Passive Breathing Research Articles

Detection of severe acute respiratory syndrome coronavirus 2 in bioaerosols using digital droplet polymerase chain reaction and loop-mediated isothermal amplification.

In the present study, we simulated human passive breathing, sampled severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) bioaerosols, and compared the detection ability of quantitative polymerase chain reaction (qPCR), digital droplet polymerase chain reaction (ddPCR), and loop-mediated isothermal amplification (LAMP). The specificity of the primer set for the LAMP-based detection of SARS-CoV-2 was evaluated, and its sensitivity using the detection threshold in the amplification curve plots was determined. Next, we used an aerosol collection environment and collected solutions containing predetermined concentrations of plasmid containing SARS-CoV-2 N gene, which were dispersed into the environment, using a cyclone sampler. Finally, we compared the ability of qPCR, ddPCR, and LAMP in detecting SARS-CoV-2 in aerosols and stock solutions. After sampling, qPCR, LAMP and ddPCR can amplify the micro viral samples exponentially. By comparing the three assays, it was judged from the results that qPCR had a slightly higher detection limit, detecting 102 copies per μL, and therefore could not be used as a test for trace samples. qPCR, LAMP, and ddPCR were able to detect aerosol samples of 101 copies per μL. LAMP was able to qualitatively detect the samples, and ddPCR was able to quantitatively detect samples of this order of magnitude. There were 23.2 that could be used as a quantitative assay. This method can be used in public places or hospitals with limited air circulation to detect aerosol-borne viruses in trace quantities and to provide a rapid early warning.

Understanding cardiopulmonary interactions through esophageal pressure monitoring.

Esophageal pressure is the closest estimate of pleural pressure. Changes in esophageal pressure reflect changes in intrathoracic pressure and affect transpulmonary pressure, both of which have multiple effects on right and left ventricular performance. During passive breathing, increasing esophageal pressure is associated with lower venous return and higher right ventricular afterload and lower left ventricular afterload and oxygen consumption. In spontaneously breathing patients, negative pleural pressure swings increase venous return, while right heart afterload increases as in passive conditions; for the left ventricle, end-diastolic pressure is increased potentially favoring lung edema. Esophageal pressure monitoring represents a simple bedside method to estimate changes in pleural pressure and can advance our understanding of the cardiovascular performance of critically ill patients undergoing passive or assisted ventilation and guide physiologically personalized treatments.

Accuracy of the estimations of respiratory mechanics using an expiratory time constant in passive and active breathing conditions: a bench study

BackgroundRespiratory mechanics monitoring provides useful information for guiding mechanical ventilation, but many measuring methods are inappropriate for awake patients. This study aimed to evaluate the accuracy of dynamic mechanics estimation using expiratory time constant (RCexp) calculation during noninvasive pressure support ventilation (PSV) with air leak in different lung models.MethodsA Respironics V60 ventilator was connected to an active breathing simulator for modeling five profiles: normal adult, restrictive, mildly and severely obstructive, and mixed obstructive/restrictive. Inspiratory pressure support was adjusted to maintain tidal volumes (VT), achieving 5.0, 7.0, and 10.0 ml/kg body weight. PEEP was set at 5 cmH2O, and the back-up rate was 10 bpm. Measurements were conducted at system leaks of 25–28 L/min. RCexp was estimated from the ratio at 75% exhaled VT and flow rate, which was then used to determine respiratory system compliance (Crs) and airway resistance (Raw).ResultsIn non-obstructive conditions (Raw ≤ 10 cmH2O/L/s), the Crs was overestimated in the PSV mode. Peak inspiratory and expiratory flow and VT increased with PS levels, as calculated Crs decreased. In passive breathing, the difference of Crs between different VT was no significant. Underestimations of inspiratory resistance and expiratory resistance were observed at VT of 5.0 ml/kg. The difference was minimal at VT of 7.0 ml/kg. During non-invasive PSV, the estimation of airway resistance with the RCexp method was accurately at VT of 7.0 ml/kg.ConclusionsThe difference between the calculated Crs and the preset value was influenced by the volume, status and inspiratory effort in spontaneously breathing.

