COVID-19 Detection Using Photoplethysmography and Neural Networks.

The early identification of microvascular changes in patients with Coronavirus Disease 2019 (COVID-19) may offer an important clinical opportunity. This study aimed to define a method, based on deep learning approaches, for the identification of COVID-19 patients from the analysis of the raw PPG signal, acquired with a pulse oximeter. To develop the method, we acquired the PPG signal of 93 COVID-19 patients and 90 healthy control subjects using a finger pulse oximeter. To select the good quality portions of the signal, we developed a template-matching method that excludes samples corrupted by noise or motion artefacts. These samples were subsequently used to develop a custom convolutional neural network model. The model accepts PPG signal segments as input and performs a binary classification between COVID-19 and control samples. The proposed model showed good performance in identifying COVID-19 patients, achieving 83.86% accuracy and 84.30% sensitivity (hold-out validation) on test data. The obtained results indicate that photoplethysmography may be a useful tool for microcirculation assessment and early recognition of SARS-CoV-2-induced microvascular changes. In addition, such a noninvasive and low-cost method is well suited for the development of a user-friendly system, potentially applicable even in resource-limited healthcare settings.

Fiber enhancement and 3D orientation analysis in label-free two-photon fluorescence microscopy.

Fluorescence microscopy can be exploited for evaluating the brain's fiber architecture with unsurpassed spatial resolution in combination with different tissue preparation and staining protocols. Differently from state-of-the-art polarimetry-based neuroimaging modalities, the quantification of fiber tract orientations from fluorescence microscopy volume images entails the application of specific image processing techniques, such as Fourier or structure tensor analysis. These, however, may lead to unreliable outcomes as they do not isolate myelinated fibers from the surrounding tissue. In this work, we describe a novel image processing pipeline that enables the computation of accurate 3D fiber orientation maps from both grey and white matter regions, exploiting the selective multiscale enhancement of tubular structures of varying diameters provided by a 3D implementation of the Frangi filter. The developed software tool can efficiently generate orientation distribution function maps at arbitrary spatial scales which may support the histological validation of modern diffusion-weighted magnetic resonance imaging tractography. Despite being tested here on two-photon scanning fluorescence microscopy images, acquired from tissue samples treated with a label-free technique enhancing the autofluorescence of myelinated fibers, the presented pipeline was developed to be employed on all types of 3D fluorescence images and fiber staining.

Morphological and Functional Effects of Ultrasound on Blood-Brain Barrier Transitory Opening: An In Vitro Study on Rat Brain Endothelial Cells.

With the recent advances in medicine, human life expectancy is increasing; however, the extra years of life are not necessarily spent in good health or free from disability, resulting in a significantly higher incidence of age-associated pathologies. Among these disorders, neurodegenerative diseases have a significant impact. To this end, the presence of the protective blood-brain barrier (BBB) represents a formidable obstacle to the delivery of therapeutics. Thus, this makes it imperative to define strategies to bypass the BBB in order to successfully target the brain with the appropriate drugs. It has been demonstrated that targeting the BBB by ultrasound (US) can transiently make this anatomical barrier permeable and in so doing, allow the delivery of therapeutics. Thus, our aim was to carry out an in depth in vitro molecular and morphological study on the effects of US treatment on the BBB. The rat brain endothelial (RBE4) cell line was challenged with exposure to 12 MHz diagnostic US treatment for 10, 20, and 30 min. Cell viability assays, Western blotting analysis on the endoplasmic reticulum (ER), and oxidative stress marker evaluation were then performed, along with cytological and immunofluorescence staining, in order to evaluate the effects of US on the intercellular spaces and tight junction distribution of the brain endothelial cells. We observed that the US treatment exerted no toxic effects on either RBE4 cell viability or the upregulation/dislocation of the ER and oxidative stress marker (GRP78 and cytochrome C, respectively). Further, we observed that the application of US induced an increase in the intercellular spaces, as shown by Papanicolaou staining, mainly due to the altered distribution of the tight junction protein zonula occludens-1 (ZO-1). This latter US-dependent effect was transient and disappeared 20 min after the removal of the stimulus. In conclusion, our results show that US induces a transient alteration of the BBB, without altering the intracellular signaling pathways such as the ER and oxidative stress that could potentially be toxic for endothelial cells. These results suggested that US treatment could represent a potential strategy for improving drug delivery to the brain.

