Control of ZIF-62 and ag ZIF-62 Film Thickness within Asymmetric Tubular Supports through Pressure and Dose Time Variation of Atomic Layer Deposition.

Thin-films of metal-organic frameworks (MOFs) have widespread potential applications, especially with the emergence of glass-forming MOFs, which remove the inherent issue of grain boundaries and allow coherent amorphous films to be produced. Herein, it is established that atomic layer deposition (ALD) of zinc oxide lends excellent control over the thickness and localization of resultant polycrystalline and glass zeolitic imidazole framework-62 (ZIF-62) thin-films within tubular α-alumina supports. Through the reduction of the chamber pressure and dose times during zinc oxide deposition, the resultant ZIF-62 films are reduced from 38 µm to 16 µm, while the presence of sporadic ZIF-62 (previously forming as far as 280 µm into the support) is prevented. Furthermore, the glass transformation shows a secondary reduction in film thickness from 16 to 2 µm.

Sugar distributions on gangliosides guide the formation and stability of amyloid-ß oligomers.

Aggregation of Aß peptides is a key contributor to the etiology of Alzheimer's disease. Being intrinsically disordered, monomeric Aß is susceptible to conformational excursions, especially in the presence of important interacting partners such as membrane lipids, to adopt specific aggregation pathways. Furthermore, components such as gangliosides in membranes and lipid rafts are known to play important roles in the adoption of pathways and the generation of discrete neurotoxic oligomers. Yet, what roles do carbohydrates on gangliosides play in this process remains unknown. Here, using GM1, GM3, and GD3 ganglioside micelles as models, we show that the sugar distributions and cationic amino acids within Aß N-terminal region modulate oligomerization of Aß temporally, and dictate the stability and maturation of oligomers. These results demonstrate the selectivity of sugar distributions on the membrane surface toward oligomerization of Aß and thus implicate cell-selective enrichment of oligomers.

Robust estimation of cortical similarity networks from brain MRI.

Structural similarity is a growing focus for magnetic resonance imaging (MRI) of connectomes. Here we propose Morphometric INverse Divergence (MIND), a new method to estimate within-subject similarity between cortical areas based on the divergence between their multivariate distributions of multiple MRI features. Compared to the prior approach of morphometric similarity networks (MSNs) on n > 11,000 scans spanning three human datasets and one macaque dataset, MIND networks were more reliable, more consistent with cortical cytoarchitectonics and symmetry and more correlated with tract-tracing measures of axonal connectivity. MIND networks derived from human T1-weighted MRI were more sensitive to age-related changes than MSNs or networks derived by tractography of diffusion-weighted MRI. Gene co-expression between cortical areas was more strongly coupled to MIND networks than to MSNs or tractography. MIND network phenotypes were also more heritable, especially edges between structurally differentiated areas. MIND network analysis provides a biologically validated lens for cortical connectomics using readily available MRI data.

De novo amyloid peptides with subtle sequence variations differ in their self-assembly and nanomechanical properties.

Proteinaceous amyloids are well known for their widespread pathological roles but lately have emerged also as key components in several biological functions. The remarkable ability of amyloid fibers to form tightly packed conformations in a cross ß-sheet arrangement manifests in their robust enzymatic and structural stabilities. These characteristics of amyloids make them attractive for designing proteinaceous biomaterials for various biomedical and pharmaceutical applications. In order to design customizable and tunable amyloid nanomaterials, it is imperative to understand the sensitivity of the peptide sequence for subtle changes based on amino acid position and chemistry. Here we report our results from four rationally-designed amyloidogenic decapeptides that subtly differ in hydrophobicity and polarity at positions 5 and 6. We show that making the two positions hydrophobic renders the peptide with enhanced aggregation and material properties while introducing polar residues in position 5 dramatically changes the structure and nanomechanical properties of the fibrils formed. A charged residue at position 6, however, abrogates amyloid formation. In sum, we show that subtle changes in the sequence do not make the peptide innocuous but rather sensitive to aggregation, reflected in the biophysical and nanomechanical properties of the fibrils. We conclude that tolerance of peptide amyloid for changes in the sequence, however small they may be, should not be neglected for the effective design of customizable amyloid nanomaterials.

Enabling quantitative analysis of complex polymer blends by infrared nanospectroscopy and isotopic deuteration.

