Breathing Conditions Research Articles

Markerless tracking of tumor and tissues: A motion model approach.

Respiratory motion management is essential in order to achieve high-precision radiotherapy. Markerless motion tracking of tumor can provide a non-invasive way to manage respiratory motion, thereby enhancing treatment accuracy. However, the low contrast in real-time x-ray images for image guidance limits the application of markerless tracking. We present a novel approach based on a motion model to perform markerless tracking of tumor and surrounding tissues even when they have low contrast in real-time x-ray images. A proof-of-concept validation of the method has been performed using digital and physical phantoms at breathing conditions that are significantly different than the planning stage. A motion model is first constructed by performing principal component analysis (PCA) on the planning 4DCT. During treatment, the motion of a surrogate is tracked and used as the input of the motion model, which generates a 3D real-time volume estimation. Such 3D estimation is then projected to 2D to create digitally reconstructed radiographs (DRRs). The relationships between the real-time DRRs, reference DRRs, and reference x-ray images are first established to simulate 2D real-time images from the real-time volume. The registration between the simulated 2D real-time images and real-time x-ray images corrects the initial motion model estimation to ensure the estimated volume matches the real-time condition. In digital phantom, the Dice index of pancreas was improved from 0.74 to 0.78 after correction using real-time DRRs in fully inhaled phase. Validation on lung and pancreas is performed in physical phantom with two motion traces. The surrogate-tumor relationships were intentionally altered to generate large target localization errors due to the differences in body condition between treatment planning stage and during treatment. The real-time correction for the estimated 3D real-time volume was performed using a pair of 2D x-ray images. For the deep breathing motion trace, the tumor localization mean absolute error (MAE) throughout the tracking decreases from around 3mm to less than 1mm after correction. For the shallow breathing motion trace with a 1.7mm baseline shift, the tumor localization MAE throughout the tracking decreases from around 1.5mm to less than 1mm after correction. The method combines the detailed structural information from planning 4DCT and real-time information from real-time x-ray images through a motion model. The matching between the real-time model estimation and 2D real-time images is performed in the same modality so that it can be applied to regions with low contrast in the images. The real-time images successfully corrected the initial motion model estimations in our proof-of-concept validation. This suggests the potential to perform markerless tracking in low-contrast region using a motion model.

Breathing modulates network activity in frontal brain regions during anxiety.

Anxiety elicits various physiological responses, including changes in respiratory rate and neuronal activity within specific brain regions such as the medial prefrontal cortex (mPFC). Previous research suggests that the olfactory bulb (OB) modulates the mPFC through respiration-coupled neuronal oscillations (RCOs), which have been linked to fear-related freezing behavior. Nevertheless, the impact of breathing on frontal brain networks during other negative emotional responses, such as anxiety-related states characterized by higher breathing rates, remains unclear. To address this, we subjected rats to the elevated plus maze (EPM) paradigm while simultaneously recording respiration and local field potentials in the OB and mPFC. Our findings demonstrate distinct respiratory patterns during EPM exploration: slower breathing frequencies prevailed in the closed arms, whereas faster frequencies were observed in the open arms, independent of locomotor activity, indicating that anxiety-like states are associated with increased respiratory rates. Additionally, we identified RCOs at different frequencies, mirroring the bimodal distribution of respiratory frequencies. RCOs exhibited higher power during open arm exploration, when they showed greater coherence with breathing at faster frequencies. Furthermore, we confirmed that nasal respiration drives RCOs in frontal brain regions, and found a stronger effect during faster breathing. Interestingly, we observed that the frequency of prefrontal gamma oscillations modulated by respiration increased with breathing frequency. Overall, our study provides evidence for a significant influence of breathing on prefrontal cortex networks during anxious states, shedding light on the complex interplay between respiratory physiology and emotional processing.Significance Statement Understanding how breathing influences brain activity during anxious states could pave the way for novel therapeutic interventions targeting respiratory control to alleviate anxiety symptoms. Our study uncovers a crucial link between respiratory patterns and anxiety-related neural activity in the brain. By investigating the interplay between breathing, neuronal oscillations, and emotional states, we reveal that anxiety induces distinct respiratory patterns, with higher breathing rates correlating with anxious behavior. Importantly, we demonstrate that respiration drives oscillatory activity in the prefrontal cortex, and this effect is potentiated during the fast breathing associated with anxiety. Furthermore, faster breathing modulates the emergence of faster prefrontal gamma oscillations. This discovery sheds new light on the intricate relationship between respiratory physiology and emotional processing.