The Assessment of Ankle Range-of-Motion and Its Relationship with Overall Muscle Strength in a Cross-Section of Soccer Players.

Soccer (football) practice can induce a limitation of ankle range of motion (ROM) that is a possible risk factor for injury and other negative consequences over time. The main objective of this research was to investigate the effects of soccer practice on ankle ROM throughout the entire period of a sports career of soccer players (SP). Furthermore, the relationship between ankle ROM and muscle strength in SP of different ages was studied. A total of 204 SP (range 6.7−45.1 years) and 87 controls (range: 7.5−45.2 years) matched for age, body mass index (BMI), and gender, were assessed. Ankle ROM in both plantar flexion (APF) and dorsiflexion (ADF) in addition to handgrip strength (HGS) were evaluated using an inclinometer and the Jamar hydraulic hand dynamometer, respectively. The comparison between SP and control groups showed a significant reduction in ankle ROM of both APF (26.3 ± 7.2° vs. 32.6 ± 7.4°; d = −0.90; p < 0.001) and ADF (95.5 ± 15.6° vs. 105.5 ± 15.8°; d = −0.66; p < 0.001). In SP, the results of the ANOVAs test indicate that age had a significant effect on ADF (F = 4.352, p = 0.038, partial eta-squared (ηp2) = 0.015) but not on APF (F = 0.430, p = 0.746, ηp2 = 0.001). Moreover, considering only the SP, a weak inverse correlation between ADF and HGS group ADF was found (rs = −0.27; p < 0.001). Factors such as the non-linear trend of growth in young SP could hinder the definition of the relationship between ankle ROM, age, and muscle strength. However, the appropriate consideration of age and muscle strength could facilitate the management of ankle ROM in PF of different ages.

Automatic COVID-19 severity assessment from HRV.

COVID-19 is known to be a cause of microvascular disease imputable to, for instance, the cytokine storm inflammatory response and the consequent blood coagulation. In this study, we propose a methodological approach for assessing the COVID-19 presence and severity based on Random Forest (RF) and Support Vector Machine (SVM) classifiers. Classifiers were applied to Heart Rate Variability (HRV) parameters extracted from photoplethysmographic (PPG) signals collected from healthy and COVID-19 affected subjects. The supervised classifiers were trained and tested on HRV parameters obtained from the PPG signals in a cohort of 50 healthy subjects and 93 COVID-19 affected subjects, divided into two groups, mild and moderate, based on the support of oxygen therapy and/or ventilation. The most informative feature set for every group's comparison was determined with the Least Absolute Shrinkage and Selection Operator (LASSO) technique. Both RF and SVM classifiers showed a high accuracy percentage during groups' comparisons. In particular, the RF classifier reached 94% of accuracy during the comparison between the healthy and minor severity COVID-19 group. Obtained results showed a strong capability of RF and SVM to discriminate between healthy subjects and COVID-19 patients and to differentiate the two different COVID-19 severity. The proposed method might be helpful for detecting, in a low-cost and fast fashion, the presence and severity of COVID-19 disease; moreover, these reasons make this method interesting as a starting point for future studies that aim to investigate its effectiveness as a possible screening method.

In Vivo Treatment with a Standardized Green Tea Extract Restores Cardiomyocyte Contractility in Diabetic Rats by Improving Mitochondrial Function through SIRT1 Activation.

