UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization.

Adam-type algorithms have become a preferred choice for optimization in the deep learning setting; however, despite their success, their convergence is still not well understood. To this end, we introduce a unified framework for Adam-type algorithms, termed UAdam. It is equipped with a general form of the second-order moment, which makes it possible to include Adam and its existing and future variants as special cases, such as NAdam, AMSGrad, AdaBound, AdaFom, and Adan. The approach is supported by a rigorous convergence analysis of UAdam in the general nonconvex stochastic setting, showing that UAdam converges to the neighborhood of stationary points with a rate of O(1/T). Furthermore, the size of the neighborhood decreases as the parameter ß1 increases. Importantly, our analysis only requires the first-order momentum factor to be close enough to 1, without any restrictions on the second-order momentum factor. Theoretical results also reveal the convergence conditions of vanilla Adam, together with the selection of appropriate hyperparameters. This provides a theoretical guarantee for the analysis, applications, and further developments of the whole general class of Adam-type algorithms. Finally, several numerical experiments are provided to support our theoretical findings.

Lattice Boltzmann simulation of deformable fluid-filled bodies: progress and perspectives.

With the rapid development of studies involving droplet microfluidics, drug delivery, cell detection, and microparticle synthesis, among others, many scientists have invested significant efforts to model the flow of these fluid-filled bodies. Motivated by the intricate coupling between hydrodynamics and the interactions of fluid-filled bodies, several methods have been developed. The objective of this review is to present a compact foundation of the methods used in the literature in the context of lattice Boltzmann methods. For hydrodynamics, we focus on the lattice Boltzmann method due to its specific ability to treat time- and spatial-dependent boundary conditions and to incorporate new physical models in a computationally efficient way. We split the existing methods into two groups with regard to the interfacial boundary: fluid-structure and fluid-fluid methods. The fluid-structure methods are characterised by the coupling between fluid dynamics and mechanics of the flowing body, often used in applications involving membranes and similar flexible solid boundaries. We further divide fluid-structure-based methods into two subcategories, those which treat the fluid-structure boundary as a continuum medium and those that treat it as a discrete collection of individual springs and particles. Next, we discuss the fluid-fluid methods, particularly useful for the simulations of fluid-fluid interfaces. We focus on models for immiscible droplets and their interaction in a suspending fluid and describe benchmark tests to validate the models for fluid-filled bodies.

Directional dependence of the electronic and transport properties of biphenylene under strain conditions.

In this study, we investigated the electronic and electronic transport properties of biphenylene (BPN) using first-principles density functional theory (DFT) calculations combined with the non-equilibrium Green's function (NEGF) formalism. We have focused on understanding the electronic properties of BPN, and the anisotropic behavior of electronic transport upon external strain. We found the emergence of electronic stripes (ESs) on the BPN surface and the formation of type-II Dirac cone near the Fermi level. In the sequence, the electronic transport results reveal that such ESs dictate the anisotropic behavior of the transmission function. Finally, we show that the tuning of the (anisotropic) electronic current, mediated by external mechanical strain, is ruled by the energy position of the lowest unoccupied states with wave-vectors perpedicular to the ESs. This control could be advantageous for applications in nanoelectronic devices that require precise control of current direction.

Graph-Regularized Tensor Regression: A Domain-Aware Framework for Interpretable Modeling of Multiway Data on Graphs.

Modern data analytics applications are increasingly characterized by exceedingly large and multidimensional data sources. This represents a challenge for traditional machine learning models, as the number of model parameters needed to process such data grows exponentially with the data dimensions, an effect known as the curse of dimensionality. Recently, tensor decomposition (TD) techniques have shown promising results in reducing the computational costs associated with large-dimensional models while achieving comparable performance. However, such tensor models are often unable to incorporate the underlying domain knowledge when compressing high-dimensional models. To this end, we introduce a novel graph-regularized tensor regression (GRTR) framework, whereby domain knowledge about intramodal relations is incorporated into the model in the form of a graph Laplacian matrix. This is then used as a regularization tool to promote a physically meaningful structure within the model parameters. By virtue of tensor algebra, the proposed framework is shown to be fully interpretable, both coefficient-wise and dimension-wise. The GRTR model is validated in a multiway regression setting and compared against competing models and is shown to achieve improved performance at reduced computational costs. Detailed visualizations are provided to help readers gain an intuitive understanding of the employed tensor operations.

