Enhanced Diagnostic Precision: Assessing Tumor Differentiation in Head and Neck Squamous Cell Carcinoma Using Multi-Slice Spiral CT Texture Analysis.

This study explores the efficacy of texture analysis by using preoperative multi-slice spiral computed tomography (MSCT) to non-invasively determine the grade of cellular differentiation in head and neck squamous cell carcinoma (HNSCC). In a retrospective study, MSCT scans of patients with HNSCC were analyzed and classified based on its histological grade as moderately differentiated, well-differentiated, or poorly differentiated. The location of the tumor was categorized as either in the bone or in soft tissues. Segmentation of the lesion areas was conducted, followed by texture analysis. Eleven GLCM parameters across five different distances were calculated. Median values and correlations of texture parameters were examined in relation to tumor differentiation grade by using Spearman's correlation coefficient and Kruskal-Wallis and Dunn tests. Forty-six patients were included, predominantly female (87%), with a mean age of 66.7 years. Texture analysis revealed significant parameter correlations with histopathological grades of tumor differentiation. The study identified no significant age correlation with tumor differentiation, which underscores the potential of texture analysis as an age-independent biomarker. The strong correlations between texture parameters and histopathological grades support the integration of this technique into the clinical decision-making process.

Psycho-physio-neurological correlates of qualitative attention, emotion and flow experiences in a close-to-real-life extreme sports situation: low- and high-altitude slackline walking.

It has been indicated that extreme sport activities result in a highly rewarding experience, despite also providing fear, stress and anxiety. Studies have related this experience to the concept of flow, a positive feeling that individuals undergo when they are completely immersed in an activity. However, little is known about the exact nature of these experiences, and, there are still no empirical results to characterize the brain dynamics during extreme sport practice. This work aimed at investigating changes in psychological responses while recording physiological (heart rate-HR, and breathing rate-BR) and neural (electroencephalographic-EEG) data of eight volunteers, during outdoors slackline walking in a mountainous environment at two different altitude conditions (1 m-low-walk- and 45 m-high-walk-from the ground). Low-walk showed a higher score on flow scale, while high-walk displayed a higher score in the negative affect aspects, which together point to some level of flow restriction during high-walk. The order of task performance was shown to be relevant for the physiological and neural variables. The brain behavior during flow, mainly considering attention networks, displayed the stimulus-driven ventral attention network-VAN, regionally prevailing (mainly at the frontal lobe), over the goal-directed dorsal attention network-DAN. Therefore, we suggest an interpretation of flow experiences as an opened attention to more changing details in the surroundings, i.e., configured as a 'task-constantly-opened-to-subtle-information experience', rather than a 'task-focused experience'.

Differences between Alzheimer's disease and mild cognitive impairment using brain networks from magnetic resonance texture analysis.

Several studies have aimed at identifying biomarkers in the initial phases of Alzheimer's disease (AD). Conversely, texture features, such as those from gray-level co-occurrence matrices (GLCMs), have highlighted important information from several types of medical images. More recently, texture-based brain networks have been shown to provide useful information in characterizing healthy individuals. However, no studies have yet explored the use of this type of network in the context of AD. This work aimed to employ texture brain networks to investigate the distinction between groups of patients with amnestic mild cognitive impairment (aMCI) and mild dementia due to AD, and a group of healthy subjects. Magnetic resonance (MR) images from the three groups acquired at two instances were used. Images were segmented and GLCM texture parameters were calculated for each region. Structural brain networks were generated using regions as nodes and the similarity among texture parameters as links, and graph theory was used to compute five network measures. An ANCOVA was performed for each network measure to assess statistical differences between groups. The thalamus showed significant differences between aMCI and AD patients for four network measures for the right hemisphere and one network measure for the left hemisphere. There were also significant differences between controls and AD patients for the left hippocampus, right superior parietal lobule, and right thalamus-one network measure each. These findings represent changes in the texture of these regions which can be associated with the cortical volume and thickness atrophies reported in the literature for AD. The texture networks showed potential to differentiate between aMCI and AD patients, as well as between controls and AD patients, offering a new tool to help understand these conditions and eventually aid early intervention and personalized treatment, thereby improving patient outcomes and advancing AD research.

