Biology subjects

Rua, C.

Publications and source records attributed to Rua, C..

9 recordsLinked to original sources

bioRxiv2026

Italia: A PARP-Directed Auger Electron-Emitting Agent for Targeted Radionuclide Therapy of Cancer

Poly(ADP-ribose) polymerase 1 (PARP1) is a central mediator of DNA damage repair and an established therapeutic target in homologous recombination-deficient cancers. Radiolabelled PARP inhibitors provide a strategy to deliver cytotoxic radiation directly to tumour DNA by exploiting PARP overexpression and trapping at sites of DNA damage. Here, we describe the design, radiosynthesis, and in vitro evaluation of [123I]Italia, a talazoparib-derived Auger electron-emitting agent for PARP-targeted radionuclide therapy. Stereochemically pure [123I]Italia, (8S,9R)-5-fluoro-8-(4-(iodo-123I)phenyl)-9-(1-methyl-1H-1,2,4-triazol-5-yl)-2,7,8,9-tetrahydro-3H-pyrido[4,3,2-de]phthalazin-3-one was synthesised in one step via copper-mediated iodo-deboronation, achieving activity yields >80% and molar activities >6.2 {+/-} 3.1 GBq/{micro}mol (n=8). UPLC analysis confirmed radiochemical purity >97%. Italia exhibited potent PARP1 inhibition (IC50 0.48 nM) and in silico predicted binding affinity comparable to talazoparib. In a panel of PARP-expressing cancer cell lines, [123I]Italia demonstrated highest uptake at 60 min, PARP-selective uptake, predominant nuclear localisation (up to 60% of added activity) and chromatin association consistent with PARP trapping (up to 15% of total activity recorded). Uptake was reduced more than 50-fold by addition of an excess of any PARP inhibitor (e.g. olaparib, talazoparib, and rucaparib) and in PARP1 knockout cells, confirming target specificity. Clonogenic assays showed a marked, added activity-dependent reduction in survival of PARP-expressing cells following a brief one-hour exposure, whereas PARP1-deficient cells were resistant. Collectively, these findings identify [123I]Italia as a promising PARP-targeted Auger electron-emitting theranostic candidate that warrants further in vivo evaluation.

cancer biology↗

bioRxiv2025

Detecting neuroplastic effects induced by ketamine in healthy human subjects: a multimodal approach

We investigated ketamines neuroplastic effects in healthy human subjects using integrated Positron Emission Tomography (PET)/Magnetic Resonance Imaging (MRI) measures before and 1-8 days after a single psychedelic dose of ketamine (1 mg/kg, intravenous). Eleven participants underwent two PET/MRI scans with [11C]-UCBJ (synaptic density/plasticity), 1H-MRS (Glutamate and GABA), and resting-state fMRI (intrinsic brain activity, functional connectivity, graph-theoretic metrics), before and after ketamine. While group-level analyses showed only trend-level increases in PET synaptic markers, we observed significantly elevated Anterior Cingulate Cortex (ACC) glutamate levels post-ketamine. Functional connectivity analyses revealed decreased within-network integrity, particularly in high-order networks like the default mode network (DMN), alongside increased low-to-high-order network integration. Our multimodal analysis showed that increased [11C]-UCBJ volume distribution (VT), a putative index of synaptic plasticity, correlated with reduced intrinsic activity in DMN regions and decreased influence of the posterior cingulate cortex (PCC) in global network dynamics. By linking molecular and network-level changes, our results point to the PCC as a central hub where ketamine may reshape brain hierarchies in the long term, providing new directions for understanding its therapeutic mechanisms and developing targeted treatments.

