Multi-Scale Evaluation of Sleep Quality Based on Motion Signal from Unobtrusive Device.

Sleep disorders are a growing threat nowadays as they are linked to neurological, cardiovascular and metabolic diseases. The gold standard methodology for sleep study is polysomnography (PSG), an intrusive and onerous technique that can disrupt normal routines. In this perspective, m-Health technologies offer an unobtrusive and rapid solution for home monitoring. We developed a multi-scale method based on motion signal extracted from an unobtrusive device to evaluate sleep behavior. Data used in this study were collected during two different acquisition campaigns by using a Pressure Bed Sensor (PBS). The first one was carried out with 22 subjects for sleep problems, and the second one comprises 11 healthy shift workers. All underwent full PSG and PBS recordings. The algorithm consists of extracting sleep quality and fragmentation indexes correlating to clinical metrics. In particular, the method classifies sleep windows of 1-s of the motion signal into: displacement (DI), quiet sleep (QS), disrupted sleep (DS) and absence from the bed (ABS). QS proved to be positively correlated (0.72±0.014) to Sleep Efficiency (SE) and DS/DI positively correlated (0.85±0.007) to the Apnea-Hypopnea Index (AHI). The work proved to be potentially helpful in the early investigation of sleep in the home environment. The minimized intrusiveness of the device together with a low complexity and good performance might provide valuable indications for the home monitoring of sleep disorders and for subjects' awareness.

Community-Driven Methods for Open and Reproducible Software Tools for Analyzing Datasets from Atom Probe Microscopy.

Atom probe tomography, and related methods, probe the composition and the three-dimensional architecture of materials. The software tools which microscopists use, and how these tools are connected into workflows, make a substantial contribution to the accuracy and precision of such material characterization experiments. Typically, we adapt methods from other communities like mathematics, data science, computational geometry, artificial intelligence, or scientific computing. We also realize that improving on research data management is a challenge when it comes to align with the FAIR data stewardship principles. Faced with this global challenge, we are convinced it is useful to join forces. Here, we report the results and challenges with an inter-laboratory call for developing test cases for several types of atom probe microscopy software tools. The results support why defining detailed recipes of software workflows and sharing these recipes is necessary and rewarding: Open source tools and (meta)data exchange can help to make our day-to-day data processing tasks become more efficient, the training of new users and knowledge transfer become easier, and assist us with automated quantification of uncertainties to gain access to substantiated results.

[Surface roughness of two composite resins after immersion in soda drinks: in vitro study]. / Rugosidad superficial de dos resinas compuestas después de la inmersión en bebidas gaseosas: estudio in vitro.

Objective: Compare the surface roughness of two composite resins after immersion in carbonated beverages. Materials and methods: 160 resin discs (6 x 2 mm) were divided into 8 groups (n=20 per group) according to type of resin (Filtek™ Z350 XT® and Palfique LX5®) and type of immersion in beverages (distilled water, Coca Cola®, Inca Kola® and Kola Escocesa®. The immersions were carried out under a structured cycle: 4 immersions a day for 5 days, intermediate storage in distilled water and overnight incubation for 8 h at 37°C. The measurements with the roughness meter were evaluated in three times: baseline, 7 and 14 days. The three-way Anova test was used at P<0.05. Results: Roughness showed differences only for the individual factors of time (P<0.000) and resin (P=0.000), and for the interaction time*drink (P=0.000) and resin*drink (P=0.003). Roughness was higher with Filtek Z350 XT® immersed with Inca Kola® (0.85 ± 0.37) than 14 days compared to other times (P=0.035) and with Palfique LX5 immersed in Coca Cola® at 7 days (1.61 ± 0.42) and in Inca Kola® at 14 days (1.66 ± 0.56) compared to distilled water (P<0,05). Conclusion: Surface roughness was affected by the type of resin, the type of soft drink and the immersion time. The roughness was greater with the Palfique LX5® nanohybrid resin, the Inca Kola® drink and after 14 days of immersion.

[Compressive stress in three types of finishing lines with lithium disilicate crowns in permanent teeth: finite element analysis]. / Tensión compresiva en tres tipos de líneas de terminación con coronas de disilicato de litio en dientes permanentes: análisis de elemento finito.

