Coylesommer2862

ns appropriate for underprivileged communities will increase care seeking and consequently diagnosis. Improved diagnostic guidelines and a strong referral chain for kala-azar will accelerate diagnosis. These steps will contribute significantly to the National Kala-azar Elimination Program of Bangladesh, especially during the post-elimination era.Ageing leads to a decline in white matter microstructure and dexterous function of the hand. In adolescents, it has previously been shown that the degree of right-left asymmetry in the corticospinal tract (CST) is linearly related with right-left asymmetry in dexterity. Here, we tested whether this association is also expressed in older adults. Participants completed a simple circle drawing task with their right and left hand as a measure of dexterity and underwent whole-brain diffusion weighted imaging at 3 Tesla (n = 199; aged 60-72 years). Fractional anisotropy and mean diffusivity of right and left CST were extracted from a manually defined region-of-interest. Linear regression analyses were computed to replicate the analyses in adolescents. Frequentist analyses were complemented with a Bayesian analytical framework. Outcome measures were compared with those previously reported in adolescents (aged 11-16 years). Asymmetries in white matter microstructure of the CST were evident and comparable to the degree of lateralisation observed in adolescence. Similarly, asymmetries in dexterity were evident, but to a lesser degree than in adolescents. Unlike in adolescents, we found no evidence of a linear relationship between asymmetries in CST microstructure and dexterity. Complementary Bayesian regression analysis provided moderate evidence in favour of the null hypothesis, pointing towards a lack of association between the structural and functional measures of right-left asymmetry. Our findings are compatible with the notion that, by late adulthood, a diverging impact of age on white matter structure and dexterous hand function dilutes the structure-function relationship between CST microstructure and manual proficiency that has been reported in adolescents.The reliability of scientific results critically depends on reproducible and transparent data processing. Cross-subject and cross-study comparability of imaging data in general, and magnetic resonance imaging (MRI) data in particular, is contingent on the quality of registration to a standard reference space. In small animal MRI this is not adequately provided by currently used processing workflows, which utilize high-level scripts optimized for human data, and adapt animal data to fit the scripts, rather than vice-versa. In this fully reproducible article we showcase a generic workflow optimized for the mouse brain, alongside a standard reference space suited to harmonize data between analysis and operation. We introduce four separate metrics for automated quality control (QC), and a visualization method to aid operator inspection. Benchmarking this workflow against common legacy practices reveals that it performs more consistently, better preserves variance across subjects while minimizing variance across sessions, and improves both volume and smoothness conservation RMSE approximately 2-fold. We propose this open source workflow and the QC metrics as a new standard for small animal MRI registration, ensuring workflow robustness, data comparability, and region assignment validity, all of which are indispensable prerequisites for the comparability of scientific results across experiments and centers.Spontaneous transient states were recently identified by functional magnetic resonance imaging and magnetoencephalography in healthy subjects. They organize and coordinate neural activity in brain networks. How spontaneous transient states are altered in abnormal brain conditions is unknown. Here, we conducted a transient state analysis on resting-state electroencephalography (EEG) source space and developed a state transfer analysis to patients with disorders of consciousness (DOC). They uncovered different neural coordination patterns, including spatial power patterns, temporal dynamics, spectral shifts, and connectivity construction varies at potentially very fast (millisecond) time scales, in groups with different consciousness levels healthy subjects, patients in minimally conscious state (MCS), and patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS). Machine learning based on transient state features reveal high classification accuracy between MCS and VS/UWS. This study developed methodology of transient states analysis on EEG source space and abnormal brain conditions. Findings correlate spontaneous transient states with human consciousness and suggest potential roles of transient states in brain disease assessment.Quantitative susceptibility mapping (QSM) and R2* mapping are MRI post-processing methods that quantify tissue magnetic susceptibility and transverse relaxation rate distributions. However, QSM and R2* acquisitions are relatively slow, even with parallel imaging. Incoherent undersampling and compressed sensing reconstruction techniques have been used to accelerate traditional magnitude-based MRI acquisitions; however, most do not recover the full phase signal, as required by QSM, due to its non-convex nature. In this study, a learning-based Deep Complex Residual Network (DCRNet) is proposed to recover both the magnitude and phase images from incoherently undersampled data, enabling high acceleration of QSM and R2* acquisition. Magnitude, phase, R2*, and QSM results from DCRNet were compared with two iterative and one deep learning methods on retrospectively undersampled acquisitions from six healthy volunteers, one intracranial hemorrhage and one multiple sclerosis patients, as well as one prospectively undersampled healthy subject using a 7T scanner. Peak signal to noise ratio (PSNR), structural similarity (SSIM), root-mean-squared error (RMSE), and region-of-interest susceptibility and R2* measurements are reported for numerical comparisons. The proposed DCRNet method substantially reduced artifacts and blurring compared to the other methods and resulted in the highest PSNR, SSIM, and RMSE on the magnitude, R2*, local field, and susceptibility maps. Compared to two iterative and one deep learning methods, the DCRNet method demonstrated a 3.2% to 9.1% accuracy improvement in deep grey matter susceptibility when accelerated by a factor of four. The DCRNet also dramatically shortened the reconstruction time of single 2D brain images from 36-140 seconds using conventional approaches to only 15-70 milliseconds.Motor imagery modulates specific neural oscillations like actual movement does. Representatively, suppression of the alpha power (e.g., event-related desynchronization [ERD]) is the typical pattern of motor imagery in the motor cortex. However, in addition to this amplitude-based feature, the coupling across frequencies includes important information about the brain functions and the existence of such complex information has been reported in various invasive studies. Yet, the interaction across multiple frequencies during motor imagery processing is still unclear and has not been widely studied, particularly concerning the non-invasive signals. In this study, we provide empirical evidence of the comodulation between the phase of alpha rhythm and the amplitude of high gamma rhythm during the motor imagery process. We used electroencephalography (EEG) in our investigation during the imagination of left- or right-hand movement recorded from 52 healthy subjects, and quantified the ERD of alpha and phase-amplitude In the evaluation, WCFC with only two electrodes yielded a performance comparable to the conventional algorithm with 64 electrodes in classifying left and right-hand motor imagery. These results indicate that the phase-amplitude frequency plays an important role in motor imagery, and that optimizing this frequency ranges is crucial for extracting information features to decode the motor imagery types.Prevention or modification of acquired epilepsy in patients at risk is an urgent, yet unmet, clinical need. Following acute brain insults, there is an increased risk of mesial temporal lobe epilepsy (mTLE), which is often associated with debilitating comorbidities and reduced life expectancy. The latent period between brain injury and the onset of epilepsy may offer a therapeutic window for interfering with epileptogenesis. The pilocarpine model of mTLE is widely used in the search for novel antiepileptogenic treatments. Recent biochemical studies indicated that cholinergic mechanisms play a role in the epileptogenic alterations induced by status epilepticus (SE) in this and other models of mTLE, which prompted us to evaluate whether treatment with the muscarinic antagonist scopolamine during the latent period after SE is capable of preventing or modifying epilepsy and associated behavioral and cognitive alterations in female Sprague-Dawley rats. First, in silico pharmacokinetic modeling was used to select a e thoroughly addresses the gender bias and video-EEG recording limitations of the present study.

