Publications

Experimental and clinical studies of consciousness identify brain states (i.e. quasi-stable functional cerebral organization) in a non-systematic manner and largely independent of the research into brain state modulation. In this narrative review, we synthesize advances in the identification of brain states associated with consciousness in animal models and physiological (sleep), pharmacological (anaesthesia) and pathological (disorders of consciousness) states of altered consciousness in humans. We show that in reduced consciousness the frequencies in which the brain operates are slowed down and that the pattern of functional communication is sparser, less efficient, and less complex. The results also highlight damaged resting-state networks, in particular the default mode network, decreased connectivity in long-range connections and especially in the thalamocortical loops. Next, we show that therapeutic approaches to treat disorders of consciousness, through pharmacology (e.g. amantadine, zolpidem), and (non-) invasive brain stimulation (e.g. transcranial direct current stimulation, deep brain stimulation) have shown partial effectiveness in promoting consciousness recovery. Although some features of conscious brain states may improve in response to neuromodulation, targeting often remains non-specific and does not always lead to (behavioural) improvements. The fields of brain state identification and neuromodulation of brain states in relation to consciousness are showing fascinating developments that, when integrated, might propel the development of new and better-targeted techniques for disorders of consciousness. We here propose a therapeutic framework for the identification and modulation of brain states to facilitate the interaction between the two fields. We propose that brain states should be identified in a predictive setting, followed by theoretical and empirical testing (i.e. in animal models, under anaesthesia and in patients with a disorder of consciousness) of neuromodulation techniques to promote consciousness in line with such predictions. This framework further helps to identify where challenges and opportunities lay for the maturation of brain state research in the context of states of consciousness. It will become apparent that one angle of opportunity is provided through the addition of computational modelling. Finally, it aids in recognizing possibilities and obstacles for the clinical translation of these diagnostic techniques and neuromodulation treatment options across both the multimodal and multi-species approaches outlined throughout the review.

JTD Keywords: (disorders of) consciousness, Anaesthesia, Animal model, Animal models, Area induces reanimation, Brain states, Direct-current stimulation, Disorder, Electrical-stimulation, Functional connectivity, General-anesthesia, Neuromodulation, Propofol-induced loss, Thalamic-stimulation, Transcranial magnetic stimulation, Vegetative state

The extracellular matrix (ECM) is a dynamic and complex network of proteins and molecules that surrounds cells and tissues in the nervous system and orchestrates a myriad of biological functions. This review carefully examines the diverse interactions between cells and the ECM, as well as the transformative chemical and physical changes that the ECM undergoes during neural development, aging, and disease. These transformations play a pivotal role in shaping tissue morphogenesis and neural activity, thereby influencing the functionality of the central nervous system (CNS). In our comprehensive review, we describe the diverse behaviors of the CNS ECM in different physiological and pathological scenarios and explore the unique properties that make ECM-based strategies attractive for CNS repair and regeneration. Addressing the challenges of scalability, variability, and integration with host tissues, we review how advanced natural, synthetic, and combinatorial matrix approaches enhance biocompatibility, mechanical properties, and functional recovery. Overall, this review highlights the potential of decellularized ECM as a powerful tool for CNS modeling and regenerative purposes and sets the stage for future research in this exciting field. This article is categorized under: Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease Implantable Materials and Surgical Technologies > Nanomaterials and Implants

JTD Keywords: Amyotrophic-lateral-sclerosis, Biologic scaffold, Central nervous system, Central-nervous-system, Chondroitin sulfate proteoglycans, Decellularization, Extracellular matrix, Motor-neurons, Neural disorders, Neural regeneratio, Perineuronal nets, Self-healing hydrogel, Spinal-cord-injury, Stem-cell, Vascular basement-membrane

Prior studies demonstrated that encapsulation in poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) enhanced the delivery of enzymes used for replacement therapy (ERT) of lysosomal storage disorders (LSDs). This study examined how the copolymer lactide:glycolide ratio impacts encapsulation, physicochemical characteristics, stability, and release under lysosomal conditions. Hyaluronidase, deficient in mucopolysaccharidosis IX, was encapsulated in NPs synthesized using 50:50, 60:40, or 75:25 lactide:glycolide copolymers. All NPs had diameters compatible with cellular transport (≤168 nm) and polydispersity indexes (≤0.16) and ζ-potentials (≤-35 mV) compatible with colloidal stability. Yet, their encapsulation efficiency varied, with 75:25 NPs and 60:40 NPs having the lowest and highest EE, respectively (15% vs. 28%). Under lysosomal conditions, the 50:50 copolymer degraded fastest (41% in 1 week), as expected, and the presence of a targeting antibody coat did not alter this result. Additionally, 60:40 NPs destabilized fastest (<1 week) because of their smaller diameter, and 75:25 NPs did not destabilize in 4 weeks. All formulations presented burst release under lysosomal conditions (56-78% of the original load within 30 min), with 50:50 and 60:40 NPs releasing an additional small fraction after week 1. This provided 4 weeks of sustained catalytic activity, sufficient to fully degrade a substrate. Altogether, the 60:40 NP formulation is preferred given its higher EE, and 50:50 NPs represent a valid alternative, while the highest stability of 75:25 NPs may impair lysosomes. These results can guide future studies aiming to translate PLGA NP-based ERT for this and other LSDs.