An In-Ear PPG-Based Blood Glucose Monitor: A Proof-of-Concept Study.

Monitoring diabetes saves lives. To this end, we introduce a novel, unobtrusive, and readily deployable in-ear device for the continuous and non-invasive measurement of blood glucose levels (BGLs). The device is equipped with a low-cost commercially available pulse oximeter whose infrared wavelength (880 nm) is used for the acquisition of photoplethysmography (PPG). For rigor, we considered a full range of diabetic conditions (non-diabetic, pre-diabetic, type I diabetic, and type II diabetic). Recordings spanned nine different days, starting in the morning while fasting, up to a minimum of a two-hour period after eating a carbohydrate-rich breakfast. The BGLs from PPG were estimated using a suite of regression-based machine learning models, which were trained on characteristic features of PPG cycles pertaining to high and low BGLs. The analysis shows that, as desired, an average of 82% of the BGLs estimated from PPG lie in region A of the Clarke error grid (CEG) plot, with 100% of the estimated BGLs in the clinically acceptable CEG regions A and B. These results demonstrate the potential of the ear canal as a site for non-invasive blood glucose monitoring.

Design and Implementation of an Atrial Fibrillation Detection Algorithm on the ARM Cortex-M4 Microcontroller.

At present, a medium-level microcontroller is capable of performing edge computing and can handle the computation of neural network kernel functions. This makes it possible to implement a complete end-to-end solution incorporating signal acquisition, digital signal processing, and machine learning for the classification of cardiac arrhythmias on a small wearable device. In this work, we describe the design and implementation of several classifiers for atrial fibrillation detection on a general-purpose ARM Cortex-M4 microcontroller. We used the CMSIS-DSP library, which supports Naïve Bayes and Support Vector Machine classifiers, with different kernel functions. We also developed Python scripts to automatically transfer the Python model (trained in Scikit-learn) to the C environment. To train and evaluate the models, we used part of the data from the PhysioNet/Computing in Cardiology Challenge 2020 and performed simple classification of atrial fibrillation based on heart-rate irregularity. The performance of the classifiers was tested on a general-purpose ARM Cortex-M4 microcontroller (STM32WB55RG). Our study reveals that among the tested classifiers, the SVM classifier with RBF kernel function achieves the highest accuracy of 96.9%, sensitivity of 98.4%, and specificity of 95.8%. The execution time of this classifier was 720 µs per recording. We also discuss the advantages of moving computing tasks to edge devices, including increased power efficiency of the system, improved patient data privacy and security, and reduced overall system operation costs. In addition, we highlight a problem with false-positive detection and unclear significance of device-detected atrial fibrillation.

Correlating drug prescriptions with prognosis in severe COVID-19: first step towards resource management.

BACKGROUND: Optimal COVID-19 management is still undefined. In this complicated scenario, the construction of a computational model capable of extracting information from electronic medical records, correlating signs, symptoms and medical prescriptions, could improve patient management/prognosis. METHODS: The aim of this study is to investigate the correlation between drug prescriptions and outcome in patients with COVID-19. We extracted data from 3674 medical records of hospitalized patients: drug prescriptions, outcome, and demographics. The outcome evaluated was hospital outcome. We applied correlation analysis using a Logistic Regression algorithm for machine learning with Lasso and Matthews correlation coefficient. RESULTS: We found correlations between drugs and patient outcomes (death/discharged alive). Anticoagulants, used very frequently during all phases of the disease, were associated with good prognosis only after the first week of symptoms. Antibiotics very frequently prescribed, especially early, were not correlated with outcome, suggesting that bacterial infections may not be important in determining prognosis. There were no differences between age groups. CONCLUSIONS: In conclusion, we achieved an important result in the area of Artificial Intelligence, as we were able to establish a correlation between concrete variables in a real and extremely complex environment of clinical data from COVID-19. Our results are an initial and promising contribution in decision-making and real-time environments to support resource management and forecasting prognosis of patients with COVID-19.

