Publications

A fundamental task of the respiratory system is to operate as a mechanical gas pump ensuring that fresh air gets in close contact with the blood circulating through the lung capillaries to achieve O2 and CO2 exchange. To ventilate the lungs, the respiratory muscles provide the pressure required to overcome the viscoelastic mechanical load of the respiratory system. From a mechanical viewpoint, the most relevant respiratory system properties are the resistance of the airways (R aw), and the compliance of the lung tissue (C L) and chest wall (C CW). Both airflow and lung volume changes in spontaneous breathing and mechanical ventilation are determined by applying the fundamental mechanical laws to the relationships between the pressures inside the respiratory system (at the airway opening, alveolar, pleural, and muscular) and R aw, C L, and C CW. These relationships also are the basis of the different methods available to measure respiratory mechanics during spontaneous and artificial ventilation. Whereas a simple mechanical model (R aw, C L, and C CW) describes the basic understanding of ventilation mechanics, more complex concepts (nonlinearity, inhomogeneous ventilation, or viscoelasticity) should be employed to better describe and measure ventilation mechanics in patients.Thieme. All rights reserved.

JTD Keywords: airway-resistance, alveolar, compliance, dilution, elastance, flow, inhomogeneous ventilation, input impedance, lung-volume, mechanical ventilation, monitoring, pendelluft, pleural pressure, respiratory-distress-syndrome, viscoelasticity, Chest-wall mechanics, Resistance

Breathing pattern has been shown to be different in chronic obstructive pulmonary disease (COPD) patients compared to healthy controls during rest and walking. In this study we evaluated respiratory parameters and the breathing variability of COPD patients as a function of their severity. Thoracic bioimpedance was acquired on 66 COPD patients during the performance of the six-minute walk test (6MWT), as well as 5 minutes before and after the test while the patients were seated, i.e. resting and recovery phases. The patients were classified by their level of airflow limitation into moderate and severe groups. We characterized the breathing patterns by evaluating common respiratory parameters using only wearable bioimpedance. Specifically, we computed the median and the coefficient of variation of the parameters during the three phases of the protocol, and evaluated the statistical differences between the two COPD severity groups. We observed significant differences between the COPD severity groups only during the sitting phases, whereas the behavior during the 6MWT was similar. Particularly, we observed an inverse relationship between breathing pattern variability and COPD severity, which may indicate that the most severely diseased patients had a more restricted breathing compared to the moderate patients.

JTD Keywords: 6mwt, activation, breathing pattern, burden, chronic obstructive pulmonary disease, exercise, muscles, pressure, pulmonary, signals, variability, volumes, wearables, Bioimpedance, Impedance pneumography

Assessing tidal volume during mechanical ventilation is critical to improving gas exchange while avoiding ventilator-induced lung injury. Conventional flow and volume measurements are usually carried out by built-in pneumotachographs in the ventilator or by stand-alone flowmeters. Such flow/volume measurement devices are expensive and thus usually unaffordable in low-resource settings. Here, we aimed to design and test low-cost and technically-simple calibration and assembly pneumotachographs. The proposed pneumotachographs are made by manual perforation of a plate with a domestic drill. Their pressure-volume relationship is characterized by a quadratic equation with parameters that can be tailored by the number and diameter of the perforations. We show that the calibration parameters of the pneumotachographs can be measured through two maneuvers with a conventional resuscitation bag and by assessing the maneuver volumes with a cheap and straightforward water displacement setting. We assessed the performance of the simplified low-cost pneumotachographs to measure flow/volume during mechanical ventilation as carried out under typical conditions in low-resource settings, i.e., lacking gold standard expensive devices. Under realistic mechanical ventilation settings (pressure- and volume-control; 200-600 mL), inspiratory tidal volume was accurately measured (errors of 2.1% on average and <4% in the worst case). In conclusion, a simple, low-cost procedure facilitates the construction of affordable and accurate pneumotachographs for monitoring mechanical ventilation in low- and middle-income countries.