Hand differences in aiming task: A complementary spatial approach and analysis of dynamic brain networks with EEG.

Left and right-hand exhibit differences in the execution of movements. Particularly, it has been shown that manual goal-directed aiming is more accurate with the right hand than with the left, which has been explained through the shorter time spent by the right hand in the feedback phase (FB). This explanation makes sense for the temporal aspects of the task; however, there is a lack of explanations for the spatial aspects. The present study hypothesizes that the right hand is more associated with the FB, while the left hand is more strongly associated with the pre-programming phase (PP). In addition, the present study aims to investigate differences between hands in functional brain connectivity (FBC). We hypothesize an increase in FBC of the right hand compared to the left hand. Twenty-two participants performed 20 trials of the goal-directed aiming task with both hands. Overall, the results confirm the study's hypotheses. Although the right hand stopped far from the target at the PP, it exhibited a lower final position error than the left hand. These findings imply that during the FB, the right hand compensates for the higher error observed in the PP, using the visual feedback to approach the target more closely than the left hand. Conversely, the left hand displayed a lower error at the PP than the right. Also, the right hand displayed greater FBC within and between brain hemispheres. This heightened connectivity in the right hand might be associated with inhibitory mechanisms between hemispheres.

Resistance training effects on pubertal children with a risk of developing pediatric dynapenia.

PURPOSE: Many modern-day children are at risk of pediatric dynapenia (muscle weakness). We examined the effects of a 12-week resistance training (RT) program on neuromuscular function and body composition parameters in pubertal children with a risk of dynapenia. METHODS: Twelve children (13.4 ± 0.9 y) with dynapenia performed a progressive RT program consisting of knee extension and flexion, bench press, abdominal crunch, back extension, lateral pull-down, elbow flexion, and upright row (1-2 sets of 10-15 repetitions/exercise) twice/week for 12 weeks. Outcome measures included one-repetition maximum (1-RM) strength, maximal voluntary isometric contraction (MVIC) torque, rate of torque development (RTD), electromyographic (EMG) activity, muscle thickness (MT), muscle quality (MQ) assessed by echo intensity (MQEI) of the knee extensors and specific tension of MVIC torque to thigh fat-free mass (MQST), and total and regional body and bone composition assessed by dual-energy X-ray absorptiometry. Changes in the measures before and after the 12-week RT and associations among the measures were analyzed by linear mixed models. RESULTS: Significant (p < 0.05) increases in 1-RM (63.9 ± 4.5%), MVIC torque (16.3 ± 17.8%), MT (18.8 ± 5.5%) and MQ (MQEI: -25.9 ± 15.2%; MQST: 15.1 ± 18.8%;) were evident from pre- to post-training. Total fat-free mass (FFM) increased by 2.3 ± 3.2% from baseline (p = 0.01), but no changes (p > 0.05) in the other measures were observed. Significant (p < 0.05) associations between the changes in 1-RM and/or MVIC torque and the changes in quadriceps MT, MQEI, MQST and total body FFM were evident. CONCLUSIONS: The 12-week RT was effective for improving neuromuscular and body composition parameters, and thereby reversed the risk of pediatric dynapenia.

Graph analysis of cortical reorganization after virtual reality-based rehabilitation following stroke: a pilot randomized study.