Introduction: In oral rehabilitation, the use of ceramic restorations is widely accepted due to its aesthetic capacity to mimic the naturalness of the dental tissue, provide longevity of the material, and present a greater marginal fit compared to crowns with a metal structure. Termination lines are biological preparations whose function is to minimize the cervical opening of the marginal seal. Consequently, analyzing the behavior of restorative materials under compressive forces decreases the risk of fracture and increases the success of the treatment. Objective: To compare the compressive stresses of lithium disilicate crowns with three different finishing lines. Methodology: In silico study of the simulation of a dental preparation on a lower right first molar with chamfer (0.6 mm), shoulder (0.5 mm) and deep chamfer (0.5 mm) finish lines. Using the SolidWorks®ï¸ version 2017 software, the maximum stresses, minimum stresses, and location of the compressive force were collected on the Megapascal (Mpa) measurement scale. Results: The chamfer type termination line (0.6mm) obtained a lower compressive stress compared to the other two shoulder type termination lines (0.5mm) and deep chamfer (0.5mm). Conclusions: It was shown that the chamfer type finishing line (0.6mm) presented a better force distribution, determining greater reliability in the selection of this finishing line with the use of a lithium disilicate crown in a unitary manner.

Assessing cardiovascular stress based on heart rate variability in female shift workers: a multiscale-multifractal analysis approach.

Introduction: Sleep-wake cycle disruption caused by shift work may lead to cardiovascular stress, which is observed as an alteration in the behavior of heart rate variability (HRV). In particular, HRV exhibits complex patterns over different time scales that help to understand the regulatory mechanisms of the autonomic nervous system, and changes in the fractality of HRV may be associated with pathological conditions, including cardiovascular disease, diabetes, or even psychological stress. The main purpose of this study is to evaluate the multifractal-multiscale structure of HRV during sleep in healthy shift and non-shift workers to identify conditions of cardiovascular stress that may be associated with shift work. Methods: The whole-sleep HRV signal was analyzed from female participants: eleven healthy shift workers and seven non-shift workers. The HRV signal was decomposed into intrinsic mode functions (IMFs) using the empirical mode decomposition method, and then the IMFs were analyzed using the multiscale-multifractal detrended fluctuation analysis (MMF-DFA) method. The MMF-DFA was applied to estimate the self-similarity coefficients, α(q, τ), considering moment orders (q) between -5 and +5 and scales (τ) between 8 and 2,048 s. Additionally, to describe the multifractality at each τ in a simple way, a multifractal index, MFI(τ), was computed. Results: Compared to non-shift workers, shift workers presented an increase in the scaling exponent, α(q, τ), at short scales (τ < 64 s) with q < 0 in the high-frequency component (IMF1, 0.15-0.4 Hz) and low-frequency components (IMF2-IMF3, 0.04-0.15 Hz), and with q> 0 in the very low frequencies (IMF4, < 0.04 Hz). In addition, at large scales (τ> 1,024 s), a decrease in α(q, τ) was observed in IMF3, suggesting an alteration in the multifractal dynamic. MFI(τ) showed an increase at small scales and a decrease at large scales in IMFs of shift workers. Conclusion: This study helps to recognize the multifractality of HRV during sleep, beyond simply looking at indices based on means and variances. This analysis helps to identify that shift workers show alterations in fractal properties, mainly on short scales. These findings suggest a disturbance in the autonomic nervous system induced by the cardiovascular stress of shift work.

Multifractal analysis of heart rate variability in pregnancy during sleep.