Semi-automatic robotic puncture system based on deformable soft tissue point cloud registration.

Traditional surgical puncture robot systems based on computed tomography (CT) and infrared camera guidance have natural disadvantages for puncture of deformable soft tissues such as the liver. Liver movement and deformation caused by breathing are difficult to accurately assess and compensate by current technical solutions. We propose a semi-automatic robotic puncture system based on real-time ultrasound images to solve this problem. Real-time ultrasound images and their spatial position information can be obtained by robot in this system. By recognizing target tissue in these ultrasound images and using reconstruction algorithm, 3D real-time ultrasound tissue point cloud can be constructed. Point cloud of the target tissue in the CT image can be obtained by using developed software. Through the point cloud registration method based on feature points, two point clouds above are registered. The puncture target will be automatically positioned, then robot quickly carries the puncture guide mechanism to the puncture site and guides the puncture. It takes about just tens of seconds from the start of image acquisition to completion of needle insertion. Patient can be controlled by a ventilator to temporarily stop breathing, and patient's breathing state does not need to be the same as taking CT scan. The average operation time of 24 phantom experiments is 64.5 s, and the average error between the needle tip and the target point after puncture is 0.8mm. Two animal puncture surgeries were performed, and the results indicated that the puncture errors of these two experiments are 1.76mm and 1.81mm, respectively. Robot system can effectively carry out and implement liver tissue puncture surgery, and the success rate of phantom experiments and experiments is 100%. It also shows that the puncture robot system has high puncture accuracy, short operation time, and great clinical value.

Heart Rate Variability, Blood Pressure and Peripheral Oxygen Saturation during Yoga Adham and Mahat Breathing Techniques without Retention in Adult Practitioners.

Background: Heart rate variability (HRV) is the change in time intervals between heart beats, reflecting the autonomic nervous system's ability to adapt to psychological and physiological demands. Slow breathing enhances parasympathetic activity, increasing HRV. Pranayama, a yoga breathing technique, affords the conscious regulation of respiration frequency. This study aimed to characterize HRV, blood pressure and peripheral oxygen saturation of basic yoga breathing slow techniques with regular yoga practitioners. Methods: In total, 45 yoga practitioners were included in the study (including 7 males, mean age of 54.04 ± 11.97 years) with varying levels of yoga experience (minimum 3 months, maximum 37 years). Participants performed three breathing conditions: baseline (control) and two yoga techniques (abdominal (adham) and complete (mahat)) breathing, each for 10 min in the supine position (i.e., savasana). For each condition, respiratory frequency, heart rate (HR), blood pressure and peripheral oxygen levels were collected. Results: The findings revealed that both abdominal and complete yoga breathing techniques promoted a decrease in respiratory frequency (p < 0.001, r = 0.61; p < 0.001, r = 0.61, respectively), and an increase in peripheral oxygen saturation (p < 0.001, r = 0.50; p < 0.001, r = 0.46, respectively), along with blood pressure decreases in all mean values, and a significant decrease in systolic pressure, considering all conditions (p = 0.034, W = 0.08). There were significant increases in standard deviation of HR during abdominal and complete yoga breathing techniques compared with the baseline (p = 0.003, r = 0.31; p < 0.001, r = 0.47, respectively), indicating enhanced parasympathetic activity. Moreover, the complete breathing technique exhibited the greatest variability in HRV measures, with several significant differences compared with abdominal breathing (standard deviation of HR, p < 0.001, r = 0.42; SD2, standard deviation of points perpendicular to the Poincaré parallel line, p < 0.003, r = 0.31; SD1/SD2, p < 0.003, r = 0.31), suggesting a more profound impact on autonomic modulation. Conclusions: simple, inexpensive and non-intrusive abdominal and complete yoga breathing techniques can effectively and momentarily enhance HRV and oxygen saturation in adults, mature adults and the elderly.

