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Given the association of Epstein-Barr virus (EBV) with subjective perception of fatigue and demyelination in clinical conditions, the question about potential subclinical effects in the adult general population remains open. We investigate the association between individuals’ EBV immune response and perceived fatigue in a community dwelling cohort (n = 864, age 62 ± 10 years old; 49% women) while monitoring brain tissue properties. Fatigue levels are assessed with the established fatigue severity scale, the EBNA-1 and VCA p18 immunoglobulin G (IgG) chronic response – with multiplex serology and the estimates of local brain volume, myelin content, and axonal density - using relaxometry- and multi-shell diffusion-based magnetic resonance imaging (MRI). In our analysis we adjust for the effects of demographic and cardiovascular risk factors, sleep apnea, depression, and polygenic risk score for multiple sclerosis. We demonstrate that EBNA-1 IgG levels are positively associated with perceived levels of fatigue, whilst VCA p18 IgG levels show a positive correlation with myelin content and a negative one with an estimate of axonal g-ratio in male participants. In the context of EBVs immune response, the polygenic risk for multiple sclerosis is not associated with increased fatigue levels, brain myelination or atrophy. Our findings bring empirical evidence about the potential role of EBVs chronic immune response in perceived fatigue and hint towards a protective role of myelination specific for men. They underscore the added value of advanced assessment of brain tissue microstructure in uncovering the mechanisms behind frequent fatigue complaints associated with EBV infection and multiple sclerosis.

Abstract Around the world, people express a variety of values of nature based on how they relate and interact with it. These values of nature, broadly classified as instrumental, intrinsic, and relational values, underlie environmental policy and decision‐making processes. In this paper, our aim was to assess the values of nature that are expressed in national environmental policy documents. We assessed the National Biodiversity Strategies and Action Plans (NBSAPs), the key national policy framework for biodiversity conservation, from 11 countries, representing the five regional United Nations groups. We used qualitative content analysis to identify the value orientation of the statements in the NBSAPs and the main themes under each. Across the 11 NBSAPs, unspecified value orientation statements were the most common (40%), followed by instrumental (38%), intrinsic (14%) and relational (9%) value orientation statements. We identified the main themes in the instrumental value orientation statements as follows: (1) sustainability, (2) natural resources and (3) ecosystem services. The main themes present in the intrinsic value orientation statements were as follows: (1) recognizing intrinsic value, (2) endangered species and habitats, (3) conservation programmes and (4) threats to nature. Relational value orientation statements referenced as follows: (1) duty and responsibility to protect nature, (2) values expressed for nature, (3) national pride and heritage, (4) Indigenous peoples and local community's (IP&LCs) relationships with nature, (5) protecting nature for future generations and (6) equity in the use and access of nature. Our findings indicate that NBSAPs respond to the directive of the Convention on Biological Diversity. They are primarily based on the instrumental values of nature, only rarely considering other ways in which nature is valuable to people. This can reinforce unjust outcomes for human well‐being since environmental policies may not reflect the diverse ways in which nature and biodiversity matter to the population. In an increasingly interconnected world, environmental policies are called on to incorporate multiple values to achieve positive outcomes for both human well‐being and biodiversity conservation. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Our knowledge of the mechanisms underlying the vulnerability of the brain’s white matter microstructure to cardiovascular risk factors (CVRFs) is still limited. We used a quantitative magnetic resonance imaging (MRI) protocol in a single centre setting to investigate the cross-sectional association between CVRFs and brain tissue properties of white matter tracts in a large community-dwelling cohort (n = 1104, age range 46–87 years). Arterial hypertension was associated with lower myelin and axonal density MRI indices, paralleled by higher extracellular water content. Obesity showed similar associations, though with myelin difference only in male participants. Associations between CVRFs and white matter microstructure were observed predominantly in limbic and prefrontal tracts. Additional genetic, lifestyle and psychiatric factors did not modulate these results, but moderate-to-vigorous physical activity was linked to higher myelin content independently of CVRFs. Our findings complement previously described CVRF-related changes in brain water diffusion properties pointing towards myelin loss and neuroinflammation rather than neurodegeneration.