Understanding the complex dynamics of heart rate variability (HRV) during pregnancy is crucial for monitoring both maternal well-being and fetal health. In this study, we use the Multifractal Detrended Fluctuations Analysis approach to investigate HRV patterns in pregnant individuals during sleep based on RR interval maxima (MM fluctuations). In addition, we study the type of multifractality within MM fluctuations, that is, if it arises from a broad probability density function or from varying long-range correlations. Furthermore, to provide a comprehensive view of HRV changes during sleep in pregnancy, classical temporal and spectral HRV indices were calculated at quarterly intervals during sleep. Our study population consists of 21 recordings from nonpregnant women, 18 from the first trimester (early-pregnancy) and 18 from the second trimester (middle-pregnancy) of pregnancy. Results. There are statistically significant differences ( p -value < 0.05) in mean heart rate, rms heart rate, mean MM fluctuations, and standard deviation of MM fluctuations, particularly in the third and fourth quarter of sleep between pregnant and non-pregnant states. In addition, the early-pregnancy group shows significant differences ( p -value < 0.05) in spectral indices during the first and fourth quarter of sleep compared to the non-pregnancy group. Furthermore, the results of our research show striking similarities in the average multifractal structure of MM fluctuations between pregnant and non-pregnant states during normal sleep. These results highlight the influence of different long-range correlations within the MM fluctuations, which could be primarily associated with the emergence of sleep cycles on multifractality during sleep. Finally, we performed a separability analysis between groups using temporal and spectral HRV indices as features per sleep quarter. Employing only three features after Principal Component Analysis (PCA) to the original feature set, achieving complete separability among all groups appears feasible. Using multifractal analysis, our study provides a comprehensive understanding of the complex HRV patterns during pregnancy, which holds promise for maternal and fetal health monitoring. The separability analysis also provides valuable insights into the potential for group differentiation using simple measures such as mean heart rate, rms heart rate, and mean MM fluctuations or in the transformed feature space based on PCA.

Integrating multiple lines of evidence to better understand the evolutionary divergence of humpback dolphins along their entire distribution range: a new dolphin species in Australian waters?

The conservation of humpback dolphins, distributed in coastal waters of the Indo-West Pacific and eastern Atlantic Oceans, has been hindered by a lack of understanding about the number of species in the genus (Sousa) and their population structure. To address this issue, we present a combined analysis of genetic and morphologic data collected from beach-cast, remote-biopsied and museum specimens from throughout the known Sousa range. We extracted genetic sequence data from 235 samples from extant populations and explored the mitochondrial control region and four nuclear introns through phylogenetic, population-level and population aggregation frameworks. In addition, 180 cranial specimens from the same geographical regions allowed comparisons of 24 morphological characters through multivariate analyses. The genetic and morphological data showed significant and concordant patterns of geographical segregation, which are typical for the kind of demographic isolation displayed by species units, across the Sousa genus distribution range. Based on our combined genetic and morphological analyses, there is convincing evidence for at least four species within the genus (S. teuszii in the Atlantic off West Africa, S. plumbea in the central and western Indian Ocean, S. chinensis in the eastern Indian and West Pacific Oceans, and a new as-yet-unnamed species off northern Australia).

[Associated factors and types of eye injuries occurring in dentistry practice: systematic review]. / Factores asociados y tipos de lesiones oculares ocurridas en la práctica odontológica: revisión sistemática.

Introduction: The dentist and auxiliary personnel are in constant risk of occupational diseases such as: allergies, infections, skin or eye injuries; that could affect patients. A problem of social interest are the ocular injuries that occur to dental personnel. The literature reveals the prevalence of eye injuries in dental practice that are associated with solid particles, fluid splashes. Our objective was, through a systematic review, to review the types of ocular injuries and their associated factors that occurred in dental practice. Material and Methods: The relevant studies were searched in the databases: PubMed, Scopus, Ebsco, among others. The search included cross-sectional studies that evaluated the evidence on ocular injuries occurring in dental practice, excluding literature reviews, letters to the reader, and editorials. Results: Eight studies were included to develop the systematic review; determining that the associated factors of ocular injuries occurred in dental practice are: a) occasional use of ocular protection b) age c) sex d) years of practice and the types of ocular injuries are the entry of liquids and foreign bodies. Conclusions: Deficiency in compliance with eye or facial protection protocols in dental practice, cause eye injuries; Type of fluid entry, foreign bodies, splash of biological fluids or conjunctivitis. These eye injuries are generated from associated factors such as the occasional use of eye protection, age, sex, and others.

Microstructure-Property Correlation and Its Evolution during Aging in an Al4.4Co26Cr19Fe18Ni27Ti5.6 High-Entropy Alloy.

