Publications

Human mesenchymal stromal cells (hMSCs) seeded on calcium phosphate (CaP) bioceramics are extensively explored in bone tissue engineering and have recently shown effective clinical outcomes. In previous pre-clinical studies, hMSCs-CaP-mediated bone formation was preceded by osteoclastogenesis at the implantation site. The current study evaluates to what extent phase composition of CaPs affects the osteoclast response and ultimately influence bone formation. To this end, four different CaP bioceramics were used, hydroxyapatite (HA), beta-tricalcium phosphate (beta-TCP) and two biphasic composites of HA/beta- TCP ratios of 60/40 and 20/80 respectively, for in vitro osteoclast differentiation and correlation with in vivo osteoclastogenesis and bone formation. All ceramics allowed osteoclast formation in vitro from mouse and human precursors, except for pure HA, which significantly impaired their maturation. Ectopic implantation alongside hMSCs in subcutis sites of nude mice revealed new bone formation at 8 weeks in all conditions with relative amounts for beta-TCP > biphasic CaPs > HA. Surprisingly, while hMSCs were essential for osteoinduction, their survival did not correlate with bone formation. By contrast, the degree of early osteoclastogenesis (2 weeks) seemed to define the extent of subsequent bone formation. Together, our findings suggest that the osteoclastic response could be used as a predictive marker in hMSC-CaPbased bone regeneration and strengthens the need to understand the underlying mechanisms for future biomaterial development. Statement of significance The combination of mesenchymal stromal cells (MSCs) and calcium phosphate (CaP) materials has demonstrated its safety and efficacy for bone regeneration in clinical trials, despite our insufficient understanding of the underlying biological mechanisms. Osteoclasts were previously suggested as key mediators between the early inflammatory phase following biomaterial implantation and the subsequent bone formation. Here we compared the affinity of osteoclasts for various CaP materials with different ratios of hydroxyapatite to beta-tricalcium phosphate. We found that osteoclast formation, both in vitro and at early stages in vivo, correlates with bone formation when the materials were implanted alongside MSCs in mice. Surprisingly, MSC survival did not correlate with bone formation, suggesting that the number or phenotype of osteoclasts formed was more important. (c) 2024 The Author(s). Published by Elsevier Ltd on behalf of Acta Materialia Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

JTD Keywords: Acid phosphatase tartrate resistant isoenzyme, Animal, Animal cell, Animal experiment, Animal tissue, Animals, Article, Beta-tricalcium phosphate, Bioceramics, Biocompatible materials, Biomaterial, Bone, Bone development, Bone formation, Bone regeneration, Calcium phosphate, Calcium phosphate materials, Calcium phosphates, Cd14 antigen, Cell differentiation, Cell engineering, Cell maturation, Cell survival, Ceramics, Chemical composition, Controlled study, Correlation analysis, Correlation coefficient, Data correlation, Durapatite, Engraftment, Flowcharting, Human, Human cell, Human mesenchymal stromal cell, Human mesenchymal stromal cells, Humans, Hydroxyapatite, Hydroxyapatites, In vitro study, In vivo study, In-vitro, In-vivo, Mammals, Marrow stromal cells, Material composition, Material compositions, Mesenchymal stroma cell, Mesenchymal stromal cells, Mice, Mice, nude, Monocyte, Mouse, Nonhuman, Nude mouse, Ossification, Osteoclast, Osteoclastogenesis, Osteoclasts, Osteogenesis, Osteoinduction, Phase composition, Regeneration strategies, Resorption, Scaffolds, Stem-cells, Subcutaneous tissue, Tissue engineering, Transmission control protocol, Tri-calcium phosphates, Vimentin

