gases over short distances, on which proper function relies, is not readily visualized. In this review we summarize progress introducing hyperpolarized 129Xe imaging as a method to follow these processes in vivo. The work is organized in sections highlighting methods to observe the gas replacement effects of breathing (Gas Dynamics during the Breathing Cycle) and gas diffusion throughout the parenchymal airspaces (3). We then describe the spectral signatures indicative of gas dissolution and uptake (4), and how these features can be used to follow the gas as it enters the tissue and capillary bed, is taken up by hemoglobin in the red blood cells (5), re-enters the gas phase prior to exhalation (6), or is carried via the vasculature to other organs and body structures (7). We conclude with a discussion of practical imaging and spectroscopy techniques that deliver quantifiable metrics despite the small size, rapid motion and decay of signal and coherence characteristic of the magnetically inhomogeneous lung in preclinical models (8).

In-House monitoring and measurement of respiration rateusing Disposable Paper Sensor

This present work provides an easily disposable paper-based interdigitated sensor embedded inside the mask for the detection of respiration rate continuously without direct contact with the human body. In present COVID scenario, everyone needs to wear mask for preventing the unwanted spreading of the said virus. But in tropical countries like India, People always complain about a suffocating situation while wearing mask. In order to address this, we have designed a non-invasive paper sensor that can be placed inside the mask (beneath nostril) for measuring breathing rate regularly to find out a cost-effective device capable of monitoring breathing rate. In general, we prefer use and throw type mask, thus the proposed paper-based sensor gives a cost-effective solution compared to the Current appliances of breathing sensing as most of them are burdensome, bulky, inconvenient as well as exorbitant than a paper-based respiration sensor. Essentially, these current approaches undergo through a practical limitation of frequency and time span i.e. static measurement. It is known that the humidity level of a paper changes according to the moisture content. Thus, it can easily detect the inhalation and exhalation through this changing. Moreover, variation of moisture level that happens due to breathing cycle changes the ionic conductivity of the sensor. The interdigitated design is the most suited for achieving higher sensitivity and easy to fabricate. First, we have designed it in Finite Element Method (FEM) based platform and finally this design is implemented with graphite-based electrodes on cellulose paper. Microcontroller based electronic circuitry is used in order to monitor and record the real-time respiration rate. It has been observed that the breathing rate as well as pattern gives a significant variation along with physical conditions and obstructive pulmonary diseases.

Характеристика стійкого стану функцій спортсменів у видах спорту з варіативними умовами змагальної діяльності

The purpose of the study was to develop generalized and specific characteristics of the steady state of the highly qualified athletes, who specialize in the standard program of sports dance and boxing. Materials and methods. Twenty sportsmen-dancers and twenty boxers of high qualification took part in the research. Gas analysis. Measurements of О2 consumption reaction, СО2 emissions, minute volume of breathing were carried out using the MetaMax 3B analyzer. Ergometry. Modeling of standard conditions of measurement was carried out on the basis of bicycle ergometer Monark. Standard conditions are associated with the use of a given ergometric load power of 50 W. The composition of Cardiorespiratory Intermittent endurance test included eight accelerated 10-second intervals, eight 20-second rest intervals. The duration of the task is four minutes. Mathematic statistics. Descriptive statistics suggested determining the arithmetic mean – x ̅, standard deviation – S, as well as median – Me, maximum (max) and minimum (min) indices, 25% and 75% indices. Steady state is a period of competitive activity, in the process of which sportsmen demonstrate high level of technical and tactical skills and physical performance. Steady state diagnostics is an essential reserve for managing the functional support of special performance of athletes in sports with variable conditions of competitive activity. Results and discussion. An increase in the response of pulmonary ventilation indicates its role as a response to respiratory compensation of metabolic acidosis. Differences in the breathing response in standard measurement conditions are related to the specificity of the breathing response of athletes-dancers. To some extent, “artificial” management of the breathing response causes a decrease in the intensity of breathing cycles. Empirical knowledge indicates that this refers to the “aesthetic” component of the judges' assessment of the performance of the sports dance program. To some extent, this is related to the specifics of the formation of programs of special physical training, correction of certain structural components of functional maintenance of working capacity, in this case, the respiratory system. Another obvious fact is related to the structure of the load, when the intensity of the work of boxers causes more significant acidemic shifts and, as a result, predicts an increase in the reaction of pulmonary ventilation as a mechanism for removing excess CO2 during work. The increase (maintenance) of the O2 consumption response of athletes-dancers is associated with the formation of excess CO2 within the RER – 1.03–1.05 and excessive pulmonary ventilation in the range of 37.2–39.1. Boxers, respectively, with the formation of excess CO2 within the limits of RER – 1.07–1.09 and excessive pulmonary ventilation in the range of 40.0–44.1. The increase in excess ventilation in the third-fifth of dancers was 4.9%, 9.9% – in boxers, provided that the O2 consumption reaction remained stable. Conclusion. The steady state of the functional support of the special performance of athletes in sports with variable conditions of competitive activity ensures the stable development of cardio-respiratory system and aerobic energy supply in the middle of intense motor activity

Microcircuit Synchronization and Heavy-Tailed Synaptic Weight Distribution Augment preBötzinger Complex Bursting Dynamics.