Atomic-force microscopy coupled with infrared spectroscopy (AFM-IR) deciphers surface morphology of thin-film polymer blends and composites by simultaneously mapping physical topography and chemical composition. However, acquiring quantitative phase and composition information from multi-component blends can be challenging using AFM-IR due to the possible overlapping infrared absorption bands between different species. Isotope labeling one of the blend components introduces a new type of bond (carbon-deuterium vibration) that can be targeted using AFM-IR and responds at wavelengths sufficiently shifted toward unoccupied regions (around 2200 cm-1). In this project, AFM-IR was used to probe the surface morphology and chemical composition of three polymer blends containing deuterated polystyrene; each blend is expected to exhibit various degrees of miscibility. AFM-IR results successfully demonstrated that deuterium labeling prevents infrared spectral overlap and enables the visualization of blend phases that could not normally be distinguished by other scanning probe techniques. The nanoscale domain composition was resolved by fast infrared spectrum analysis. Overall, we presented isotope labeling as a robust approach for circumventing obstacles preventing the quantitative analysis of multiphase systems by AFM-IR.

Semantic Speech Networks Linked to Formal Thought Disorder in Early Psychosis.

BACKGROUND AND HYPOTHESIS: Mapping a patient's speech as a network has proved to be a useful way of understanding formal thought disorder in psychosis. However, to date, graph theory tools have not explicitly modelled the semantic content of speech, which is altered in psychosis. STUDY DESIGN: We developed an algorithm, "netts," to map the semantic content of speech as a network, then applied netts to construct semantic speech networks for a general population sample (N = 436), and a clinical sample comprising patients with first episode psychosis (FEP), people at clinical high risk of psychosis (CHR-P), and healthy controls (total N = 53). STUDY RESULTS: Semantic speech networks from the general population were more connected than size-matched randomized networks, with fewer and larger connected components, reflecting the nonrandom nature of speech. Networks from FEP patients were smaller than from healthy participants, for a picture description task but not a story recall task. For the former task, FEP networks were also more fragmented than those from controls; showing more connected components, which tended to include fewer nodes on average. CHR-P networks showed fragmentation values in-between FEP patients and controls. A clustering analysis suggested that semantic speech networks captured novel signals not already described by existing NLP measures. Network features were also related to negative symptom scores and scores on the Thought and Language Index, although these relationships did not survive correcting for multiple comparisons. CONCLUSIONS: Overall, these data suggest that semantic networks can enable deeper phenotyping of formal thought disorder in psychosis. Whilst here we focus on network fragmentation, the semantic speech networks created by Netts also contain other, rich information which could be extracted to shed further light on formal thought disorder. We are releasing Netts as an open Python package alongside this manuscript.

Toxin-Blocking Textiles: Rapid, Benign, Roll-to-Roll Production of Robust MOF-Fabric Composites for Organophosphate Separation and Hydrolysis.

Current approaches to create zirconium-based metal-organic framework (MOF) fabric composites for catalysis, water purification, wound healing, gas sorption, and other applications often rely on toxic solvents, long reaction/post processing times, and batch methods hindering process scalability. Here, a novel mechanism was reported for rapid UiO-66-NH2 synthesis in common low-boiling-point solvents (water, ethanol, and acetic acid) and revealed acid-base chemistry promoting full linker dissolution and vapor-based crystallization. The mechanism enabled scalable roll-to-roll production of mechanically resilient UiO-66-NH2 fabrics with superior chemical protective capability. Solvent choice and segregated spray delivery of organic linker and metal salt MOF precursor solutions allowed for rapid MOF nucleation on the fiber surface and decreased the energy and time needed for post-processing, producing an activated composite in less than 165 min, far outpacing conventional MOF-fabric synthesis approaches. The MOF-fabric hydrolyzed and blocked permeation of the chemical warfare agent soman, outperforming the protection-standard activated carbon cloth. This work presents both chemical insights into Zr-MOF powder and fabric composite formation by a rapid, industrially relevant approach and demonstrates its practicality and affordability for high-performing personal protective equipment.

Exploiting Partial Solubility in Partially Fluorinated Thermoplastic Blends to Improve Adhesion during Fused Deposition Modeling.