We aimed to characterize the cerebral hemodynamic response to obstructive sleep apnea/hypopnea events, and evaluate their association to polysomnographic parameters. The characterization of the cerebral hemodynamics in obstructive sleep apnea (OSA) may add complementary information to further the understanding of the severity of the syndrome beyond the conventional polysomnography.Severe OSA patients were studied during night sleep while monitored by polysomnography. Transcranial, bed-side diffuse correlation spectroscopy (DCS) and frequency-domain near-infrared diffuse correlation spectroscopy (NIRS-DOS) were used to follow microvascular cerebral hemodynamics in the frontal lobes of the cerebral cortex. Changes in cerebral blood flow (CBF), total hemoglobin concentration (THC), and cerebral blood oxygen saturation (StO2) were analyzed.We considered 3283 obstructive apnea/hypopnea events from sixteen OSA patients (Age (median, interquartile range) 57 (52-64.5); females 25%; AHI (apnea-hypopnea index) 84.4 (76.1-93.7)). A biphasic response (maximum/minimum followed by a minimum/maximum) was observed for each cerebral hemodynamic variable (CBF, THC, StO2), heart rate and peripheral arterial oxygen saturation (SpO2). Changes of the StO2 followed the dynamics of the SpO2, and were out of phase from the THC and CBF. Longer events were associated with larger CBF changes, faster responses and slower recoveries. Moreover, the extrema of the response to obstructive hypopneas were lower compared to apneas (p < .001).Obstructive apneas/hypopneas cause profound, periodic changes in cerebral hemodynamics, including periods of hyper- and hypo-perfusion and intermittent cerebral hypoxia. The duration of the events is a strong determinant of the cerebral hemodynamic response, which is more pronounced in apnea than hypopnea events.© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society.

JTD Keywords: cerebral hemodynamics, desaturation, diffuse correlation spectroscopy, duration, hypopnea, hypoxemia, near-infrared spectroscopy, optical pathlength, oxygenation, severity, sleep disorder, spectroscopy, tissue, Adult, Airway obstruction, Apnea hypopnea index, Arterial oxygen saturation, Article, Blood oxygen tension, Blood-flow, Brain blood flow, Brain cortex, Cerebral hemodynamics, Controlled study, Diffuse correlation spectroscopy, Disease severity, Female, Frequency, Frontal lobe, Heart rate, Hemodynamics, Hemoglobin, Hemoglobin determination, Human, Humans, Major clinical study, Male, Near infrared spectroscopy, Near-infrared spectroscopy, Obstructive sleep apnea, Oxygen, Periodicity, Polysomnography, Sleep apnea syndromes, Sleep apnea, obstructive, Sleep disorder, Spectroscopy, near-infrared

Brain function is a product of the balance between excitatory and inhibitory (E/I) brain activity. Variation in the regulation of this activity is thought to give rise to normal variation in human traits, and disruptions are thought to potentially underlie a spectrum of neuropsychiatric conditions (e.g., Autism, Schizophrenia, Downs' Syndrome, intellectual disability). Hypotheses related to E/I dysfunction have the potential to provide cross-diagnostic explanations and to combine genetic and neurological evidence that exists within and between psychiatric conditions. However, the hypothesis has been difficult to test because: (1) it lacks specificity-an E/I dysfunction could pertain to any level in the neural system- neurotransmitters, single neurons/receptors, local networks of neurons, or global brain balance - most researchers do not define the level at which they are examining E/I function; (2) We lack validated methods for assessing E/I function at any of these neural levels in humans. As a result, it has not been possible to reliably or robustly test the E/I hypothesis of psychiatric disorders in a large cohort or longitudinal patient studies. Currently available, in vivo markers of E/I in humans either carry significant risks (e.g., deep brain electrode recordings or using Positron Emission Tomography (PET) with radioactive tracers) and/or are highly restrictive (e.g., limited spatial extent for Transcranial Magnetic Stimulation (TMS) and Magnetic Resonance Spectroscopy (MRS). More recently, a range of novel Electroencephalography (EEG) features has been described, which could serve as proxy markers for E/I at a given level of inference. Thus, in this perspective review, we survey the theories and experimental evidence underlying 6 novel EEG markers and their biological underpinnings at a specific neural level. These cheap-to-record and scalable proxy markers may offer clinical utility for identifying subgroups within and between diagnostic categories, thus directing more tailored sub-grouping and, therefore, treatment strategies. However, we argue that studies in clinical populations are premature. To maximize the potential of prospective EEG markers, we first need to understand the link between underlying E/I mechanisms and measurement techniques.