The preBötzinger Complex (preBötC) encodes inspiratory time as rhythmic bursts of activity underlying each breath. Spike synchronization throughout a sparsely connected preBötC microcircuit initiates bursts that ultimately drive the inspiratory motor patterns. Using minimal microcircuit models to explore burst initiation dynamics, we examined the variability in probability and latency to burst following exogenous stimulation of a small subset of neurons, mimicking experiments. Among various physiologically plausible graphs of 1000 excitatory neurons constructed using experimentally determined synaptic and connectivity parameters, directed Erdős-Rényi graphs with a broad (lognormal) distribution of synaptic weights best captured the experimentally observed dynamics. preBötC synchronization leading to bursts was regulated by the efferent connectivity of spiking neurons that are optimally tuned to amplify modest preinspiratory activity through input convergence. Using graph-theoretic and machine learning-based analyses, we found that input convergence of efferent connectivity at the next-nearest neighbor order was a strong predictor of incipient synchronization. Our analyses revealed a crucial role of synaptic heterogeneity in imparting exceptionally robust yet flexible preBötC attractor dynamics. Given the pervasiveness of lognormally distributed synaptic strengths throughout the nervous system, we postulate that these mechanisms represent a ubiquitous template for temporal processing and decision-making computational motifs.SIGNIFICANCE STATEMENT Mammalian breathing is robust, virtually continuous throughout life, yet is inherently labile: to adapt to rapid metabolic shifts (e.g., fleeing a predator or chasing prey); for airway reflexes; and to enable nonventilatory behaviors (e.g., vocalization, breathholding, laughing). Canonical theoretical frameworks-based on pacemakers and intrinsic bursting-cannot account for the observed robustness and flexibility of the preBötzinger Complex rhythm. Experiments reveal that network synchronization is the key to initiate inspiratory bursts in each breathing cycle. We investigated preBötC synchronization dynamics using network models constructed with experimentally determined neuronal and synaptic parameters. We discovered that a fat-tailed (non-Gaussian) synaptic weight distribution-a manifestation of synaptic heterogeneity-augments neuronal synchronization and attractor dynamics in this vital rhythmogenic network, contributing to its extraordinary reliability and responsiveness.

Non-Invasive 3D Photoacoustic Tomography of Angiographic Anatomy and Hemodynamics of Fatty Livers in Rats.

Non-alcoholic fatty liver disease is the most common liver disorder worldwide, which strongly correlates to obesity, diabetes, and metabolic syndromes. Complementary to mainstream liver diagnostic modalities, photoacoustic tomography (PAT) can provide high-speed images with functional optical contrast. However, PAT has not been demonstrated to study fatty liver anatomy with clear volumetric vasculatures. The livers of multiple rats are non-invasively imaged in vivo using the recently developed 3D PAT platform. The system provides isotropically high spatial resolution in 3D space, presenting clear angiographic structures of rat livers without injecting contrast agents. Furthermore, to quantitatively analyze the difference between the livers of lean and obese rats, the authors measured several PAT features and statistical differences between the two groups are observed. In addition to the anatomy, a time-gated strategy is applied to correct respiration-induced motion artifacts and extracted the hemodynamics of major blood vessels during the breathing cycles. This study demonstrates the capabilities of 3D-PAT to reveal both angiographic anatomy and function in rat livers, providing hematogenous information for fatty liver diagnosis. 3D-PAT, as a new tool for preclinical research, warrants further improvements to be transferred to human pediatric liver imaging.

Cross-System Integration of Respiration and Deglutition: Function, Treatment, and Future Directions.

Swallowing occurs preferentially in the expiratory phase of the quiet breathing cycle and at mid-to-low tidal volume. This coordinative pattern imparts important biomechanical advantages to swallowing and airway protection and facilitate laryngeal elevation, laryngeal vestibular and vocal fold closure, and cricopharyngeal sphincter opening. This preferred coordinative relationship between breathing and swallowing is impaired in a variety of patient populations, including head and neck cancer survivors with dysphagia. We developed a training protocol to re-establish more optimal phasing of swallowing with breathing in these patients with striking outcomes, including reduced swallowing physiological impairments and improved airway protection. This motivated us to continue to refine and expand this training protocol and develop new assistive technologies for swallowing monitoring outside of the lab. In this review, we highlight the origins of our optimal respiratory-swallowing coordination hypothesis, describe the biomechanical advantages it provides, carefully describe our training protocol and findings, and chart a course for the next phase of this work. Our overall goal is to harness technology combined with carefully constructed learning paradigms to improve the lives of patients with impaired respiratory-swallowing coordination consequent to a variety of pathologies including head and neck cancer and degenerative neurological conditions such as Parkinson's disease.

P019 Automatic Detection of Patient-Ventilator Asynchrony during Non-Invasive Ventilation using Matrix Profiles

Abstract Automated Patient-Ventilator Asynchrony (PVA) detection and classification has been described previously, however most approaches target specific asynchrony types, are not applicable in non-invasive ventilation, and require manual pre-processing, removing the opportunity for real-time analysis. During our previous study of polysomnography-assisted NIV implementation (Hannan 2019), each participants’ sleep studies were manually, breath-by-breath scored for PVA. The data were collected over approximately 8 hours and included &amp;gt; 650,000 breath cycles. The source data for the machine learning consisted of the 21 recorded signal traces exported as text files. We employed an outlier detection approach to detect asynchrony with Artificial Intelligence (AI) models as the core engine. The fully automated approach starts with pre-processing to filter and de-noise the polysomnography data, with AI models, including Multidimensional Matrix Profiles, employed to find asynchronies from a signal subset. We initially investigated the best features for PVA and arousal detection in a subset of the 59 participant sleep studies with the highest number of labelled asynchronies and arousals. These six participants had a total of 6,942 events: 799 Arousal, 3,026 Ineffective Triggering, 1,983 Double Triggering and 1,134 Auto Triggering. All events were used in the training/testing stage. The best-balanced model employed a denoising technique with 300 milliseconds as the aggregating data points interval across: mask pressure, ventilator measured flow, abdominal, and thoracic band traces. This approach resulted in 0.80 for both sensitivity and specificity.