This work studies the effect of interlayer adhesion on mechanical performance of fluorinated thermoplastics produced by fused deposition modeling (FDM). Here, we study the anisotropic mechanical response of 3D-printed binary blends of poly (vinylidene fluoride) (PVDF) and poly (methyl methacrylate) (PMMA) with the isotropic mechanical response of these blends fabricated via injection molding. Various PVDF/PMMA filament compositions were produced by twin-screw extrusion and, subsequently, injection-molded or 3D printed into dog-bone shapes. Specimen mechanical and thermal properties were evaluated by mode I tensile testing and differential scanning calorimetry, respectively. Results show that higher PMMA concentration not only improved the tensile strength and decreased ductility but reduced PVDF crystallization. As expected, injection-molded samples revealed better mechanical properties compared to 3D printed specimens. Interestingly, 3D printed blends with lower PMMA content demonstrated better diffusion (adhesion) across interfaces than those with a higher amount of PMMA. The present study provides new findings that may be used to tune mechanical response in 3D printed fluorinated thermoplastics, particularly for energy applications.

Synthesis and Morphology of High-Molecular-Weight Polyisobutylene-Polystyrene Block Copolymers Containing Dynamic Covalent Bonds.

Incorporating dynamic covalent bonds into block copolymers provides useful molecular level information during mechanical testing, but it is currently unknown how the incorporation of these units affects the resultant polymer morphology. High-molecular-weight polyisobutylene-b-polystyrene block copolymers containing an anthracene/maleimide dynamic covalent bond are synthesized through a combination of postpolymerization modification, reversible addition-fragmentation chain-transfer polymerization, and Diels-Alder coupling. The bulk morphologies with and without dynamic covalent bond are characterized by atomic force microscopy  and small-angle X-ray scattering, which reveal a strong dependence on annealing time and casting solvent. Morphology is largely unaffected by the inclusion of the mechanophore. The high-molecular-weight polymers synthesized allow interrogation of a large range of polymer domain sizes.

Diketoenamine-Based Vitrimers via Thiol-ene Photopolymerization.

Likened to both thermosets and thermoplastics, vitrimers are a unique class of materials that combine remarkable stability, healability, and reprocessability. Herein, this work describes a photopolymerized thiol-ene-based vitrimer that undergoes dynamic covalent exchanges through uncatalyzed transamination of enamines derived from cyclic ß-triketones, whereby the low energy barrier for exchange facilitates reprocessing and enables rapid depolymerization. Accordingly, an alkene-functionalized ß-triketone, 5,5-dimethyl-2-(pent-4-enoyl)cyclohexane-1,3-dione, is devised which is then reacted with 1,6-diaminohexane in a stoichiometrically imbalanced fashion (≈1:0.85 primary amine:triketone). The resulting networks exhibit subambient glass transition temperature (Tg = 5.66 °C) by differential scanning calorimetry. Using a Maxwell stress-relaxation fit, the topology-freezing temperature (Tv ) is calculated to be -32 °C. Small-amplitude oscillatory shear rheological analysis enables to identify a practical critical temperature above which the vitrimer can be successfully reprocessed (Tv,eff ). Via the introduction of excess primary amines, this work can readily degrade the networks into monomeric precursors, which are in turn reacted with diamines to regenerate reprocessable networks. Photopolymerization provides unique spatiotemporal control over the network topology, thereby opening the path for further investigation of vitrimer properties. As such, this work expands the toolbox of chemical upcycling of networks and enables their wider implementation.

Charge and redox states modulate granulin-TDP-43 coacervation toward phase separation or aggregation.

Cytoplasmic inclusions containing aberrant proteolytic fragments of TDP-43 are associated with frontotemporal lobar degeneration (FTLD) and other related pathologies. In FTLD, TDP-43 is translocated into the cytoplasm and proteolytically cleaved to generate a prion-like domain (PrLD) containing C-terminal fragments (C25 and C35) that form toxic inclusions. Under stress, TDP-43 partitions into membraneless organelles called stress granules (SGs) by coacervating with RNA and other proteins. To study the factors that influence the dynamics between these cytoplasmic foci, we investigated the effects of cysteine-rich granulins (GRNs 1-7), which are the proteolytic products of progranulin, a protein implicated in FTLD, on TDP-43. We show that extracellular GRNs, typically generated during inflammation, internalize and colocalize with PrLD as puncta in the cytoplasm of neuroblastoma cells but show less likelihood of their presence in SGs. In addition, we show GRNs and PrLD coacervate to undergo liquid-liquid phase separation (LLPS) or form gel- or solid-like aggregates. Using charge patterning and conserved cysteines among the wild-type GRNs as guides, along with specifically engineered mutants, we discover that the negative charges on GRNs drive LLPS while the positive charges and the redox state of cysteines modulate these phase transitions. Furthermore, RNA and GRNs compete and expel one another from PrLD condensates, providing a basis for GRN's absence in SGs. Together, the results help uncover potential modulatory mechanisms by which extracellular GRNs, formed during chronic inflammatory conditions, could internalize and modulate cytoplasmic TDP-43 inclusions in proteinopathies.

