Distinct spatiotemporal atrophy patterns in corticobasal syndrome are associated with different underlying pathologies.

Objective: To identify imaging subtypes of the cortico-basal syndrome (CBS) based solely on a data-driven assessment of MRI atrophy patterns, and investigate whether these subtypes provide information on the underlying pathology. Methods: We applied Subtype and Stage Inference (SuStaIn), a machine learning algorithm that identifies groups of individuals with distinct biomarker progression patterns, to a large cohort of 135 CBS cases (52 had a pathological or biomarker defined diagnosis) and 252 controls. The model was fit using volumetric features extracted from baseline T1-weighted MRI scans and validated using follow-up MRI. We compared the clinical phenotypes of each subtype and investigated whether there were differences in associated pathology between the subtypes. Results: SuStaIn identified two subtypes with distinct sequences of atrophy progression; four-repeat-tauopathy confirmed cases were most commonly assigned to the Subcortical subtype (83% of CBS-PSP and 75% of CBS-CBD), while CBS-AD was most commonly assigned to the Fronto-parieto-occipital subtype (81% of CBS-AD). Subtype assignment was stable at follow-up (98% of cases), and individuals consistently progressed to higher stages (100% stayed at the same stage or progressed), supporting the model's ability to stage progression. Interpretation: By jointly modelling disease stage and subtype, we provide data-driven evidence for at least two distinct and longitudinally stable spatiotemporal subtypes of atrophy in CBS that are associated with different underlying pathologies. In the absence of sensitive and specific biomarkers, accurately subtyping and staging individuals with CBS at baseline has important implications for screening on entry into clinical trials, as well as for tracking disease progression.

A neuroimaging measure to capture heterogeneous patterns of atrophy in Parkinson's disease and dementia with Lewy bodies.

INTRODUCTION: Parkinson's disease (PD) and Dementia with Lewy bodies (DLB) show heterogeneous brain atrophy patterns which group-average analyses fail to capture. Neuroanatomical normative modelling overcomes this by comparing individuals to a large reference cohort. Patient-specific atrophy patterns are measured objectively and summarised to index overall neurodegeneration (the 'total outlier count'). We aimed to quantify patterns of neurodegenerative dissimilarity in participants with PD and DLB and evaluate the potential clinical relevance of total outlier count by testing its association with key clinical measures in PD and DLB. MATERIALS AND METHODS: We included 108 participants with PD and 61 with DLB. PD participants were subclassified into high and low visual performers as this has previously been shown to stratify those at increased dementia risk. We generated z-scores from T1w-MRI scans for each participant relative to normative regional cortical thickness and subcortical volumes, modelled in a reference cohort (n = 58,836). Outliers (z < -1.96) were aggregated across 169 brain regions per participant. To measure dissimilarity, individuals' Hamming distance scores were calculated. We also examined total outlier counts between high versus low visual performance in PD; and PD versus DLB; and tested associations between these and cognition. RESULTS: There was significantly greater inter-individual dissimilarity in brain-outlier patterns in PD poor compared to high visual performers (W = 522.5; p < 0.01) and in DLB compared to PD (W = 5649; p < 0.01). PD poor visual performers had significantly greater total outlier counts compared to high (ß = -4.73 (SE = 1.30); t = -3.64; p < 0.01) whereas a conventional group-level GLM failed to identify differences. Higher total outlier counts were associated with poorer MoCA (ß = -0.55 (SE = 0.27), t = -2.04, p = 0.05) and composite cognitive scores (ß = -2.01 (SE = 0.79); t = -2.54; p = 0.02) in DLB, and visuoperception (ß = -0.67 (SE = 0.19); t = -3.59; p < 0.01), in PD. CONCLUSIONS: Neuroanatomical normative modelling shows promise as a clinically informative technique in PD and DLB, where patterns of atrophy are variable.

A data-driven model of brain volume changes in progressive supranuclear palsy.