Introduction: Stroke is the leading cause of functional disability worldwide. With the increase of the global population, motor rehabilitation of stroke survivors is of ever-increasing importance. In the last decade, virtual reality (VR) technologies for rehabilitation have been extensively studied, to be used instead of or together with conventional treatments such as physiotherapy or occupational therapy. The aim of this work was to evaluate the GestureCollection VR-based rehabilitation tool in terms of the brain changes and clinical outcomes of the patients. Methods: Two groups of chronic patients underwent a rehabilitation treatment with (experimental) or without (control) complementation with GestureCollection. Functional magnetic resonance imaging exams and clinical assessments were performed before and after the treatment. A functional connectivity graph-based analysis was used to assess differences between the connections and in the network parameters strength and clustering coefficient. Results: Patients in both groups showed improvement in clinical scales, but there were more increases in functional connectivity in the experimental group than in the control group. Discussion: The experimental group presented changes in the connections between the frontoparietal and the somatomotor networks, associative cerebellum and basal ganglia, which are regions associated with reward-based motor learning. On the other hand, the control group also had results in the somatomotor network, in its ipsilateral connections with the thalamus and with the motor cerebellum, which are regions more related to a purely mechanical activity. Thus, the use of the GestureCollection system was successfully shown to promote neuroplasticity in several motor-related areas.

Texture-based brain networks for characterization of healthy subjects from MRI.

Brain networks have been widely used to study the relationships between brain regions based on their dynamics using, e.g. fMRI or EEG, and to characterize their real physical connections using DTI. However, few studies have investigated brain networks derived from structural properties; and those have been based on cortical thickness or gray matter volume. The main objective of this work was to investigate the feasibility of obtaining useful information from brain networks derived from structural MRI, using texture features. We also wanted to verify if texture brain networks had any relation with established functional networks. T1-MR images were segmented using AAL and texture parameters from the gray-level co-occurrence matrix were computed for each region, for 760 subjects. Individual texture networks were used to evaluate the structural connections between regions of well-established functional networks; assess possible gender differences; investigate the dependence of texture network measures with age; and single out brain regions with different texture-network characteristics. Although around 70% of texture connections between regions belonging to the default mode, attention, and visual network were greater than the mean connection value, this effect was small (only between 7 and 15% of these connections were larger than one standard deviation), implying that texture-based morphology does not seem to subside function. This differs from cortical thickness-based morphology, which has been shown to relate to functional networks. Seventy-five out of 86 evaluated regions showed significant (ANCOVA, p < 0.05) differences between genders. Forty-four out of 86 regions showed significant (ANCOVA, p < 0.05) dependence with age; however, the R2 indicates that this is not a linear relation. Thalamus and putamen showed a very unique texture-wise structure compared to other analyzed regions. Texture networks were able to provide useful information regarding gender and age-related differences, as well as for singling out specific brain regions. We did not find a morphological texture-based subsidy for the evaluated functional brain networks. In the future, this approach will be extended to neurological patients to investigate the possibility of extracting biomarkers to help monitor disease evolution or treatment effectiveness.

Magnetic resonance imaging texture analysis to differentiate ameloblastoma from odontogenic keratocyst.

The differentiation between ameloblastoma (AB) and odontogenic keratocyst (OKC) is essential for the formulation of the surgical plan, especially considering the biological behavior of these two pathological entities. Therefore, developing means to increase the accuracy of the diagnostic process is extremely important for a safe treatment. The aim of this study was to use magnetic resonance imaging (MRI) based on texture analysis (TA) as an aid in differentiating AB from OKC. This study comprised 18 patients; eight patients with AB and ten with OKC. All diagnoses were determined through incisional biopsy and later through histological examination of the surgical specimen. MRI was performed using a 3 T scanner with a neurovascular coil according to a specific protocol. All images were exported to segmentation software in which the volume of interest (VOI) was determined by a radiologist, who was blind to the histopathological results. Next, the textural parameters were computed by using the MATLAB software. Spearman's correlation coefficient was used to assess the correlation between texture parameters and the selected variables. Differences in TA parameters were compared between AB and OKC by using the Mann-Whitney test. Mann-Whitney test showed a statistically significant difference between AB and OKC for the parameters entropy (P = 0.033) and sum average (P = 0.033). MRI texture analysis has the potential to discriminate between AB and OKC as a noninvasive method. MRI texture analysis can be an additional tool to differentiate ameloblastoma from odontogenic keratocyst.