SARS-CoV-2 Omicron variant shedding during respiratory activities

ObjectivesAs the world transitions to COVID-19 endemicity, studies focusing on aerosol shedding of highly transmissible SARS-CoV-2 variants of concern (VOCs) are vital for the calibration of infection control measures against VOCs that are likely to circulate seasonally. This follow-up Gesundheit-II aerosol sampling study aims to compare the aerosol shedding patterns of Omicron VOC samples with pre-Omicron variants analyzed in our previous study. DesignCoarse and fine aerosol samples from 47 patients infected with SARS-CoV-2 were collected during various respiratory activities (passive breathing, talking, and singing) and analyzed using reverse transcription-quantitative polymerase chain reaction and virus culture. ResultsCompared with patients infected with pre-Omicron variants, comparable SARS-CoV-2 RNA copy numbers were detectable in aerosol samples of patients infected with Omicron despite being fully vaccinated. Patients infected with Omicron also showed a slight increase in viral aerosol shedding during breathing activities and were more likely to have persistent aerosol shedding beyond 7 days after disease onset. ConclusionThis follow-up study reaffirms the aerosol shedding properties of Omicron and should guide continued layering of public health interventions even in highly vaccinated populations.

Design of a multilayer lung chip with multigenerational alveolar ducts to investigate the inhaled particle deposition.

We present the development and application of a multilayer microfluidic lung chip designed to accurately replicate the human respiratory bronchi, providing an innovative platform for controlled particle deposition in the lung. By employing a quantitative control method of fluid velocity through the deformation of an elastic PDMS membrane, this platform mimics the passive breathing process in humans and allows for precise simulation of the respiration cycle. We utilized time-lapse photography of fluorescent particles in a water/glycerol solution to qualitatively observe fluid morphology in the channel, while a chip-aerosol exposure device combined with microscopy imaging was employed to visualise aerosol deposition. Both experimental and numerical simulation results showed that particle concentration decreased towards the distal generations of the lung, and that changes in breathing pattern significantly affected particle deposition trends. Furthermore, we found that increasing the residence time of particles in the channel facilitated deeper particle deposition, achievable by adjusting parameters such as breath-hold time, exhalation time, respiration cycle length, and tidal volume. The proposed microfluidic lung chip device has significant potential for future research in respiratory health and inhaled drug delivery, providing an efficient, cost-effective, and ethical alternative to traditional in vivo studies.

Evolution of respiratory system compliance and potential for lung recruitment in COVID-19–induced acute respiratory distress syndrome

BackgroundCoronavirus disease 2019 (COVID-19) has been frequently complicated by severe acute respiratory distress syndrome (ARDS) with prolonged invasive ventilation. While respiratory system compliance and lung recruitability have been described within the first days after ICU admission, data about their longitudinal changes are still limited. Therefore, we conducted this study to assess the evolution of respiratory system compliance and lung recruitability in patients with COVID-19–related ARDS. MethodWe conducted a prospective single-center study in patients admitted for COVID-19–related ARDS during the first wave of the pandemic, from March 16, 2020 to April 10, 2020. Respiratory system compliance was calculated daily at clinical positive end-expiratory pressure (PEEP) during passive breathing. The potential for lung recruitment was assessed by measuring the volume derecruited between PEEP 15 cmH2O and 5 cmH2O, and using the calculation of the recruitment-to-inflation ratio (R/I ratio). Recruitable lung was considered when the R/I ratio was at least 0.5. The primary outcome was the evolution of respiratory mechanics over time. The secondary outcome was the evolution of lung recruitability over time. ResultsThirty-two patients were included in this study. The respiratory mechanics were assessed 222 times (7 ± 5 times per patient). Respiratory system compliance at clinical PEEP was 29.1 mL/cmH2O (interquartile range [IQR]: 24.1–33.9 mL/cmH2O) and decreased significantly over time (P <0.0001). Lung recruitability was assessed in 22 out of the 32 patients (60 assessments). The median volume derecruited between PEEP 15 cmH2O and 5 cmH2O was 246.8 mL (IQR: 180.8–352.2 mL) and the median R/I ratio was 0.56 (IQR: 0.39–0.73). Neither changed significantly over time. The proportion of patients with recruitable lung was 50.0% (6/12) within the first 3 days after intubation, 69.2% (9/13) between day 4 and day 7, and 66.7% (8/12) after day 7 (P=0.7934). ConclusionsIn our cohort, respiratory system compliance was low and decreased over time. The potential for lung recruitment was high and persisted despite prolonged mechanical ventilation, suggesting that maintaining high PEEP levels in the later course of COVID-19 could be adequate.

