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1.
Chemosphere ; 263: 128083, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33297081

RESUMO

Mechanistic insight into protein binding by poly- and perfluoroalkyl substances (PFASs) is critical to understanding how PFASs distribute and accumulate within the body and to developing predictive models within and across classes of PFASs. Fluorine nuclear magnetic resonance spectroscopy (19F NMR) has proven to be a powerful, yet underutilized tool to study PFAS binding; chemical shifts of each fluorine group reflect the local environment along the length of the PFAS molecule. Using bovine serum albumin (BSA), we report dissociation constants, Kd, for four common PFASs well below reported critical micelle concentrations (CMCs) - perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorohexanesulfonic acid (PFHxS), and perfluorooctanesulfonic acid (PFOS) - as a function of temperature in phosphate buffered saline. Kd values were determined based on the difluoroethyl group adjacent to the anionic headgroups and the terminal trifluoromethyl groups. Our results indicate that the hydrophobic tails exhibit greater binding affinity relative to the headgroup, and that the binding affinities are generally consistent with previous results showing that greater PFAS hydrophobicity leads to greater protein binding. However, the binding mechanism was dominated by entropic hydrophobic interactions attributed to desolvation of the PFAS tails within the hydrophobic cavities of the protein and on the surface of the protein. In addition, PFNA appears to form hemimicelles on the protein surfaces below reported CMC values. This work provides a renewed approach to utilizing 19F NMR for PFAS-protein binding studies and a new perspective on the role of solvent entropy.


Assuntos
Ácidos Alcanossulfônicos , Poluentes Ambientais , Fluorcarbonetos , Albuminas , Entropia , Espectroscopia de Ressonância Magnética
2.
Zhongguo Zhong Yao Za Zhi ; 45(21): 5200-5208, 2020 Nov.
Artigo em Chinês | MEDLINE | ID: mdl-33350236

RESUMO

In order to discuss the "entropy weight method" for weighting various indicators in the comprehensive evaluation of Angelicae Sinensis Radix slices(ASR), the quality of ASR was comprehensively evaluated by entropy weight-based gray systematic theory and cluster analysis. In this study, the contents of ferulic acid, volatile oil, polysaccharide, alcohol extract, water extract, moisture, total ash and acid-insoluble ash in 44 batches of ASR from different sources were determined. The entropy weight method was used for objective weighting. With relative correlation(r_i) as a measure, a multi-index comprehensive evaluation model was constructed for the quality of ASR. The results showed that the relative correlation value of 44 batches of ASR ranged from 0.301 9 to 0.662 9. There were certain differences in the quality of ASR from different sources. The ASR S1-S8, traceable and standardized in processing techno-logy, showed a high relative correlation degree and high quality ranking, indicating that the implementation of systemic management of the production chain of Chinese herbal pieces was beneficial to the quality control of ASR. The quality evaluation results of 44 batches of ASR were consistent with those of traditional geo-authentic habitats for ASR and the mainstream varieties of ASR on market, and basically consistent with the results of cluster analysis. This study suggests that the gray systematic theory based on the entropy weighting method can be used for the quality evaluation of ASR. The objective weighting of the entropy weight method improves the reliability of the gray correlation method and the scientificity of ASR quality evaluation.


Assuntos
Angelica sinensis , Medicamentos de Ervas Chinesas , Óleos Voláteis , Entropia , Raízes de Plantas , Reprodutibilidade dos Testes
3.
PLoS One ; 15(11): e0242330, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33180843

RESUMO

Temporal variability of the neural signal has been demonstrated to be closely related to healthy brain function. Meanwhile, the evolving brain functions are supported by dynamic relationships among brain regions. We hypothesized that the spatial variability of brain signal might provide important information about brain function. Here we used the spatial sample entropy (SSE) to investigate the spatial variability of neuroimaging signal during a steady-state presented face detection task. Lower SSE was found during task state than during resting state, associating with more repetitive functional interactions between brain regions. The standard deviation (SD) of SSE during the task was negatively related to the SD of reaction time, suggesting that the spatial pattern of neural activity is reorganized according to particular cognitive function and supporting the previous theory that greater variability is associated with better task performance. These results were replicated with reordered data, implying the reliability of SSE in measuring the spatial organization of neural activity. Overall, the present study extends the research scope of brain signal variability from the temporal dimension to the spatial dimension, improving our understanding of the spatiotemporal characteristics of brain activities and the theory of brain signal variability.