Sexually divergent development of depression-related brain networks during healthy human adolescence.

Sexual differences in human brain development could be relevant to sex differences in the incidence of depression during adolescence. We tested for sex differences in parameters of normative brain network development using fMRI data on N = 298 healthy adolescents, aged 14 to 26 years, each scanned one to three times. Sexually divergent development of functional connectivity was located in the default mode network, limbic cortex, and subcortical nuclei. Females had a more "disruptive" pattern of development, where weak functional connectivity at age 14 became stronger during adolescence. This fMRI-derived map of sexually divergent brain network development was robustly colocated with i prior loci of reward-related brain activation ii a map of functional dysconnectivity in major depressive disorder (MDD), and iii an adult brain gene transcriptional pattern enriched for genes on the X chromosome, neurodevelopmental genes, and risk genes for MDD. We found normative sexual divergence in adolescent development of a cortico-subcortical brain functional network that is relevant to depression.

Cationic Glycopolyelectrolytes for RNA Interference in Tick Cells.

The black-legged tick (Ixodes scapularis) is the primary vector for bacteria that cause Lyme disease (Borrelia burgdorferi), where numerous glycosylated tick proteins are involved at the interface of vector-host-pathogen interactions. Reducing the expression of key tick proteins, such as selenoprotein K (SelK), through RNA interference is a promising approach to reduce pathogen transmission, but efficient delivery of nucleic acids to arthropods has proven challenging. While cationic glycopolymers have been used as nonviral gene delivery vehicles in mammalian cells, their use in arthropod or insect gene transfection has not been established. In this study, statistical acrylamide-based cationic glycopolymers with glucose or galactose pendant groups were synthesized by reversible addition-fragmentation chain transfer polymerization, and the effects of the saccharide pendant group and cationic monomer loading on polymer cytotoxicity, RNA complexation, and SelK gene knockdown in ISE6 cells were evaluated. All polymers exhibited low cytotoxicity, yet RNA/copolymer complex cell uptake and gene knockdown were highly dependent on the saccharide structure and the N:P (amino to phosphate groups) ratio.

Natural Language Processing markers in first episode psychosis and people at clinical high-risk.

Recent work has suggested that disorganised speech might be a powerful predictor of later psychotic illness in clinical high risk subjects. To that end, several automated measures to quantify disorganisation of transcribed speech have been proposed. However, it remains unclear which measures are most strongly associated with psychosis, how different measures are related to each other and what the best strategies are to collect speech data from participants. Here, we assessed whether twelve automated Natural Language Processing markers could differentiate transcribed speech excerpts from subjects at clinical high risk for psychosis, first episode psychosis patients and healthy control subjects (total N = 54). In-line with previous work, several measures showed significant differences between groups, including semantic coherence, speech graph connectivity and a measure of whether speech was on-topic, the latter of which outperformed the related measure of tangentiality. Most NLP measures examined were only weakly related to each other, suggesting they provide complementary information. Finally, we compared the ability of transcribed speech generated using different tasks to differentiate the groups. Speech generated from picture descriptions of the Thematic Apperception Test and a story re-telling task outperformed free speech, suggesting that choice of speech generation method may be an important consideration. Overall, quantitative speech markers represent a promising direction for future clinical applications.

Dysconnectivity of a brain functional network was associated with blood inflammatory markers in depression.