JTD Keywords: calibration, flow measurement, low- and middle-income countries, mechanical ventilation, pneumotachograph, Calibration, Flow, Flow measurement, Low- and middle-income countries, Lung injury, Mechanical ventilation, Pneumotachograph, Pressure-drop, Resistance, Tidal volume

This study explored the use of parasternal second intercostal space and lower intercostal space surface electromyogram (sEMG) and surface mechanomyogram (sMMG) recordings (sEMGpara and sMMGpara, and sEMGlic and sMMGlic, respectively) to assess neural respiratory drive (NRD), neuromechanical (NMC) and neuroventilatory (NVC) coupling, and mechanical efficiency (MEff) noninvasively in healthy subjects and chronic obstructive pulmonary disease (COPD) patients. sEMGpara, sMMGpara, sEMGlic, sMMGlic, mouth pressure (Pmo), and volume (Vi) were measured at rest, and during an inspiratory loading protocol, in 16 COPD patients (8 moderate and 8 severe) and 9 healthy subjects. Myographic signals were analyzed using fixed sample entropy and normalized to their largest values (fSEsEMGpara%max, fSEsMMGpara%max, fSEsEMGlic%max, and fSEsMMGlic%max). fSEsMMGpara%max, fSEsEMGpara%max, and fSEsEMGlic%max were significantly higher in COPD than in healthy participants at rest. Parasternal intercostal muscle NMC was significantly higher in healthy than in COPD participants at rest, but not during threshold loading. Pmo-derived NMC and MEff ratios were lower in severe patients than in mild patients or healthy subjects during threshold loading, but differences were not consistently significant. During resting breathing and threshold loading, Vi-derived NVC and MEff ratios were significantly lower in severe patients than in mild patients or healthy subjects. sMMG is a potential noninvasive alternative to sEMG for assessing NRD in COPD. The ratios of Pmo and Vi to sMMG and sEMG measurements provide wholly noninvasive NMC, NVC, and MEff indices that are sensitive to impaired respiratory mechanics in COPD and are therefore of potential value to assess disease severity in clinical practice. Author

JTD Keywords: biomedical measurement, chronic obstructive pulmonary disease, couplings, diaphragm, disease severity, efficiency, electromyography, exacerbations, healthy volunteers, inspiratory muscles, loading, mechanomyography, obstructive pulmonary-disease, pressure measurement, protocols, respiratory mechanics, respiratory muscles, responsiveness, spirometry, stimulation, volume measurement, At rests, Biomedical measurement, Biomedical measurements, Chronic obstructive pulmonary disease, Couplings, Disease severity, Efficiency ratio, Electromyography, Healthy subjects, Healthy volunteers, Loading, Mechanical efficiency, Mechanomyogram, Muscle, Muscles, Neural respiratory drive, Noninvasive medical procedures, Pressure measurement, Protocols, Pulmonary diseases, Surface electromyogram, Volume measurement

The impact of diet and digestive disorders in flatus composition remains largely unexplored. This is partially due to the lack of standardized sampling collection methods, and the easy atmospheric contamination. This paper describes a method to quantitatively determine the major gases in flatus and their application in a nutritional intervention. We describe how to direct sample flatus into Tedlar bags, and simultaneous analysis by gas chromatography–thermal conductivity detection (GC–TCD). Results are analyzed by univariate hypothesis testing and by multilevel principal component analysis. The reported methodology allows simultaneous determination of the five major gases with root mean measurement errors of 0.8% for oxygen (O2), 0.9% for nitrogen (N2), 0.14% for carbon dioxide (CO2), 0.11% for methane (CH4), and 0.26% for hydrogen (H2). The atmospheric contamination was limited to 0.86 (95% CI: [0.7–1.0])% for oxygen and 3.4 (95% CI: [1.4–5.3])% for nitrogen. As an illustration, the method has been successfully applied to measure the response to a nutritional intervention in a reduced crossover study in healthy subjects. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

JTD Keywords: breath, colonic microbiota, diet effect on flatus, disorders, evacuation, excretion, flatulence, hydrogen gas, major flatus gas components, multilevel principal component analysis, rectal gas collection, systems, volume, Atmospheric contamination, Carbon dioxide, Conductivity detection, Diet effect on flatus, Gas chromatography, Gas collections, Gas component, Gases, Major flatus gas component, Major flatus gas components, Multilevel principal component analyse, Multilevel principal component analysis, Multilevels, Nitrogen, Nutrition, Oxygen, Principal component analysis, Principal-component analysis, Rectal gas collection, Volatile organic-compounds