Assuntos
Encéfalo/fisiologia , Adolescente , Adulto , Encéfalo/diagnóstico por imagem , Cognição/fisiologia , Entropia , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Imagem por Ressonância Magnética , Masculino , Estimulação Luminosa , Tempo de Reação , Análise Espaço-Temporal , Análise e Desempenho de Tarefas , Adulto Jovem
4.
PLoS One ; 15(11): e0242056, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33226992

RESUMO

How and to what extent electrical brain activity reflects pharmacologically altered states and contents of consciousness, is not well understood. Therefore, we investigated whether measures of evoked and spontaneous electroencephalographic (EEG) signal diversity are altered by sub-anaesthetic levels of ketamine compared to normal wakefulness, and how these measures relate to subjective experience. High-density 62-channel EEG was used to record spontaneous brain activity and responses evoked by transcranial magnetic stimulation (TMS) in 10 healthy volunteers before and during administration of sub-anaesthetic doses of ketamine in an open-label within-subject design. Evoked signal diversity was assessed using the perturbational complexity index (PCI), calculated from EEG responses to TMS perturbations. Signal diversity of spontaneous EEG, with eyes open and eyes closed, was assessed by Lempel Ziv complexity (LZc), amplitude coalition entropy (ACE), and synchrony coalition entropy (SCE). Although no significant difference was found in TMS-evoked complexity (PCI) between the sub-anaesthetic ketamine condition and normal wakefulness, all measures of spontaneous EEG signal diversity (LZc, ACE, SCE) showed significantly increased values in the sub-anaesthetic ketamine condition. This increase in signal diversity correlated with subjective assessment of altered states of consciousness. Moreover, spontaneous signal diversity was significantly higher when participants had eyes open compared to eyes closed, both during normal wakefulness and during influence of sub-anaesthetic ketamine. The results suggest that PCI and spontaneous signal diversity may reflect distinct, complementary aspects of changes in brain properties related to altered states of consciousness: the brain's capacity for information integration, assessed by PCI, might be indicative of the brain's ability to sustain consciousness, while spontaneous complexity, as measured by EEG signal diversity, may be indicative of the complexity of conscious content. Thus, sub-anaesthetic ketamine may increase the complexity of the conscious content and the brain activity underlying it, while the level or general capacity for consciousness remains largely unaffected.


Assuntos
Encéfalo/fisiologia , Eletroencefalografia/efeitos dos fármacos , Alucinógenos/administração & dosagem , Ketamina/administração & dosagem , Adulto , Encéfalo/efeitos dos fármacos , Entropia , Potenciais Evocados/efeitos dos fármacos , Feminino , Alucinógenos/farmacologia , Voluntários Saudáveis , Humanos , Ketamina/farmacologia , Masculino , Estimulação Magnética Transcraniana/efeitos dos fármacos , Vigília/fisiologia , Adulto Jovem
5.
Mar Pollut Bull ; 160: 111675, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33181948

RESUMO

This study separates marine carrying capacity into four key dimensions, i.e., social, economic, resource, and ecological, and uses the entropy method to evaluate the carrying capacity of China's 11 coastal regions during the period 2007-2016. We then predict the values of marine carrying capacity in the subsequent five years (2017-2021) using the grey Verhulst model. Results reveal a significant disparity in marine carrying capacity among the 11 coastal regions of China, and social and ecological carrying capacities illustrate among the four subcategories. Pearl River Delta in the south has the highest marine carrying capacity value and shows an increasing trend, while Yangtze River Delta and Bohai Rim Region in the north are stable. With regard to the predicted values for 2017-2021, forecasting results illustrate that the industrial structure of China's coastal areas is gradually turning towards the mode of diversified and comprehensive utilization of marine resources.