Background. Green tea catechins are known to promote mitochondrial function, and to modulate gene expression and signalling pathways that are altered in the diabetic heart. We thus evaluated the effectiveness of the in vivo administration of a standardized green tea extract (GTE) in restoring cardiac performance, in a rat model of early streptozotocin-induced diabetes, with a focus on the underlying mechanisms. Methods. Twenty-five male adult Wistar rats were studied: the control (n = 9), untreated diabetic animals (n = 7) and diabetic rats subjected to daily GTE administration for 28 days (n = 9). Isolated ventricular cardiomyocytes were used for ex vivo measurements of cell mechanics and calcium transients, and molecular assays, including the analysis of functional protein and specific miRNA expression. Results. GTE treatment induced an almost complete recovery of cardiomyocyte contractility that was markedly impaired in the diabetic cells, by preserving mitochondrial function and energy availability, and modulating the expression of the sarcoplasmic reticulum calcium ATPase and phospholamban. Increased Sirtuin 1 (SIRT1) expression and activity substantially contributed to the observed cardioprotective effects. Conclusions. The data supported the hypothesis that green tea dietary polyphenols, by targeting SIRT1, can constitute an adjuvant strategy for counteracting the initial damage of the diabetic heart, before the occurrence of diabetic cardiomyopathy.

Classifying sepsis from photoplethysmography.

Sepsis is a life-threatening organ dysfunction. It is caused by a dysregulated immune response to an infection and is one of the leading causes of death in the intensive care unit (ICU). Early detection and treatment of sepsis can increase the survival rate of patients. The use of devices such as the photoplethysmograph could allow the early evaluation in addition to continuous monitoring of septic patients. The aim of this study was to verify the possibility of detecting sepsis in patients from whom the photoplethysmographic signal was acquired via a pulse oximeter. In this work, we developed a deep learning-based model for sepsis identification. The model takes a single input, the photoplethysmographic signal acquired by pulse oximeter, and performs a binary classification between septic and nonseptic samples. To develop the method, we used MIMIC-III database, which contains data from ICU patients. Specifically, the selected dataset includes 85 septic subjects and 101 control subjects. The PPG signals acquired from these patients were segmented, processed and used as input for the developed model with the aim of identifying sepsis. The proposed method achieved an accuracy of 76.37% with a sensitivity of 70.95% and a specificity of 81.04% on the test set. As regards the ROC curve, the Area Under Curve reached a value of 0.842. The results of this study indicate how the plethysmographic signal can be used as a warning sign for the early detection of sepsis with the aim of reducing the time for diagnosis and therapeutic intervention. Furthermore, the proposed method is suitable for integration in continuous patient monitoring.

COVID-19 detection using a model of photoplethysmography (PPG) signals.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) targets several tissues of the human body; among these, a serious impact has been observed in the microvascular system. The aim of this study was to verify the presence of photoplethysmographic (PPG) signal modifications in patients affected by COVID-19 at different levels of severity. APPROACH: The photoplethysmographic signal was evaluated in 93 patients with COVID-19 of different severity (46: grade 1; 47: grade 2) and in 50 healthy control subjects. A pre-processing step removes the long-term trend and segments of each pulsation in the input signal. Each pulse is approximated with a model generated from a multi-exponential curve, and a Least Squares fitting algorithm determines the optimal model parameters. Using the parameters of the mathematical model, three different classifiers (Bayesian, SVM and KNN) were trained and tested to discriminate among healthy controls and patients with COVID, stratified according to the severity of the disease. Results are validated with the leave-one-subject-out validation method. MAIN RESULTS: Results indicate that the fitting procedure obtains a very high determination coefficient (above 99% in both controls and pathological subjects). The proposed Bayesian classifier obtains promising results, given the size of the dataset, and variable depending on the classification strategy. The optimal classification strategy corresponds to 79% of accuracy, with 90% of specificity and 67% of sensibility. SIGNIFICANCE: The proposed approach opens the possibility of introducing a low cost and non-invasive screening procedure for the fast detection of COVID-19 disease, as well as a promising monitoring tool for hospitalized patients, with the purpose of stratifying the severity of the disease.

Decline of cardiomyocyte contractile performance and bioenergetic function in socially stressed male rats.