Axonal dysfunction is associated with interferon-γ levels in childhood-onset systemic lupus erythematosus: a multivoxel magnetic resonance spectroscopy study.

OBJECTIVE: Axonal/neuronal damage has been shown to be a pathological finding that precedes neuropsychiatric manifestations in SLE. The objective of this study was to determine the presence of axonal dysfunction in childhood-onset SLE patients (cSLE) and to determine clinical, immunological and treatment features associated with its occurrence. METHODS: We included 86 consecutive cSLE patients [median age 17 (range 5-28) years] and 71 controls [median age 18 (5-28) years]. We performed proton magnetic resonance spectroscopic imaging using point resolved spectroscopy sequence over the superior-posterior region of the corpus callosum and signals from N-acetylaspartate (NAA), choline-based (CHO), creatine-containing (Cr), myo-inositol (mI), glutamate, glutamine and lactate were measured and metabolites/Cr ratios were determined. Complete clinical, laboratory and neurological evaluations were performed in all subjects. Serum IL-4, IL-5, IL-6, IL-10, IL-12, IL-17, TNF-α and INF-γ cytokine levels, antiribosomal P protein antibodies (anti-P) and S100ß were measured by ELISA using commercial kits. Data were compared by non-parametric tests. RESULTS: NAA/Cr ratios (P = 0.035) and lactate/Cr ratios (P = 0.019) were significantly decreased in cSLE patients when compared with controls. In multivariate analysis, IFN-γ levels [odds ratio (OR) = 4.1; 95% CI: 2.01, 7.9] and depressive symptoms (OR = 1.9; 95% CI: 1.1, 3.2) were associated with NAA/Cr ratio. Increased CHO/Cr was associated with the presence of cognitive impairment (OR = 3.4; 95% CI: 2.034, 5.078; P < 0.001). mI/Cr ratio correlated with cumulative glucocorticoids dosage (r = 0.361, P = 0.014). CONCLUSION: NAA and CHO ratios may be useful as biomarkers in neuropsychiatric cSLE. Longitudinal studies are necessary to determine whether they predict structural damage.

Effects of virtual reality-based motor rehabilitation: a systematic review of fMRI studies.

Background.The use of virtual reality (VR) as a rehabilitation tool has been shown to induce motor and cognitive improvements in different populations. Functional magnetic resonance imaging (fMRI) has been used to investigate neuroplasticity resulting from these treatments. We hypothesize that VR rehabilitation induces functional improvement and brain changes that can be detected by fMRI.Objective.To systematically review the effects of VR intervention on the cortical reorganization measured by fMRI and associated with functional improvement.Approach.We performed a systematic review of studies published between 2005 and 2021. Papers were retrieved from six databases using the following keywords: 'motor rehabilitation', 'fMRI' and 'virtual reality'. Case studies, pre-post studies, cross-sectional studies, and randomized controlled trials published were included. Manuscripts were assessed by The National Institutes of Health study quality assessment tools to determine their quality.Main results.Twenty-three articles met our eligibility criteria: 18 about VR rehabilitation in stroke and five on other clinical conditions (older adults, cerebral palsy, and Parkinson's disease). Changes in neural patterns of activation and reorganization were revealed in both the ipsilesional and the contralesional hemispheres. Results were located mainly in the primary motor cortex, sensorimotor cortex and supplementary motor area in post-stroke patients in the acute, subacute, and chronic rehabilitation phases, and were associated with functional improvement after VR intervention. Similar effects were observed in older adults and in patients with other neurological diseases with improved performance.Significance.Most stroke-related studies showed either restoration to normal or increase of activation patterns or relateralization at/to the ipsilesional hemisphere, with some also reporting a decrease in activity or extent of activation after VR therapy. In general, VR intervention demonstrated evidence of efficacy both in neurological rehabilitation and in performance improvement of older adults, accompanied by fMRI evidence of brain reorganization.