Assuntos
Conservação dos Recursos Naturais , Rios , China , Entropia , Indústrias
6.
Proc Natl Acad Sci U S A ; 117(44): 27116-27123, 2020 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-33087575

RESUMO

Recent single-molecule experiments have observed transition paths, i.e., brief events where molecules (particularly biomolecules) are caught in the act of surmounting activation barriers. Such measurements offer unprecedented mechanistic insights into the dynamics of biomolecular folding and binding, molecular machines, and biological membrane channels. A key challenge to these studies is to infer the complex details of the multidimensional energy landscape traversed by the transition paths from inherently low-dimensional experimental signals. A common minimalist model attempting to do so is that of one-dimensional diffusion along a reaction coordinate, yet its validity has been called into question. Here, we show that the distribution of the transition path time, which is a common experimental observable, can be used to differentiate between the dynamics described by models of one-dimensional diffusion from the dynamics in which multidimensionality is essential. Specifically, we prove that the coefficient of variation obtained from this distribution cannot possibly exceed 1 for any one-dimensional diffusive model, no matter how rugged its underlying free energy landscape is: In other words, this distribution cannot be broader than the single-exponential one. Thus, a coefficient of variation exceeding 1 is a fingerprint of multidimensional dynamics. Analysis of transition paths in atomistic simulations of proteins shows that this coefficient often exceeds 1, signifying essential multidimensionality of those systems.


Assuntos
Biologia Computacional/métodos , Temperatura de Transição , Membrana Celular , Difusão , Entropia , Nanotecnologia , Pinças Ópticas , Dobramento de Proteína , Proteínas/química , Termodinâmica
7.
PLoS One ; 15(10): e0235885, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33119617

RESUMO

Kernel methods are powerful machine learning techniques which use generic non-linear functions to solve complex tasks. They have a solid mathematical foundation and exhibit excellent performance in practice. However, kernel machines are still considered black-box models as the kernel feature mapping cannot be accessed directly thus making the kernels difficult to interpret. The aim of this work is to show that it is indeed possible to interpret the functions learned by various kernel methods as they can be intuitive despite their complexity. Specifically, we show that derivatives of these functions have a simple mathematical formulation, are easy to compute, and can be applied to various problems. The model function derivatives in kernel machines is proportional to the kernel function derivative and we provide the explicit analytic form of the first and second derivatives of the most common kernel functions with regard to the inputs as well as generic formulas to compute higher order derivatives. We use them to analyze the most used supervised and unsupervised kernel learning methods: Gaussian Processes for regression, Support Vector Machines for classification, Kernel Entropy Component Analysis for density estimation, and the Hilbert-Schmidt Independence Criterion for estimating the dependency between random variables. For all cases we expressed the derivative of the learned function as a linear combination of the kernel function derivative. Moreover we provide intuitive explanations through illustrative toy examples and show how these same kernel methods can be applied to applications in the context of spatio-temporal Earth system data cubes. This work reflects on the observation that function derivatives may play a crucial role in kernel methods analysis and understanding.


Assuntos
Simulação por Computador , Ciências da Terra , Aprendizado de Máquina , Máquina de Vetores de Suporte , Entropia , Humanos , Distribuição Normal
8.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2740-2743, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018573

RESUMO

Lung sound (LS) signals are often contaminated by impulsive artifacts that complicate the estimation of lung sound intensity (LSI) using conventional amplitude estimators. Fixed sample entropy (fSampEn) has proven to be robust to cardiac artifacts in myographic respiratory signals. Similarly, fSampEn is expected to be robust to artifacts in LS signals, thus providing accurate LSI estimates. However, the choice of fSampEn parameters depends on the application and fSampEn has not previously been applied to LS signals. This study aimed to perform an evaluation of the performance of the most relevant fSampEn parameters on LS signals, and to propose optimal fSampEn parameters for LSI estimation. Different combinations of fSampEn parameters were analyzed in LS signals recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing. The performance of fSampEn was assessed by means of its cross-covariance with flow signals, and optimal fSampEn parameters for LSI estimation were proposed.