JTD Keywords: Cortical networks, Direction selectivity, Excitation/inhibition balance, Fast network oscillations, Gaba concentration, Gamma oscillation frequency, Neuronal oscillations, Range temporal correlations, Self-organized criticality, Theta-oscillations

Introduction: After a stroke, a wide range of deficits can occur with varying onset latencies. As a result, assessing impairment and recovery are enormous challenges in neurorehabilitation. Although several clinical scales are generally accepted, they are time-consuming, show high inter-rater variability, have low ecological validity, and are vulnerable to biases introduced by compensatory movements and action modifications. Alternative methods need to be developed for efficient and objective assessment. In this study, we explore the potential of computer-based body tracking systems and classification tools to estimate the motor impairment of the more affected arm in stroke patients. Methods: We present a method for estimating clinical scores from movement parameters that are extracted from kinematic data recorded during unsupervised computer-based rehabilitation sessions. We identify a number of kinematic descriptors that characterise the patients' hemiparesis (e.g., movement smoothness, work area), we implement a double-noise model and perform a multivariate regression using clinical data from 98 stroke patients who completed a total of 191 sessions with RGS. Results: Our results reveal a new digital biomarker of arm function, the Total Goal-Directed Movement (TGDM), which relates to the patients work area during the execution of goal-oriented reaching movements. The model's performance to estimate FM-UE scores reaches an accuracy of R-2: 0.38 with an error (sigma: 12.8). Next, we evaluate its reliability (r = 0.89 for test-retest), longitudinal external validity (95% true positive rate), sensitivity, and generalisation to other tasks that involve planar reaching movements (R-2: 0.39). The model achieves comparable accuracy also for the Chedoke Arm and Hand Activity Inventory (R-2: 0.40) and Barthel Index (R-2: 0.35). Conclusions: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.

JTD Keywords: interactive feedback, motion classification, motion sensing, multivariate regression, posture monitoring, rehabilitation, stroke, Adult, Aged, Analytic method, Arm movement, Article, Barthel index, Brain hemorrhage, Cerebrovascular accident, Chedoke arm and hand activity inventory, Clinical protocol, Cognitive defect, Computer analysis, Controlled study, Convergent validity, Correlation coefficient, Disease severity, External validity, Female, Fugl meyer assessment for the upper extremity, Functional assessment, Functional status assessment, General health status assessment, Hemiparesis, Human, Interactive feedback, Ischemic stroke, Kinematics, Major clinical study, Male, Mini mental state examination, Motion classification, Motion sensing, Motor analog scale, Movement, Multivariate regression, Muscle function, Posture monitoring, Probability, Recovery, Rehabilitation, Reliability, Retrospective study, Stroke, Stroke patient, Test retest reliability, Therapy, Total goal directed movement, Upper extremities, Upper limb, Upper-limb, Wolf motor function test

The visualization of microtubules by combining optical and electron microscopy techniques provides valuable information to understand correlated intracellular activities. However, the lack of appropriate probes to bridge both microscopic resolutions restricts the areas and structures that can be comprehended within such highly assembled structures. Here, a versatile cyclometalated iridium (III) complex is designed that achieves synchronous fluorescence–electron microscopy correlation. The selective insertion of the probe into a microtubule triggers remarkable fluorescence enhancement and promising electron contrast. The long-life, highly photostable probe allows live-cell super-resolution imaging of tubulin localization and motion with a resolution of ≈30 nm. Furthermore, correlative light–electron microscopy and energy-filtered transmission electron microscopy reveal the well-associated optical and electron signal at a high specificity, with an interspace of ≈41 Å of microtubule monomer in cells.