JTD Keywords: biodegradation, copolymer ratio, degradation, drug-delivery, emulsification, enzyme release, enzyme replacement therapy, hyaluronidase, mechanisms, microspheres, nanoparticle stability, poly(lactide-co-glycolide) nanoparticles, size, sphingomyelinase, transport, Central-nervous-system, Copolymer ratio, Enzyme release, Enzyme replacement therapy, Hyaluronidase, Lysosomal storage disorder, Nanoparticle stability, Poly(lactide-co-glycolide) nanoparticles

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

We show that catalyst-free aqueous solutions of hyperpolarized [1-13C]succinate can be produced using parahydrogen-induced polarization (PHIP) and a combination of homogeneous and heterogeneous catalytic hydrogenation reactions. We generate hyperpolarized [1-13C]fumarate via PHIP using para-enriched hydrogen gas with a homogeneous ruthenium catalyst, and subsequently remove the toxic catalyst and reaction side products via a purification procedure. Following this, we perform a second hydrogenation reaction using normal hydrogen gas to convert the fumarate into succinate using a solid Pd/Al2O3 catalyst. This inexpensive polarization protocol has a turnover time of a few minutes, and represents a major advance for in vivo applications of [1-13C]succinate as a hyperpolarized contrast agent.

JTD Keywords: acid, c-13, conversion, fumarate, in-vivo, metabolism, order, Induced polarization

JTD Keywords: Decellularised matrices, Nervous system (brain-central-peripheral / disorders)

Lysosomes play a central role in cellular homeostasis and alterations in this compartment associate with many diseases. The most studied example is that of lysosomal storage disorders (LSDs), a group of 60 + maladies due to genetic mutations affecting lysosomal components, mostly enzymes. This leads to aberrant intracellular storage of macromolecules, altering normal cell function and causing multiorgan syndromes, often fatal within the first years of life. Several treatment modalities are available for a dozen LSDs, mostly consisting of enzyme replacement therapy (ERT) strategies. Yet, poor biodistribution to main targets such as the central nervous system, musculoskeletal tissue, and others, as well as generation of blocking antibodies and adverse effects hinder effective LSD treatment. Drug delivery systems are being studied to surmount these obstacles, including polymeric constructs and nanoparticles that consti-tute the focus of this article. We provide an overview of the formulations being tested, the diseases they aim to treat, and the results observed from respective in vitro and in vivo studies. We also discuss the advantages and disadvantages of these strategies, the remaining gaps of knowledge regarding their per-formance, and important items to consider for their clinical translation. Overall, polymeric nanocon-structs hold considerable promise to advance treatment for LSDs.(c) 2023 Elsevier B.V. All rights reserved.

JTD Keywords: cellular and animal models, enzyme replacement therapy, lysosomal storage disorders, nanoemulsions, nanoparticles, Beta-glucuronidase deficiency, Blood-brain-barrier, Cellular and animal models, Central-nervous-system, Drug delivery systems, Enzyme replacement therapy, Feline gm1 gangliosidosis, Human acid sphingomyelinase, Human alpha-galactosidase, Humans, Lysosomal storage diseases, Lysosomal storage disorders, Lysosomes, Mucopolysaccharidosis type-ii, Nanoemulsions, Nanoparticles, Neuronal ceroid-lipofuscinosis, Niemann-pick-disease, Pluripotent stem-cells, Polymer-based drug delivery systems, Polymers, Tissue distribution

Identification of asymptomatic patients at higher risk for suffering cardiac events remains controversial and challenging in Brugada syndrome (BS). In this work, we proposed an ECG-based classifier to predict BS-related symptoms, by merging the most predictive electrophysiological features derived from the ventricular depolarization and repolarization periods, along with autonomic-related markers. The initial feature space included local and dynamic ECG markers, assessed during a physical exercise test performed in 110 BS patients (25 symptomatic). Morphological, temporal and spatial properties quantifying the ECG dynamic response to exercise and recovery were considered. Our model was obtained by proposing a two-stage feature selection process that combined a resampled-based regularization approach with a wrapper model assessment for balancing, simplicity and performance. For the classification step, an ensemble was constructed by several logistic regression base classifiers, whose outputs were fused using a performance-based weighted average. The most relevant predictors corresponded to the repolarization interval, followed by two autonomic markers and two other makers of depolarization dynamics. Our classifier allowed for the identification of novel symptom-related markers from autonomic and dynamic ECG responses during exercise testing, suggesting the need for multifactorial risk stratification approaches in order to predict future cardiac events in asymptomatic BS patients.

JTD Keywords: brugada syndrome, depolarization disorders, ensemble classifier, heart-rate recovery, Acute myocardial-ischemia, Autonomics, Brugada syndrome, Brugadum syndrome, Cardiac death, Depolarization, Depolarization disorder, Depolarization disorders, Dynamic ecg, Electrocardiography, Electrophysiology, Ensemble classifier, Ensemble-classifier, Events, Exercise, Forecasting, Heart, Heart-rate, Heart-rate recovery, Prognosis, Qrs, Quantification, Recovery, Repolarization, Sudden cardiac death

Autism is a neurodevelopmental disorder characterized by deficits in social communication and repetitive patterns of behavior. Individuals affected by Autism Spectrum Disorder (ASD) may face overwhelming sensory hypersensitivities that hamper their everyday life. In order to promote awareness about neurodiversity among the neurotypical population, we have developed an interactive virtual reality simulation to experience the oversensory stimulation that an individual with autism spectrum disorder may experience in a natural environment. In this experience, we project the user in a first-person perspective in a classroom where a teacher is presenting a lecture. As the user explores the classroom and attends the lecture, he/she is confronted with sensory distortions which are commonly experienced by persons with ASD. We provide the users with a virtual reality headset with motion tracking, two wireless controllers for interaction, and a wristband for physiological data acquisition to create a closed feedback loop. This wearable device measures blood volume pulse (BVP) and electrodermal activity (EDA), which we use to perform online estimations of the arousal levels of users as they respond to the virtual stimuli. We use this information to modulate the intensity of auditory and visual stimuli simulating a vicious cycle in which increased arousal translates into increased oversensory stimulation. Here, we present the architecture and technical implementation of this system.