Chronic social stress has been epidemiologically linked to increased risk for cardiovascular disease, yet the underlying pathophysiological mechanisms are still largely elusive. Mitochondrial (dys)function represents a potential intersection point between social stress exposure and (mal)adaptive cardiac responses. In this study, we used a rodent model of social stress to study the extent to which alterations in the cellular mechanical properties of the heart were associated with changes in indexes of mitochondrial function. Male adult rats were exposed to repeated episodes of social defeat stress or left undisturbed (controls). ECG signals were recorded during and after social defeat stress. Twenty-four hours after the last social defeat, cardiomyocytes were isolated for analyses of mechanical properties and intracellular Ca2+ dynamics, mitochondrial respiration, and ATP content. Results indicated that social defeat stress induced potent cardiac sympathetic activation that lasted well beyond stress exposure. Moreover, cardiomyocytes of stressed rats showed poor contractile performance (e.g., slower contraction and relaxation rates) and intracellular Ca2+ derangement (e.g., slower Ca2+ clearing), which were associated with indexes of reduced reserve respiratory capacity and decreased ATP production. In conclusion, this study suggests that repeated social stress provokes impaired cardiomyocyte contractile performance and signs of altered mitochondrial bioenergetics in the rat heart. Future studies are needed to clarify the causal link between cardiac and mitochondrial functional remodeling under conditions of chronic social stress.

Cardiovascular Dynamics in COVID-19: A Heart Rate Variability Investigation.

COVID-19 is known to be a cause of microvascular disease due, for example, to the cytokine storm inflammatory response and the result of blood coagulation. This study reports an investigation on Heart Rate Variability (HRV) extracted from photoplethysmography (PPG) signals measured from healthy subjects and COVID-19 affected patients. We aimed to determine a statistical difference between HRV parameters among subjects' groups. Specifically, statistical analysis through Mann-Whitney U Test (MWUT) was applied to compare 42 dif-ferent parameters extracted from PPG signals of 143 subjects: 50 healthy subjects (i.e. group 0) and 93 affected from COVID-19 patients stratified through increasing COVID severity index (i.e. groups 1 and 2). Results showed significant statistical differences between groups in several HRV parameters. In particular, Multiscale Entropy (MSE) analysis provided the master key in patient stratification assessment. In fact, MSE11, MSE12, MSE15, MSE16, MSE17, MSE18, MSE19 and MSE20 keep statistical significant difference during all the comparisons between healthy subjects and patients from all the pathological groups. Our preliminary results suggest that it could be possible to distinguish between healthy and COVID-19 affected subjects based on cardiovascular dynamics. This study opens to future evaluations in using machine learning models for automatic decision-makers to distinguish between healthy and COVID-19 subjects, as well as within COVID-19 severity levels. Clinical Relevance - This establishes the possibility to distin-guish healthy subjects from COVID-19 affected patients basing on HRV parameters monitored non invasively by PPG.

Detecting sepsis from photoplethysmography: strategies for dataset preparation.

Sepsis is one of the most frequent causes of death in Intensive Care Units, and its prognosis greatly depend on timeliness of diagnosis. MIMIC-III database is a frequent source of data for developing method for automatic sepsis detection. However, the heterogeneity of data jeopardize the feasibility of the task. In this work we propose a selection strategy for generating high quality data suitable for training a sepsis detection system based on the utilization of only plethysmographic data. Clinical relevance A system for detecting sepsis based only on PPG may be potentially at virtually no cost in any case clinicians suspect the possibility of developing sepsis.

Mortality Risk Associated with Diabetic Foot Complications in People with or without History of Diabetic Foot Hospitalizations.