Motor imagery practice and feedback effects on functional connectivity.

- Objective: the use of motor imagery (MI) in motor rehabilitation protocols has been increasingly investigated as a potential technique for enhancing traditional treatments, yielding better clinical outcomes. However, since MI performance can be challenging, practice is usually required. This demands appropriate training, actively engaging the MI-related brain areas, consequently enabling the user to properly benefit from it. The role of feedback is central for MI practice. Yet, assessing which underlying neural changes are feedback-specific or purely due to MI practice is still a challenging effort, mainly due to the difficulty in isolating their contributions. In this work, we aimed to assess functional connectivity (FC) changes following MI practice that are either extrinsic or specific to feedback. APPROACH: to achieve this, we investigated FC, using graph theory, in electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, during MI performance and at resting-state (rs), respectively. Thirty healthy subjects were divided into three groups, receiving no feedback (control), "false" feedback (sham) or actual neurofeedback (active). Participants underwent 12 to 13 hands-MI EEG sessions and pre- and post-MI training fMRI exams. MAIN RESULTS: following MI practice, control participants presented significant increases in degree and in eigenvector centrality for occipital nodes at rs-fMRI scans, whereas sham-feedback produced similar effects, but to a lesser extent. Therefore, MI practice, by itself, seems to stimulate visual information processing mechanisms that become apparent during basal brain activity. Additionally, only the active group displayed decreases in inter-subject FC patterns, both during MI performance and at rs-fMRI. SIGNIFICANCE: hence, actual neurofeedback impacted FC by disrupting common inter-subject patterns, suggesting that subject-specific neural plasticity mechanisms become important. Future studies should consider this when designing experimental NFBT protocols and analyses.

EEG Signal Connectivity for Characterizing Interictal Activity in Patients With Mesial Temporal Lobe Epilepsy.

Over the last decade, several methods for analysis of epileptiform signals in electroencephalography (EEG) have been proposed. These methods mainly use EEG signal features in either the time or the frequency domain to separate regular, interictal, and ictal brain activity. The aim of this work was to evaluate the feasibility of using functional connectivity (FC) based feature extraction methods for the analysis of epileptiform discharges in EEG signals. These signals were obtained from EEG-fMRI sessions of 10 patients with mesial temporal lobe epilepsy (MTLE) with unilateral hippocampal atrophy. The connectivity functions investigated were motif synchronization, imaginary coherence, and magnitude squared coherence in the alpha, beta, and gamma bands of the EEG. EEG signals were sectioned into 1-s epochs and classified according to (using neurologist markers): activity far from interictal epileptiform discharges (IED), activity immediately before an IED and, finally, mid-IED activity. Connectivity matrices for each epoch for each FC function were built, and graph theory was used to obtain the following metrics: strength, cluster coefficient, betweenness centrality, eigenvector centrality (both local and global), and global efficiency. The statistical distributions of these metrics were compared among the three classes, using ANOVA, for each FC function. We found significant differences in all global (p < 0.001) and local (p < 0.00002) graph metrics of the far class compared with before and mid for motif synchronization on the beta band; local betweenness centrality also pointed to a degree of lateralization on the frontotemporal structures. This analysis demonstrates the potential of FC measures, computed using motif synchronization, for the characterization of epileptiform activity of MTLE patients. This methodology may be helpful in the analysis of EEG-fMRI data applied to epileptic foci localization. Nonetheless, the methods must be tested with a larger sample and with other epileptic phenotypes.

Channel capacity in brain-computer interfaces.