JTD Keywords: autism spectrum disorder, neurodiversity, physiology, Autism, Autism spectrum disorder, Neurodiversity, Physiology, Virtual reality

Treatment of neurological lysosomal storage disorders (LSDs) are limited because of impermeability of the blood-brain barrier (BBB) to macromolecules. Nanoformulations targeting BBB transcytosis are being explored, but the status of these routes in LSDs is unknown. We studied nanocarriers (NCs) targeted to the transferrin receptor (TfR), ganglioside GM1 or ICAM1, associated to the clathrin, caveolar or cell adhesion molecule (CAM) routes, respectively. We used brain endothelial cells and mouse models of acid sphingomyelinase-deficient Niemann Pick disease (NPD), and postmortem LSD patients' brains, all compared to respective controls. NC transcytosis across brain endothelial cells and brain distribution in mice were affected, yet through different mechanisms. Reduced TfR and clathrin expression were found, along with decreased transcytosis in cells and mouse brain distribution. Caveolin-1 expression and GM1 transcytosis were also reduced, yet increased GM1 levels seemed to compensate, providing similar NC brain distribution in NPD vs. control mice. A tendency to lower NHE-1 levels was seen, but highly increased ICAM1 expression in cells and human brains correlated with increased transcytosis and brain distribution in mice. Thus, transcytosis-related alterations in NPD and likely other LSDs may impact therapeutic access to the brain, illustrating the need for these mechanistic studies.Copyright © 2022 Elsevier B.V. All rights reserved.

JTD Keywords: acid sphingomyelinase, antibody-affinity, blood -brain barrier, drug-delivery, icam-1-targeted nanocarriers, in-vivo, mediated endocytosis, model, neurological diseases, niemann-pick, targeted nanocarriers, trafficking, transcytosis pathways, Blood-brain barrier, Central-nervous-system, Lysosomal storage disorders, Neurological diseases, Targeted nanocarriers, Transcytosis pathways

The severe neurological disorder epilepsy affects almost 1% of the world population. For patients who suffer from pharmacoresistant focal-onset epilepsy, electroencephalographic (EEG) recordings are essential for the localization of the brain area where seizures start. Apart from the visual inspection of the recordings, quantitative EEG signal analysis techniques proved to be useful for this purpose. Among other features, regularity versus irregularity and phase coherence versus phase independence allowed characterizing brain dynamics from the measured EEG signals. Can phase irregularities also characterize brain dynamics? To address this question, we use the univariate coefficient of phase velocity variation, defined as the ratio of phase velocity standard deviation and the mean phase velocity. Beyond that, as a bivariate measure we use the classical mean phase coherence to quantify the degree of phase locking. All phase-based measures are combined with surrogates to test null hypotheses about the dynamics underlying the signals. In the first part of our analysis, we use the Rössler model system to study our approach under controlled conditions. In the second part, we use the Bern-Barcelona EEG database which consists of focal and nonfocal signals extracted from seizure-free recordings. Focal signals are recorded from brain areas where the first seizure EEG signal changes can be detected, and nonfocal signals are recorded from areas that are not involved in the seizure at its onset. Our results show that focal signals have less phase variability and more phase coherence than nonfocal signals. Once combined with surrogates, the mean phase velocity proved to have the highest discriminative power between focal and nonfocal signals. In conclusion, conceptually simple and easy to compute phase-based measures can help to detect features induced by epilepsy from EEG signals. This holds not only for the classical mean phase coherence but even more so for univariate measures of phase irregularity. © 2022 American Physical Society.

JTD Keywords: brain, entropy, epileptogenic networks, functional connectivity, hilbert transform, seizure onset, surrogate data, synchronization, time-series, Biomedical signal processing, Brain areas, Brain dynamics, Dynamics, Electroencephalographic signals, Electroencephalography, Electrophysiology, Intracranial eeg signals, Localisation, Neurological disorders, Neurology, Phase based, Phase coherence, Signal detection, Simple++, Univariate, Velocity, World population

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

Obstructive sleep apnea (OSA) is a sleep disorder in which repetitive upper airway obstructive events occur during sleep. These events can induce hypoxia, which is a risk factor for multiple cardiovascular and cerebrovascular diseases. Chronic obstructive pulmonary disease (COPD) is a disorder which induces a persistent inflammation of the lungs. This condition produces hypoventilation, affecting the blood oxygenation, and leads to an increased risk of developing lung cancer and heart disease. In this study, we evaluated how COPD affects the severity and characteristics of OSA in a multivariate demographic database including polysomnographic signals. Results showed SpO2 subtle variations, such as more non-recovered desaturations and increased time below a 90% SpO2 level, which, in the long term, could worsen the risk to suffer cardiovascular and cerebrovascular diseases.Clinical Relevance - COPD increases the OSA risk due to hypoventilation and altered SpO2 behavior. © 2021 IEEE.