Abstract Given controversial findings of reduced depressive symptom severity and increased hippocampus volume in CYP2C19 poor metabolizers, we sought to provide empirical evidence from a large-scale single-center longitudinal cohort in the community-dwelling adult population—Colaus|PsyCoLaus in Lausanne, Switzerland (n = 4152). We looked for CYP2C19 genotype-related behavioral and brain anatomy patterns using a comprehensive set of psychometry, water diffusion- and relaxometry-based magnetic resonance imaging (MRI) data (BrainLaus, n = 1187). Our statistical models tested for differential associations between poor metabolizer and other metabolizer status with imaging-derived indices of brain volume and tissue properties that explain individuals’ current and lifetime mood characteristics. The observed association between CYP2C19 genotype and lifetime affective status showing higher functioning scores in poor metabolizers, was mainly driven by female participants (ß = 3.9, p = 0.010). There was no difference in total hippocampus volume between poor metabolizer and other metabolizer, though there was higher subiculum volume in the right hippocampus of poor metabolizers (ß = 0.03, p FDRcorrected = 0.036). Our study supports the notion of association between mood phenotype and CYP2C19 genotype, however, finds no evidence for concomitant hippocampus volume differences, with the exception of the right subiculum.

Understanding economic scenarios is crucial in all production chains. Tropical pastures are Brazil’s primary food source for beef cattle production, and current pasture management is not ideal due to land degradation. An economic evaluation assists farmers with improving pasture management using novel techniques, such as nitrogen (N) fertilization, which is straightforward and practical. The economic effects of different N fertilizer levels in beef cattle production were evaluated. This study was conducted over three years (2014/2015, 2015/2016, and 2016/2017) using four concentrations of urea fertilizer (0, 90, 180, and 270 kg N/ha). A principal component analysis and sensitivity analysis were performed using financial data. A financial pattern was observed, with increases in some variables, such as cost-effective operating and cost-total operating from those measuring costs and gross revenue, operating profit, and net income from those estimating revenues. Treatment with 180 kg N/ha fertilizer resulted in increased profitability, payback, internal rate of return, and net present value (at 6% and 12% tax) of 17.76%, 2.79 years, 35.79%, and USD 5926.03 and USD 1854.35, respectively. For this study, the main costs associated with profitability were supplementation, animal purchases, and sale prices. The best treatment to achieve excellent grazing pressure in tropical areas with oxisol is 180 kg/ha per year.

There is an ongoing debate about differential clinical outcome and associated adverse effects of deep brain stimulation (DBS) in Parkinson’s disease (PD) targeting the subthalamic nucleus (STN) or the globus pallidus pars interna (GPi). Given that functional connectivity profiles suggest beneficial DBS effects within a common network, the empirical evidence about the underlying anatomical circuitry is still scarce. Therefore, we investigate the STN and GPi-associated structural covariance brain patterns in PD patients and healthy controls.We estimate GPi’s and STN’s whole-brain structural covariance from magnetic resonance imaging (MRI) in a normative mid- to old-age community-dwelling cohort (n = 1184) across maps of grey matter volume, magnetization transfer (MT) saturation, longitudinal relaxation rate (R1), effective transversal relaxation rate (R2*) and effective proton density (PD*). We compare these with the structural covariance estimates in patients with idiopathic PD (n = 32) followed by validation using a reduced size controls’ cohort (n = 32).In the normative data set, we observed overlapping spatially distributed cortical and subcortical covariance patterns across maps confined to basal ganglia, thalamus, motor, and premotor cortical areas. Only the subcortical and midline motor cortical areas were confirmed in the reduced size cohort. These findings contrasted with the absence of structural covariance with cortical areas in the PD cohort.We interpret with caution the differential covariance maps of overlapping STN and GPi networks in patients with PD and healthy controls as correlates of motor network disruption. Our study provides face validity to the proposed extension of the currently existing structural covariance methods based on morphometry features to multiparameter MRI sensitive to brain tissue microstructure.

Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1, and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the method's sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MTsat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

Survival in biological environments requires learning associations between predictive sensory cues and threatening outcomes. Such aversive learning may be implemented through reinforcement learning algorithms that are driven by the signed difference between expected and encountered outcomes, termed prediction errors (PEs). While PE-based learning is well established for reward learning, the role of putative PE signals in aversive learning is less clear. Here, we used functional magnetic resonance imaging in humans (21 healthy men and women) to investigate the neural representation of PEs during maintenance of learned aversive associations. Four visual cues, each with a different probability (0, 33, 66, 100%) of being followed by an aversive outcome (electric shock), were repeatedly presented to participants. We found that neural activity at omission (US-) but not occurrence of the aversive outcome (US+) encoded PEs in the medial prefrontal cortex. More expected omission of aversive outcome was associated with lower neural activity. No neural signals fulfilled axiomatic criteria, which specify necessary and sufficient components of PE signals, for signed PE representation in a whole-brain search or in a-priori regions of interest. Our results might suggest that, different from reward learning, aversive learning does not involve signed PE signals that are represented within the same brain region for all conditions.

Abstract The effects of nitrogen (N) fertilization levels on protein and carbohydrate fractions in Marandu palisadegrass pasture [Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster] were investigated in a pasture over five years. The experimental design was completely randomized with four levels of N (0, 90, 180, and 270 kg N ha-1, as urea) for five years, and with three replicates. The study was conducted in a continuously stocked pasture during the forage growing season (December to April) in a tropical region. The effects of N fertilization were similar across the five years. With increasing N fertilization, the concentrations of crude protein (CP) increased from 103 to 173 g kg−1 (P

Introduction The association between CYP2C19 poor metabolizer status, depressive symptom severity and hippocampal volume in humans is controversial. Progress in understanding not only the pathophysiology of depression but also potential protective mechanisms is important both for daily clinical practice and for the development of new antidepressant therapies. Objectives To test and validate previous findings regarding the impact of CYP2C19 status on depressive symptoms and to examine whether it could influence hippocampus subregions and brain tissue microstructure. Methods A total of 4152 individuals from the Longitudinal cohort in the community-dwelling adult population - Colaus|PsyCoLaus in Lausanne, Switzerland were included. They have participated in at least one psychiatric evaluation. Brain anatomy patterns using a comprehensive set of psychometry, water diffusion- and relaxometry-based magnetic resonance imaging data were analysed in a subset of the cohort (BrainLaus, n=1187). Results In this population-based cohort study, better lifetime global assessment of functioning scores were observed in poor metabolizers when compared to other metabolizers, this result was mainly driven by female participants (ß=3.9, P=0.01). Examination of brain imaging data revealed that higher right hippocampal subiculum volume was related to poor metabolizer status (ß=0.03, P=0.006). In addition, associations were observed between metabolizer status and white matter microstructure in the left uncinate fasciculus (ß=-0.01, P=0.01) and the left cingulum bundle (ß=-0.01, P=0.01). Conclusions CYP2C19 status is associated with modifications in lifetime global functioning, and brain anatomy. Such differences in brain structures can contribute to explain the protective effect of CYP2C19 poor metabolizer status. Disclosure No significant relationships.

PurposeWe present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity.TheoryThe proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and β.MethodsMRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract.ResultsThe estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ – the width of the right tail of the axonal radius distribution – and β – the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 μm and the parameter β was 0.67 ± 0.02 μm−α.ConclusionThe estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.

To date, we have scarce information about the relative myelination level of different fiber bundles in the human brain. Indirect evidence comes from postmortem histology data but histological stainings are unable to follow a specific bundle and determine its intrinsic myelination. In this context, quantitative MRI, and diffusion MRI tractography may offer a viable solution by providing, respectively, voxel-wise myelin sensitive maps and the pathways of the major tracts of the brain. Then, “tractometry” can be used to combine these two pieces of information by averaging tissue features (obtained from any voxel-wise map) along the streamlines recovered with diffusion tractography. Although this method has been widely used in the literature, in cases of voxels containing multiple fiber populations (each with different levels of myelination), tractometry provides biased results because the same value will be attributed to any bundle passing through the voxel. To overcome this bias, we propose a new method - named “myelin streamline decomposition” (MySD) - which extends convex optimization modeling for microstructure informed tractography (COMMIT) allowing the actual value measured by a microstructural map to be deconvolved on each individual streamline, thereby recovering unique bundle-specific myelin fractions (BMFs). We demonstrate the advantage of our method with respect to tractometry in well-studied bundles and compare the cortical projection of the obtained bundle-wise myelin values of both methods. We also prove the stability of our approach across different subjects and different MRI sensitive myelin mapping approaches. This work provides a proof-of-concept of in vivo investigations of entire neuronal pathways that, to date, are not possible.