A Pilot Study of Heart Rate Variability Synchrony as a Marker of Intraoperative Surgical Teamwork and Its Correlation to the Length of Procedure.

Objective: Quality of intraoperative teamwork may have a direct impact on patient outcomes. Heart rate variability (HRV) synchrony may be useful for objective assessment of team cohesion and good teamwork. The primary aim of this study was to investigate the feasibility of using HRV synchrony in surgical teams. Secondary aims were to investigate the association of HRV synchrony with length of procedure (LOP), complications, number of intraoperative glitches and length of stay (LOS). We also investigated the correlation between HRV synchrony and team familiarity, pre- and intraoperative stress levels (STAI questionnaire), NOTECHS score and experience of team members. Methods: Ear, nose and throat (ENT) and vascular surgeons (consultant and registrar team members) were recruited into the study. Baseline demographics including level of team members' experience were gathered before each procedure. For each procedure, continuous electrocardiogram (ECG) recording was performed and questionnaires regarding pre- and intraoperative stress levels and non-technical skills (NOTECHS) scores were collected for each team member. An independent observer documented the time of each intraoperative glitch. Statistical analysis was conducted using stepwise multiple linear regression. Results: Four HRV synchrony metrics which may be markers of efficient surgical collaboration were identified from the data: 1. number of HRV synchronies per hour of procedure, 2. number of HRV synchrony trends per hour of procedure, 3. length of HRV synchrony trends per hour of procedure, 4. area under the HRV synchrony trend curve per hour of procedure. LOP was inversely correlated with number of HRV synchrony trends per hour of procedure (p < 0.0001), area under HRV synchrony trend curve per hour of procedure (p = 0.001), length of HRV synchrony trends per hour of procedure (p = 0.002) and number of HRV synchronies per hour of procedure (p < 0.0001). LOP was positively correlated with: FS (p = 0.043; R = 0.358) and intraoperative STAI score of the whole team (p = 0.007; R = 0.493). Conclusions: HRV synchrony metrics within operating teams may be used as an objective marker to quantify surgical teamwork. We have shown that LOP is shorter when the intraoperative surgical teams' HRV is more synchronised.

Multivariate Multiscale Cosine Similarity Entropy and Its Application to Examine Circularity Properties in Division Algebras.

The extension of sample entropy methodologies to multivariate signals has received considerable attention, with traditional univariate entropy methods, such as sample entropy (SampEn) and fuzzy entropy (FuzzyEn), introduced to measure the complexity of chaotic systems in terms of irregularity and randomness. The corresponding multivariate methods, multivariate multiscale sample entropy (MMSE) and multivariate multiscale fuzzy entropy (MMFE), were developed to explore the structural richness within signals at high scales. However, the requirement of high scale limits the selection of embedding dimension and thus, the performance is unavoidably restricted by the trade-off between the data size and the required high scale. More importantly, the scale of interest in different situations is varying, yet little is known about the optimal setting of the scale range in MMSE and MMFE. To this end, we extend the univariate cosine similarity entropy (CSE) method to the multivariate case, and show that the resulting multivariate multiscale cosine similarity entropy (MMCSE) is capable of quantifying structural complexity through the degree of self-correlation within signals. The proposed approach relaxes the prohibitive constraints between the embedding dimension and data length, and aims to quantify the structural complexity based on the degree of self-correlation at low scales. The proposed MMCSE is applied to the examination of the complex and quaternion circularity properties of signals with varying correlation behaviors, and simulations show the MMCSE outperforming the standard methods, MMSE and MMFE.