JTD Keywords: Chronic obstructive lung disease, Complication, Epidemiologic studies, Epidemiology, Human, Humans, Oxygen saturation, Pulmonary disease, chronic obstructive, Sleep apnea, obstructive, Sleep disordered breathing, Syndrome

Patients suffering from obstructive sleep apnea (OSA) usually present an increased sympathetic activity caused by the intermittent hypoxia effect on autonomic control. This study evaluated the relationship between sleep stages and the apnea duration, frequency, and type, as well as their impact on HRV markers in different groups of disease severity. The hypnogram and R-R interval signals were extracted in 81 OSA patients from night polysomnographic (PSG) recordings. The apnea-hypopnea index (AHI) defined patient classification as mild-moderate (AHI< 30, n 44) or severe (AHI>30, n 37). The normalized power in VLH, LF, and HF bands of RR series were estimated by a time-frequency approach and averaged in 1-min epochs of normal and apnea segments. The autonomic response and the impact of sleep stages were assessed in both segments to compare patient groups. Deeper sleep stages (particularly S2) concentrated the shorter and mild apnea episodes (from 10 to 40 s) compared to light (SWS) and REM sleep. Longer episodes (>50 s) although less frequent, were of similar incidence in all stages. This pattern was more pronounced for the group of severe patients. Moreover, during apnea segments, LF nu was higher (p 0.044) for the severe group, since V LF nu and HF nu presented the greatest changes when compared to normal segments. The non-REM sleep seems to better differentiate OSA patients groups, particularly through VLF nu and HF nu (p<0.001). A significant difference in both sympathetic and vagal modulation between REM and non-REM sleep was only found within the severe group. These results confirm the importance of considering sleep stages for HRV analysis to further assess OSA disease severity, beyond the traditional and clinically limited AHI values.Clinical relevance - Accounting for sleep stages during HRV analysis could better assess disease severity in OSA patients. © 2021 IEEE.

JTD Keywords: blood-pressure, genomic consequences, intermittent hypoxia, rapid-eye-movement, sympathetic activity, Heart rate, Heart-rate-variability, Human, Humans, Polysomnography, Rem sleep, Sleep apnea, obstructive, Sleep disordered breathing, Sleep stage, Sleep stages, Sleep, rem

Abstract Critical dynamics, characterized by scale-free neuronal avalanches, is thought to underlie optimal function in the sensory cortices by maximizing information transmission, capacity, and dynamic range. In contrast, deviations from criticality have not yet been considered to support any cognitive processes. Nonetheless, neocortical areas related to working memory and decision-making seem to rely on long-lasting periods of ignition-like persistent firing. Such firing patterns are reminiscent of supercritical states where runaway excitation dominates the circuit dynamics. In addition, a macroscopic gradient of the relative density of Somatostatin (SST+) and Parvalbumin (PV+) inhibitory interneurons throughout the cortical hierarchy has been suggested to determine the functional specialization of low- versus high-order cortex. These observations thus raise the question of whether persistent activity in high-order areas results from the intrinsic features of the neocortical circuitry. We used an attractor model of the canonical cortical circuit performing a perceptual decision-making task to address this question. Our model reproduces the known saddle-node bifurcation where persistent activity emerges, merely by increasing the SST+/PV+ ratio while keeping the input and recurrent excitation constant. The regime beyond such a phase transition renders the circuit increasingly sensitive to random fluctuations of the inputs -i.e., chaotic-, defining an optimal SST+/PV+ ratio around the edge-of-chaos. Further, we show that both the optimal SST+/PV+ ratio and the region of the phase transition decrease monotonically with increasing input noise. This suggests that cortical circuits regulate their intrinsic dynamics via inhibitory interneurons to attain optimal sensitivity in the face of varying uncertainty. Hence, on the one hand, we link the emergence of supercritical dynamics at the edge-of-chaos to the gradient of the SST+/PV+ ratio along the cortical hierarchy, and, on the other hand, explain the behavioral effects of the differential regulation of SST+ and PV+ interneurons by neuromodulators like acetylcholine in the presence of input uncertainty.

JTD Keywords: attractor model, cortex, cortical networks, edge-of-chaos, model, nmda receptors, Attractor model, Cortical hierarchies, Decision making, Dynamics, Edge of chaos, Edge-of-chaos, High-order, Higher-order, Inhibitory interneurons, Neurons, Optimal decision making, Persistent activities, Persistent activity, Supercritical, Supercriticality

Patients with spinal cord injury (SCI) have an increased risk of sleep-disordered breathing (SDB), which can lead to serious comorbidities and impact patients’ recovery and quality of life. However, sleep tests are rarely performed on SCI patients, given their multiple health needs and the cost and complexity of diagnostic equipment. The objective of this study was to use a novel smartphone system as a simple non-invasive tool to monitor SDB in SCI patients. We recorded pulse oximetry, acoustic, and accelerometer data using a smartphone during overnight tests in 19 SCI patients and 19 able-bodied controls. Then, we analyzed these signals with automatic algorithms to detect desaturation, apnea, and hypopnea events and monitor sleep position. The apnea–hypopnea index (AHI) was significantly higher in SCI patients than controls (25 ± 15 vs. 9 ± 7, p < 0.001). We found that 63% of SCI patients had moderate-to-severe SDB (AHI ? 15) in contrast to 21% of control subjects. Most SCI patients slept predominantly in supine position, but an increased occurrence of events in supine position was only observed for eight patients. This study highlights the problem of SDB in SCI and provides simple cost-effective sleep monitoring tools to facilitate the detection, understanding, and management of SDB in SCI patients.

JTD Keywords: apnea syndrome, biomedical signal processing, individuals, mhealth, monitoring, nasal resistance, people, position, prevalence, questionnaire, sample, sleep apnea, sleep position, sleep-disordered breathing, smartphone, time, Apnea-hypopnea indices, Biomedical signal processing, Biomedical signals processing, Cost effectiveness, Diagnosis, Mhealth, Monitoring, Noninvasive medical procedures, Oximeters, Oxygen-saturation, Patient rehabilitation, Simple++, Sleep apnea, Sleep position, Sleep research, Sleep-disordered breathing, Smart phones, Smartphone, Smartphones, Spinal cord injury, Spinal cord injury patients