PPG2RespNet: a deep learning model for respirational signal synthesis and monitoring from photoplethysmography (PPG) signal.

Breathing conditions affect a wide range of people, including those with respiratory issues like asthma and sleep apnea. Smartwatches with photoplethysmogram (PPG) sensors can monitor breathing. However, current methods have limitations due to manual parameter tuning and pre-defined features. To address this challenge, we propose the PPG2RespNet deep-learning framework. It draws inspiration from the UNet and UNet + + models. It uses three publicly available PPG datasets (VORTAL, BIDMC, Capnobase) to autonomously and efficiently extract respiratory signals. The datasets contain PPG data from different groups, such as intensive care unit patients, pediatric patients, and healthy subjects. Unlike conventional U-Net architectures, PPG2RespNet introduces layered skip connections, establishing hierarchical and dense connections for robust signal extraction. The bottleneck layer of the model is also modified to enhance the extraction of latent features. To evaluate PPG2RespNet's performance, we assessed its ability to reconstruct respiratory signals and estimate respiration rates. The model outperformed other models in signal-to-signal synthesis, achieving exceptional Pearson correlation coefficients (PCCs) with ground truth respiratory signals: 0.94 for BIDMC, 0.95 for VORTAL, and 0.96 for Capnobase. With mean absolute errors (MAE) of 0.69, 0.58, and 0.11 for the respective datasets, the model exhibited remarkable precision in estimating respiration rates. We used regression and Bland-Altman plots to analyze the predictions of the model in comparison to the ground truth. PPG2RespNet can thus obtain high-quality respiratory signals non-invasively, making it a valuable tool for calculating respiration rates.

Effect of sleep-disordered breathing on stable electroencephalographic characteristics during night sleep in patients with arterial hypertension

Introduction. Obstructive sleep apnea (OSA) is the most common sleep-disordered breathing condition. A significant number of OSA patients often present with cardiovascular comorbidities, particularly arterial hypertension. OSA is associated with changes in bioelectrical activity of the brain, such as slowing of electroencephalographic activity in the cortex and reduced interhemispheric synchronization. These changes can become pathophysiological markers of sleep-disordered breathing.Aim. To investigate the effect of sleep-disordered breathing on a range of quantitative electroencephalogram (EEG) characteristics during nighttime sleep in patients with arterial hypertension and clinically significant OSA.Materials and methods. The material for this retrospective study consisted of 84 polysomnographic records of patients predominantly diagnosed with arterial hypertension. Patients were divided into three groups based on the apneahypopnea index (AHI). Polysomnographic records were used to assess the synchronization measure of brain electrical activity between occipital EEG leads. The synchronization measure was evaluated using a method based on wavelet bicoherence calculation.Results. Statistically significant differences were observed in the low-frequency ranges Δf1-Δf4: 0.2-1.0 Hz, 0.8-1.6 Hz, 1.0-2.0 Hz, 1.0-4.0 Hz. In these frequencies, the interhemispheric synchronization measure significantly decreased with increasing severity of apnea.Conclusion. To determine the severity of obstructive sleep apnea, a parameter based on the synchronization measure evaluated from symmetrical occipital EEG signals in the frequency ranges 0.2-1.0 Hz, 0.8-1.6 Hz, 1.0-2.0 Hz, and 1.0-4.0 Hz can be considered. This may serve as the basis for developing and implementing new diagnostic tools for assessing the severity of sleep-disordered breathing in practice.