JTD Keywords: Correlation light–electron microscopy, Microtubules, Organometallic probes, Super-resolution microscopy

Respiration rate can be assessed by analyzing respiratory changes of the electrocardiogram (ECG). Several methods can be applied to derive the respiratory signal from the ECG (EDR signal). In this study, four EDR estimation methods based on QRS features were analyzed. A database with 44 healthy subjects (16 females) in supine and sitting positions was analyzed. Respiratory flow and ECG recordings on leads I, II, III and a Chest lead was studied. A QR slope-based method, an RS slope-based method, an QRS angle-based method and an QRS area-based method were applied. Their performance was evaluated by the correlation coefficient with the reference respiratory volume signal. Significantly higher correlation coefficients in the range r = 0.77 – 0.86 were obtained with the Chest lead for all methods. The EDR estimation method based on the QRS angle provided the highest similarity with the volume signal for all recording leads and subject positions. We found no statistically significant differences according to gender or subject position.Clinical Relevance— This work analyzes the EDR signal from four electrocardiographic leads to obtain the respiratory signal and contributes to a simplified analysis of respiratory activity.

JTD Keywords: Electrocardiography, Lead, Estimation, Correlation coefficient, Databases, Heart, Correlation

Estimating the affective state of a user during a computer task traditionally relies on either subjective reports or analysis of physiological signals, facial expressions, and other measures. These methods have known limitations, can be intrusive and may require specialized equipment. An alternative would be employing a ubiquitous device of everyday use such as a standard keyboard. Here we investigate if we can infer the emotional state of a user by analyzing their typing patterns. To test this hypothesis, we asked 400 participants to caption a set of emotionally charged images taken from a standard database with known ratings of arousal and valence. We computed different keystroke pattern dynamics, including keystroke duration (dwell time) and latency (flight time). By computing the mean value of all of these features for each image, we found a statistically significant negative correlation between dwell times and valence, and between flight times and arousal. These results highlight the potential of using keystroke dynamics to estimate the affective state of a user in a non-obtrusive way and without the need for specialized devices.

JTD Keywords: Feature extraction, Correlation, Keyboards, Task analysis, Statistical analysis, Affective computing, Standards, Keystroke, Keyboard, Typing, Arousal, Valence, Affect

Obstructive apnea causes periodic changes in cerebral and systemic hemodynamics, which may contribute to the increased risk of cerebrovascular disease of patients with obstructive sleep apnea (OSA) syndrome. The improved understanding of the consequences of an apneic event on the brain perfusion may improve our knowledge of these consequences and then allow for the development of preventive strategies. Our aim was to characterize the typical microvascular, cortical cerebral blood flow (CBF) changes in an OSA population during an apneic event. Sixteen patients (age 58  ±  8  years, 75% male) with a high risk of severe OSA were measured with a polysomnography device and with diffuse correlation spectroscopy (DCS) during one night of sleep with 1365 obstructive apneic events detected. All patients were later confirmed to suffer from severe OSA syndrome with a mean of 83  ±  15 apneas and hypopneas per hour. DCS has been shown to be able to characterize the microvascular CBF response to each event with a sufficient contrast-to-noise ratio to reveal its dynamics. It has also revealed that an apnea causes a peak increase of microvascular CBF (30  ±  17  %  ) at the end of the event followed by a drop (−20  ±  12  %  ) similar to what was observed in macrovascular CBF velocity of the middle cerebral artery. This study paves the way for the utilization of DCS for further studies on these populations.