© The Author(s) 2021. Background: The negative discrepancy between residual functional capacity and reduced use of the contralesional hand, frequently observed after a brain lesion, has been termed Learned Non-Use (LNU) and is thought to depend on the interaction of neuronal mechanisms during recovery and learning-dependent mechanisms. Objective: Albeit the LNU phenomenon is generally accepted to exist, currently, no transdisciplinary definition exists. Furthermore, although therapeutic approaches are implemented in clinical practice targeting LNU, no standardized diagnostic routine is described in the available literature. Our objective was to reach consensus regarding a definition as well as synthesize knowledge about the current diagnostic procedures. Methods: We used a structured group communication following the Delphi method among clinical and scientific experts in the field, knowledge from both, the work with patient populations and with animal models. Results: Consensus was reached regarding a transdisciplinary definition of the LNU phenomenon. Furthermore, the mode and strategy of the diagnostic process, as well as the sources of information and outcome parameters relevant for the clinical decision making, were described with a wide range showing the current lack of a consistent universal diagnostic approach. Conclusions: The need for the development of a structured diagnostic procedure and its implementation into clinical practice is emphasized. Moreover, it exists a striking gap between the prevailing hypotheses regarding the mechanisms underlying the LNU phenomenon and the actual evidence. Therefore, basic research is needed to bridge between bedside and bench and eventually improve clinical decision making and further development of interventional strategies beyond the field of stroke rehabilitation.

JTD Keywords: diagnosis, experience-dependent non-use, perceptual disorders, rehabilitation, sensorimotor learning, Diagnosis, Experience-dependent non-use, Perceptual disorders, Rehabilitation, Sensorimotor learning

In the present study the use of extracellular vesicles (EVs) as vehicles for therapeutic enzymes in lysosomal storage disorders was explored. EVs were isolated from mammalian cells overexpressing alpha-galactosidase A (GLA) or N-sulfoglucosamine sulfohydrolase (SGSH) enzymes, defective in Fabry and Sanfilippo A diseases, respectively. Direct purification of EVs from cell supernatants was found to be a simple and efficient method to obtain highly active GLA and SGSH proteins, even after EV lyophilization. Likewise, EVs carrying GLA (EV-GLA) were rapidly uptaken and reached the lysosomes in cellular models of Fabry disease, restoring lysosomal functionality much more efficiently than the recombinant enzyme in clinical use. In vivo, EVs were well tolerated and distributed among all main organs, including the brain. DiR-labelled EVs were localized in brain parenchyma 1 h after intra-arterial (internal carotid artery) or intravenous (tail vein) administrations. Moreover, a single intravenous administration of EV-GLA was able to reduce globotriaosylceramide (Gb3) substrate levels in clinically relevant tissues, such kidneys and brain. Overall, our results demonstrate that EVs from cells overexpressing lysosomal enzymes act as natural protein delivery systems, improving the activity and the efficacy of the recombinant proteins and facilitating their access to organs neglected by conventional enzyme replacement therapies.

JTD Keywords: alpha?galactosidase a, alpha‐galactosidase a, drug delivery, enzyme replacement therapy, fabry disease, lysosomal storage disorders, n-sulfoglucosamine sulfohydrolase, n?sulfoglucosamine sulfohydrolase, n‐sulfoglucosamine sulfohydrolase, sanfilippo syndrome, Alpha-galactosidase a, Drug delivery, Enzyme replacement therapy, Fabry disease, Lysosomal storage disorders, N-sulfoglucosamine sulfohydrolase, Sanfilippo syndrome

Objective: Starting from the controversial results showed by empirical research on Linehan’s Biosocial model of Borderline Personality Disorder (BPD), this study aims to empirically evaluate Linehan’s conceptualization of emotional hypersensitivity and hyperreactivity, as well as to investigate the role of pre-existing emotional states in BPD altered physiological responsivity. Methods: We asked 24 participants (BPD = 12; Healthy Controls = 12) to complete a self-reported questionnaire (Positive and Negative Affect Schedule) in order to assess their pre-task affective state. Subsequently, 36 emotional pictures from four valence categories (i.e. erotic, negative, positive, neutral) were administered while assessing participants self-reported and electrodermal responses. Results: BPD patients showed higher levels of pre-task negative affectivity as well as an enhanced physiological response to neutral stimuli. No main BPD group effect was found for the physiological data. Moreover, pre-task negative affectivity levels were exclusively related to physiological responses among BPD subjects. Discussion: Our findings supported the hypersensitivity hypothesis operationalized as an enhanced responsiveness to non-emotional cues. Hyperreactivity assumption was not supported. Conversely, our study revealed heightened physiological responses in relation to pre-existent negative emotional states in BPD. We discussed our results in the context of the putative pathological processes underlying BPD.

JTD Keywords: Borderline Personality Disorder, Biosocial model, Hyperreactivity, Hypersensitivity, Negative affectivity, Physiology.

Ambroxol is a pharmacological chaperone (PC) for Gaucher disease that increases lysosomal activity of misfolded β-glucocerebrosidase (GCase) while displaying a safe toxicological profile. In this work, different poly(ε-caprolactone) (PCL)-based systems are developed to regulate the sustained release of small polar drugs in physiological environments. For this purpose, ambroxol is selected as test case since the encapsulation and release of PCs using polymeric scaffolds have not been explored yet. More specifically, ambroxol is successfully loaded in electrospun PCL microfibers, which are subsequently coated with additional PCL layers using dip-coating or spin-coating. The time needed to achieve 80% release of loaded ambroxol increases from ≈15 min for uncoated fibrous scaffolds to 3 days and 1 week for dip-coated and spin-coated systems, respectively. Furthermore, it is proven that the released drug maintains its bioactivity, protecting GCase against induced thermal denaturation.