Objectives This study aimed to compare the performance of a xenograft (XG) and a biomimetic synthetic graft (SG) in three-wall alveolar defects in minipigs by means of 3D computerised tomography and histology. Materials and methods Eight minipigs were used. A total of eight defects were created in the jaw of each animal, three of which were grafted with XGs, three with SGs, and two were left empty as a negative control. The allocation of the different grafts was randomised. Four animals were euthanised at 6 weeks and four at 12 weeks. The grafted volume was then measured by spiral computed tomography to assess volume preservation. Additionally, a histological analysis was performed in undecalcified samples by backscattered scanning electron microscopy and optical microscopy after Masson's trichrome staining. Results A linear mixed-effects model was applied considering four fixed factors (bone graft type, regeneration time, anatomic position, and maxilla/mandible) and one random factor (animal). The SG exhibited significantly larger grafted volume (19%) than the XG. The anterior sites preserved better the grafted volume than the posterior ones. Finally, regeneration time had a positive effect on the grafted volume. Histological observations revealed excellent osseointegration and osteoconductive properties for both biomaterials. Some concavities found in the spheroidal morphologies of SGs were associated with osteoclastic resorption. Conclusions Both biomaterials met the requirements for bone grafting, i.e. biocompatibility, osseointegration, and osteoconduction. Granule morphology was identified as an important factor to ensure a good volume preservation.

JTD Keywords: bone graft, bone regeneration, in vivo, miniature swine, synthetic graft, 3-dimensional changes, Anorganic bovine bone, Autogenous bone, Bio-oss, Biomaterials, Bone graft, Bone regeneration, Calcium-phosphate, Hydroxyapatite, In vivo, Miniature swine, Sinus floor augmentation, Substitute, Synthetic graft, Volume, Xenograft

One of the most challenging problems in intensive care is still the process of discontinuing mechanical ventilation, called weaning process. Both an unnecessary delay in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we analyzed respiratory pattern variability using the respiratory volume signal of patients submitted to two different levels of pressure support ventilation (PSV), prior to withdrawal of the mechanical ventilation. In order to characterize the respiratory pattern, we analyzed the following time series: inspiratory time, expiratory time, breath duration, tidal volume, fractional inspiratory time, mean inspiratory flow and rapid shallow breathing. Several autoregressive modeling techniques were considered: autoregressive models (AR), autoregressive moving average models (ARMA), and autoregressive models with exogenous input (ARX). The following classification methods were used: logistic regression (LR), linear discriminant analysis (LDA) and support vector machines (SVM). 20 patients on weaning trials from mechanical ventilation were analyzed. The patients, submitted to two different levels of PSV, were classified as low PSV and high PSV. The variability of the respiratory patterns of these patients were analyzed. The most relevant parameters were extracted using the classifiers methods. The best results were obtained with the interquartile range and the final prediction errors of AR, ARMA and ARX models. An accuracy of 95% (93% sensitivity and 90% specificity) was obtained when the interquartile range of the expiratory time and the breath duration time series were used a LDA model. All classifiers showed a good compromise between sensitivity and specificity.

JTD Keywords: autoregressive moving average processes, feature extraction, medical signal processing, patient care, pneumodynamics, signal classification, support vector machines, time series, ARX, autoregressive modeling techniques, autoregressive models with exogenous input, autoregressive moving average model, breath duration time series, classification method, classifier method, discontinuing mechanical ventilation, expiratory time, feature extraction, final prediction errors, fractional inspiratory time, intensive care, interquartile range, linear discriminant analysis, logistic regression analysis, mean inspiratory flow, patient respiratory volume signal, pressure support level, pressure support ventilation, rapid shallow breathing, respiratory pattern variability characterization, support vector machines, tidal volume, weaning trial, Analytical models, Autoregressive processes, Biological system modeling, Estimation, Support vector machines, Time series analysis, Ventilation

Weaning trials process of patients in intensive care units is a complex clinical procedure. 153 patients under extubation process (T-tube test) were studied: 94 patients with successful trials (group S), 38 patients who failed to maintain spontaneous breathing and were reconnected (group F), and 21 patients with successful test but that had to be reintubated before 48 hours (group R). The respiratory pattern of each patient was characterized through the following time series: inspiratory time (T_I), expiratory time (T_E), breathing cycle duration (T_Tot), tidal volume (V_T), inspiratory fraction (T_I/T_Tot), half inspired flow (V_T/T_I), and rapid shallow index (f/V_T), where f is respiratory rate. Using techniques as autoregressive models (AR), autoregressive moving average models (ARMA) and autoregressive models with exogenous input (ARX), the most relevant parameters of the respiratory pattern were obtained. We proposed the evaluation of these parameters using classifiers as logistic regression (LR), linear discriminant analysis (LDA), support vector machines (SVM) and classification and regression tree (CART) to discriminate between patients from groups S, F and R. An accuracy of 93% (98% sensitivity and 82% specificity) has been obtained using CART classification.