Plasticity at corticostriatal synapses is a key substrate for a variety of brain functions - including motor control, learning and reward processing - and is often disrupted in disease conditions. learn more Despite intense research pointing toward a dynamic interplay between glutamate, dopamine (DA), and serotonin (5-HT) neurotransmission, their precise circuit and synaptic mechanisms regulating their role in striatal plasticity are still unclear. Here, we analyze the role of serotonergic raphe-striatal innervation in the regulation of DA-dependent corticostriatal plasticity.

Mice (males and females, 2-6months of age) were housed in standard plexiglass cages at constant temperature (22±1°C) and maintained on a 12/12h light/dark cycle with food and demineralized water ad libitum. In the present study, we used a knock-in mouse line in which the green fluorescent protein reporter gene (GFP) replaced the I Tph2 exon (Tph2

mice), allowing selective expression of GFP in the whole 5-HT system, highlighting both somata aerminant of disease-associated plasticity defects.

We showed a relevant role of the interaction between dopaminergic and serotonergic systems in controlling striatal synaptic plasticity. Overall, our data unveil that 5-HT plays a primary role in regulating DA-dependent corticostriatal plasticity in a sex-related manner and propose altered 5-HT levels as a critical determinant of disease-associated plasticity defects.

The prognostic value of cardiopulmonary exercise testing (CPET) in patients with wild-type transthyretin cardiac amyloidosis treated with tafamidis is unknown.

This retrospective study included patients with wtATTR who underwent baseline cardiopulmonary exercise testing and were treated with tafamidis from August 31, 2018, until March 31, 2020. Univariate logistic and multivariate cox-regression models were used to predict the occurrence of the primary outcome (composite of mortality, heart transplant, and palliative inotrope initiation). A total of 33 patients were included (median age 82 years, interquartile range [IQR] 79-84 years), 84% were Caucasians and 79% were males). Majority of patients had New York Heart Association functional class III disease at baseline (67%). The baseline median peak oxygen consumption (VO

) and peak circulatory power (CP) were 11.35 mL/kg/min (IQR 8.5-14.2 mL/kg/min) and 1485.8 mm Hg/mL/min (IQR 988-2184 mm Hg/mL/min), respectively, the median ventilatory efficiency was 35.