JTD Keywords: Electrospinning, Gaucher's disease, Lysosomal storage disorders, Misfolding diseases, Poly(ε-caprolactone), Polyester, Release regulation

Background: Many experimental studies have evaluated Linehan’s biological emotional vulnerability in Borderline Personality Disorder (BPD). However, some inconsistencies were observed in operationalizing and supporting its components. This study aims at clarifying which aspects of Linehan’s model are altered in BPD, considering a multimodal evaluation of processes concerned with emotional responsiveness (self-report, psychophysiology and eye-tracking). Methods: Forty-eight socio-emotional pictures were administered to 28 participants (14 BPD, 14 Healthy Controls, HCs), gender- and age-matched, by employing two different lengths of stimuli exposure (5 s and 15 s). Results: Our results supported the hypersensitivity hypothesis in terms of faster physiological responses and altered visual processing. Furthermore, hypersensitivity was associated with detailed socio-emotional contents. Hyperreactivity assumption was not experimentally sustained by physiological and self-report data. Ultimately, the slow return to emotional baseline was demonstrated as an impaired emotional modulation. Conclusions: Our data alternatively supported the hypersensitivity and the slow return to emotional baseline hypotheses, postulated by Linehan’s Biosocial model, rather than the hyperreactivity assumption. Results have been discussed in light of other BPD core psychopathological processes.

JTD Keywords: Borderline personality disorder, Emotional vulnerability, Linehan’s model, Hypersensitivity, Slow return to emotional baseline

Obstructive Sleep Apnea severity is commonly determined after a sleep polysomnographic study by the Apnea-Hypopnea Index (AHI). This index does not contain information about the duration of events, and weights apneas and hypopneas alike. Significant differences in disease severity have been reported in patients with the same AHI. The aim of this work was to study the effect of obstructive event type and duration on the subsequent oxygen desaturation (SaO2) by mixed-effects models. These models allow continuous and categorical independent variables and can model within-subject variability through random effects. The desaturation depth dSaO2, desaturation duration dtSaO2 and desaturation area dSaO2A were analyzed in the 2022 apneas and hypopneas of eight severe patients. A mixed-effects model was defined to account for the influence of event duration (AD), event type, and their interaction on SaO2 parameters. A two-step backward model reduction process was applied for random and fixed effects optimization. The optimum model obtained for dtSaO2 suggests an almost subject-independent proportion increase with AD, which did not significantly change in apneas as compared to hypopneas. The optimum model for dSaO2 reveals a significantly higher increase as a function of AD in apneas than hypopneas. Dependence of on event type and duration was different in every subject, and a subject-specific model could be obtained. The optimum model for SaO2A combines the effects of the other two. In conclusion, the proposed mixed-effects models for SaO2 parameters allow to study the effect of respiratory event duration and type, and to include repeated events within each subject. This simple model can be easily extended to include the contribution of other important factors such as patient severity, sleep stage, sleeping position, or the presence of arousals.

JTD Keywords: Biological system modeling, Sleep apnea, Mathematical model, Indexes, Reduced order systems, Optimization

Prions are a singular subset of proteins able to switch between a soluble conformation and a self-perpetuating amyloid state. Traditionally associated with neurodegenerative diseases, increasing evidence indicates that organisms exploit prion-like mechanisms for beneficial purposes. The ability to transit between conformations is encoded in the so-called prion domains, long disordered regions usually enriched in glutamine/asparagines residues. Interestingly, Plasmodium falciparum, the parasite that causes the most virulent form of malaria, is exceptionally rich in proteins bearing long Q/N-rich sequence stretches, accounting for roughly 30% of the proteome. This biased composition suggests that these protein regions might correspond to prion-like domains (PrLDs) and potentially form amyloid assemblies. To investigate this possibility, we performed a stringent computational survey for Q/N-rich PrLDs on P. falciparum. Our data indicate that ~10% of P. falciparum protein sequences have prionic signatures, and that this subproteome is enriched in regulatory proteins, such as transcription factors and RNA-binding proteins. Furthermore, we experimentally demonstrate for several of the identified PrLDs that, despite their disordered nature, they contain inner short sequences able to spontaneously self-assemble into amyloid-like structures. Although the ability of these sequences to nucleate the conformational conversion of the respective full-length proteins should still be demonstrated, our analysis suggests that, as previously described for other organisms, prion-like proteins might also play a functional role in P. falciparum.

JTD Keywords: Plasmodium, Protein aggregation, Amyloid, Prion, Q-N-rich sequences, Protein Disorder

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

Background: Most stroke survivors continue to experience motor impairments even after hospital discharge. Virtual reality-based techniques have shown potential for rehabilitative training of these motor impairments. Here we assess the impact of at-home VR-based motor training on functional motor recovery, corticospinal excitability and cortical reorganization. Objective: The aim of this study was to identify the effects of home-based VR-based motor rehabilitation on (1) cortical reorganization, (2) corticospinal tract, and (3) functional recovery after stroke in comparison to home-based occupational therapy. Methods: We conducted a parallel-group, controlled trial to compare the effectiveness of domiciliary VR-based therapy with occupational therapy in inducing motor recovery of the upper extremities. A total of 35 participants with chronic stroke underwent 3 weeks of home-based treatment. A group of subjects was trained using a VR-based system for motor rehabilitation, while the control group followed a conventional therapy. Motor function was evaluated at baseline, after the intervention, and at 12-weeks follow-up. In a subgroup of subjects, we used Navigated Brain Stimulation (NBS) procedures to measure the effect of the interventions on corticospinal excitability and cortical reorganization. Results: Results from the system?s recordings and clinical evaluation showed significantly greater functional recovery for the experimental group when compared with the control group (1.53, SD 2.4 in Chedoke Arm and Hand Activity Inventory). However, functional improvements did not reach clinical significance. After the therapy, physiological measures obtained from a subgroup of subjects revealed an increased corticospinal excitability for distal muscles driven by the pathological hemisphere, that is, abductor pollicis brevis. We also observed a displacement of the centroid of the cortical map for each tested muscle in the damaged hemisphere, which strongly correlated with improvements in clinical scales. Conclusions: These findings suggest that, in chronic stages, remote delivery of customized VR-based motor training promotes functional gains that are accompanied by neuroplastic changes. Trial Registration: International Standard Randomized Controlled Trial Number NCT02699398 (Archived by ClinicalTrials.gov at https://clinicaltrials.gov/ct2/show/NCT02699398?term=NCT02699398&rank=1)