OBJECTIVE: There is increasing evidence for a subgroup of major depressive disorder (MDD) associated with heightened peripheral blood inflammatory markers. In this study, we aimed to understand the mechanistic brain-immune axis in inflammation-linked depression by investigating associations between functional connectivity (FC) of brain networks and peripheral blood immune markers in depression. METHODS: Resting-state functional magnetic resonance imaging (fMRI) and peripheral blood inflammatory markers (C-reactive protein; CRP, interleukin-6; IL-6 and immune cells) were collected on N = 46 healthy controls (HC; CRP ≤ 3 mg/L) and N = 83 cases of depression, stratified further into low CRP cases (loCRP cases; ≤ 3 mg/L; N = 50) and high CRP cases (hiCRP cases; > 3 mg/L; N = 33). In a two-part analysis, network-based statistics (NBS) was firstly used to ascertain whole-brain FC differences in HC vs hiCRP cases. Secondly, we investigated the association between this network of interconnected brain regions and continuous measures of peripheral CRP (N = 83), IL-6 (N = 72), neutrophils and CD4+ T-cells (N = 36) in depression cases only. RESULTS: Case-control NBS testing revealed a single network of abnormally attenuated FC in the high CRP depression cases compared to healthy controls. Connections within this network were mainly between brain regions located in the left insula/frontal operculum and posterior cingulate cortex, which were assigned to ventral attention and default mode canonical fMRI networks respectively. Within-group analysis across all depression cases, secondarily demonstrated that FC within the identified network significantly negatively scaled with CRP, IL-6 and neutrophils. CONCLUSIONS: The findings suggest that inflammation is associated with disruption of functional connectivity within a brain network deemed critical for interoceptive signalling, e.g. accurate communication of peripheral bodily signals such as immune states to the brain, with implications for the pathogenesis of inflammation-linked depression.

Stretchable and Multi-Metal-Organic Framework Fabrics Via High-Yield Rapid Sorption-Vapor Synthesis and Their Application in Chemical Warfare Agent Hydrolysis.

Protocols to create metal-organic framework (MOF)/polymer composites for separation, chemical capture, and catalytic applications currently rely on relatively slow solution-based processing to form single MOF composites. Here, we report a rapid, high-yield sorption-vapor method for direct simultaneous growth of single and multiple MOF materials onto untreated flexible and stretchable polymer fibers and films. The synthesis utilizes favorable reactant absorption into polymers coupled with rapid vapor-driven MOF crystallization to form high surface area (>250 m2/gcomposite) composites, including UiO-66-NH2, HKUST-1, and MOF-525 on spandex, nylon, and other fabrics. The resulting composites are robust and maintain their functionality even after stretching. Stretchable MOF fabrics enable rapid solid-state hydrolysis of the highly toxic chemical warfare agent soman and paraoxon-methyl simulant. We show that this approach can readily be scaled by solution spray-coating of MOF precursors and to large area substrates.

Prion-like C-Terminal Domain of TDP-43 and α-Synuclein Interact Synergistically to Generate Neurotoxic Hybrid Fibrils.

Aberrant aggregation and amyloid formation of tar DNA binding protein (TDP-43) and α-synuclein (αS) underlie frontotemporal dementia (FTD) and Parkinson's disease (PD), respectively. Amyloid inclusions of TDP-43 and αS are also commonly co-observed in amyotrophic lateral sclerosis (ALS), dementia with Lewy bodies (DLB) and Alzheimer disease (AD). Emerging evidence from cellular and animal models show colocalization of the TDP-43 and αS aggregates, raising the possibility of direct interactions and co-aggregation between the two proteins. In this report, we set out to answer this question by investigating the interactions between αS and prion-like pathogenic C-terminal domain of TDP-43 (TDP-43 PrLD). PrLD is an aggregation-prone fragment generated both by alternative splicing as well as aberrant proteolytic cleavage of full length TDP-43. Our results indicate that two proteins interact in a synergistic manner to augment each other's aggregation towards hybrid fibrils. While monomers, oligomers and sonicated fibrils of αS seed TDP-43 PrLD monomers, TDP-43 PrLD fibrils failed to seed αS monomers indicating selectivity in interactions. Furthermore, αS modulates liquid droplets formed by TDP-43 PrLD and RNA to promote insoluble amyloid aggregates. Importantly, the cross-seeded hybrid aggregates show greater cytotoxicity as compared to the individual homotypic aggregates suggesting that the interactions between the two proteins have a discernable impact on cellular functions. Together, these results bring forth insights into TDP-43 PrLD - αS interactions that could help explain clinical and pathological presentations in patients with co-morbidities involving the two proteins.