The efficient energy use in multiple sectors of modern industry is partly based on the efficient use of high-strength, high-performance alloys that retain remarkable mechanical properties at elevated and high temperatures. High-entropy alloys (HEAs) represent the most recent class of these materials with a high potential for high-temperature high-strength applications. Aside from their chemical composition and microstructure-property relationship, limited information on the effect of heat treatment as a decisive factor for alloy design is available in the literature. This work intends to contribute to this research topic by investigating the effect of heat treatment on the microstructure and mechanical performance of an Al4.4Co26Cr19Fe18Ni27Ti5.6 HEA. The solution annealed state is compared to aged states obtained at different heat treatment times at 750 °C. The temporal evolution of the matrix and the γ'-precipitates are analyzed in terms of chemical composition, crystallography, size, shape, and volume fraction by means of scanning electron microscopy, transmission electron microscopy, and atom probe tomography. The yield strength evolution and strength contributions are calculated by classical state-of-the-art models as well as by ab-initio-based calculations of the critical resolved shear stress. The findings indicate promising mechanical properties of the investigated alloy and provide insight not only into possible strengthening mechanisms but also into the evolution of main phases during the heat treatment.

[Validation of the instrument to measure the level of knowledge of postgraduate and university professors on the labor law of the dental surgeon]. / Validación de instrumento para medir el nivel de conocimiento de estudiantes de posgrado y docentes universitarios sobre la ley de trabajo del cirujano dentista.

Objective: To build and validate an instrument to measure the level of knowledge about the Law that regulates the work of the dental surgeon in the Peruvian territory (Law No. 27878) of postgraduate students and teachers of the Stomatology Career of the Scientific University of Peru. South. Material and methods: : The sample consisted of 38 dental surgeons, participants in the postgraduate program (20) and professors (18) of the Stomatology Career at the Universidad Científica del Sur. A structured questionnaire of 15 questions was developed based on the articles of Law No. 27878. Results: It was approved by Expert Judgment and submitted to Aiken's V with an average result of 0.95. A moderate level of correlation was obtained through the Pearson Correlation Coefficient and a Cronbach's Alpha of 0.8. Through the Exploratory Factor Analysis, 3 dimensions were formed. Conclusions: The instrument was correctly validated through 4 validity tests. The level of knowledge of postgraduate students and teachers was very good in 60.5%.

Body Composition Assessment in Mexican Children and Adolescents. Part 1: Comparisons between Skinfold-Thickness, Dual X-ray Absorptiometry, Air-Displacement Plethysmography, Deuterium Oxide Dilution, and Magnetic Resonance Imaging with the 4-C Model.

The evaluation of body composition (BC) is relevant in the evaluation of children's health-disease states. Different methods and devices are used to estimate BC. The availability of methods and the clinical condition of the patient usually defines the ideal approach to be used. In this cross-sectional study, we evaluate the accuracy of different methods to estimate BC in Mexican children and adolescents, using the 4-C model as the reference. In a sample of 288 Mexican children and adolescents, 4-C body composition assessment, skinfold-thickness (SF), dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), and deuterium dilution (D2O) were performed, along with MRI in a subsample (52 participants). The analysis of validity was performed by correlation analysis, linear regression, and the Bland-Altman method. All methods analyzed showed strong correlations for FM with 4-C values and between each other; however, DXA and MRI overestimated FM, whereas skinfolds and ADP under-estimated FM. Conclusion: The clinical assessment of BC by means of SF, ADP, DXA, MRI and D2O correlated well with the 4-C model and between them, providing evidence of their clinical validity and utility. The results from different methods are not interchangeable. Preference between methods may depend on their availability and the specific clinical setting.

3D nanoscale elemental mapping of precipitates in steel: Evaluation of analytical electron tomography and comparison to atom probe tomography.

To identify different types of precipitates and their composition, analytical electron tomography analysis on a needle-shaped sample was performed. Three-dimensional chemical maps from each element in a high alloyed steel are acquired and the resulting elemental maps are jointly reconstructed. Since analytical electron tomography data suffers from noise, total generalized variation regularization is used to improve the reconstruction quality compared to conventional reconstruction techniques. We analyse the influence of regularization parameters on these reconstructions in terms of elemental quantification, and compare these results to atom probe tomography measurements done on another sample of the same material.

Assessment of Singularities in the EEG During A-Phases of Sleep Based on Wavelet Decomposition.