JTD Keywords: Sleep disorder breathing, Cerebral blood flow, Brain perfusion, Diffuse correlation spectroscopy

Cardiac death risk is still a big problem by an important part of the population, especially in elderly patients. In this study, we propose to characterize and analyze the cardiovascular and cardiorespiratory systems using the Poincaré plot. A total of 46 cardiomyopathy patients and 36 healthy subjets were analyzed. Left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF > 35%, 16 patients), and high risk (HR: LVEF ≤ 35%, 30 patients) of heart attack. RR, SBP and TTot time series were extracted from the ECG, blood pressure and respiratory flow signals, respectively. Parameters that describe the scatterplott of Poincaré method, related to short- and long-term variabilities, acceleration and deceleration of the dynamic system, and the complex correlation index were extracted. The linear discriminant analysis (LDA) and the support vector machines (SVM) classification methods were used to analyze the results of the extracted parameters. The results showed that cardiac parameters were the best to discriminate between HR and LR groups, especially the complex correlation index (p = 0.009). Analising the interaction, the best result was obtained with the relation between the difference of the standard deviation of the cardiac and respiratory system (p = 0.003). When comparing HR vs LR groups, the best classification was obtained applying SVM method, using an ANOVA kernel, with an accuracy of 98.12%. An accuracy of 97.01% was obtained by comparing patients versus healthy, with a SVM classifier and Laplacian kernel. The morphology of Poincaré plot introduces parameters that allow the characterization of the cardiorespiratory system dynamics.

JTD Keywords: Time series analysis, Electrocardiography, Support vector machines, Kernel, Standards, Correlation, RF signals

Obstructive Sleep Apnea (OSA) is a sleep disorder with a high prevalence in the general population. It is a risk factor for many cardiovascular diseases, and an independent risk factor for cerebrovascular diseases such as stroke. After an apnea episode, both arterial blood pressure and cerebral blood flow velocity change in function of the apnea duration (AD). We hypothesized that the relative excursion in heart rate (AHR), defined as the percentage difference between the maximum and the minimum heart rate values associated to an obstructive apnea event, is also related to AD. In this work we studied the relationship between apnea-related AHR and AD in a population of eight patients with severe OSA. AHR and AD showed a moderate but statistically significant correlation (p <; 0.0001) in a total of 1454 obstructive apneas analyzed. The average heart rate excursion for apneas with AD ≥ 30s (ΔHR = 31.29 ± 6.64%) was significantly greater (p = 0.0002) than for apneas with AD ∈ [10,20)s (ΔHR = 18.14±3.08%). We also observed that patients with similar Apnea-Hypopnea Index (AHI) may exhibit remarkably different distributions of AHR and AD, and that patients with a high AHI need not have a higher average AHR than others with a lower severity index. We conclude that the overall apnea-induced heart rate excursion is partially explained by the duration of apnoeic episodes, and it may be a simple measure of the cardiovascular stress associated with OSA that is not directly reflected in the AHI.

JTD Keywords: Heart rate, Sleep apnea, Correlation, Indexes, Sociology, Blood vessels

A method for online decorrelation of chemical sensor signals from the effects of environmental humidity and temperature variations is proposed. The goal is to improve the accuracy of electronic nose measurements for continuous monitoring by processing data from simultaneous readings of environmental humidity and temperature. The electronic nose setup built for this study included eight metal-oxide sensors, temperature and humidity sensors with a wireless communication link to external computer. This wireless electronic nose was used to monitor the air for two years in the residence of one of the authors and it collected data continuously during 537 days with a sampling rate of 1 sample per second. To estimate the effects of variations in air humidity and temperature on the chemical sensors' signals, we used a standard energy band model for an n-type metal-oxide (MOX) gas sensor. The main assumption of the model is that variations in sensor conductivity can be expressed as a nonlinear function of changes in the semiconductor energy bands in the presence of external humidity and temperature variations. Fitting this model to the collected data, we confirmed that the most statistically significant factors are humidity changes and correlated changes of temperature and humidity. This simple model achieves excellent accuracy with a coefficient of determination R2 close to 1. To show how the humidity–temperature correction model works for gas discrimination, we constructed a model for online discrimination among banana, wine and baseline response. This shows that pattern recognition algorithms improve performance and reliability by including the filtered signal of the chemical sensors.