OBJECTIVE: Adapted from the concept of channel capacity, the information transfer rate (ITR) has been widely used to evaluate the performance of a brain-computer interface (BCI). However, its traditional formula considers the model of a discrete memoryless channel in which the transition matrix presents very particular symmetries. As an alternative to compute the ITR, this work indicates a more general closed-form expression-also based on that channel model, but with less restrictive assumptions-and, with the aid of a selection heuristic based on a wrapper algorithm, extends such formula to detect classes that deteriorate the operation of a BCI system. APPROACH: The benchmark is a steady-state visually evoked potential (SSVEP)-based BCI dataset with 40 frequencies/classes, in which two scenarios are tested: (1) our proposed formula is used and the classes are gradually evaluated in the order of the class labels provided with the dataset; and (2) the same formula is used but with the classes evaluated progressively by a wrapper algorithm. In both scenarios, the canonical correlation analysis (CCA) is the tool to detect SSVEPs. MAIN RESULTS: Before and after class selection using this alternative ITR, the average capacity among all subjects goes from 3.71 [Formula: see text] 1.68 to 4.79 [Formula: see text] 0.70 bits per symbol, with p -value <0.01, and, for a supposedly BCI-illiterate subject, her/his capacity goes from 1.53 to 3.90 bits per symbol. SIGNIFICANCE: Besides indicating a consistent formula to compute ITR, this work provides an efficient method to perform channel assessment in the context of a BCI experiment and argues that such method can be used to study BCI illiteracy.

Space-time recurrences for functional connectivity evaluation and feature extraction in motor imagery brain-computer interfaces.

This work presents a classification performance comparison between different frameworks for functional connectivity evaluation and complex network feature extraction aiming to distinguish motor imagery classes in electroencephalography (EEG)-based brain-computer interfaces (BCIs). The analysis was performed in two online datasets: (1) a classical benchmark-the BCI competition IV dataset 2a-allowing a comparison with a representative set of strategies previously employed in this BCI paradigm and (2) a statistically representative dataset for signal processing technique comparisons over 52 subjects. Besides exploring three classical similarity measures-Pearson correlation, Spearman correlation, and mean phase coherence-this work also proposes a recurrence-based alternative for estimating EEG brain functional connectivity, which takes into account the recurrence density between pairwise electrodes over a time window. These strategies were followed by graph feature evaluation considering clustering coefficient, degree, betweenness centrality, and eigenvector centrality. The features were selected by Fisher's discriminating ratio and classification was performed by a least squares classifier in agreement with classical and online BCI processing strategies. The results revealed that the recurrence-based approach for functional connectivity evaluation was significantly better than the other frameworks, which is probably associated with the use of higher order statistics underlying the electrode joint probability estimation and a higher capability of capturing nonlinear inter-relations. There were no significant differences in performance among the evaluated graph features, but the eigenvector centrality was the best feature regarding processing time. Finally, the best ranked graph-based attributes were found in classical EEG motor cortex positions for the subjects with best performances, relating functional organization and motor activity. Graphical Abstract Evaluating functional connectivity based on Space-Time Recurrence Counting for motor imagery classification in brain-computer interfaces. Recurrences are evaluated between electrodes over a time window, and, after a density threshold, the electrodes adjacency matrix is stablish, leading to a graph. Graph-based topological measures are used for motor imagery classification.

Investigation of anisotropic fishing line-based phantom as tool in quality control of diffusion tensor imaging.

This work proposes a low-cost, fishing line-based phantom for quality control of diffusion tensor imaging (DTI). The device was applied to investigate the relationship between DTI indexes (DTIi) and imaging acquisition parameters. A Dyneema® fishing line phantom was built with fiber bundles of different thicknesses. DTI acquisitions were performed in a 3T magnetic resonance imaging scanner using an 8-channel and a 32-channel head coil. For each coil, the following acquisition parameters were changed, one at a time: diffusion sensitivity factor (b value), echo time, sensitivity encoding, voxel size, number of signal averages, and number of diffusion gradient directions (NDGD). DTIi including fractional anisotropy, relative anisotropy (RA), linear anisotropy (CL), and planar anisotropy (CP) were calculated for each image; the data were analyzed using the coefficient of variation (CV) and distributions of DTIi values. The 32-channel head coil presented higher CV values for the DTIi RA, CL, and CP when voxel size was changed. Using the phantom, dependences between diffusion-related parameters (b value and NDGD) and DTIi were also observed; the majority of these were for the smaller thickness fiber bundles. The device proved to be useful for the verification of the DTI performance over time.