Passive Breathing of Earth‐Air: “Fingerprint” Evidence From Moisture Records

Abstract“Earth‐air” refers to air in the vadose zone. Studies have long suggested that earth‐air undergoes a passive breathing effect due to atmospheric pumping. The earth‐air can be modeled as an ideal gas in a closed system, so that the volume of earth‐air varies as the atmospheric pressure (AP) fluctuates. When AP rises, earth‐air is compressed and external air is drawn into the vadose zone. Conversely, when AP drops, earth‐air expands and moist earth‐air enters the atmosphere. In arid regions, there is a moisture gradient in soil due to dryness of the climate: the humidity is relatively low in the upper soil layer, and relatively high in the subsoil. Therefore, if earth‐air undergoes passive breathing, the humidity of earth‐air will fluctuate with AP. This means that passive breathing of the earth‐air should leave traces in the recorded moisture which exactly match AP fluctuations. In this work, clear evidence is presented for the existence of earth‐air passive breathing. This is accomplished by using an innovatively‐designed trap to monitor humidity in 30 cm gravelly sand and showing that these moisture/temperature records contain fingerprints which are characteristic of passive breathing. It is found that relative humidity (RH) in soil is negatively correlated with the atmospheric fluctuations. The correlation between 10‐min average AP and RH timeseries reaches −0.75 for the time‐periods of 20 days. This study provides a new understanding in land‐atmosphere heat/mass exchange from the perspective of vertical fluid dynamics.

BreathTrack

Breathing biomarkers, such as breathing rate, fractional inspiratory time, and inhalation-exhalation ratio, are vital for monitoring the user's health and well-being. Accurate estimation of such biomarkers requires breathing phase detection, i.e., inhalation and exhalation. However, traditional breathing phase monitoring relies on uncomfortable equipment, e.g., chestbands. Smartphone acoustic sensors have shown promising results for passive breathing monitoring during sleep or guided breathing. However, detecting breathing phases using acoustic data can be challenging for various reasons. One of the major obstacles is the complexity of annotating breathing sounds due to inaudible parts in regular breathing and background noises. This paper assesses the potential of using smartphone acoustic sensors for passive unguided breathing phase monitoring in a natural environment. We address the annotation challenges by developing a novel variant of the teacher-student training method for transferring knowledge from an inertial sensor to an acoustic sensor, eliminating the need for manual breathing sound annotation by fusing signal processing with deep learning techniques. We train and evaluate our model on the breathing data collected from 131 subjects, including healthy individuals and respiratory patients. Experimental results show that our model can detect breathing phases with 77.33% accuracy using acoustic sensors. We further present an example use-case of breathing phase-detection by first estimating the biomarkers from the estimated breathing phases and then using these biomarkers for pulmonary patient detection. Using the detected breathing phases, we can estimate fractional inspiratory time with 92.08% accuracy, the inhalation-exhalation ratio with 86.76% accuracy, and the breathing rate with 91.74% accuracy. Moreover, we can distinguish respiratory patients from healthy individuals with up to 76% accuracy. This paper is the first to show the feasibility of detecting regular breathing phases towards passively monitoring respiratory health and well-being using acoustic data captured by a smartphone.