Assuntos
Sons Respiratórios , Processamento de Sinais Assistido por Computador , Artefatos , Entropia , Coração , Humanos
9.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2748-2751, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018575

RESUMO

Neural respiratory drive as measured by the electromyography allows the study of the imbalance between the load on respiratory muscles and its capacity. Surface respiratory electromyography (sEMG) is a non-invasive tool used for indirectly assessment of NRD. It also provides a way to evaluate the level and pattern of respiratory muscle activation. The prevalence of electrocardiographic activity (ECG) in respiratory sEMG signals hinders its proper evaluation. Moreover, the occurrence of abnormal heartbeats or cardiac arrhythmias in respiratory sEMG measures can make even more challenging the NRD estimation. Respiratory sEMG can be evaluated using the fixed sample entropy (fSampEn), a technique which is less affected by cardiac artefacts. The aim of this work was to investigate the performance of the fSampEn, the root mean square (RMS) and the average rectified value (ARV) on respiratory sEMG signals with supraventricular arrhythmias (SVA) for NRD estimation. fSampEn, ARV and RMS parameters increased as the inspiratory load increased during the test. fSampEn was less influenced by ECG with SVAs for the NRD estimation showing a greater response to respiratory sEMG, reflected with a higher percentage increase with increasing load (228 % total increase, compared to 142 % and 135 % for ARV and RMS, respectively).


Assuntos
Eletrocardiografia , Músculos Respiratórios , Arritmias Cardíacas/diagnóstico , Eletromiografia , Entropia , Humanos
10.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2897-2900, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018612

RESUMO

It is well known that physiological systems show complex and nonlinear behaviours. In spite of that, functional near-infrared spectroscopy (fNIRS) is usually analyzed in the time and frequency domains with the assumption that metabolic activity is generated from a linear system. To leverage the full information provided by fNIRS signals, in this study we investigate topological entropy in fNIRS series collected from 10 healthy subjects during mental mental arithmetic task. While sample entropy and fuzzy entropy were used to estimate time series irregularity, distribution entropy was used to estimate time series complexity. Our findings show that entropy estimates may provide complementary characterization of fNIRS dynamics with respect to reference time domain measurements. This finding paves the way to further investigate functional activation in fNIRS in different case studies using nonlinear and complexity system theory.


Assuntos
Espectroscopia de Luz Próxima ao Infravermelho , Análise de Sistemas , Entropia
11.
Environ Sci Pollut Res Int ; 27(35): 44623-44628, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33040286

RESUMO

To substantiate the validity and usefulness of the symbolic transfer entropy test for longitudinal data, and how it validate or contrast existing study results generated using other forms of causality tests, we empirically examine panel-based causality relationships among foreign direct investment, energy consumption, globalization, and economic growth respectively, between the periods 1970 and 2014 using sub-Saharan African countries as a case study. Based on our findings, we are of the opinion that STE causality test results resonate existing findings, and it is a suitable causality approach for longitudinal data and for developing countries with poor-quality data, most specifically for the sample region.


Assuntos
Dióxido de Carbono , Desenvolvimento Econômico , Entropia , Internacionalidade , Investimentos em Saúde
12.
An Acad Bras Cienc ; 92(3): e20200594, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33053108

RESUMO

In this research, the trade-off between the number of restrictions and the robustness of the primary formulation of entropy models was evaluated. The performance of six hydrodynamic models in open channels was assessed based on 1730 Laser-Doppler anemometry data. It was investigated whether it is better to use an entropy-based model with more restrictions and a weak primary formulation or a model with fewer restrictions, but with a strong formulation. In addition, it was also investigated whether the model performance improves with the insertion of restrictions. Three of the investigated models have a weak formulation (open-channel velocity field represented by Cartesian coordinates); while the other three models have a strong formulation, according to which isovels are represented by curvilinear coordinates. The results indicated that models with two restrictions performed better than those with one restriction, since the additional restriction includes information relevant to the system. Models with three restrictions perform worse than those with two restrictions, because the information lost due to the use of a numerical solution was more substantial than the information gained by the third restriction. In conclusion, a strong primary formulation brought more information to the system than the inclusion of a third constraint.