Insights into the fluid dynamics of bioaerosol formation in a model respiratory tract

Bioaerosols produced within the respiratory system play an important role in respiratory disease transmission. These include infectious diseases such as common cold, influenza, tuberculosis, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among several others. It is, therefore, of immense interest to understand how bioaerosols are produced within the respiratory system. This has not been extensively investigated. The present study computationally investigates how bioaerosols are produced in a model respiratory tract due to hydrodynamic interactions between breathed air and a thin mucus layer, which lines the inner surface of the tract. It is observed that Kelvin–Helmholtz instability is established in the thin mucus layer due to associated fluid dynamics. This induces interfacial surface waves which fragment forming bioaerosols under certain conditions. A regime map is created—based on pertinent dimensionless parameters—to enable identification of such conditions. Analysis indicates that bioaerosols may be produced even under normal breathing conditions, contrary to expectations, depending on mucus rheology and thickness of the mucus layer. This is possible during medical conditions as well as during some treatment protocols. However, such bioaerosols are observed to be larger (∼O(100)μm) and are produced in less numbers (∼100), as compared to those produced under coughing conditions. Treatment protocols and therapeutic strategies may be suitably devised based on these findings.

How Effective is Deep Inspiration Breath Hold in Minimizing Cardiac Doses During Hybrid Radiotherapy Treatment for Left-Sided Breast Cancer with Comprehensive Regional Nodes?

In the context of left breast cancer radiotherapy, long term cardiopulmonary toxicity has been well-documented, significant efforts have been undertaken to mitigate such toxicity by using 4D gating, deep inspiration breath-hold(DIBH) and active breath control(ABC) techniques. To evaluate and compare the cardio-pulmonary radiation doses incurred during postmastectomy radiotherapy (PMRT) in two distinct breathing conditions such as DIBH and Free Breathing (FB), with a specific focus on the left chest wall with comprehensive regional nodal irradiation. A prospective dosimetric study was conducted on 15 patients who received adjuvant loco-regional radiotherapy of chest-wall (CW), supraclavicular fossa(SCF), and internal mammary region(IMC), with or without axilla. Two sets of planning CT scans were taken in DIBH and FB conditions. The dosimetric difference between DIBH CT and FB CT plans analyzed using Wilcoxon signed-rank test, employing SPSS software version 21.0. Comparison of DIBH and FB parameters for target coverage revealed a statistically significant advantage with DIBH in SCF(D95, V90, p<0.017) and IMC(D98, V90 & V95, p<0.03). Dosimetric characteristics of heart and LAD exhibited statistically significant lower doses with DIBH (V20, V25, and Dmean, p<0.001) compared to FB plans. Lung doses were similar with no discernible advantage of one technique over the other. Other OARs such as contralateral breast (p=0.027) and esophagus (p=0.001) received lower doses with the DIBH technique while the spinal cord (p=0.691) and thyroid(p=0.496) showed no significant difference. Maximum heart distance (p= 0.001), central lung distance (p= 0.011) and Haller index (p= 0.001) exhibited statistical significance between the two techniques, whereas chest wall separation showed no significant statistical difference (p=0.629). DIBH demonstrates a substantial reduction in cardiac and LAD doses compared to the FB technique. This study underscores the efficacy of DIBH as a viable strategy for mitigating cardiac and LAD radiation doses in left-sided breast cancer patients undergoing PMRT of chest wall with comprehensive regional nodes.

Dynamic oxygen assessment techniques enable determination of anesthesia's impact on tissue.

Tissue oxygenation is well understood to impact radiosensitivity, with reports demonstrating a significant effect of breathing condition and anesthesia type on tissue oxygenation levels and radiobiological response. However, the temporal kinetics of intracellular and extracellular oxygenation have never been quantified, on the timescale that may affect radiotherapy studies. C57BL/6 mice were anesthetized using isoflurane at various percentages or ketamine/xylazine (ket/xyl: 100/10 mg/kg) (N = 48). Skin pO2 was measured using Oxyphor PdG4 and tracked after anesthetization began. Oxyphor data was validated with relative measurements of intracellular oxygen via protoporphyrin IX (PpIX) delayed fluorescence (DF) imaging. Ex vivo localization of both PdG4 Oxyphor and PpIX were quantified. Under all isoflurane anesthesia conditions, leg skin pO2 levels significantly increased from 12-15 mmHg at the start of anesthesia induction (4-6 minutes) to 24-27 mmHg after 10 minutes (p < 0.05). Ketamine/xylazine anesthesia led to skin pO2 maintained at 15-16 mmHg throughout the 10-minute study period (p < 0.01). An increase of pO2 in mice breathing isoflurane was demonstrated with Oxyphor and PpIX DF, indicating similar intracellular and extracellular oxygenation. These findings demonstrate the importance of routine anesthesia administration, where consistency in the timing between induction and irradiation may be crucial to minimizing variability in radiation response.