Effect of earth–air breathing on evaporation of deeply buried phreatic water in extremely arid regions

AbstractIn extremely arid regions, deeply buried phreatic water evaporates during the daytime from March to November in the northern hemisphere. It has been found that the earth–air undergoes ‘autonomous breathing’ and ‘passive breathing’, respectively caused by the changes of temperature and atmospheric pressure. In this paper, the effects of these breathing modes on phreatic evaporation (PhE) were investigated as well as the responsible mechanisms. Quantitative estimates suggest that the direct contribution from autonomous breathing is only 0.55 g·m−2·yr−1. Passive breathing pumps water vapour upwards from the deeply buried phreatic water table. Film water on the soil continuously migrates in pulsation from deep layers to the upper layer. Na2SO4 in the shallow soil absorbs moisture from the earth–air at night and decomposes during the day, forming water vapour, which is critical to the occurrence of PhE. The diurnal PhE process can be elucidated in detail by the bimodal variation in the atmospheric pressure. PhE occurs mainly from 10:00 to 17:00 during daytime from March to November, which correlates with passive breathing of the earth–air. The amplitude of atmospheric fluctuation determines the amount of earth–air that outflows, while temperature determines the water vapour concentration. In calculation, PhE is equal to the net absolute humidity (AH) times the amount of earth–air. There is 1.55 mm·year−1 of PhE caused by daily peak→valley differences, and about 2.97 mm·year−1 in estimation caused by numerous atmospheric fluctuations smaller than 2.84 hPa. The results coincide with the actual amount of PhE monitored of 4.52 mm·year−1. Therefore, the amount of PhE is proportional to the range and frequency of fluctuation in external atmospheric pressure, and is also positively related to soil temperature, salt content, water content, porosity, and vadose zone thickness.

Mechanisms of the breathing contribution to bodily self-consciousness in healthy humans: Lessons from machine-assisted breathing?

Previous studies investigated bodily self‐consciousness (BSC) by experimentally exposing subjects to multisensory conflicts (i.e., visuo‐tactile, audio‐tactile, visuo‐cardiac) in virtual reality (VR) that involve the participant's torso in a paradigm known as the full‐body illusion (FBI). Using a modified FBI paradigm, we found that synchrony of visuo‐respiratory stimulation (i.e., a flashing outline surrounding an avatar in VR; the flash intensity depending on breathing), is also able to modulate BSC by increasing self‐location and breathing agency toward the virtual body. Our aim was to investigate such visuo‐respiratory effects and determine whether respiratory motor commands contributes to BSC, using non‐invasive mechanical ventilation (i.e., machine‐delivered breathing). Seventeen healthy participants took part in a visuo‐respiratory FBI paradigm and performed the FBI during two breathing conditions: (a) “active breathing” (i.e., participants actively initiate machine‐delivered breaths) and (b) “passive breathing” (i.e., breaths’ timing was determined by the machine). Respiration rate, tidal volume, and their variability were recorded. In line with previous results, participants experienced subjective changes in self‐location, breathing agency, and self‐identification toward the avatar's body, when presented with synchronous visuo‐respiratory stimulation. Moreover, drift in self‐location was reduced and tidal volume variability were increased by asynchronous visuo‐respiratory stimulations. Such effects were not modulated by breathing control manipulations. Our results extend previous FBI findings showing that visuo‐respiratory stimulation affects BSC, independently from breathing motor command initiation. Also, variability of respiratory parameters was influenced by visuo‐respiratory feedback and might reduce breathing discomfort. Further exploration of such findings might inform the development of respiratory therapeutic tools using VR in patients.

Lattice defects induce microtubule self-renewal.

Microtubules are dynamic polymers, which grow and shrink by addition and removal of tubulin dimers at their extremities. Within the microtubule shaft, dimers adopt a densely packed and highly ordered crystal-like lattice structure, which is generally not considered to be dynamic. Here we report that thermal forces are sufficient to remodel the microtubule shaft, despite its apparent stability. Our combined experimental data and numerical simulations on lattice dynamics and structure suggest that dimers can spontaneously leave and be incorporated into the lattice at structural defects. We propose a model mechanism, where the lattice dynamics is initiated via a passive breathing mechanism at dislocations, which are frequent in rapidly growing microtubules. These results show that we may need to extend the concept of dissipative dynamics, previously established for microtubule extremities, to the entire shaft, instead of considering it as a passive material.