JTD Keywords: Accuracy, Indexes, Logistics, Regression tree analysis, Support vector machines, Time series analysis, Autoregressive moving average processes, Medical signal processing, Pattern classification, Pneumodynamics, Regression analysis, Sensitivity, Signal classification, Support vector machines, Time series, SVM, T-tube testing, Autoregressive models-with-exogenous input, Autoregressive moving average models, Breathing cycle duration, Classification-and-regression tree, Expiratory time, Extubation process, Half inspired flow, Inspiratory fraction, Inspiratory time, Intensive care units, Linear discriminant analysis, Logistic regression, Rapid shallow index, Respiratory pattern parameter performance, Sensitivity, Spontaneous breathing, Support vector machines, Tidal volume, Time 48 hr, Time series, Weaning process classifiers

High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1_st and 2_nd ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO₂ and periodic breathing cycles significantly increased with acclimatization (p-value <; 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO₂, through a significant negative correlation (p-value <; 0.01). Higher Pm is observed at climbing periods visually labeled as PB with >; 5 periodic breathing cycles through a significant positive correlation (p-value <; 0.01). Our data demonstrate that quantification of the respiratory volum- signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.

JTD Keywords: Frequency domain analysis, Frequency modulation, Heart, Sleep apnea, Ventilation, Visualization, Cardiology, Medical disorders, Medical signal processing, Plethysmography, Pneumodynamics, Sensitivity analysis, Sleep, Spectral analysis, Cheyne-Stokes respiration, Climbing periods, Dataset, Heart failure patients, High altitude PB, High altitude periodic breathing, Hypobaric hypoxia, Linear discriminant analysis, Pathophysiologic aspects, Physical activity, Physiologic mechanisms, Power spectral density, Receiver operating characteristic curve, Respiratory control, Respiratory frequency, Respiratory inductive plethysmography, Respiratory pattern, Respiratory volume signal, Sleep apnea, Spectral analysis, Spectral parameters

Near-field optical microscopy is a technique not limited by the laws of diffraction that enables simultaneous high-resolution fluorescence and topographic measurements at the nanometer scale. This chapter highlights the intrinsic advantages of near-field optics in the study of cellular structures. The first part of the chapter lays the foundations of the near-field concept and technical implementation of near-field scanning optical microscopy (NSOM), whereas the second part of the chapter focuses on applications of NSOM to the study of model membranes and cellular structures on the plasma membrane. The last part of the chapter discusses further directions of near-field optics, including optical antennas and fluorescence correlation spectroscopy approaches in the near-field regime.

JTD Keywords: Biological membranes, Cell membrane nanoscale compartmentalization, Cellular nanodomains, Fluorescence correlation spectroscopy in reduced volumes, Immunoreceptor imaging, Lipid rafts, Near-field scanning optical microscopy, Optical nano-antennas, Shear force imaging, Single molecule detection, Super-resolution microscopy

A new method for obtaining a three-dimensional volumetric reconstruction from a set of views improving the classical Shape from Silhouette method (SFS) is presented. SFS approaches can be easily accelerated through hardware and software techniques but they are very sensible to errors arising during calibration and segmentation processes so they present difficulties when dealing with real images. This paper proposes a new algorithm which uses the information about pixel segmentation uncertainty contained in each view in order to get a reliable 3D reconstruction of the scene. Aggregation of the projected uncertainties permits to classify scene's voxels by means of a decision rule but also makes it possible to create a three-dimensional confidence map of the scene. As a consequence, the regions where more information is needed can be foreseen. Sample reconstructions from real image sets are presented and evaluated.

JTD Keywords: Calibration, Image classification, Image reconstruction, Image segmentation, 3D reconstruction, Calibration process, Decision rule, Hardware technique, Pixel segmentation, Pixel-level certainty measures, Scene voxel classification, Segmentation process, Shape from silhouette method, Software technique, Three-dimensional confidence map, Three-dimensional volumetric reconstruction

The aim was to assess whether induction of ventilator-induced lung injury (VILI) in one lung triggers a concomitant inflammatory response in the normally ventilated contralateral lung. To this end, a differential ventilator was used in 6 rats. One lung was normally ventilated (3.5 ml/kg b.w.) and the contralateral lung was overstretched (15 ml/kg b.w.). Six control rats were normally ventilated (3.5 ml/kg b.w. each lung). After 3h, edema and gene expression of MIP-2 in the lung, and plasma and liver TNF-alpha were assessed. Overexpression of MIP-2 and edema were found in the overventilated lung but not in the normally ventilated contralateral lung. No detectable levels of circulating and liver TNF-alpha were detected. These data do not support the hypothesis of an early positive feedback in the lung inflammation during the mechanical ventilation.

JTD Keywords: Mechanical ventilation, Lung injury, Lung edema, Lung over stretch, High volume ventilation, Differential ventilation