Au – MoS2 nanoflowers sensors on interdigitated electrode for monitoring human respiration

Abstract Respiratory humidity sensors are essential for monitoring breath conditions in a variety of applications such as respiratory disease diagnosis, sleep apnea screening, and personalized medicine. With the increasing prevalence of respiratory diseases, such as asthma, chronic obstructive pulmonary disease (COPD), and sleep apnea, they have become essential tools for healthcare professionals, researchers and individuals. However, existing humidity sensors often suffer from poor sensitivity, slow response, and limited flexibility. In this paper, we report a novel Au – MoS2 respiratory humidity sensor that exhibits high resistivity, fast response, and excellent flexibility. The sensor is fabricated by drop casting a thin layer of Au decorated MoS2 on copper interdigitated electrodes (fabricated using copper clad PCB). The increase in the intensity of the peak was observed in Au – MoS2 hybrids in comparison to MoS2 analyzed using micro–Raman Spectroscopy. Using scanning electron microscopy (SEM), the morphology of MoS2 was observed, confirming its flower like structure. The Au nanoparticles were detected on the edges of MoS2, confirmed by transmission electron microscope (TEM).&amp;#xD;The interfacial electronic interaction suggests that there is the formation of Schottky barrier between Au and MoS2 as confirmed by X–Ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS). The improved electronic interaction results in better sensing properties. The high dielectric constant and excellent surface-to-volume ratio of the MoS2 layer make it extremely sensitive to humidity; the Au nanoparticles offer good electrical conductivity and mechanical flexibility in its place. The study tested a respiratory sensor in a simulated environment, finding it more responsive to breathing and quick to return to rest. This suggests potential for the Au-MoS2 sensor in tracking breath states due to its sensitivity and adaptability, promising applications across various fields.&amp;#xD;

Lignin Nanosphere‐Modified MXene Activated‐Rapid Gelation of Mechanically Robust, Environmental Adaptive, Highly Conductive Hydrogel for Wearable Sensors Application

AbstractAdvanced conductive hydrogels demonstrate substantial potential for wearable devices. Nevertheless, the transformative advance in soft electronics raises harsh requirements on the hydrogel candidates, such as rapid and on‐site fabrication, mechanical flexibility, high sensitivity, and wide use temperature. Here, this problem is overcome by incorporating a dual catalytic system based on lignin‐modified MXene‐Fe3+ into commercial hydrogels. This system 1) can form a composite hydrogel in a time scale of min at ambient condition without the supply of external energy, 2) incorporates multiple enhanced strategies into polymer chains, and 3) constructs well‐organized hybrid conductive network. The fabricated hydrogel displays an improved and balanced overall performance, including high ductility (2139%), moderate electrical conductivity, and strong temperature tolerance (−70–50 °C). Combined with the great merits of above performance, the hydrogel‐based sensor with good sensing (maximum GF: 2.8), stable repeatability (200% for 200 cycles), and wide work window of 0%–947%, thereby disclosing promising application in physiological movements, such as motion recognition and breathing state detection. Sensationally, even in complex or harsh surroundings, the sensors also produce stable and reliable signal output. Together, the strategy provides a new mentality of designing hydrogel materials for booming and advanced wearable electronics.

Unraveling the temporal interplay of slow-paced breathing and prefrontal transcranial direct current stimulation on cardiac indices of autonomic activity.