Driving Pressure: Defining the Range.

Recent literature suggests that optimization of tidal driving pressure (ΔP) would be a better variable to target for lung protection at the bedside than tidal volume (VT) or plateau pressure (Pplat), the traditional indicators of ventilator-induced lung injury. However, the usual range or variability of ΔP over time for any subject category have not been defined. This study sought to document the ΔP ranges observed in current practice among mechanically ventilated subjects receiving routine care for diverse acute conditions in a community hospital environment. This was a retrospective, observational study in a university-affiliated and house staff-aided institution with respiratory care protocols based on extant lung-protective guidelines for VT. Demographic characteristics and measured parameters related to mechanical ventilation and hemodynamics were extracted from electronic records of intubated subjects for each 8-h period of the first 24 h in the ICU. Pplat values reported by the ventilator were validated by the respiratory therapist before those data were entered into the electronic medical record. The mean ΔP was significantly higher at Time 1 (mean 16.1, range 7.0-31.0 cm H2O) compared to both Time 2 (mean 14.5, range 7.0-35.0 cm H2O) (P < .001) and Time 3 (mean 14.8, range 8.0-32 cm H2O) (P < .001). At all time points, the median ΔP was higher for completely passive breathing compared to triggered breathing. The widest difference between presumed entirely passive and presumed intermittently or consistently triggered breaths occurred at Time 1 (mean ΔP = 17.2 vs 14.9 cm H2O, respectively) (P = .01). Suggested safety thresholds for ΔP are often violated by a strategy that focuses on only VT and Pplat. Our data suggest that ΔP is lower for passive versus triggered breathing cycles. Vigilance is especially important in the initial stages of mechanical ventilator support, and attention should be paid to triggering efforts when interpreting and comparing machine-determined numerical values for ΔP.

Yoga and breathing technique training in patients with heart failure and preserved ejection fraction: study protocol for a randomized clinical trial

BackgroundCurrent therapies for heart failure (HF) are followed by strategies to improve quality of life and exercise tolerance, besides reducing morbidity and mortality. Some HF patients present changes in the musculoskeletal system and inspiratory muscle weakness, which may be restored by inspiratory muscle training, thus increasing respiratory muscle strength and endurance, maximal oxygen uptake (VO2), functional capacity, respiratory responses to exercise, and quality of life. Yoga therapies have been shown to improve quality of life, inflammatory markers, and peak VO2 mostly in HF patients with a reduced ejection fraction. However, the effect of different yoga breathing techniques in patients showing HF with a preserved ejection fraction (HFpEF) remain to be assessed.Methods/designA PROBE (prospective randomized open blinded end-point) parallel-group trial will be conducted at two specialized HF clinics. Adult patients previously diagnosed with HFpEF will be included. After signing informed consent and performing a pre-test intervention, patients will be randomized into three groups and provided with either (1) active yoga breathing techniques; (2) passive yoga breathing techniques (pranayama); or and (3) control (standard pharmacological treatment). Follow-up will last 8 weeks (16 sessions). The post-intervention tests will be performed at the end of the intervention period for analysis of outcomes. Interventions will occur continuously according to patients’ enrollment. The main outcome is respiratory muscular resistance. A total of 33 enrolled patients are expected. The present protocol followed the SPIRIT guidelines and fulfilled the SPIRIT checklist.DiscussionThis trial is probably the first to assess the effects of a non-pharmacological intervention, namely yoga and specific breathing techniques, to improve cardiorespiratory function, autonomic system, and quality of life in patients with HFpEF.Trial registrationREBEC Identifier: RBR-64mbnx (August 19, 2012).Clinical Trials Register: NCT03028168. Registered on 16 January 2017).