Association of Carotid Plaques and Common Carotid Intima-media Thickness with Modifiable Cardiovascular Risk Factors.

OBJECTIVE: To assess the association of carotid plaques and common carotid artery intima-media thickness with traditional modifiable cardiovascular risk factors. METHODS: We examined 4,266 participants aged 35-74years in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline. The presence of plaques at all carotid arteries sites was evaluated. The mean far wall common carotid artery intima-media thickness was measured. To evaluate the association of cardiovascular risk factors with plaques and plaque burden, we applied logistic regression models presented as crude, adjusted by sociodemographic variables, along with multivariate further adjustment for hypertension, diabetes, hypercholesterolemia, and smoking. For the association of cardiovascular risk factors and common carotid artery intima-media thickness, linear regression models were used with the same adjustments. RESULTS: Median age was 51 years (interquartile range: 45-58 years; 54.5% of females). Plaque prevalence in at least one segment of the carotid arteries was 35.9%. Mean common carotid artery intima-media thickness of the far walls was 0.609 ± 0.133 mm. In the multivariate model for plaque presence, the odds ratios were:1.39 (1.19-1.63) for hypertension;1.58 (1.36-1.82) for hypercholesterolemia; 2.00 (1.65-2.43),1.19 (1.02-1.40) for current and past smoking, and 1.13 (0.95-1.35) for diabetes. In the multivariate linear regression models, common carotid artery intima-media thickness beta-coefficients were: 0.035 mm (0.027-0.043) for hypertension; 0.020 mm (0.013-0.027) for hypercholesterolemia; 0.020 mm (0.010-0.029), 0.012 mm (0.004-0.020) for current and past smoking, and 0.024 mm (0.015-0.033) for diabetes. CONCLUSION: Cardiovascular risk factors were independently associated with increasing common carotid artery intima-media thickness, plaque prevalence, and plaque scores. Diabetes did not show an independent association with plaques in the multivariate model.

Variational Embedding Multiscale Sample Entropy: A Tool for Complexity Analysis of Multichannel Systems.

Entropy-based methods have received considerable attention in the quantification of structural complexity of real-world systems. Among numerous empirical entropy algorithms, conditional entropy-based methods such as sample entropy, which are associated with amplitude distance calculation, are quite intuitive to interpret but require excessive data lengths for meaningful evaluation at large scales. To address this issue, we propose the variational embedding multiscale sample entropy (veMSE) method and conclusively demonstrate its ability to operate robustly, even with several times shorter data than the existing conditional entropy-based methods. The analysis reveals that veMSE also exhibits other desirable properties, such as the robustness to the variation in embedding dimension and noise resilience. For rigor, unlike the existing multivariate methods, the proposed veMSE assigns a different embedding dimension to every data channel, which makes its operation independent of channel permutation. The veMSE is tested on both stimulated and real world signals, and its performance is evaluated against the existing multivariate multiscale sample entropy methods. The proposed veMSE is also shown to exhibit computational advantages over the existing amplitude distance-based entropy methods.

An oviposition trap to collect immatures of coprophagous moth flies (Diptera: Psychodidae).

Larvae of Psychodidae develop in a variety of breeding sites, including vertebrate feces. As searching for the larvae can be an extremely difficult task, immatures of many species are little known, with descriptions of coprophagous moth flies all from outside the Neotropics. In an attempt to mitigate this challenge, we tested an oviposition trap using cattle dung as attractant, measured the efficiency and specificity of the traps and the most efficient period of exposition in the field. With 60 traps installed in one fragment of ombrophilous forest, 344 immatures were collected, distributed in four species of Psychoda and one of Feuerborniella. Psychodidae accounted for 75% of the collected Diptera. The high specificity of the trap to Psychodidae contrasts with other studies on coprophagous fauna where they appear in low abundance. Based on the metrics in this study, the most efficient period of trapping exposition was between five to eight days, but the difference was not significant probably due to the high number of zero observations among the traps. Many questions pertaining to coprophagous moth flies remain unanswered. Further research is needed to improve trapping efficiency, elucidate the effects of attractants and determine how environmental factors influence the attractiveness of bait.