The neurovisceral integration model proposes that information flows bidirectionally between the brain and the heart via the vagus nerve, indexed by vagally mediated heart rate variability (vmHRV). Voluntary reduction in breathing rate (slow-paced breathing, SPB, 5.5 Breathing Per Minute (BPM)) can enhance vmHRV. Additionally, prefrontal transcranial direct current stimulation (tDCS) can modulate the excitability of the prefrontal region and influence the vagus nerve. However, research on the combination of SPB and prefrontal tDCS to increase vmHRV and other cardiac (heart rate (HR) and blood pressure) and peripheral (skin conductance) indices is scarce. We hypothesized that the combination of 20 min of SPB and prefrontal tDCS would have a greater effect than each intervention in isolation. Hence, 200 participants were divided into four groups: active tDCS with SPB, active tDCS with 15 BPM breathing, sham tDCS with SPB, and sham tDCS with 15 BPM breathing. Regardless of the tDCS condition, the 5.5 BPM group showed a significant increase in vmHRV over 20 minutes and significant decreases in HR at the first and second 5-min epochs of the intervention. Regardless of breathing condition, the active tDCS group exhibited higher HR at the fourth 5-min epoch of the intervention than the sham tDCS group. No other effects were observed. Overall, SPB is a robust technique for increasing vmHRV, whereas prefrontal tDCS may produce effects that counteract those of SPB. More research is necessary to test whether and how SPB and neuromodulation approaches can be combined to improve cardiac vagal tone.

REM sleep breathing: Insights beyond conventional respiratory metrics.

Breathing and sleep state are tightly linked. The traditional approach to evaluation of breathing in rapid eye movement sleep has been to focus on apneas and hypopneas, and associated hypoxia or hypercapnia. However, rapid eye movement sleep breathing offers novel insights into sleep physiology and pathology, secondary to complex interactions of rapid eye movement state and cardiorespiratory biology. In this review, morphological analysis of clinical polysomnogram data to assess respiratory patterns and associations across a range of health and disease is presented. There are several relatively unique insights that may be evident by assessment of breathing during rapid eye movement sleep. These include the original discovery of rapid eye movement sleep and scoring of neonatal sleep, control of breathing in rapid eye movement sleep, rapid eye movement sleep homeostasis, sleep apnea endotyping and pharmacotherapy, rapid eye movement sleep stability, non-electroencephalogram sleep staging, influences on cataplexy, mimics of rapid eye movement behaviour disorder, a reflection of autonomic health, and insights into cardiac arrhythmogenesis. In summary, there is rich clinically actionable information beyond sleep apnea encoded in the respiratory patterns of rapid eye movement sleep.

The effect of different breathing conditions on cerebral blood flow in young males during maximal aerobic exercise: A pilot study

BackgroundDuring aerobic exercise, cerebral blood flow (CBF) decreases past 70 % of maximal oxygen uptake (VO2), but transient hypercapnia could mitigate the reduction. AimsTo examine the effect of oral (OB), nasal (NB), and combined (CB) breathing on CBF during a graded maximal exercise test (GXT). MethodsSix young males (age: 21.8 ± 2.3 years) performed three GXTs until volitional fatigue using a randomized breathing condition (OB, NB, or CB) order. Respiratory gases were assessed via a metabolic cart. Ultrasound sonography (7.5 MHz linear transducer) was utilized to assess the peak systolic velocity (PSV), end-diastolic velocity (EDV), and vessel diameter of the internal (ICA) and external (ECA) carotid artery. A one-way ANCOVA, with VO2 as a covariate, followed by a Bonferroni post-hoc analysis, was utilized to examine the differences between the breathing conditions. ResultsThe end-tidal partial pressure of CO2 (PetCO2) was significantly greater (p = 0.006) during NB (33.16 ± 1.37 mmHg) than that of CB (26.63 ± 1.32 mmHg) and OB (26.72 ± 1.37) at 100 % VO2max. There was a trend of a greater PSV in the ICA throughout the entire GXT that was only significantly greater (p = 0.027) during NB (126.12 ± 7.51 cm/s) compared to OB (92.47 ± 7.34 cm/s) but not CB (111.91 ± 7.14 cm/s) at 70 % VO2max. ConclusionsDuring a GXT, NB demonstrated a superior capacity to increase CBF, denoted by a higher PSV in the ICA compared to CB and OB, which might be partly related to an increased PetCO2.

Three-dimensional geometric morphometric shape analysis of chest wall kinematics in different breathing conditions.