Assuntos
Entropia , Modelos Teóricos
13.
J Cancer Res Ther ; 16(5): 1171-1176, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-33004766

RESUMO

Background: Targetable drug delivery is an important method for the treatment of liver tumors. For the quantitative analysis of drug diffusion, the establishment of a method for information collection and characterization of extracellular space is developed by imaging analysis of magnetic resonance imaging (MRI) sequences. In this paper, we smoothed out interferential part in scanned digital MRI images. Materials and Methods: Making full use of priors of low rank, nonlocal self-similarity, and regularized sparsity-promoting entropy, a block-matching regularized entropy minimization algorithm is proposed. Sparsity-promoting entropy function produces much sparser representation of grouped nonlocal similar blocks of image by solving a nonconvex minimization problem. Moreover, an alternating direction method of multipliers algorithm is proposed to iteratively solve the problem above. Results and Conclusions: Experiments on simulated and real images reveal that the proposed method obtains better image restorations compared with some state-of-the-art methods, where most information is recovered and few artifacts are produced.


Assuntos
Algoritmos , Antineoplásicos/metabolismo , Preparações de Ação Retardada/metabolismo , Sistemas de Liberação de Medicamentos/métodos , Processamento de Imagem Assistida por Computador/métodos , Neoplasias Hepáticas/metabolismo , Imagem por Ressonância Magnética/métodos , Difusão , Entropia , Humanos , Neoplasias Hepáticas/patologia
14.
Proc Natl Acad Sci U S A ; 117(42): 26031-26039, 2020 10 20.
Artigo em Inglês | MEDLINE | ID: mdl-33020277

RESUMO

While allostery is of paramount importance for protein regulation, the underlying dynamical process of ligand (un)binding at one site, resulting time evolution of the protein structure, and change of the binding affinity at a remote site are not well understood. Here the ligand-induced conformational transition in a widely studied model system of allostery, the PDZ2 domain, is investigated by transient infrared spectroscopy accompanied by molecular dynamics simulations. To this end, an azobenzene-derived photoswitch is linked to a peptide ligand in a way that its binding affinity to the PDZ2 domain changes upon switching, thus initiating an allosteric transition in the PDZ2 domain protein. The subsequent response of the protein, covering four decades of time, ranging from ∼1 ns to ∼µs, can be rationalized by a remodeling of its rugged free-energy landscape, with very subtle shifts in the populations of a small number of structurally well-defined states. It is proposed that structurally and dynamically driven allostery, often discussed as limiting scenarios of allosteric communication, actually go hand-in-hand, allowing the protein to adapt its free-energy landscape to incoming signals.


Assuntos
Simulação de Dinâmica Molecular , Domínios PDZ , Conformação Proteica , Proteínas Tirosina Fosfatases/química , Proteínas Tirosina Fosfatases/metabolismo , Regulação Alostérica , Sítios de Ligação , Entropia , Humanos , Ligantes , Mutação , Ligação Proteica , Proteínas Tirosina Fosfatases/genética , Espectrofotometria Infravermelho
15.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 5176-5179, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33019151

RESUMO

Clinical assessment of Multiple Sclerosis relies heavily on the Expanded Disability Status Scale, a non-linear rating system based on physician assessment of disease progression and walking ability. This inherently makes this method both subjective and limited in repeatability. This study developed a technically derived outcome measure of posture to compare a cohort of Multiple Sclerosis and Control subjects during an Eyes-Open and Eyes-closed task. Analysing traditional sway parameters and a multiscale entropy derived complexity index of posturography showed a significant difference in medio-lateral sway between groups during the Eyes-Open condition. This technically derived outcome measure may be of clinical benefit in the longitudinal assessment of the functional impact of balance in MS cohorts and assist in the evaluation of pharmaceutical and rehabilitation interventions.


Assuntos
Esclerose Múltipla , Progressão da Doença , Entropia , Humanos , Equilíbrio Postural , Postura
16.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 5280-5283, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33019175

RESUMO

Depression is a harmful disease with high incidence. However, no effective method based on physiological information detection has been published to diagnose depression. Electroencephalography (EEG) has been used as a tool to detect physiological information of depressed patients and the symmetry of EEG receives much attention. This research focused on the symmetry of EEG in left and right homologous brain regions. 22 healthy volunteers and 41 volunteers of major depression were tested and three methods, average power ratio, waveform correlation and power spectral correlation, were adopted to measure the symmetry in all frequency bands and all brain regions. After t-test, homologous site pairs in particular frequency bands with significant differences between major depressed patients and controls were found out. Then sample entropy analysis was adopted, trying to figure out further connections between EEG symmetry and major depression. The accuracy tests were also taken and the average accuracy of some tests could reach 93.7%. The result of this research can hopefully serve as a theoretical basis for pattern recognition in the diagnosis of depression. The accuracy of pattern recognition based on multiple processing methods and sites will increase dramatically.