Selective sensory deafferentation induces structural and functional brain plasticity.

Sensory-motor integration models have been proposed aiming to explain how the brain uses sensory information to guide and check the planning and execution of movements. Sensory neuronopathy (SN) is a peculiar disease characterized by exclusive, severe and widespread sensory loss. It is a valuable condition to investigate how sensory deafferentation impacts brain organization. We thus recruited patients with clinical and electrophysiological criteria for SN to perform structural and functional MRI analyses. We investigated volumetric changes in gray matter (GM) using anatomical images; the microstructure of WM within segmented regions of interest (ROI), via diffusion images; and brain activation related to a finger tapping task. All significant results were related to the long disease duration subgroup of patients. Structural analysis showed hypertrophy of the caudate nucleus, whereas the diffusion study identified reduction of fractional anisotropy values in ROIs located around the thalamus and the striatum. We also found differences regarding finger-tapping activation in the posterior parietal regions and in the medial areas of the cerebellum. Our results stress the role of the caudate nucleus over the other basal ganglia in the sensory-motor integration models, and suggest an inhibitory function of a recently discovered tract between the thalamus and the striatum. Overall, our findings confirm plasticity in the adult brain and open new avenues to design neurorehabilitation strategies.

Cognitive Reserve Relates to Functional Network Efficiency in Alzheimer's Disease.

Alzheimer's disease (AD) is the most common form of dementia, with no means of cure or prevention. The presence of abnormal disease-related proteins in the population is, in turn, much more common than the incidence of dementia. In this context, the cognitive reserve (CR) hypothesis has been proposed to explain the discontinuity between pathophysiological and clinical expression of AD, suggesting that CR mitigates the effects of pathology on clinical expression and cognition. fMRI studies of the human connectome have recently reported that AD patients present diminished functional efficiency in resting-state networks, leading to a loss in information flow and cognitive processing. No study has investigated, however, whether CR modifies the effects of the pathology in functional network efficiency in AD patients. We analyzed the relationship between CR, pathophysiology and network efficiency, and whether CR modifies the relationship between them. Fourteen mild AD, 28 amnestic mild cognitive impairment (aMCI) due to AD, and 28 controls were enrolled. We used education to measure CR, cerebrospinal fluid (CSF) biomarkers to evaluate pathophysiology, and graph metrics to measure network efficiency. We found no relationship between CR and CSF biomarkers; CR was related to higher network efficiency in all groups; and abnormal levels of CSF protein biomarkers were related to more efficient networks in the AD group. Education modified the effects of tau-related pathology in the aMCI and mild AD groups. Although higher CR might not protect individuals from developing AD pathophysiology, AD patients with higher CR are better able to cope with the effects of pathology-presenting more efficient networks despite pathology burden. The present study highlights that interventions focusing on cognitive stimulation might be useful to slow age-related cognitive decline or dementia and lengthen healthy aging.

EEG sensorimotor rhythms' variation and functional connectivity measures during motor imagery: linear relations and classification approaches.