Growth curve of selectively bred and non-selectively bred tambaqui (Colossoma macropomum).

The aim of this study was to evaluate the growth curve of selectively bred and non-selectively bred tambaqui (Colossoma macropomum). The experiment involved 388 fish (weight: 65.38 ± 20.00 g; age: 217 days), consisting of 252 fish from seven selectively bred families (18 fish per family) and 18 non-selectively bred fish (control group). Groups were placed in two 800-m² tanks. Biometric measurements were taken on nine occasions at 30-day intervals, for a period of 254 days. Weight and morphometric traits were evaluated. To describe the tambaqui growth behavior, we adopted the Gompertz nonlinear regression model. Greater growth (p < 0.05) was observed in selectively bred families compared with control group. Four families stood out with higher (p < 0.05) asymptotic values for weight (F1: 2448.7 g; F7: 2284.7 g; F5 2180.1 g; F4: 2080.5 g; and control: 1808.4 g) and other morphometric traits. None of the selectively bred families (except F5) had a higher growth rate and age at inflection point than the fish from control group. In conclusion, selectively bred and non-selectively bred fish present distinct growth curves, but some families have greatly superior growth.

In-Ear SpO2: A Tool for Wearable, Unobtrusive Monitoring of Core Blood Oxygen Saturation.

The non-invasive estimation of blood oxygen saturation (SpO2) by pulse oximetry is of vital importance clinically, from the detection of sleep apnea to the recent ambulatory monitoring of hypoxemia in the delayed post-infective phase of COVID-19. In this proof of concept study, we set out to establish the feasibility of SpO2 measurement from the ear canal as a convenient site for long term monitoring, and perform a comprehensive comparison with the right index finger-the conventional clinical measurement site. During resting blood oxygen saturation estimation, we found a root mean square difference of 1.47% between the two measurement sites, with a mean difference of 0.23% higher SpO2 in the right ear canal. Using breath holds, we observe the known phenomena of time delay between central circulation and peripheral circulation with a mean delay between the ear and finger of 12.4 s across all subjects. Furthermore, we document the lower photoplethysmogram amplitude from the ear canal and suggest ways to mitigate this issue. In conjunction with the well-known robustness to temperature induced vasoconstriction, this makes conclusive evidence for in-ear SpO2 monitoring being both convenient and superior to conventional finger measurement for continuous non-intrusive monitoring in both clinical and everyday-life settings.

Viability assessment of primary growth oocytes following ovarian tissue vitrification of neotropical teleost pacu (Piaractus mesopotamicus).

Vitrification of ovarian tissue containing immature oocytes provides an important tool for protecting the endangered species and genetic diversity in aquatic species. Therefore, the main objective was to assess primary growth (PG) oocytes viability following ovarian tissue vitrification using histological analysis, two staining protocols (trypan blue or fluorescein diacetate combined with propidium iodide) and mitochondrial activity assay (MTT assay). In addition, oocyte histomorphometry was performed to evaluate the morphometric parameters after vitrification and the relationship with the occurrence of damage (nucleus and/or membrane) in PG oocytes. There was no significant difference among the vitrified oocytes using trypan blue dye or FDA + IP staining. Oocyte viability assessed using histological analysis showed that vitrification solution 2.0 M Me2SO + 2.5 M etilenoglycol +0.5 M sucrose (VS3; 66.43 ± 4.68%) and 1.5 M methanol + 5.5 M Me2SO + 0.5 M sucrose (VS5; 74.14 ± 3.71%) had the lowest viability rate. Similar results were observed in MTT assay where VS3 (1.63 ± 0.12) and VS5 (1.58 ± 0.09) had the lowest averages when compare with VS1 (2.39 ± 0.14), VS2 (1.78 ± 0.06) and VS4 (2.34 ± 0.19) (P = 0.0002). In membrane damage evaluation by histology, there was no difference among vitrified oocytes and control. However, the highest percentages of nucleus damage were observed in treatments VS3 (26.00 ± 5.55) and VS5 (26.00 ± 5.55). Oocyte diameter did not change after vitrification; however, nucleus diameter was significantly higher in control group (49.03 ± 1.07). Oocyte viability by histological analysis was positive-correlated to the occurrence of nucleus (r2 = 0.78) and membrane (r2 = 0.45) damage after vitrification/warming. The high viability of PG oocytes obtained after ovarian tissue vitrification of Piaractus mesopotamicus suggests that the protocol applied here might be used successfully in other teleost species for food production.