Assuntos
Transtorno Depressivo Maior , Atenção , Encéfalo , Transtorno Depressivo Maior/diagnóstico , Eletroencefalografia , Entropia , Humanos
17.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 5963-5966, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33019330

RESUMO

Electroencephalography (EEG) is a highly complex and non-stationary signal that reflects the cortical electric activity. Feature selection and analysis of EEG for various purposes, such as epileptic seizure detection, are highly in demand. This paper presents an approach to enhance classification performance by selecting discriminative features from a combined feature set consisting of frequency domain and entropy based features. For each EEG channel, nine different features are extracted, including six sub-band spectral powers and three entropy values (sample, permutation and spectral entropy). Features are then ranked across all channels using F-statistic values and selected for SVM classification. Experimentation using CHB-MIT dataset shows that our method achieves average sensitivity, specificity and F-1 score of 92.63%, 99.72% and 91.21%, respectively.


Assuntos
Eletroencefalografia , Epilepsia , Entropia , Epilepsia/diagnóstico , Humanos , Convulsões , Sensibilidade e Especificidade
18.
Artigo em Inglês | MEDLINE | ID: mdl-33017922

RESUMO

The framework of information dynamics allows to quantify different aspects of the statistical structure of multivariate processes reflecting the temporal dynamics of a complex network. The information transfer from one process to another can be quantified through Transfer Entropy, and under the assumption of joint Gaussian variables it is strictly related to the concept of Granger Causality (GC). According to the most recent developments in the field, the computation of GC entails representing the processes through a Vector Autoregressive (VAR) model and a state space (SS) model typically identified by means of the Ordinary Least Squares (OLS). In this work, we propose a new identification approach for the VAR and SS models, based on Least Absolute Shrinkage and Selection Operator (LASSO), that has the advantages of maintaining good accuracy even when few data samples are available and yielding as output a sparse matrix of estimated information transfer. The performances of LASSO identification were first tested and compared to those of OLS by a simulation study and then validated on real electroencephalographic (EEG) signals recorded during a motor imagery task. Both studies indicated that LASSO, under conditions of data paucity, provides better performances in terms of network structure. Given the general nature of the model, this work opens the way to the use of LASSO regression for the computation of several measures of information dynamics currently in use in computational neuroscience.


Assuntos
Eletroencefalografia , Entropia , Análise dos Mínimos Quadrados , Modelos Lineares , Distribuição Normal
19.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 120-123, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33017945

RESUMO

A two-stage deep learning-based scheme is presented to predict the Hamilton Depression Scale (HAM-D) in this study. First, the cross-sample entropy (CSE) that allows assessing the degree of similarity of two data series are evaluated for the 90 brain regions of interest partitioned according to Automated Anatomical Labeling. The obtained CSE maps are then converted to 3D CSE volumes to serve as the inputs to the deep learning network models for the HAM-D scale level classification and prediction. The efficacy of the proposed scheme was illustrated by the resting-state functional magnetic resonance imaging data from 38 patients. From the results, the root mean square errors for the HAM-D scale prediction obtained during training, validation, and testing were 2.73, 2.66, and 2.18, which were less than those of a scheme having only a regression stage.


Assuntos
Aprendizado Profundo , Depressão , Encéfalo , Depressão/diagnóstico , Entropia , Humanos , Imagem por Ressonância Magnética
20.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 280-283, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33017983

RESUMO

This paper evaluated the pupillary light reflex of glaucomatous eyes in the presence of constant lighting via light-induced pupillometry using sample entropy. The study used 20 patients and 15 controls, applied three different light intensities to their eyes, and recorded the behavior of the pupil. This study has validated that there is a difference in the entropy of pupillary data in glaucoma and healthy eyes. We concluded that entropy analysis is an excellent method to differentiate glaucoma eyes with the control through light-induced pupillometry. Hence, pupillometry has potential clinical applications in glaucoma investigation.


Assuntos
Glaucoma , Tetrahymenina , Entropia , Glaucoma/diagnóstico , Humanos , Pupila , Reflexo Pupilar
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