Learning how to reach a reward over long series of actions is a remarkable capability of humans, and potentially guided by multiple parallel learning modules. Current brain imaging of learning modules is limited by (i) simple experimental paradigms, (ii) entanglement of brain signals of different learning modules, and (iii) a limited number of computational models considered as candidates for explaining behavior. Here, we address these three limitations and (i) introduce a complex sequential decision making task with surprising events that allows us to (ii) dissociate correlates of reward prediction errors from those of surprise in functional magnetic resonance imaging (fMRI); and (iii) we test behavior against a large repertoire of model-free, model-based, and hybrid reinforcement learning algorithms, including a novel surprise-modulated actor-critic algorithm. Surprise, derived from an approximate Bayesian approach for learning the world-model, is extracted in our algorithm from a state prediction error. Surprise is then used to modulate the learning rate of a model-free actor, which itself learns via the reward prediction error from model-free value estimation by the critic. We find that action choices are well explained by pure model-free policy gradient, but reaction times and neural data are not. We identify signatures of both model-free and surprise-based learning signals in blood oxygen level dependent (BOLD) responses, supporting the existence of multiple parallel learning modules in the brain. Our results extend previous fMRI findings to a multi-step setting and emphasize the role of policy gradient and surprise signalling in human learning.

Introduction: Multiple Sclerosis (MS) is a common neurological disease primarily characterized by myelin damage in lesions and in normal - appearing white and gray matter (NAWM, NAGM).Several quantitative MRI (qMRI) methods are sensitive to myelin characteristics by measuring specific tissue biophysical properties. However, there are currently few studies assessing the relative reproducibility and sensitivity of qMRI measures to MS pathology in vivo in patients. Methods: We performed two studies. The first study assessed of the sensitivity of qMRI measures to MS pathology: in this work, we recruited 150 MS and 100 healthy subjects, who underwent brain MRI at 3 T including quantitative T1 mapping (qT1), quantitative susceptibility mapping (QSM), magnetization transfer saturation imaging (MTsat) and myelin water imaging for myelin water fraction (MWF). The sensitivity of qMRIs to MS focal pathology (MS lesions vs peri-plaque white/gray matter (PPWM/PPGM)) was studied lesion-wise; the sensitivity to diffuse normal appearing (NA) pathology was measured using voxel-wise threshold-free cluster enhancement (TFCE) in NAWM and vertex-wise inflated cortex analysis in NAGM. Furthermore, the sensitivity of qMRI to the identification of lesion tissue was investigated using a voxel-wise logistic regression analysis to distinguish MS lesion and PP voxels.The second study assessed the reproducibility of myelin-sensitive qMRI measures in a single scanner. To evaluate the intra-session and inter-session reproducibility of qMRI measures, we have investigated 10 healthy subjects, who underwent two brain 3 T MRIs within the same day (without repositioning), and one after 1-week interval. Five region of interest (ROIs) in white and deep grey matter areas were segmented, and inter- and intra- session reproducibility was studied using the intra-class correlation coefficient (ICC). Further, we also investigated the voxel-wise reproducibility of qMRI measures in NAWM and NAGM. Results: qT1 and QSM showed the highest sensitivity to distinguish MS focal WM and cortical pathology from peri-plaque WM (P

