12 research outputs found

    tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel

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    Background and objective Transcranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. Methods Data from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change. Results In M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = −3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis. Conclusions Our data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects

    tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel

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    Background and objectiveTranscranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. MethdsData from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change. ResultsIn M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = -3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis. ConclusionsOur data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects

    Fludarabine, cytarabine, granulocyte colony-stimulating factor, and idarubicin with gemtuzumab ozogamicin improves event-free survival in younger patients with newly diagnosed aml and overall survival in patients with npm1 and flt3 mutations

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    Purpose To determine the optimal induction chemotherapy regimen for younger adults with newly diagnosed AML without known adverse risk cytogenetics. Patients and Methods One thousand thirty-three patients were randomly assigned to intensified (fludarabine, cytarabine, granulocyte colony-stimulating factor, and idarubicin [FLAG-Ida]) or standard (daunorubicin and Ara-C [DA]) induction chemotherapy, with one or two doses of gemtuzumab ozogamicin (GO). The primary end point was overall survival (OS). Results There was no difference in remission rate after two courses between FLAG-Ida + GO and DA + GO (complete remission [CR] + CR with incomplete hematologic recovery 93% v 91%) or in day 60 mortality (4.3% v 4.6%). There was no difference in OS (66% v 63%; P = .41); however, the risk of relapse was lower with FLAG-Ida + GO (24% v 41%; P < .001) and 3-year event-free survival was higher (57% v 45%; P < .001). In patients with an NPM1 mutation (30%), 3-year OS was significantly higher with FLAG-Ida + GO (82% v 64%; P = .005). NPM1 measurable residual disease (MRD) clearance was also greater, with 88% versus 77% becoming MRD-negative in peripheral blood after cycle 2 (P = .02). Three-year OS was also higher in patients with a FLT3 mutation (64% v 54%; P = .047). Fewer transplants were performed in patients receiving FLAG-Ida + GO (238 v 278; P = .02). There was no difference in outcome according to the number of GO doses, although NPM1 MRD clearance was higher with two doses in the DA arm. Patients with core binding factor AML treated with DA and one dose of GO had a 3-year OS of 96% with no survival benefit from FLAG-Ida + GO. Conclusion Overall, FLAG-Ida + GO significantly reduced relapse without improving OS. However, exploratory analyses show that patients with NPM1 and FLT3 mutations had substantial improvements in OS. By contrast, in patients with core binding factor AML, outcomes were excellent with DA + GO with no FLAG-Ida benefit

    Learning to optimize perceptual decisions through suppressive interactions in the human brain.

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    Translating noisy sensory signals to perceptual decisions is critical for successful interactions in complex environments. Learning is known to improve perceptual judgments by filtering external noise and task-irrelevant information. Yet, little is known about the brain mechanisms that mediate learning-dependent suppression. Here, we employ ultra-high field magnetic resonance spectroscopy of GABA to test whether suppressive processing in decision-related and visual areas facilitates perceptual judgments during training. We demonstrate that parietal GABA relates to suppression of task-irrelevant information, while learning-dependent changes in visual GABA relate to enhanced performance in target detection and feature discrimination tasks. Combining GABA measurements with functional brain connectivity demonstrates that training on a target detection task involves local connectivity and disinhibition of visual cortex, while training on a feature discrimination task involves inter-cortical interactions that relate to suppressive visual processing. Our findings provide evidence that learning optimizes perceptual decisions through suppressive interactions in decision-related networks.This work was supported by 717 funding to ZK from the Alan Turing Institute, the Biotechnology and Biological Sciences 718 Research Council (Grants: H012508, P021255), the European Community’s Seventh 719 Framework Programme (Grant FP7/ 2007–2013 under agreement PITN-GA 2011-290011), 720 and the Wellcome Trust (Grant 205067). CJS holds a Sir Henry Dale Fellowship, funded by 721 the Wellcome Trust and the Royal Society (102584/Z/13/Z). ELH is supported by the NIHR 722 Oxford Health Biomedical Research Centre. The Wellcome Centre for Integrative 723 Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z)

    Magnetic resonance spectroscopic imaging markers of inhibitory and excitatory motor cortical function in healthy individuals and those with amyotrophic lateral sclerosis

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    A balance of excitatory and inhibitory signalling within key cortical regions in the motor network regulates overall network activity and connectivity in humans. This balance can be non-invasively assessed by quantifying glutamate and GABA across cortical regions using magnetic resonance spectroscopic imaging (MRSI). We present planned analyses of a large dataset comprising healthy adults across a range of ages, and patients with amyotrophic lateral sclerosis (ALS) - a neurodegenerative disorder of the motor system in which altered cortical excitability is consistently observed. Using a novel MRSI protocol, GABA and glutamate are mapped in high spatial resolution across a region of interest encompassing both primary motor cortices. We will use the free software FSL-MRS toolkit to pre-process the MRSI data, fit spectra and quantify metabolite concentration. This dataset will allow the spatial distribution of neurochemical concentrations to be characterised in healthy individuals and disease, and the effect of age to be addressed. Furthermore, by combining MRS and functional MRI data, the role of neurochemicals in determining motor network function can be investigated and biomarkers of future therapeutic response to be developed. Identifying physiological processes underlying motor function and plasticity may yield targets for modulation to improve function or treat disease

    Myocardial Gene Expression Profiling to Predict and Identify Cardiac Allograft Acute Cellular Rejection: The GET-Study

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    Serial invasive endomyocardial biopsies (EMB) remain the gold standard for acute cellular rejection (ACR) diagnosis. However histological grading has several limitations. We aimed to explore the value of myocardial Gene Expression Profiling (GEP) for diagnosing and identifying predictive biomarkers of ACR.A case-control study nested within a retrospective heart transplant patients cohort included 126 patients with median (IQR) age 50 (41-57) years and 111 (88%) males. Among 1157 EMB performed, 467 were eligible (i.e, corresponding to either ISHLT grade 0 or ≄3A), among which 36 were selected for GEP according to the grading: 0 (CISHLT, n = 13); rejection ≄3A (RISHLT, n = 13); 0 one month before ACR (BRISHLT, n = 10).We found 294 genes differentially expressed between CISHLT and RISHLT, mainly involved in immune activation, and inflammation. Hierarchical clustering showed a clear segregation of CISHLT and RISHLT groups and heterogeneity of GEP within RISHLT. All EMB presented immune activation, but some RISHLT EMB were strongly subject to inflammation, whereas others, closer to CISHLT, were characterized by structural modifications with lower inflammation level. We identified 15 probes significantly different between BRISHLT and CISHLT, including the gene of the muscular protein TTN. This result suggests that structural alterations precede inflammation in ACR. Linear Discriminant Analysis based on these 15 probes was able to identify the histological status of every 36 samples.Myocardial GEP is a helpful method to accurately diagnose ACR, and predicts rejection one month before its histological occurrence. These results should be considered in cardiac allograft recipients' care
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