JTD Keywords: Electronic nose, Chemical sensors, Humidity, Temperature, Decorrelation, Wireless e-nose, MOX sensors, Energy band model, Home monitoring

Obstructive Sleep Apnea (OSA) is a sleep disorder highly prevalent in the general population. Cardiorespiratory Phase Synchronization (CRPS) is a form of non-linear interaction between respiratory and cardiovascular systems that was found to be reduced in severe OSA patients. The Hilbert Transform (HT) method was the recommended choice for estimating the respiratory phase in CRPS studies. But we have noticed that HT provides a phase that is aligned to the transition between the exhalation and the inhalation parts of different breathing cycles, instead of being aligned to the breathing onsets. In this work we proposed a Realigned HT phase estimation method (RHT) and we compared it to the conventional HT and to the Linear Phase (LP) approximation for estimating CRPS in a database of 28 patients with different OSA severity levels. RHT provided similar synchronization percentages (%Sync) as HT, and it enhanced the significant differences in %Sync between mild and severe OSA patients. %Sync showed the highest negative correlation with the Apnea-Hypopnea Index (AHI) when using RHT (rAHI=-0.692, p<;0.001), which only had an 10% extra computational cost. On the other hand, LP method significantly overestimated %Sync especially in the more severe patients, because it was unable to track the phase non-linearities that can be observed during sleep disordered breathing. Therefore, the newly proposed RHT can be the preferred alternative over the conventional HT or the LP approximation for estimating CRPS in OSA patients.

JTD Keywords: Correlation, Databases, Electrocardiography, Phase estimation, Sleep apnea, Synchronization, Transforms

The scope of our work focuses on investigating the potential use of the built-in accelerometer of the smartphones for the recording of the respiratory activity and deriving the respiratory rate. Five healthy subjects performed an inspiratory load protocol. The excursion of the right chest was recorded using the built-in triaxial accelerometer of a smartphone along the x, y and z axes and with an external uniaxial accelerometer. Simultaneously, the respiratory airflow and the inspiratory mouth pressure were recorded, as reference respiratory signals. The chest acceleration signal recorded in the z axis with the smartphone was denoised using a scheme based on the ensemble empirical mode decomposition, a noise data assisted method which decomposes nonstationary and nonlinear signals into intrinsic mode functions. To distinguish noisy oscillatory modes from the relevant modes we use the detrended fluctuation analysis. We reported a very strong correlation between the acceleration of the z axis of the smartphone and the reference accelerometer across the inspiratory load protocol (from 0.80 to 0.97). Furthermore, the evaluation of the respiratory rate showed a very strong correlation (0.98). A good agreement was observed between the respiratory rate estimated with the chest acceleration signal from the z axis of the smartphone and with the respiratory airflow signal: Bland-Altman limits of agreement between -1.44 and 1.46 breaths per minute with a mean bias of -0.01 breaths per minute. This preliminary study provides a valuable insight into the use of the smartphone and its built-in accelerometer for respiratory monitoring.

JTD Keywords: Acceleration, Accelerometers, Correlation, Empirical mode decomposition, Fluctuations, Protocols, Time series analysis