Aim of study: To assess the effects of replacing virginiamycin (VM) by functional oils (FO) from castor beans and cashew nut on beef cattle system during the early dry season (Experiment I) and during the finishing phase were evaluated the historical effect, keeping the treatments and methods intact (Experiment II). Area of study: These experiments were conducted at the Forage Crops and Grasslands section of São Paulo State University, “Julio de Mesquita Filho” (Unesp–Jaboticabal, São Paulo, Brazil). Material and methods: Two supplementation levels combined with two additives (four treatments in total) were evaluated: LSVM, low supplementation (0.3% body weight [BW]) with VM; LSFO, low supplementation (0.3% BW) with FO, HSVM, high supplementation (0.6% BW) with VM, and HSFO, high supplementation (0.6% BW) with FO. In both experiments, the experimental design was completely randomized with a 2 × 2 factorial arrangement (supplementation levels × additives). Main results: In Exp. I, the additive effect of VM provided greater average daily gain (ADG, p=0.02), higher supplementation level resulted in higher ADG (p=0.04) and the greatest crude protein apparent digestibility (p=0.002). However, no effects were observed between supplementation levels, additives, and interactions (p≥0.11) on voluntary intake and ruminal parameters. In Exp. II, LSVM treatment resulted in lower dry matter intake (p=0.04). Animals maintained on LSFO during the early dry season exhibited lower carcass yield (p=0.004). Research highlights: FO can be used to replace VM in beef cattle diet during the finishing phase in the feedlot without altering animal performance.

Background: After more than eight decades of electroconvulsive therapy (ECT) for pharmaco-resistant depression, the mechanisms governing its anti-depressant effects remain poorly understood. Computational anatomy studies using longitudinal T1-weighted magnetic resonance imaging (MRI) data have demonstrated ECT effects on hippocampus volume and cortical thickness, but they lack the interpretational specificity about underlying neurobiological processes. Methods: We sought to fill in the gap of knowledge by acquiring quantitative MRI indicative for brain's myelin, iron and tissue water content at multiple time-points before, during and after ECT treatment. We adapted established tools for longitudinal spatial registration of MRI data to the relaxometry-based multi-parameter maps aiming to preserve the initial total signal amount and introduced a dedicated multivariate analytical framework. Results: The whole-brain voxel-based analysis based on a multivariate general linear model showed that there is no brain tissue oedema contributing to the predicted ECT-induced hippocampus volume increase neither in the short, nor in the long-term observations. Improvements in depression symptom severity over time were associated with changes in both volume estimates and brain tissue properties expanding beyond mesial temporal lobe structures to anterior cingulate cortex, precuneus and striatum. Conclusion: The obtained results stemming from multi-contrast MRI quantitative data provided a fingerprint of ECT-induced brain tissue changes over time that are contrasted against the background of established morphometry findings. The introduced data processing and statistical testing algorithms provided a reliable analytical framework for longitudinal multi-parameter brain maps. The results, particularly the evidence of lack of ECT impact on brain tissue water, should be considered preliminary considering the small sample size of the study.

There is much controversy about the potential impact of spinal cord injury (SCI) on brain anatomy and function, which is mirrored in the substantial divergence of findings between animal models and human imaging studies. Given recent advances in quantitative magnetic resonance imaging (MRI) we sought to tackle the unresolved question about the link between the presumed injury associated volume differences and underlying brain tissue property changes in a cohort of chronic complete SCI patients. Using the established computational anatomy methods of voxel-based morphometry (VBM) and voxel-based quantification (VBQ), we performed statistical analyses on grey and white matter volumes as well as on parameter maps indicative for myelin, iron, and free tissue water content in the brain of complete SCI patients (n = 14) and healthy individuals (n = 14). Our regionally unbiased white matter analysis showed a significant volume reduction of the dorsal aspect at the junction between the most rostral part of the spinal cord and the medulla oblongata consistent with Wallerian degeneration of proprioceptive axons in the dorsal column tracts in SCI subjects. This observation strongly correlated with spinal cord atrophy assessed by quantification of the spinal cord cross-sectional area at the cervical level C2/3. These findings suggest that Wallerian degeneration of the dorsal column tracts represents a main contributor to the observed spinal cord atrophy, which is highly consistent with preclinical histological evidence of remote changes in the central nervous system secondary to SCI. Structural changes in other brain regions representing remote changes in the course of chronic SCI could neither be confirmed by conventional VBM nor by VBQ analysis. Whether and how MRI based brain morphometry and brain tissue property analysis will inform clinical decision making and clinical trial outcomes in spinal cord medicine remains to be determined.

Tradução de artigo de Norbert Waszek