neuroscience↗

bioRxiv2025

Neurochemical markers of uncertainty processing in humans

How individuals process and respond to uncertainty has important implications for cognition and mental health. Here we use computational phenotyping to examine individualised "uncertainty fingerprints" in relation to neurometabolites and trait anxiety in humans. We introduce a novel categorical state-transition extension of the Hierarchical Gaussian Filter (HGF) to capture implicit learning in a four-choice probabilistic sensorimotor reversal learning task by tracking beliefs about stimulus transitions. Using 7-Tesla Magnetic Resonance Spectroscopy, we measured baseline neurotransmitter levels in the primary motor cortex (M1). Model-based results revealed dynamic belief updating in response to environmental changes. We further found region-specific relationships between M1 glutamate+ glutamine levels and prediction errors and volatility beliefs, revealing an important neural marker of probabilistic reversal learning in humans. High trait anxiety was associated with faster post-reversal responses. By integrating computational modelling with neurochemical assessments, this study provides novel insights into the neurocomputations that drive individual differences in processing uncertainty.

neuroscience↗

bioRxiv2023

Path integration selectively predicts midlife risk of Alzheimer's disease

The entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimers disease (AD), associated with EC grid cell dysfunction. Given the role of grid cells in path integration, we predicted that path integration impairment would represent the first behavioural change in adults at-risk of AD. Using immersive virtual reality, we found that midlife path integration impairments predicted both hereditary and physiological AD risk, with no corresponding impairment on tests of episodic memory or other spatial behaviours. Impairments related to poorer angular estimation and were associated with hexadirectional grid-like fMRI signal in the posterior-medial EC. These results indicate that altered path integration may represent the transition point from at-risk state to disease onset in AD, prior to impairment in other cognitive domains.

neuroscience↗

bioRxiv2020

Correcting for Superficial Bias in 7T Gradient Echo fMRI

1The arrival of submillimetre ultra high-field fMRI makes it possible to compare activation profiles across cortical layers. However, the Blood Oxygenation Level Dependent (BOLD) signal measured by Gradient-Echo fMRI is biased towards superficial layers of the cortex, which is a serious confound for laminar analysis. Several univariate and multivariate analysis methods have been proposed to correct this bias. We compare these methods using computational simulations and example human 7T fMRI data from Regions-of-Interest (ROIs) during a visual attention paradigm. The simulations show that two methods - the ratio of ROI means across conditions and a novel application of Deming regression - offer the most robust correction for superficial bias. Deming regression has the additional advantage that it does not require that the conditions differ in their mean activation over voxels within an ROI. When applied to the example dataset, these methods suggest that attentional modulation of activation is similar across cortical layers within the ventral visual stream, despite a naive activation-based analysis producing stronger modulation in superficial layers. Our study demonstrates that accurate correction of superficial bias is crucial to avoid drawing erroneous conclusions from laminar analyses of Gradient-Echo fMRI data.

neuroscience↗

bioRxiv2020

Multi-centre, multi-vendor reproducibility of 7T QSM and R2* in the human brain: results from the UK7T study

We present the reliability of ultra-high field T2* MRI at 7T, as part of the UK7T Networks "Travelling Heads" study. T2*-weighted MRI images can be processed to produce quantitative susceptibility maps (QSM) and R2* maps. These reflect iron and myelin concentrations, which are altered in many pathophysiological processes. The relaxation parameters of human brain tissue are such that R2* mapping and QSM show particularly strong gains in contrast-to-noise ratio at ultra-high field (7T) vs clinical field strengths (1.5 - 3T). We aimed to determine the inter-subject and inter-site reproducibility of QSM and R2* mapping at 7T, in readiness for future multi-site clinical studies. MethodsTen healthy volunteers were scanned with harmonised single- and multi-echo T2*-weighted gradient echo pulse sequences. Participants were scanned five times at each "home" site and once at each of four other sites. The five sites had 1x Philips, 2x Siemens Magnetom, and 2x Siemens Terra scanners. QSM and R2* maps were computed with the Multi-Scale Dipole Inversion (MSDI) algorithm (https://github.com/fil-physics/Publication-Code). Results were assessed in relevant subcortical and cortical regions of interest (ROIs) defined manually or by the MNI152 standard space. Results and DiscussionMean susceptibility ({chi}) and R2* values agreed broadly with literature values in all ROIs. The inter-site within-subject standard deviation was 0.001 - 0.005 ppm ({chi}) and 0.0005 - 0.001 ms-1 (R2*). For {chi} this is 2.1-4.8 fold better than 3T reports, and 1.1-3.4 fold better for R2*. The median ICC from within- and cross-site R2* data was 0.98 and 0.91, respectively. Multi-echo QSM had greater variability vs single-echo QSM especially in areas with large B0 inhomogeneity such as the inferior frontal cortex. Across sites, R2* values were more consistent than QSM in subcortical structures due to differences in B0-shimming. On a between-subject level, our measured {chi} and R2* cross-site variance is comparable to within-site variance in the literature, suggesting that it is reasonable to pool data across sites using our harmonised protocol. ConclusionThe harmonized UK7T protocol and pipeline delivers on average a 3-fold improvement in the coefficient of reproducibility for QSM and R2* at 7T compared to previous reports of multi-site reproducibility at 3T. These protocols are ready for use in multi-site clinical studies at 7T.