Hands motor imagery (MI) has been reported to alter synchronization patterns amongst neurons, yielding variations in the mu and beta bands' power spectral density (PSD) of the electroencephalography (EEG) signal. These alterations have been used in the field of brain-computer interfaces (BCI), in an attempt to assign distinct MI tasks to commands of such a system. Recent studies have highlighted that information may be missing if knowledge about brain functional connectivity is not considered. In this work, we modeled the brain as a graph in which each EEG electrode represents a node. Our goal was to understand if there exists any linear correlation between variations in the synchronization patterns-that is, variations in the PSD of mu and beta bands-induced by MI and alterations in the corresponding functional networks. Moreover, we (1) explored the feasibility of using functional connectivity parameters as features for a classifier in the context of an MI-BCI; (2) investigated three different types of feature selection (FS) techniques; and (3) compared our approach to a more traditional method using the signal PSD as classifier inputs. Ten healthy subjects participated in this study. We observed significant correlations (p < 0.05) with values ranging from 0.4 to 0.9 between PSD variations and functional network alterations for some electrodes, prominently in the beta band. The PSD method performed better for data classification, with mean accuracies of (90 ± 8)% and (87 ± 7)% for the mu and beta band, respectively, versus (83 ± 8)% and (83 ± 7)% for the same bands for the graph method. Moreover, the number of features for the graph method was considerably larger. However, results for both methods were relatively close, and even overlapped when the uncertainties of the accuracy rates were considered. Further investigation regarding a careful exploration of other graph metrics may provide better alternatives.

Phantoms for diffusion-weighted imaging and diffusion tensor imaging quality control: a review and new perspectives

Abstract: Introduction Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) combine magnetic resonance imaging (MRI) techniques and diffusion measures. In DWI, the contrast is defined by microscopic motion of water protons. Nowadays, DWI has become important for early diagnostic of acute stroke. DTI images are calculated from DWI images acquired in at least six directions, which give information of diffusion directionality, making it possible to reconstruct axonal or muscle fiber images. Both techniques have been applied to study body structures in healthy and pathological conditions. Currently, it is known that these images and derived parameters are quite sensitive to factors related to acquisition and processing. Magnetic field inhomogeneity, susceptibility, chemical shift, radiofrequency (RF) interference, eddy currents and low signal-to-noise ratio (SNR) can have a more harmful effect in diffusion data than in T1- or T2-weighted image data. However, even today there are not reference phantoms and guidelines for DWI or DTI quality control (QC). Review Proposals for construction and use of DWI and DTI QC phantoms can be found in literature. DWI have been evaluated using containers filled by gel or liquid with tissue-like MRI properties, as well as using microfabricated devices. DTI acquisitions also have been checked with these devices or using natural or artificial fiber structures. The head phantom from American College of Radiology (ACR) is also pointed out as an alternative for DTI QC. This article brings a discussion about proposed DWI and DTI phantoms, challenges involved and future perspectives for standardization of DWI and DTI QC.

Neumonía por Corynebacterium pseudodiphtheriticum / Pneumonia caused by Corynebacterium pseudodiphtheriticum

Corynebacterium pseudodiphtheriticum forma parte de la microbiota normal de orofaringe y de piel. Sin embargo, en las últimas décadas está emergiendo como oportunista causante de infecciones clínicamente significativas en pacientes con algún compromiso previo. Se refiere el caso clínico de una paciente de 76 años con antecedentes de hipertensión arterial, hipotiroidismo, diabetes tipo 2 e insuficiencia renal crónica, que presentó neumonía durante su estadía en terapia intensiva. El examen directo del esputo inducido (coloración de Gram) reveló una muestra representativa con abundante microbiota monomicrobiana constituida por bacilos gram positivos pleomórficos corineformes y el cultivo presencia de C. pseudodiphtheriticum. La paciente recibió medicación empírica con cefalosporina de tercera generación con evolución favorable.

Microorganisms of the genera Corynebacterium, specie pseudodiphtheriticum are a part of the indigenous microbiota of human skin and oropharinx. Nevertheless in recent decades these bacilli are emerging as opportunistic pathogens causing clinically significant infections in patients with previous compromise. We report the case of a 76 years old female patient, with a history of hypertension, hypothyroidism, type 2 diabetes and chronic renal failure, who presented pneumonia during their stay at the intensive care unit. The induced sputum revealed a representative sample with monomicrobial gram positive pleomorphic coryneform rods (Gram stain) and cultures demonstrated the presence of C. pseudodiphtheriticum as the only bacteria recovered. The pacient received an empirical third generation cephalosporin medication with a succesfull recovery.