Breathing motion is based on the differential activity of the thoracic, diaphragmatic and abdominal muscles. Muscle contributions differ between rest and exercise conditions and depend on posture and other factors. Traditionally, these changes are investigated on volumetric data using optoelectronic plethysmography (OEP). OEP offers insight into size variations of different chest wall (CW) compartments but does not provide three-dimensional visualization methods of CW breathing kinematics. Here we explore the use of three-dimensional geometric morphometrics to analyse size and shape changes caused by spontaneous breathing motion during quiet (QB), and recovery breathing (REC, immediately after heavy exercise) in two different postures (SIT, sitting on cycle ergometer; STA, standing position). Our findings show that size and shape differ significantly between inspiration and expiration and that differences are greater in REC than in QB. However, this is achieved by stronger expiration in SIT but by greater expiratory and inspiratory movements in STA. Shape analysis suggests that these differences may be attributed to constrained mobility of the shoulder girdle and a minor thoracic spine extension during inspiration owing to position on the ergometer. Breathing motion in STA seems biomechanically less constrained. Geometric morphometrics analyses can provide additional insights into data obtained by OEP.

Apnea or normal breathing during repeated high-intensity swimming enhance sprint efficiency and which metabolic disorder?

The aim of this study was to investigate the effect of normal breath and apnea swimming on acid-base balance, physiological responses and performance during high-intensity interval training in swimming. Sixteen swimmers completed 6×50 m intervals of freestyle swimming with normal breath and apnea at maximum intensity, with 1 minute rest. Capillary blood gases (pH, PCO<inf>2</inf>, PO<inf>2</inf>, HCO<inf>3</inf>, Hct, Hb) were collected at four (4) measurement time points: 1) at rest once; 2) at rest just after the 3rd repetition; 3) at finish; and 4) at 10 min of recovery. Heart rate (HR) during swimming, lactate acid (La) concentration and swimming time (t<inf>50</inf>) were measured. Our study showed uncompensated metabolic acidosis due to increased lactic acidosis in both breathing conditions, more pronounced in apnea, and faster swimming times in apnea without different heart rate responses. Apnea during repetitive high intensity long distance interval 50 m freestyle swimming causes uncompensated metabolic acidosis but improves sprint performance.

Association of Obstructive Sleep Apnea with Nonalcoholic Fatty Liver Disease: Evidence, Mechanism, and Treatment.

Obstructive sleep apnea (OSA), a common sleep-disordered breathing condition, is characterized by intermittent hypoxia (IH) and sleep fragmentation and has been implicated in the pathogenesis and severity of nonalcoholic fatty liver disease (NAFLD). Abnormal molecular changes mediated by IH, such as high expression of hypoxia-inducible factors, are reportedly involved in abnormal pathophysiological states, including insulin resistance, abnormal lipid metabolism, cell death, and inflammation, which mediate the development of NAFLD. However, the relationship between IH and NAFLD remains to be fully elucidated. In this review, we discuss the clinical correlation between OSA and NAFLD, focusing on the molecular mechanisms of IH in NAFLD progression. We meticulously summarize clinical studies evaluating the therapeutic efficacy of continuous positive airway pressure treatment for NAFLD in OSA. Additionally, we compile potential molecular biomarkers for the co-occurrence of OSA and NAFLD. Finally, we discuss the current research progress and challenges in the field of OSA and NAFLD and propose future directions and prospects.

Tactile breathing guidance increases oxygen saturation but not alertness or hypoxia symptoms.

We investigated the effect of tactile guided slow deep breathing compared with that of spontaneous breathing on blood oxygen saturation (SpO2), alertness, and hypoxia symptoms during acute hypobaric hypoxia. We also evaluated the usability of this tactile breathing guidance. Twelve male military pilots were exposed to a simulated altitude of 4,572 m (15,000 ft) in a repeated measures study while breathing spontaneously and during tactile guided slow deep breathing. Under both breathing conditions, measurements were performed at rest and during the performance of a cognitive task. The Stanford Sleepiness Scale was used to rate alertness, and hypoxia symptoms were reported using a list of general hypoxia symptoms. Usability was evaluated in a questionnaire. Tactile guidance of slow deep breathing significantly increased (p <.001) the SpO2 - 88% (95% confidence interval (CI) [84%, 91%]) at rest and 85% (95% CI [81%, 88%]) during the cognitive task - compared with spontaneous breathing - 78% (95% CI [75%, 81%]) at rest and 78% (95% CI [76%, 80%]) during the cognitive task. This increase in SpO2 had no effect on the level of alertness and number of hypoxia symptoms. Pilots were positive about the intensity and sensation of the vibration signal, but had difficulty following the vibration pattern during the cognitive task. Pre-training may improve slow deep breathing technique during performance of cognitive tasks.