Electroencephalography (EEG) signals convey information related to different processes that take place in the brain. From the EEG fluctuations during sleep, it is possible to establish the sleep stages and identify short events, commonly related to a specific physiological process or pathology. Some of these short events (called A-phases) present an organization and build up the concept of the Cyclic Alternating Pattern (CAP) phenomenon. In general, the A-phases abruptly modify the EEG fluctuations, and a singular behavior could occur. With the aim to quantify the abrupt changes during A-phases, in this work the wavelet analysis is considered to compute Hölder exponents, which measure the singularity strength. We considered time windows of 2s outside and 5s inside A-phases onset (or offset). A total number of 5121 A-phases from 9 healthy participants and 10 patients with periodic leg movements were analyzed. Within an A-phase the Hölder numerical value tends to be 0.6, which implies a less abrupt singularity. Whereas outside of A-phases, it is observed that the Hölder value is approximately equal to 0.3, which implies stronger singularities, i.e., a more evident discontinuity in the signal behavior. In addition, it seems that the number of singularities increases inside of A-phases. The numerical results suggest that the EEG naturally conveys singularities modified by the A-phase occurrence, and this information could help to conceptualize the CAP phenomenon from a new perspective based on the sharpness of the EEG instead of the oscillatory way.

Raman Spectroscopy Study of Skin Biopsies from Patients with Parkinson's Disease: Trends in Alpha-Synuclein Aggregation from the Amide I Region.

Parkinson's disease (PD) is one of the most common neurological pathologies with a high prevalence worldwide. PD is characterized by Lewy bodies, whose major component is the aggregates of α-synuclein (αSyn) protein. Interestingly, recent works have demonstrated that skin biopsy studies are a promising diagnostic tool for evaluating α-synucleinopathies. In this sense, this work focuses on the detection of αSyn in skin biopsies employing Raman spectroscopy, using three different approaches: (i) the in vitro Raman spectrum of α-synuclein, (ii) the ex vivo Raman spectra of human skin biopsies from healthy and Parkinson's disease patients, and (iii) theoretical calculations of the Raman spectra obtained from different model αSyn fragments using density functional theory (DFT). Significant differences in the intensity and location of Raman active frequencies in the amide I region were found when comparing healthy and PD subjects related to α-synuclein conformational changes and variations in their aggregation behavior. In samples from healthy patients, we identified well-known Raman peaks at 1655, 1664, and 1680 cm-1 associated with the normal state of the protein. In PD subjects, shifted Raman bands and intensity variations were found at 1650, 1670, and 1687 cm-1 associated with aggregated forms of the protein. DFT calculations reveal that the shape of the amide I Raman peak in model αSyn fragments strongly depends on the degree of aggregation. Sizable frequency shifts and intensity variations are found within the highly relevant 1600-1700 cm-1 domain, revealing the sensitivity of the amide I Raman band to the changes in the local atomic environment. Interestingly, we obtain that the presence of surrounding waters also affects the structure of the amide I band, leading to the appearance of new peaks on the low-frequency side and a notable broadening of the Raman spectra. These results strongly suggest that, through Raman spectroscopy, it is possible to infer the presence of aggregated forms of αSyn in skin biopsies, a result that could have important implications for understanding α-synuclein related diseases.

Isolation by environmental distance in mobile marine species: molecular ecology of franciscana dolphins at their southern range.

The assessment of population structure is a valuable tool for studying the ecology of endangered species and drafting conservation strategies. As we enhance our understanding about the structuring of natural populations, it becomes important that we also understand the processes behind these patterns. However, there are few rigorous assessments of the influence of environmental factors on genetic patterns in mobile marine species. Given their dispersal capabilities and localized habitat preferences, coastal cetaceans are adequate study species for evaluating environmental effects on marine population structure. The franciscana dolphin, a rare coastal cetacean endemic to the Western South Atlantic, was studied to examine these issues. We analysed genetic data from the mitochondrial DNA and 12 microsatellite markers for 275 franciscana samples utilizing frequency-based, maximum-likelihood and Bayesian algorithms to assess population structure and migration patterns. This information was combined with 10 years of remote sensing environmental data (chlorophyll concentration, water turbidity and surface temperature). Our analyses show the occurrence of genetically isolated populations within Argentina, in areas that are environmentally distinct. Combined evidence of genetic and environmental structure suggests that isolation by distance and a process here termed isolation by environmental distance can explain the observed correlations. Our approach elucidated important ecological and conservation aspects of franciscana dolphins, and has the potential to increase our understanding of ecological processes influencing genetic patterns in other marine species.