Prognostic value of carotid intima-media in the short- and long-term mortality in the Strategy of Registry of Acute Coronary Syndrome (ERICO) study.

BACKGROUND AND AIMS: Atherosclerotic in carotids can determinate a poor prognosis in individuals after acute coronary syndrome (ACS). Thus, we aimed to evaluate mortality associated to carotid intima media thickness (CIMT) in the participants from the Strategy of Registry of Acute Coronary Syndrome (ERICO) study. METHODS: Carotid intima media thickness was evaluated by B-mode ultrasound for mortality risk assessment in 180 days, 1-3 years. We performed Kaplan-Meier survival curves and Cox logistic regression models to evaluate all-cause, cardiovascular (CVD) and coronary heart disease (CHD) mortality by CIMT tertiles in crude, age and sex- and multivariate models. RESULTS: Among 644 ACS individuals (median age 61-year old), we observed a median CIMT of 0.74 mm. Besides aging, low education, hypertension, diabetes, and dyslipidemia were associated with the 3rd tertile of CIMT values. During 3 years of follow-up, we observed 65 deaths (10.1%), crude case-fatality rates were progressively higher across the CIMT tertiles in all periods, being the highest rates observed in participants with the highest CIMT (3rd tertile) (180-day: 6.6% vs 1-year: 9.0% vs 2-year:12.3% vs 3-year:16.0%, P < .05). In crude analyses, lowest survival rates (all-cause, CVD and CHD, p log-rank values <0.005) and higher hazard ratios of dying for all-cause and CVD (from 1 to 3 years) and for CHD (2 and 3 years) were observed. However, we kept no significant results after adjusting for age. CONCLUSION: Carotid intima media thickness was mainly influenced by aging. CIMT was not a good predictor of all-cause, CVD or CHD mortality in the ERICO study.

Asilidae (Diptera) of two Atlantic Forest protected areas of Rio de Janeiro, Southeastern Brazil.

As few Asilidae inventories of Rio de Janeiro areas have been published, there are many data gaps. This paper aims to contribute to the knowledge of richness, abundance and distribution of this family in this State. From January 2013 to March 2014, insects were collected monthly using Malaise traps and every two months using entomological nets in the Reserva Biológica União (REBIO), and Estação Ecológica Estadual de Guaxindiba (EEEG). 682 specimens of Asilidae were collected in the present study, distributed in 31 genera and 51 species (20 identified and 31 unidentified), 527 of REBIO (in 19 genera and 38 species - 14 identified and 24 unidentified), and 155 specimens of EEEG (in 12 genera and 19 species - 6 identified and 13 unidentified). Leptogaster was the most abundant genus being L. tropica (Curran 1934) the most abundant species in the REBIO, with 268 specimens and Leptogaster sp., with 54 specimens, the most abundant in the EEEG. All records of genera and species in the present study are new in the REBIO and EEEG, wich contribute to the knowledge of the Asilidae geographic distribution and richness in the State of Rio de Janeiro.

A Novel Multivariate Sample Entropy Algorithm for Modeling Time Series Synchronization.