Is the mouse nose a miniature version of a rat nose? A computational comparative study

Background and objectiveAlthough the mouse is a widely used animal model in biomedical research, there are few published studies on its nasal aerodynamics, potentially due to its small size. It is not appropriate to assume that mice and rats' nasal structure and airflow characteristics are the same because the ratio of nasal surface area to nasal volume and body weight is much higher in a mouse than in a rat. The aim of this work is to use anatomically accurate image-based computational fluid dynamic modeling to quantitatively reveal the characteristics of mouse nasal airflow and mass transport that haven't been detailed before and find key differences to that of rat nose, which will deepen our understanding of the mouse's physiological functions. MethodsWe created an anatomically accurate 3D computational nasal model of a B6 mouse using postmortem high-resolution micro-CT scans and simulated the airflow distribution and odor transport patterns under restful breathing conditions. The deposition pattern of airborne particles was also simulated and validated against experimental data. In addition, we calculated the gas chromatograph efficiency of odor transport in the mouse employing the theoretical plate concept and compared it with previous studies involving cat and rat models. ResultsSimilar to the published rat model, respiratory and olfactory flow regimes are clearly separated in the mouse nasal cavity. A high-speed dorsal medial (DM) stream was observed, which enhances the delivery speed and efficiency of odor to the ethmoid (olfactory) recess (ER). The DM stream split into axial and secondary paths in the ER. However, the secondary flow in the mouse is less extensive than in the rat. The gas chromatograph efficiency calculations suggest that the rat may possess a moderately higher odorant transport efficiency than that of the mouse due to its more complex ethmoid recess structure and extensive secondary flow. However, the mouse's nasal structure seems to adapt better to varying airflow velocity. ConclusionsDue to the inherent structural disparities, the rat and mouse models exhibit moderate differences in airflow and mass transport patterns, potentially impacting their olfaction and other behavioral habits.

A comprehensive evaluation of linear and non-linear HRV parameters between paced breathing and stressful mental state

BackgroundHeart rate variability (HRV) is a crucial metric that provides valuable insight into the balance between relaxation and stress. Previous research has shown that most HRV parameters improve during periods of mental relaxation, while decreasing during tasks involving cognitive workload. Although a comprehensive analysis of both linear and non-linear HRV parameters has been carried out in existing literature, there still exists a need for further research in this area. Additionally, limited knowledge exists regarding how specific interventions may influence the interpretation of these parameters and how the different parameters correlate under different interventions. This study aims to address these gaps by conducting a thorough comparison of different linear and non-linear HRV parameters under mentally relaxed versus stressful states. MethodologyParticipants were randomly and equally divided among two between-subjects groups: relaxed-stress (RS) (N = 22) and stress-relaxed (SR) (N = 22). In the RS group, a paced breathing task was given for 5 min to create relaxation, and was followed by a 5-min time-based mental calculation task to create stress. In the SR group, the order of the stress and relaxed tasks was reversed. There was a washout period of 15 min after the first task in both groups. ResultsOf the 37 HRV parameters, 33 differed significantly between the two interventions. The majority of the parameters exhibited an improving and degrading tendency of HRV parameters in the relaxed and stressed states, respectively. The correlation of the majority of HRV parameters decreases during stress, while prominent time domain and geometric domain parameters stand out in the correlation. ConclusionOverall, HRV parameters can be reliably used to assess a person's relaxed and stressed mental states during paced breathing and mental arithmetic task respectively. Furthermore, non-linear HRV parameters provide accurate estimators of the mental state, in addition to the commonly used linear parameters.