A novel automatic method for monitoring Tourette motor tics through a wearable device.

The aim of this study was to propose a novel automatic method for quantifying motor-tics caused by the Tourette Syndrome (TS). In this preliminary report, the feasibility of the monitoring process was tested over a series of standard clinical trials in a population of 12 subjects affected by TS. A wearable instrument with an embedded three-axial accelerometer was used to detect and classify motor tics during standing and walking activities. An algorithm was devised to analyze acceleration data by: eliminating noise; detecting peaks connected to pathological events; and classifying intensity and frequency of motor tics into quantitative scores. These indexes were compared with the video-based ones provided by expert clinicians, which were taken as the gold-standard. Sensitivity, specificity, and accuracy of tic detection were estimated, and an agreement analysis was performed through the least square regression and the Bland-Altman test. The tic recognition algorithm showed sensitivity = 80.8% ± 8.5% (mean ± SD), specificity = 75.8% ± 17.3%, and accuracy = 80.5% ± 12.2%. The agreement study showed that automatic detection tended to overestimate the number of tics occurred. Although, it appeared this may be a systematic error due to the different recognition principles of the wearable and video-based systems. Furthermore, there was substantial concurrency with the gold-standard in estimating the severity indexes. The proposed methodology gave promising performances in terms of automatic motor-tics detection and classification in a standard clinical context. The system may provide physicians with a quantitative aid for TS assessment. Further developments will focus on the extension of its application to everyday long-term monitoring out of clinical environments.

A-phase classification using convolutional neural networks.

A series of short events, called A-phases, can be observed in the human electroencephalogram (EEG) during Non-Rapid Eye Movement (NREM) sleep. These events can be classified in three groups (A1, A2, and A3) according to their spectral contents, and are thought to play a role in the transitions between the different sleep stages. A-phase detection and classification is usually performed manually by a trained expert, but it is a tedious and time-consuming task. In the past two decades, various researchers have designed algorithms to automatically detect and classify the A-phases with varying degrees of success, but the problem remains open. In this paper, a different approach is proposed: instead of attempting to design a general classifier for all subjects, we propose to train ad-hoc classifiers for each subject using as little data as possible, in order to drastically reduce the amount of time required from the expert. The proposed classifiers are based on deep convolutional neural networks using the log-spectrogram of the EEG signal as input data. Results are encouraging, achieving average accuracies of 80.31% when discriminating between A-phases and non A-phases, and 71.87% when classifying among A-phase sub-types, with only 25% of the total A-phases used for training. When additional expert-validated data is considered, the sub-type classification accuracy increases to 78.92%. These results show that a semi-automatic annotation system with assistance from an expert could provide a better alternative to fully automatic classifiers. Graphical abstract A/N Deep Learning Classifier.

Heat Treatments and Critical Quenching Rates in Additively Manufactured Al-Si-Mg Alloys.

Laser powder-bed fusion (LPBF) has significantly gained in importance and has become one of the major fabrication techniques within metal additive manufacturing. The fast cooling rates achieved in LPBF due to a relatively small melt pool on a much larger component or substrate, acting as heat sink, result in fine-grained microstructures and high oversaturation of alloying elements in the α-aluminum. Al-Si-Mg alloys thus can be effectively precipitation hardened. Moreover, the solidified material undergoes an intrinsic heat treatment, whilst the layers above are irradiated and the elevated temperature in the built chamber starts the clustering process of alloying elements directly after a scan track is fabricated. These silicon-magnesium clusters were observed with atom probe tomography in as-built samples. Similar beneficial clustering behavior at higher temperatures is known from the direct-aging approach in cast samples, whereby the artificial aging is performed immediately after solution annealing and quenching. Transferring this approach to LPBF samples as a possible post-heat treatment revealed that even after direct aging, the outstanding hardness of the as-built condition could, at best, be met, but for most instances it was significantly lower. Our investigations showed that LPBF Al-Si-Mg exhibited a high dependency on the quenching rate, which is significantly more pronounced than in cast reference samples, requiring two to three times higher quenching rate after solution annealing to yield similar hardness results. This suggests that due to the finer microstructure and the shorter diffusion path in Al-Si-Mg fabricated by LPBF, it is more challenging to achieve a metastable oversaturation necessary for precipitation hardening. This may be especially problematic in larger components.