Lung volumes and transpulmonary pressure are decreased with expiratory effort and restored with passive breathing in ARDS: a reapplication of the traditional Campbell diagram

Lung volumes and transpulmonary pressure are decreased with expiratory effort and restored with passive breathing in ARDS: a reapplication of the traditional Campbell diagram

Assessing mechanical ventilation asynchrony through iterative airway pressure reconstruction

Background and objectiveRespiratory mechanics estimation can be used to guide mechanical ventilation (MV) but is severely compromised when asynchronous breathing occurs. In addition, asynchrony during MV is often not monitored and little is known about the impact or magnitude of asynchronous breathing towards recovery. Thus, it is important to monitor and quantify asynchronous breathing over every breath in an automated fashion, enabling the ability to overcome the limitations of model-based respiratory mechanics estimation during asynchronous breathing ventilation. MethodsAn iterative airway pressure reconstruction (IPR) method is used to reconstruct asynchronous airway pressure waveforms to better match passive breathing airway waveforms using a single compartment model. The reconstructed pressure enables estimation of respiratory mechanics of airway pressure waveform essentially free from asynchrony. Reconstruction enables real-time breath-to-breath monitoring and quantification of the magnitude of the asynchrony (MAsyn). Results and discussionOver 100,000 breathing cycles from MV patients with known asynchronous breathing were analyzed. The IPR was able to reconstruct different types of asynchronous breathing. The resulting respiratory mechanics estimated using pressure reconstruction were more consistent with smaller interquartile range (IQR) compared to respiratory mechanics estimated using asynchronous pressure. Comparing reconstructed pressure with asynchronous pressure waveforms quantifies the magnitude of asynchronous breathing, which has a median value MAsyn for the entire dataset of 3.8%. ConclusionThe iterative pressure reconstruction method is capable of identifying asynchronous breaths and improving respiratory mechanics estimation consistency compared to conventional model-based methods. It provides an opportunity to automate real-time quantification of asynchronous breathing frequency and magnitude that was previously limited to invasively method only.

Wireless Breathing Sensor Based on Wearable Modulated Frequency Selective Surface

This paper presents a wireless apnoea detector using a passive breathing sensor. The device is based on the measurement of the airflow temperature changes that are produced during breathing. The sensor is a negative temperature coefficient resistor, which is to be placed close to the nose. The functional principle is based on the change of resistance, since the body increases the temperature of the airflow, which the device receives during breathing. The wireless communication is performed using the backscattered field technique, and is based on the modulation of the response from a transponder. This backscattering technique saves a lot of energy in comparison to its alternatives and guarantees a long lifetime for the device. The transponder is composed of an array of dipoles, loaded with varactor diodes, which implement a frequency selective surface. NTC measured temperature controls the oscillation frequency of a low-frequency, two-inverter oscillator. The output of the latter modulates the varactor diodes which, in turn, modulate the backscattered response of the transponder. An algorithm, which is based on the detection of the peaks on the breathing signal in order to calculate real-time respiration and apnoea intervals, has been implemented. The reader used is also presented and experimental results are shown. The sensor can be used to perform continuous real-time measurements for long period on time due to its low-power consumption.

Rodent ultrasonic vocalizations are bound to active sniffing behavior.

During rodent active behavior, multiple orofacial sensorimotor behaviors, including sniffing and whisking, display rhythmicity in the theta range (~5–10 Hz). During specific behaviors, these rhythmic patterns interlock, such that execution of individual motor programs becomes dependent on the state of the others. Here we performed simultaneous recordings of the respiratory cycle and ultrasonic vocalization emission by adult rats and mice in social settings. We used automated analysis to examine the relationship between breathing patterns and vocalization over long time periods. Rat ultrasonic vocalizations (USVs, “50 kHz”) were emitted within stretches of active sniffing (5–10 Hz) and were largely absent during periods of passive breathing (1–4 Hz). Because ultrasound was tightly linked to the exhalation phase, the sniffing cycle segmented vocal production into discrete calls and imposed its theta rhythmicity on their timing. In turn, calls briefly prolonged exhalations, causing an immediate drop in sniffing rate. Similar results were obtained in mice. Our results show that ultrasonic vocalizations are an integral part of the rhythmic orofacial behavioral ensemble. This complex behavioral program is thus involved not only in active sensing but also in the temporal structuring of social communication signals. Many other social signals of mammals, including monkey calls and human speech, show structure in the theta range. Our work points to a mechanism for such structuring in rodent ultrasonic vocalizations.