The aim of this study was to evaluate the risk of death after hospitalizations for diabetic foot (DF) complications, comparing two different cohorts of people with or without a prior history of DF hospitalizations across the years 2011 to 2018 in Tuscany, Italy. The DF complications were categorized by administrative source datasets such as: amputations (both major and minor), gangrene, ulcers, infections, Charcot and revascularizations. A further aim was to present the trend over time of the first ever incidents of diabetic foot hospitalizations in Tuscany. The eight-year-mortality rate was higher in the cohort with prior hospitalizations (n = 6633; 59%) compared with the cohort with first incident DF hospitalizations (n = 5028; 44%). Amputations (especially major ones) and ulcers had the worst effect on survival in people without basal history of DF hospitalizations and respectively in those with a history of prior DF hospitalizations. In both cohorts, revascularization procedures, when compared to ulcers, were associated with a significantly reduced risk of mortality. The prevalence rate of minor amputations showed a slightly rising trend over time. This result agrees with the national trend. Conversely, the progressive increase over time of revascularizations, associated with the fractional decrease in the rate of gangrene, suggests a trend for more proactive behavior by DF care teams in Tuscany.

Linear and Nonlinear Directed Connectivity Analysis of the Cardio-Respiratory System in Type 1 Diabetes.

In this study, we explored the possibility of developing non-invasive biomarkers for patients with type 1 diabetes (T1D) by quantifying the directional couplings between the cardiac, vascular, and respiratory systems, treating them as interconnected nodes in a network configuration. Towards this goal, we employed a linear directional connectivity measure, the directed transfer function (DTF), estimated by a linear multivariate autoregressive modelling of ECG, respiratory and skin perfusion signals, and a nonlinear method, the dynamical Bayesian inference (DBI) analysis of bivariate phase interactions. The physiological data were recorded concurrently for a relatively short time period (5 min) from 10 healthy control subjects and 10 T1D patients. We found that, in both control and T1D subjects, breathing had greater influence on the heart and perfusion with respect to the opposite coupling direction and that, by both employed methods of analysis, the causal influence of breathing on the heart was significantly decreased (p < 0.05) in T1D patients compared to the control group. These preliminary results, although obtained from a limited number of subjects, provide a strong indication for the usefulness of a network-based multi-modal analysis for the development of biomarkers of T1D-related complications from short-duration data, as well as their potential in the exploration of the pathophysiological mechanisms that underlie this devastating and very widespread disease.

Quantification of Myocyte Disarray in Human Cardiac Tissue.

Proper three-dimensional (3D)-cardiomyocyte orientation is important for an effective tension production in cardiac muscle. Cardiac diseases can cause severe remodeling processes in the heart, such as cellular misalignment, that can affect both the electrical and mechanical functions of the organ. To date, a proven methodology to map and quantify myocytes disarray in massive samples is missing. In this study, we present an experimental pipeline to reconstruct and analyze the 3D cardiomyocyte architecture in massive samples. We employed tissue clearing, staining, and advanced microscopy techniques to detect sarcomeres in relatively large human myocardial strips with micrometric resolution. Z-bands periodicity was exploited in a frequency analysis approach to extract the 3D myofilament orientation, providing an orientation map used to characterize the tissue organization at different spatial scales. As a proof-of-principle, we applied the proposed method to healthy and pathologically remodeled human cardiac tissue strips. Preliminary results suggest the reliability of the method: strips from a healthy donor are characterized by a well-organized tissue, where the local disarray is log-normally distributed and slightly depends on the spatial scale of analysis; on the contrary, pathological strips show pronounced tissue disorganization, characterized by local disarray significantly dependent on the spatial scale of analysis. A virtual sample generator is developed to link this multi-scale disarray analysis with the underlying cellular architecture. This approach allowed us to quantitatively assess tissue organization in terms of 3D myocyte angular dispersion and may pave the way for developing novel predictive models based on structural data at cellular resolution.

The Role of New Technological Opportunities and the Need to Evaluate the Activities Performed in the Prevention of Diabetic Foot with Exercise Therapy.