Approximate and sample entropy (AE and SE) provide robust measures of the deterministic or stochastic content of a time series (regularity), as well as the degree of structural richness (complexity), through operations at multiple data scales. Despite the success of the univariate algorithms, multivariate sample entropy (mSE) algorithms are still in their infancy and have considerable shortcomings. Not only are existing mSE algorithms unable to analyse within- and cross-channel dynamics, they can counter-intuitively interpret increased correlation between variates as decreased regularity. To this end, we first revisit the embedding of multivariate delay vectors (DVs), critical to ensuring physically meaningful and accurate analysis. We next propose a novel mSE algorithm and demonstrate its improved performance over existing work, for synthetic data and for classifying wake and sleep states from real-world physiological data. It is furthermore revealed that, unlike other tools, such as the correlation of phase synchrony, synchronized regularity dynamics are uniquely identified via mSE analysis. In addition, a model for the operation of this novel algorithm in the presence of white Gaussian noise is presented, which, in contrast to the existing algorithms, reveals for the first time that increasing correlation between different variates reduces entropy.

Physiological artifacts in scalp EEG and ear-EEG.

BACKGROUND: A problem inherent to recording EEG is the interference arising from noise and artifacts. While in a laboratory environment, artifacts and interference can, to a large extent, be avoided or controlled, in real-life scenarios this is a challenge. Ear-EEG is a concept where EEG is acquired from electrodes in the ear. METHODS: We present a characterization of physiological artifacts generated in a controlled environment for nine subjects. The influence of the artifacts was quantified in terms of the signal-to-noise ratio (SNR) deterioration of the auditory steady-state response. Alpha band modulation was also studied in an open/closed eyes paradigm. RESULTS: Artifacts related to jaw muscle contractions were present all over the scalp and in the ear, with the highest SNR deteriorations in the gamma band. The SNR deterioration for jaw artifacts were in general higher in the ear compared to the scalp. Whereas eye-blinking did not influence the SNR in the ear, it was significant for all groups of scalps electrodes in the delta and theta bands. Eye movements resulted in statistical significant SNR deterioration in both frontal, temporal and ear electrodes. Recordings of alpha band modulation showed increased power and coherence of the EEG for ear and scalp electrodes in the closed-eyes periods. CONCLUSIONS: Ear-EEG is a method developed for unobtrusive and discreet recording over long periods of time and in real-life environments. This study investigated the influence of the most important types of physiological artifacts, and demonstrated that spontaneous activity, in terms of alpha band oscillations, could be recorded from the ear-EEG platform. In its present form ear-EEG was more prone to jaw related artifacts and less prone to eye-blinking artifacts compared to state-of-the-art scalp based systems.

The effect of cryoprotectant agents on DNA methylation patterns and progeny development in the spermatozoa of Colossoma macropomum.

DNA methylation patterns are inherited from parents and are imperative for proper embryonic development; however, alterations in these patterns can compromise fertilization and development into a fully functioning adult animal because DNA methylation is part of a complex program of gene transcription. In this study, we investigated the impact of cryoprotectant agents (CPAs) on DNA methylation patterns in spermatozoa and the consequences on embryonic development and the survival rate of progeny. Global methylation was assessed by enzymatic reactions in Colossoma macropomum spermatozoa that were cryopreserved using dimethylsulfoxide, dimethylformamide, methanol, ethyl glycol and glycerol as CPAs. Fertilization was carried out to evaluate survival rates and abnormalities in embryonic development upon treatment with each of the CPAs. Fresh semen served as the control. Our results indicated that, compared to the control group, spermatozoa cryopreservation decreased the fertilization rate and delayed embryonic development from the midblastula stage. Furthermore, spermatozoa cryopreserved in all CPAs had lower methylation levels and exhibited more delays and abnormalities during embryonic development than did fresh semen. Methanol resulted in fertilization, hatching rates and embryonic development that were closer to the control but had lower methylation levels. In conclusion, ours results show significant alterations on spermatozoa DNA methylation patterns caused by CPAs that are used in the semen cryopreservation process. DNA methylation pattern alterations affected the viability of progeny (r=0.48); however, these effects can be minimized by choosing the CPA that will compose the freezing solution.