15 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

    Association between tDCS induced GABA change and estimated electric field in the cortex

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    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 inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the actual electric field in the cortex. Our aim was to examine whether the variability in electric fields, estimated using computational simulations, explains the variability in tDCS induced GABA changes measured using magnetic resonance spectroscopy (MRS). Data from five studies (total N = 56 complete cases) were combined. The anode and cathode were placed over the left M1 (3 studies, N = 24) or right temporal cortex (2 studies, N = 32), and contralateral supraorbital ridge respectively. GABA to total Creatine ratios were measured and estimated, before and after tDCS application. sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. The electric fields were simulated in a finite element model of the head, based on individual MPRAGE images, using SimNIBS. Twelve linear mixed effects models were run, one for each E-field variable (mean and 95th percentile of magnitude, normal and tangential components), and separately for the M1 and temporal data. We found that in M1, E-field in the MRS voxel is related to the GABA drop, adding to the accumulating evidence that supports individualised dosing of tDCS. We also found an interaction with grey matter volume within the MRS voxel, emphasising the need to appropriately choose and evaluate any outcome measures which we expect to be related to E-field. While we did not find a similar association in the temporal region, given the challenges of modelling the E-field in this region and possible homeostatic metaplastic effects, such an association cannot be ruled out

    Sarcomere function activates a p53-dependent DNA damage response that promotes polyploidization and limits in vivo cell engraftment.

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    Human cardiac regeneration is limited by low cardiomyocyte replicative rates and progressive polyploidization by unclear mechanisms. To study this process, we engineer a human cardiomyocyte model to track replication and polyploidization using fluorescently tagged cyclin B1 and cardiac troponin T. Using time-lapse imaging, in vitro cardiomyocyte replication patterns recapitulate the progressive mononuclear polyploidization and replicative arrest observed in vivo. Single-cell transcriptomics and chromatin state analyses reveal that polyploidization is preceded by sarcomere assembly, enhanced oxidative metabolism, a DNA damage response, and p53 activation. CRISPR knockout screening reveals p53 as a driver of cell-cycle arrest and polyploidization. Inhibiting sarcomere function, or scavenging ROS, inhibits cell-cycle arrest and polyploidization. Finally, we show that cardiomyocyte engraftment in infarcted rat hearts is enhanced 4-fold by the increased proliferation of troponin-knockout cardiomyocytes. Thus, the sarcomere inhibits cell division through a DNA damage response that can be targeted to improve cardiomyocyte replacement strategies

    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

    A randomised comparison of CPX-351 and FLAG-Ida in adverse karyotype AML and high-risk MDS: the UK NCRI AML19 trial

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    Liposomal daunorubicin and cytarabine (CPX-351) improves overall survival (OS) compared to 7+3 chemotherapy in older patients with secondary acute myeloid leukaemia (AML); to date there have been no randomized studies in younger patients. The high-risk cohort of the UK NCRI AML19 trial (ISRCTN78449203) compared CPX-351 with FLAG-Ida in younger adults with newly-diagnosed adverse cytogenetic AML or high-risk myelodysplastic syndromes (MDS). 189 patients were randomized (median age 56y). By clinical criteria 49% had de novo AML, 20% secondary AML and 30% high risk MDS. MDS-related cytogenetics were present in 73% of patients, with complex karyotype in 49%. TP53 was the most commonly mutated gene, in 43%. Myelodysplasia-related gene mutations were present in 75 patients (44%). The overall response rate (CR + CRi) after course two was 64% and 76% for CPX-351 and FLAG-Ida (OR:0.54, 95%CI 0.28-1.04, p=0.06). There was no difference in OS (13.3 months vs 11.4 months, HR:0.78, 95%CI 0.55-1.12, p=0.17) or event-free survival (HR:0.90, 95%CI 0.64-1.27, p=0.55) in multivariable analyses. However, relapse-free survival was significantly longer with CPX-351 (median 22.1 vs 8.35 months, HR:0.58, 95% CI 0.36-0.95, p=0.03). There was no difference between the treatment arms in patients with clinically defined secondary AML (HR:1.1, 95%CI 0.52-2.30) or those with MDS-related cytogenetic abnormalities (HR:0.94, 95%CI 0.63-1.40), however an exploratory sub-group of patients with MDS-related gene mutations had significantly longer OS with CPX-351 (median 38.4 vs 16.3 months, HR:0.42, 95%CI 0.21-0.84, heterogeneity p=0.05). In conclusion, OS in younger patients with adverse risk AML/MDS was not significantly different between CPX-351 and FLAG-Ida

    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

    The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

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    INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

    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)
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