Biophysical characteristics of lipid-induced Aß oligomers correlate to distinctive phenotypes in transgenic mice.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects cognition and memory. Recent advances have helped identify many clinical sub-types in AD. Mounting evidence point toward structural polymorphism among fibrillar aggregates of amyloid-ß (Aß) to being responsible for the phenotypes and clinical manifestations. In the emerging paradigm of polymorphism and prion-like propagation of aggregates in AD, the role of low molecular weight soluble oligomers, which are long known to be the primary toxic agents, in effecting phenotypes remains inconspicuous. In this study, we present the characterization of three soluble oligomers of Aß42, namely 14LPOs, 16LPOs, and GM1Os with discreet biophysical and biochemical properties generated using lysophosphatidyl glycerols and GM1 gangliosides. The results indicate that the oligomers share some biophysical similarities but display distinctive differences with GM1Os. Unlike the other two, GM1Os were observed to be complexed with the lipid upon isolation. It also differs mainly in detection by conformation-sensitive dyes and conformation-specific antibodies, temperature and enzymatic stability, and in the ability to propagate morphologically-distinct fibrils. GM1Os also show distinguishable biochemical behavior with pronounced neuronal toxicity. Furthermore, all the oligomers induce cerebral amyloid angiopathy (CAA) and plaque burden in transgenic AD mice, which seems to be a consistent feature among all lipid-derived oligomers, but 16LPOs and GM1Os displayed significantly higher effect than the others. These results establish a correlation between molecular features of Aß42 oligomers and their distinguishable effects in transgenic AD mice attuned by lipid characteristics, and therefore help bridge the knowledge gap in understanding how oligomer conformers could elicit AD phenotypes.

Functional Magnetic Resonance Imaging Connectivity Accurately Distinguishes Cases With Psychotic Disorders From Healthy Controls, Based on Cortical Features Associated With Brain Network Development.

BACKGROUND: Machine learning (ML) can distinguish cases with psychotic disorder from healthy controls based on magnetic resonance imaging (MRI) data, but it is not yet clear which MRI metrics are the most informative for case-control ML, or how ML algorithms relate to the underlying biology. METHODS: We analyzed multimodal MRI data from 2 independent case-control studies of psychotic disorders (cases, n = 65, 28; controls, n = 59, 80) and compared ML accuracy across 5 selected MRI metrics from 3 modalities. Cortical thickness, mean diffusivity, and fractional anisotropy were estimated at each of 308 cortical regions, as well as functional and structural connectivity between each pair of regions. Functional connectivity data were also used to classify nonpsychotic siblings of cases (n = 64) and to distinguish cases from controls in a third independent study (cases, n = 67; controls, n = 81). RESULTS: In both principal studies, the most informative metric was functional MRI connectivity: The areas under the receiver operating characteristic curve were 88% and 76%, respectively. The cortical map of diagnostic connectivity features (ML weights) was replicable between studies (r = 0.27, p < .001); correlated with replicable case-control differences in functional MRI degree centrality and with a prior cortical map of adolescent development of functional connectivity; predicted intermediate probabilities of psychosis in siblings; and was replicated in the third case-control study. CONCLUSIONS: ML most accurately distinguished cases from controls by a replicable pattern of functional MRI connectivity features, highlighting abnormal hubness of cortical nodes in an anatomical pattern consistent with the concept of psychosis as a disorder of network development.

Lower speech connectedness linked to incidence of psychosis in people at clinical high risk.

BACKGROUND: Formal thought disorder is a cardinal feature of psychotic disorders, and is also evident in subtle forms before psychosis onset in individuals at clinical high-risk for psychosis (CHR-P). Assessing speech output or assessing expressive language with speech as the medium at this stage may be particularly useful in predicting later transition to psychosis. METHOD: Speech samples were acquired through administration of the Thought and Language Index (TLI) in 24 CHR-P participants, 16 people with first-episode psychosis (FEP) and 13 healthy controls. The CHR-P individuals were then followed clinically for a mean of 7 years (s.d. = 1.5) to determine if they transitioned to psychosis. Non-semantic speech graph analysis was used to assess the connectedness of transcribed speech in all groups. RESULTS: Speech was significantly more disconnected in the FEP group than in both healthy controls (p < .01) and the CHR-P group (p < .05). Results remained significant when IQ was included as a covariate. Significant correlations were found between speech connectedness measures and scores on the TLI, a manual assessment of formal thought disorder. In the CHR-P group, lower scores on two measures of speech connectedness were associated with subsequent transition to psychosis (8 transitions, 16 non-transitions; p < .05). CONCLUSION: These findings support the utility and validity of speech graph analysis methods in characterizing speech connectedness in the early phases of psychosis. This approach has the potential to be developed into an automated, objective and time-efficient way of stratifying individuals at CHR-P according to level of psychosis risk.