The diabetic foot (DF) is one of the most feared conditions among chronic complications of diabetes, which affects a growing number of patients. Although exercise therapy (ET) has always been considered a pillar in the treatment of patients at risk of DF it is not usually used. Several causes can contribute to hindering both the organization of ET protocols for Diabetes Units and the participation in ET programs for patients at different levels of risk of foot ulceration. The risk of favoring the occurrence of ulcers and the absence of clear evidence on the role played by ET in the prevention of ulcers could be considered among the most important causes leading to the low application of ET. The increased availability of new technologies and in particular of systems and devices equipped with sensors can enable the remote monitoring and management of physical activity performed by patients. Consequently, they can become an opportunity for introducing the systematic use of ET for the treatment of patients at risk. Considering the complexity of the clinical conditions that patients at risk or with diabetic foot ulcer can show, the evaluation of how patients perform the ET proposed can consequently be very important. All this can contribute to improving the treatment of patients and avoiding possible adverse effects. The aim of this brief review was to describe that the use of new technologies and the assessment of the execution of the ET proposed allows an important step forward in the management of patients at risk.

Vascular ageing and peripheral pulse: an improved model for assessing their relationship.

Objective.Vascular ageing is associated with several alterations, including arterial stiffness and endothelial dysfunction. Such alterations represent an independent factor in the development of cardiovascular disease (CVD). In our previous works we demonstrated the alterations occurring in the vascular system are themselves reflected in the shape of the peripheral waveform; thus, a model that describes the waveform as a sum of Gaussian curves provides a set of parameters that successfully discriminate betweenunder(≤35 years old) andoversubjects (>35 years old). In the present work, we explored the feasibility of a new decomposition model, based on a sum of exponential pulses, applied to the same problem.Approach.The first processing step extracts each pulsation from the input signal and removes the long-term trend using a cubic spline with nodes between consecutive pulsations. After that, a Least Squares fitting algorithm determines the set of optimal model parameters that best approximates each single pulse. The vector of model parameters gives a compact representation of the pulse waveform that constitutes the basis for the classification step. Each subject is associated to his/her 'representative' pulse waveform, obtained by averaging the vector parameters corresponding to all pulses. Finally, a Bayesan classifier has been designed to discriminate the waveforms of under and over subjects, using the leave-one-subject-out validation method.Main results.Results indicate that the fitting procedure reaches a rate of 96% in under subjects and 95% in over subjects and that the Bayesan classifier is able to correctly classify 91% of the subjects with a specificity of 94% and a sensibility of 84%.Significance.This study shows a sensible vascular age estimation accuracy with a multi-exponential model, which may help to predict CVD.

Monitoring Flexions and Torsions of the Trunk via Gyroscope-Calibrated Capacitive Elastomeric Wearable Sensors.

Reliable, easy-to-use, and cost-effective wearable sensors are desirable for continuous measurements of flexions and torsions of the trunk, in order to assess risks and prevent injuries related to body movements in various contexts. Piezo-capacitive stretch sensors, made of dielectric elastomer membranes coated with compliant electrodes, have recently been described as a wearable, lightweight and low-cost technology to monitor body kinematics. An increase of their capacitance upon stretching can be used to sense angular movements. Here, we report on a wearable wireless system that, using two sensing stripes arranged on shoulder straps, can detect flexions and torsions of the trunk, following a simple and fast calibration with a conventional tri-axial gyroscope on board. The piezo-capacitive sensors avoid the errors that would be introduced by continuous sensing with a gyroscope, due to its typical drift. Relative to stereophotogrammetry (non-wearable standard system for motion capture), pure flexions and pure torsions could be detected by the piezo-capacitive sensors with a root mean square error of ~8° and ~12°, respectively, whilst for flexion and torsion components in compound movements, the error was ~13° and ~15°, respectively.

Wearable Detection of Trunk Flexions: Capacitive Elastomeric Sensors Compared to Inertial Sensors.

Continuous monitoring of flexions of the trunk via wearable sensors could help various types of workers to reduce risks associated with incorrect postures and movements. Stretchable piezo-capacitive elastomeric sensors based on dielectric elastomers have recently been described as a wearable, lightweight and cost-effective technology to monitor human kinematics. Their stretching causes an increase of capacitance, which can be related to angular movements. Here, we describe a wearable wireless system to detect flexions of the trunk, based on such sensors. In particular, we present: (i) a comparison of different calibration strategies for the capacitive sensors, using either an accelerometer or a gyroscope as an inclinometer; (ii) a comparison of the capacitive sensors' performance with those of the accelerometer and gyroscope; to that aim, the three types of sensors were evaluated relative to stereophotogrammetry. Compared to the gyroscope, the capacitive sensors showed a higher accuracy. Compared to the accelerometer, their performance was lower when used as quasi-static inclinometers but also higher in case of highly dynamic accelerations. This makes the capacitive sensors attractive as a complementary, rather than alternative, technology to inertial sensors.