neuroscience↗

bioRxiv2020

Recurrent plasticity mechanisms for perceptual decisions in the human brain

Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet, evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer-scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high field (7T) functional imaging at sub-millimetre resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths. Our results provide evidence for recurrent plasticity, by contrast to sensory encoding vs. feedback mechanisms. We demonstrate that learning alters orientation-specific representations in superficial rather than middle V1 layers, suggesting changes in read-out rather than input signals. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings propose finer-scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro-circuits of experience-dependent plasticity.

neuroscience↗

bioRxiv2020

An in vivo Probabilistic Atlas of the Human Locus Coeruleus at Ultra-high Field

Early and profound pathological changes are evident in the locus coeruleus (LC) in dementia and Parkinsons disease, with effects on arousal, attention, cognitive and motor control. The LC can be identified in vivo using non-invasive magnetic resonance imaging techniques which have potential as biomarkers for detecting and monitoring disease progression. Technical limitations of existing imaging protocols have impaired the sensitivity to regional contrast variance or the spatial variability on the rostrocaudal extent of the LC, with spatial mapping consistent with post mortem findings. The current study employs a sensitive magnetisation transfer sequence using ultrahigh field 7T MRI to investigate the LC structure in vivo at high-resolution (resolution 0.4x0.4x0.5 mm, duration seven minutes). Magnetisation transfer images from 53 healthy older volunteers (52-84 years) revealed the spatial features of the LC and were used to create a probabilistic LC atlas for older adults, appropriate for clinical research. Consistent rostrocaudal gradients of slice-wise volume, contrast and variance differences of the LC were observed, mirroring distinctive ex vivo spatial distributions of LC cells in its subregions. The contrast-to-noise ratios were calculated for the peak voxels, and for the averaged signals within the atlas, to accommodate the volumetric differences in estimated contrast. The probabilistic atlas is freely available, and the MRI dataset is available for researchers, for replication or to facilitate accurate LC localisation and unbiased contrast extraction in future studies.

neuroscience↗

bioRxiv2018

Accurate autocorrelation modeling substantially improves fMRI reliability

Given the recent controversies in some neuroimaging statistical methods, we compare the most frequently used functional Magnetic Resonance Imaging (fMRI) analysis packages: AFNI, FSL and SPM, with regard to temporal autocorrelation modeling. This process, sometimes known as pre-whitening, is conducted in virtually all task fMRI studies. We employ eleven datasets containing 980 scans corresponding to different fMRI protocols and subject populations. Though autocorrelation modeling in AFNI is not perfect, its performance is much higher than the performance of autocorrelation modeling in FSL and SPM. The residual autocorrelated noise in FSL and SPM leads to heavily confounded first level results, particularly for low-frequency experimental designs. Our results show superior performance of SPMs alternative pre-whitening: FAST, over SPMs default. The reliability of task fMRI studies would increase with more accurate autocorrelation modeling. Furthermore, reliability could increase if the packages provided diagnostic plots. This way the investigator would be aware of pre-whitening problems.

neuroscience↗