The Effect of Targeting Scheme on Tidal Volume Delivery During Volume Control Mechanical Ventilation

Technological advances have increased ventilator mode complexity and risk of operator error. To compare differences in volume control (VC) ventilation with set-point and dual targeting. Two hypotheses were tested: tidal volume (V(T)) delivery is different with VC using set-point versus dual targeting during active versus passive breathing; VC with dual targeting delivers V(T) similar to pressure support ventilation (PS) with active breathing. The Ingmar Medical ASL 5000 lung model simulated pulmonary mechanics of an adult patient with ARDS during active and passive ventilation. Resistance was standardized at 10 cm H(2)O/L/s and compliance at 32 mL/cm H(2)O. Active breathing was simulated by setting the frequency (f) = 26 breaths/min, and adjusting the muscle pressure (P(mus)) to produce a V(T) of 384 mL. VC was initiated with the Puritan Bennett 840 (set-point targeting) and the Servo-i (dual targeting) at V(T) = 430 mL, mandatory f = 15 breaths/min, and PEEP = 10 cm H(2)O. During PS, cycle threshold was set to 30% and peak inspiratory pressure adjusted to produce a V(T) similar to that delivered during VC. Expiratory V(T) was collected on 10 consecutive breaths during active and passive breathing with VC and PS. Mean V(T) differences (active vs passive model) were compared using analysis of variance. Statistical significance was established at P < .05. The mean ± SD V(T) difference varied with targeting schemes: VC set-point = 37.3 ± 3.5 mL, VC-dual = 77.1 ± 3.3 mL, and PS = 406.1 ± 1.5 mL (P < .001). Auto-triggering occurred during VC set-point with the active model. Dual targeting during VC allows increased V(T), compared to set-point, but not as much as PS.

Interactions between Behaviorally Relevant Rhythms and Synaptic Plasticity Alter Coding in the Piriform Cortex

Understanding how neural and behavioral timescales interact to influence cortical activity and stimulus coding is an important issue in sensory neuroscience. In air-breathing animals, voluntary changes in respiratory frequency alter the temporal patterning olfactory input. In the olfactory bulb, these behavioral timescales are reflected in the temporal properties of mitral/tufted (M/T) cell spike trains. As the odor information contained in these spike trains is relayed from the bulb to the cortex, interactions between presynaptic spike timing and short-term synaptic plasticity dictate how stimulus features are represented in cortical spike trains. Here, we demonstrate how the timescales associated with respiratory frequency, spike timing, and short-term synaptic plasticity interact to shape cortical responses. Specifically, we quantified the timescales of short-term synaptic facilitation and depression at excitatory synapses between bulbar M/T cells and cortical neurons in slices of mouse olfactory cortex. We then used these results to generate simulated M/T population synaptic currents that were injected into real cortical neurons. M/T population inputs were modulated at frequencies consistent with passive respiration or active sniffing. We show how the differential recruitment of short-term plasticity at breathing versus sniffing frequencies alters cortical spike responses. For inputs at sniffing frequencies, cortical neurons linearly encoded increases in presynaptic firing rates with increased phase-locked, firing rates. In contrast, at passive breathing frequencies, cortical responses saturated with changes in presynaptic rate. Our results suggest that changes in respiratory behavior can gate the transfer of stimulus information between the olfactory bulb and cortex.

Use of a fully closed-loop ventilation mode in long-term ventilated ICU patients: a prospective study

IntelliVent-ASV® is a closed-loop ventilation mode that automatically adjusts ventilation and oxygenation settings in passive and active breathing patients. The minute volume is adjusted according to end-tidal CO2 (ETCO2) information in passive breathing patients (and respiratory rate in active breathing patients), and oxygenation is adjusted according to SpO2 information. This study reports the ventilation and oxygenation delivered by IntelliVent-ASV® in long-term ventilated ICU patients.