The most common clinical phenotype of progressive supranuclear palsy is Richardson syndrome, characterized by levodopa unresponsive symmetric parkinsonism, with a vertical supranuclear gaze palsy, early falls and cognitive impairment. There is currently no detailed understanding of the full sequence of disease pathophysiology in progressive supranuclear palsy. Determining the sequence of brain atrophy in progressive supranuclear palsy could provide important insights into the mechanisms of disease progression, as well as guide patient stratification and monitoring for clinical trials. We used a probabilistic event-based model applied to cross-sectional structural MRI scans in a large international cohort, to determine the sequence of brain atrophy in clinically diagnosed progressive supranuclear palsy Richardson syndrome. A total of 341 people with Richardson syndrome (of whom 255 had 12-month follow-up imaging) and 260 controls were included in the study. We used a combination of 12-month follow-up MRI scans, and a validated clinical rating score (progressive supranuclear palsy rating scale) to demonstrate the longitudinal consistency and utility of the event-based model's staging system. The event-based model estimated that the earliest atrophy occurs in the brainstem and subcortical regions followed by progression caudally into the superior cerebellar peduncle and deep cerebellar nuclei, and rostrally to the cortex. The sequence of cortical atrophy progresses in an anterior to posterior direction, beginning in the insula and then the frontal lobe before spreading to the temporal, parietal and finally the occipital lobe. This in vivo ordering accords with the post-mortem neuropathological staging of progressive supranuclear palsy and was robust under cross-validation. Using longitudinal information from 12-month follow-up scans, we demonstrate that subjects consistently move to later stages over this time interval, supporting the validity of the model. In addition, both clinical severity (progressive supranuclear palsy rating scale) and disease duration were significantly correlated with the predicted subject event-based model stage (P < 0.01). Our results provide new insights into the sequence of atrophy progression in progressive supranuclear palsy and offer potential utility to stratify people with this disease on entry into clinical trials based on disease stage, as well as track disease progression.

Towards a European health research and innovation cloud (HRIC).

The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe.

Sub-50 nm positioning of organic compounds onto silicon oxide patterns fabricated by local oxidation nanolithography.

We present a process to fabricate molecule-based nanostructures by merging a bottom-up interaction and a top-down nanolithography. Direct nanoscale positioning arises from the attractive electrostatic interactions between the molecules and silicon dioxide nanopatterns. Local oxidation nanolithography is used to fabricate silicon oxide domains with variable gap separations ranging from 40 nm to several microns in length. We demonstrate that an ionic tetrathiafulvalene (TTF) semiconductor can be directed from a macroscopic liquid solution (1 µM) and selectively deposited onto predefined nanoscale regions of a 1 cm(2) silicon chip with an accuracy of 40 nm.

Growth induced reordering of fullerene clusters trapped in a two-dimensional supramolecular network.

We have investigated the growth of molecular clusters in confined geometries defined by a bimolecular supramolecular network. This framework provides a regular array of identical nanoscale traps in which further deposited molecules nucleate cluster growth. For the higher fullerene, C84, molecules aggregate into close packed assemblies with an orientation which switches when the cluster size increases by one molecule. This change is controlled by the interactions between the molecules and the confining boundaries of the network pore. We show that, following nucleation of small clusters, further growth requires a reconfiguration of previously captured molecules resulting in a transition between nanoscale phases with different ordering.

Square, hexagonal, and row phases of PTCDA and PTCDI on Ag-Si(111)square root(3) x square root(3)R30 degrees.

We have investigated the ordered phases of the perylene derivatives perylene-3,4,9,10-tetracarboxylic-3,4,9,10-dianhydride (PTCDA) and the imide analogue PTCDI on the Ag-Si(111)square root(3) x square root(3)R30 degrees surface using scanning tunneling microscopy. We find that PTCDA forms square, hexagonal, and herringbone phases, which coexist on the surface. The existence of a square phase on a hexagonal surface is of particular interest and is a result of a near commensurability between the molecular dimensions and the surface lattice. Contrast variations across the square islands arise from PTCDA molecules binding to different sites on the surface. PTCDI on Ag-Si(111)square root(3) x square root(3)R30 degrees forms extended rows, as well as two-dimensional islands, both of which are stabilized by hydrogen bonding mediated by the presence of imide groups. We present models for the molecular arrangements in all these phases and highlight the role of hydrogen bonding in controlling this order.