Elevated miR-34a expression and altered transcriptional profile are associated with adverse electromechanical remodeling in the heart of male rats exposed to social stress.

This study investigated epigenetic risk factors that may contribute to stress-related cardiac disease in a rodent model. Experiment 1 was designed to evaluate the expression of microRNA-34a (miR-34a), a known modulator of both stress responses and cardiac pathophysiology, in the heart of male adult rats exposed to a single or repeated episodes of social defeat stress. Moreover, RNA sequencing was conducted to identify transcriptomic profile changes in the heart of repeatedly stressed rats. Experiment 2 was designed to assess cardiac electromechanical changes induced by repeated social defeat stress that may predispose rats to cardiac dysfunction. Results indicated a larger cardiac miR-34a expression after repeated social defeat stress compared to a control condition. This molecular modification was associated with increased vulnerability to pharmacologically induced arrhythmias and signs of systolic left ventricular dysfunction. Gene expression analysis identified clusters of differentially expressed genes in the heart of repeatedly stressed rats that are mainly associated with morphological and functional properties of the mitochondria and may be directly regulated by miR-34a. These results suggest the presence of an association between miR-34a overexpression and signs of adverse electromechanical remodeling in the heart of rats exposed to repeated social defeat stress, and point to compromised mitochondria efficiency as a potential mediator of this link. This rat model may provide a useful tool for investigating the causal relationship between miR-34a expression, mitochondrial (dys)function, and cardiac alterations under stressful conditions, which could have important implications in the context of stress-related cardiac disease.

Cobalt oxide nanoparticles induce oxidative stress and alter electromechanical function in rat ventricular myocytes.

BACKGROUND: Nanotoxicology is an increasingly relevant field and sound paradigms on how inhaled nanoparticles (NPs) interact with organs at the cellular level, causing harmful conditions, have yet to be established. This is particularly true in the case of the cardiovascular system, where experimental and clinical evidence shows morphological and functional damage associated with NP exposure. Giving the increasing interest on cobalt oxide (Co3O4) NPs applications in industrial and bio-medical fields, a detailed knowledge of the involved toxicological effects is required, in view of assessing health risk for subjects/workers daily exposed to nanomaterials. Specifically, it is of interest to evaluate whether NPs enter cardiac cells and interact with cell function. We addressed this issue by investigating the effect of acute exposure to Co3O4-NPs on excitation-contraction coupling in freshly isolated rat ventricular myocytes. RESULTS: Patch clamp analysis showed instability of resting membrane potential, decrease in membrane electrical capacitance, and dose-dependent decrease in action potential duration in cardiomyocytes acutely exposed to Co3O4-NPs. Motion detection and intracellular calcium fluorescence highlighted a parallel impairment of cell contractility in comparison with controls. Specifically, NP-treated cardiomyocytes exhibited a dose-dependent decrease in the fraction of shortening and in the maximal rate of shortening and re-lengthening, as well as a less efficient cytosolic calcium clearing and an increased tendency to develop spontaneous twitches. In addition, treatment with Co3O4-NPs strongly increased ROS accumulation and induced nuclear DNA damage in a dose dependent manner. Finally, transmission electron microscopy analysis demonstrated that acute exposure did lead to cellular internalization of NPs. CONCLUSIONS: Taken together, our observations indicate that Co3O4-NPs alter cardiomyocyte electromechanical efficiency and intracellular calcium handling, and induce ROS production resulting in oxidative stress that can be related to DNA damage and adverse effects on cardiomyocyte functionality.