JTD Keywords: Stroke, Movement disorder, Recovery of function, neuroplasticity, Transcranial magnetic stimulation, Physical therapy, Hemiparesis, Computer applications software

Many hippocampal cell types are characterized by a progressive increase in scale along the dorsal-to-ventral axis, such as in the cases of head-direction, grid and place cells. Also located in the medial entorhinal cortex (MEC), border cells would be expected to benefit from such scale modulations. However, this phenomenon has not been experimentally observed. Grid cells in the MEC of mammals integrate velocity related signals to map the environment with characteristic hexagonal tessellation patterns. Due to the noisy nature of these input signals, path integration processes tend to accumulate errors as animals explore the environment, leading to a loss of grid-like activity. It has been suggested that border-to-grid cells' associations minimize the accumulated grid cells' error when rodents explore enclosures. Thus, the border-grid interaction for error minimization is a suitable scenario to study the effects of border cell scaling within the context of spatial representation. In this study, we computationally address the question of (i) border cells' scale from the perspective of their role in maintaining the regularity of grid cells' firing fields, as well as (ii) what are the underlying mechanisms of grid-border associations relative to the scales of both grid and border cells. Our results suggest that for optimal contribution to grid cells' error minimization, border cells should express smaller firing fields relative to those of the associated grid cells, which is consistent with the hypothesis of border cells functioning as spatial anchoring signals.

JTD Keywords: Border cells, Error minimization, Grid cells, Navigation, Path integration

Among the most common sleep disorders are those related to disruptions in airflow (apnea) or reductions in the breath amplitude (hypopnea) with or without obstruction of the upper airway (UA). One of the most important sleep disorders is obstructive sleep apnea (OSA). This sleep-disordered breathing, quantified by the apnea-hypopnea index (AHI), can produce a significant reduction of oxygen saturation and an abnormal elevation of carbon dioxide levels in the blood. Apnea and hypopnea episodes are associated with arousals and sleep fragmentation during the night and compensatory response of the autonomic nervous system.

JTD Keywords: Biomedical engineering, Biomedical measurements, Biomedical monitoring, Breathing disorders, Medical conditions, Medical treatment, Sleep, Sleep apnea

Background: The identification of obstructive and central hypopneas is considered challenging in clinical practice. Presently, obstructive and central hypopneas are usually not differentiated or scores lack reliability due to the technical limitations of standard polysomnography. Esophageal pressure measurement is the gold-standard for identifying these events but its invasiveness deters its usage in daily practice. Objectives: To determine the feasibility and efficacy of an automatic noninvasive analysis method for the differentiation of obstructive and central hypopneas based solely on a single-channel nasal airflow signal. The obtained results are compared with gold-standard esophageal pressure scores. Methods: A total of 41 patients underwent full night polysomnography with systematic esophageal pressure recording. Two experts in sleep medicine independently differentiated hypopneas with the gold-standard esophageal pressure signal. Features were automatically extracted from the nasal airflow signal of each annotated hypopnea to train and test the automatic analysis method. Interscorer agreement between automatic and visual scorers was measured with Cohen's kappa statistic (κ). Results: A total of 1,237 hypopneas were visually differentiated. The automatic analysis achieved an interscorer agreement of κ = 0.37 and an accuracy of 69% for scorer A, κ = 0.40 and 70% for scorer B and κ = 0.41 and 71% for the agreed scores of scorers A and B. Conclusions: The promising results obtained in this pilot study demonstrate the feasibility of noninvasive single-channel hypopnea differentiation. Further development of this method may help improving initial diagnosis with home screening devices and offering a means of therapy selection and/or control.

JTD Keywords: Central sleep hypopnea, Esophageal pressure, Home monitoring, Obstructive sleep hypopnea, Sleep disordered breathing

Ischemic and dilated cardiomyopathy are associated with disorders of myocardium. Using the blood pressure (BP) signal and the values of the ventricular ejection fraction, we obtained parameters for stratifying cardiomyopathy patients as low- and high-risk. We studied 48 cardiomyopathy patients characterized by NYHA ≥2: 19 patients with dilated cardiomyopathy (DCM) and 29 patients with ischemic cardiomyopathy (ICM). The left ventricular ejection fraction (LVEF) percentage was used to classify patients in low risk (LR: LVEF > 35%, 17 patients) and high risk (HR: LVEF ≤ 35%, 31 patients) groups. From the BP signal, we extracted the upward systolic slope (BP_sl), the difference between systolic and diastolic BP (BPA), and systolic time intervals (STI). When we compared the LR and HR groups in the time domain analysis, the best parameters were standard deviation (SD) of 1=STI, kurtosis (K) of BP_sl, and K of BPA. In the frequency domain analysis, very low frequency (VLF) and high frequency (HF) bands showed statistically significant differences in comaprisons of LR and HR groups. The area under the curve of power spectral density was the best parameter in all classifications, and particularly in the very-low-and high- frequency bands (p <; 0.001). These parameters could help to improve the risk stratification of cardiomyopathy patients.