Obstructive Sleep Apnea (OSA) is currently diagnosed by a full nocturnal polysomnography (PSG), a very expensive and time-consuming method. In previous studies we were able to distinguish patients with OSA through formant frequencies of breath sound during sleep. In this study we aimed at identifying OSA patients from breath sound analysis during wakefulness. The respiratory sound was acquired by a tracheal microphone simultaneously to PSG recordings. We selected several cycles of consecutive inspiration and exhalation episodes in 10 mild-moderate (AHI<;30) and 13 severe (AHI>=30) OSA patients during their wake state before getting asleep. Each episode's formant frequencies were estimated by linear predictive coding. We studied several formant features, as well as their variability, in consecutive inspiration and exhalation episodes. In most subjects formant frequencies were similar during inspiration and exhalation. Formant features in some specific frequency band were significantly different in mild OSA as compared to severe OSA patients, and showed a decreasing correlation with OSA severity. These formant characteristics, in combination with some anthropometric measures, allowed the classification of OSA subjects between mild-moderate and severe groups with sensitivity (specificity) up to 88.9% (84.6%) and accuracy up to 86.4%. In conclusion, the information provided by formant frequencies of tracheal breath sound recorded during wakefulness may allow identifying subjects with severe OSA.

JTD Keywords: Correlation, Databases, Sensitivity, Sleep apnea, Speech, Synchronization

The study of the mechanomyographic signal of the diaphragm muscle (MMGdi) is a promising technique in order to evaluate the respiratory muscles effort. The relationship between amplitude and frequency parameters of this signal with the respiratory effort performed during respiration is of great interest for researchers and physicians due to its diagnostic potentials. However, MMGdi signals are frequently contaminated by a cardiac vibration or mechanocardiographic (MCG) signal. An adaptive noise cancellation (ANC) can be used to reduce the MCG interference in the recorded MMGdi activity. In this paper, it is evaluated the proposed ANC scheme by means of a synthetic MMGdi signal with a controlled MCG interference. The Pearson's correlation coefficient (PCC) between both root mean square (RMS) and mean frequency (fm) of the synthetic MMGdi signal are considerably reduced with the presence of cardiac vibration noise (from 0.95 to 0.87, and from 0.97 to 0.76, respectively). With the ANC algorithm proposed the effect of the MCG noise on the amplitude and frequency of MMG parameters is reduced considerably (PCC of 0.93 and 0.97 for the RMS and fm, respectively). The ANC method proposed in this work is an interesting technique to attenuate the cardiac interference in respiratory MMG signals. Further investigation should be carried out to evaluate the performance of the ANC algorithm in real MMGdi signals.

JTD Keywords: Adaptive filters, Frequency modulation, Interference, Muscles, Noise cancellation, Vibrations, Cardiology, Medical signal processing, Muscle, Signal denoising, ANC algorithm, MCG interference, Pearson correlation coefficient, Adaptive noise cancellation, Cardiac vibration interference, Cardiac vibration noise, Diaphragm muscle, Mechanocardiographic signal, Mechanomyographic signals, Respiratory muscles effort

Sleep in patients with Sleep Apnea-Hypopnea Syndrome (SAHS) is frequently interrupted with arousals. Increased amounts of arousals result in shortening total sleep time and repeated sleep-arousal change can result in sleep fragmentation. According to the American Sleep Disorders Association (ASDA) an arousal is a marker of sleep disruption representing a detrimental and harmful feature for sleep. The nature of arousals and its role on the regulation of the sleep process raises controversy and has sparked the debate in the last years. In this work, we analyzed and compared the EEG spectral content of respiratory and spontaneous arousals on a database of 45 SAHS subjects. A total of 3980 arousals (1996 respiratory and 1984 spontaneous) were analyzed. The results showed no differences between the spectral content of the two kinds of arousals. Our findings raise doubt as to whether these two kinds of arousals are truly triggered by different organic mechanisms. Furthermore, they may also challenge the current beliefs regarding the underestimation of the importance of spontaneous arousals and their contribution to sleep fragmentation in patients suffering from SAHS.

JTD Keywords: Adaptive filters, Correlation, Databases, Electroencephalography, Hospitals, Sleep apnea, Electroencephalography, Medical signal processing, Pneumodynamics, Sleep, EEG spectral content, Organic mechanism, Respiratory, Sleep apnea hypopnea syndrome, Sleep fragmentation, Spectral content, Spontaneous arousal

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