JTD Keywords: blood pressure measurement, cardiovascular system, diseases, medical disorders, medical signal processing, statistical analysis, time-domain analysis, BP signal, HR groups, LR groups, blood pressure signal analysis, cardiomyopathy patients, diastolic BP, dilated cardiomyopathy, frequency domain analysis, high-frequency bands, ischemic cardiomyopathy, left ventricular ejection fraction, low-frequency bands, myocardium disorders, patient characterization, power spectral density curve, standard deviation, statistical significant differences, systolic BP, systolic slope, systolic time intervals, time domain analysis, ventricular ejection fraction, Abstracts, Databases, Parameter extraction, Telecommunication standards, Time-frequency analysis

Rat model of Obstructive Sleep Apnea (OSA) is a realistic approach for studying physiological mechanisms involved in sleep. Rats are usually anesthetized and autonomic nervous system (ANS) could be blocked. This study aimed to assess the effect of anesthesia on ANS activity during OSA episodes. Seven male Sprague-Dawley rats were anesthetized intraperitoneally with urethane (1g/kg). The experiments were conducted applying airway obstructions, simulating 15s-apnea episodes for 15 minutes. Five signals were acquired: respiratory pressure and flow, SaO2, ECG and photoplethysmography (PPG). In total, 210 apnea episodes were studied. Normalized power spectrum of Pulse Rate Variability (PRV) was analyzed in the Low Frequency (LF) and High Frequency (HF) bands, for each episode in consecutive 15s intervals (before, during and after the apnea). All episodes showed changes in respiratory flow and SaO₂ signal. Conversely, decreases in the amplitude fluctuations of PPG (DAP) were not observed. Normalized LF presented extremely low values during breathing (median=7,67%), suggesting inhibition of sympathetic system due to anesthetic effect. Subtle increases of LF were observed during apnea. HRV and PPG analysis during apnea could be an indirect tool to assess the effect and deep of anesthesia.

JTD Keywords: electrocardiography, fluctuations, medical disorders, medical signal detection, medical signal processing, neurophysiology, photoplethysmography, pneumodynamics, sleep, ECG, SaO₂ flow, SaO₂ signal, airway obstructions, amplitude fluctuations, anesthesia effects, anesthetized nervous system, autonomic evaluation, autonomic nervous system, breathing, heart rate variability, high-frequency bands, low-frequency bands, male Sprague-Dawley rats, normalized power spectrum, obstructive sleep apnea, photoplethysmography, physiological mechanisms, pulse rate variability, rat model, respiratory flow, respiratory pressure, signal acquisition, sympathetic system inhibition, time 15 min, time 15 s, Abstracts, Atmospheric modeling, Computational modeling, Electrocardiography, Rats, Resonant frequency

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

Objective: Patients with idiopathic rapid eye movement (REM) sleep behavior disorder (IRBD) may show electroencephalographic (EEG) slowing reflecting cortical dysfunction and are at risk for developing neurological conditions characterized by cognitive dysfunction including mild cognitive impairment (MCI), dementia with Lewy bodies and Parkinson's disease with associated dementia. We hypothesized that those IRBD patients who later developed MCI had pronounced cortical EEG slowing at presentation. Methods: Power EEG spectral analysis was blindly quantified from the polysomnographic studies of 23 IRBD patients without cognitive complaints and 10 healthy controls without RBD. After a mean clinical follow-up of 2.40 +/- 1.55 years, 10 patients developed MCI (RBD + MCI) and the remaining 13 remained idiopathic. Results: Patients with RBD + MCI had marked EEG slowing (increased delta and theta activity) in central and occipital regions during wakefulness and REM sleep, particularly in the right hemisphere, when compared with controls and, to a lesser extent, with IRBD subjects who remained idiopathic. The EEG spectral pattern of the RBD + MCI group was similar to that seen in patients with dementia with Lewy bodies and Parkinson's disease associated with dementia. Conclusion: Our findings suggest that the presence of marked EEG slowing on spectral analysis might be indicative of the short-term development of MCI in patients initially diagnosed with IRBD.

JTD Keywords: Idiopathic REM sleep behavior disorder, Power EEG spectral analysis, Mild cognitive impairment, REM sleep, Parkinson's disease, Dementia with Lewy bodies

The differentiation of obstructive and central respiratory events is a major challenge in the diagnosis of sleep disordered breathing. Esophageal pressure (Pes) measurement is the gold-standard method to identify these events but its invasiveness deters its usage in clinical routine. Flattening patterns appear in the airflow signal during episodes of inspiratory flow limitation (IFL) and have been shown with invasive techniques to be useful to differentiate between central and obstructive hypopneas. In this study we present a new method for the automatic non-invasive differentiation of obstructive and central hypopneas solely with nasal airflow. An overall of 36 patients underwent full night polysomnography with systematic Pes recording and a total of 1069 hypopneas were manually scored by human experts to create a gold-standard annotation set. Features were automatically extracted from the nasal airflow signal to train and test our automatic classifier (Discriminant Analysis). Flattening patterns were non-invasively assessed in the airflow signal using spectral and time analysis. The automatic non-invasive classifier obtained a sensitivity of 0.71 and an accuracy of 0.69, similar to the results obtained with a manual non-invasive classification algorithm. Hence, flattening airflow patterns seem promising for the non-invasive differentiation of obstructive and central hypopneas.

JTD Keywords: Practical, Experimental/ biomedical measurement, Feature extraction, Flow measurement, Medical disorders, Medical signal processing, Patient diagnosis, Pneumodynamics, Pressure measurement, Signal classification, Sleep, Spectral analysis/ automatic noninvasive differentiation, Obstructive hypopnea, Central hypopnea, Inspiratory flow limitation, Nasal airflow, Esophageal pressure, Polysomnography, Feature extraction, Discriminant analysis, Spectral analysis