Astrocytes are a target for regenerative neurobiology because in brain injury their phenotype arbitrates brain integrity, neuronal death and subsequent repair and reconstruction. We explored the ability of 3D scaffolds to direct astrocytes into phenotypes with the potential to support neuronal survival. Poly-ε-caprolactone scaffolds were electrospun with random and aligned fibre orientations on which murine astrocytes were sub-cultured and analysed at 4 and 12 DIV. Astrocytes survived, proliferated and migrated into scaffolds adopting 3D morphologies, mimicking in vivo stellated phenotypes. Cells on random poly-ε-caprolactone scaffolds grew as circular colonies extending processes deep within sub-micron fibres, whereas astrocytes on aligned scaffolds exhibited rectangular colonies with processes following not only the direction of fibre alignment but also penetrating the scaffold. Cell viability was maintained over 12 DIV, and cytochemistry for F-/G-actin showed fewer stress fibres on bioscaffolds relative to 2D astrocytes. Reduced cytoskeletal stress was confirmed by the decreased expression of glial fibrillary acidic protein. PCR demonstrated up-regulation of genes (excitatory amino acid transporter 2, brain-derived neurotrophic factor and anti-oxidant) reflecting healthy biologies of mature astrocytes in our extended culture protocol. This study illustrates the therapeutic potential of bioengineering strategies using 3D electrospun scaffolds which direct astrocytes into phenotypes supporting brain repair. Astrocytes exist in phenotypes with pro-survival and destructive components, and their biology can be modulated by changing phenotype. Our findings demonstrate murine astrocytes adopt a healthy phenotype when cultured in 3D. Astrocytes proliferate and extend into poly-ε-caprolactone scaffolds displaying 3D stellated morphologies with reduced GFAP expression and actin stress fibres, plus a cytotrophic gene profile. Bioengineered 3D scaffolds have potential to direct inflammation to aid regenerative neurobiology.

Multiple sclerosis is a chronic inflammatory neurological condition characterized by focal and diffuse neurodegeneration and demyelination throughout the central nervous system. Factors influencing the progression of pathology are poorly understood. One hypothesis is that anatomical connectivity influences the spread of neurodegeneration. This predicts that measures of neurodegeneration will correlate most strongly between interconnected structures. However, such patterns have been difficult to quantify through post-mortem neuropathology or in vivo scanning alone. In this study, we used the complementary approaches of whole brain post-mortem magnetic resonance imaging and quantitative histology to assess patterns of multiple sclerosis pathology. Two thalamo-cortical projection systems were considered based on their distinct neuroanatomy and their documented involvement in multiple sclerosis: lateral geniculate nucleus to primary visual cortex and mediodorsal nucleus of the thalamus to prefrontal cortex. Within the anatomically distinct thalamo-cortical projection systems, magnetic resonance imaging derived cortical thickness was correlated significantly with both a measure of myelination in the connected tract and a measure of connected thalamic nucleus cell density. Such correlations did not exist between these markers of neurodegeneration across different thalamo-cortical systems. Magnetic resonance imaging lesion analysis depicted clearly demarcated subcortical lesions impinging on the white matter tracts of interest; however, quantitation of the extent of lesion-tract overlap failed to demonstrate any appreciable association with the severity of markers of diffuse pathology within each thalamo-cortical projection system. Diffusion-weighted magnetic resonance imaging metrics in both white matter tracts were correlated significantly with a histologically derived measure of tract myelination. These data demonstrate for the first time the relevance of functional anatomical connectivity to the spread of multiple sclerosis pathology in a 'tract-specific' pattern. Furthermore, the persisting relationship between metrics from post-mortem diffusion-weighted magnetic resonance imaging and histological measures from fixed tissue further validates the potential of imaging for future neuropathological studies.

Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.

Age-related macular degeneration (AMD) is a leading cause of blindness in Western countries and is diagnosed by the clinical appearance of yellow subretinal deposits called drusen. Genetic changes in immune components are clearly implicated in the pathology of this disease. We have previously shown that the purinergic receptor P2X7 can act as a scavenger receptor, mediating phagocytosis of apoptotic cells and insoluble debris. We performed a genetic association study of functional polymorphisms in the P2RX7 and P2RX4 genes in a cohort of 744 patients with AMD and 557 age-matched Caucasian control subjects. The P2X4 Tyr315Cys variant was 2-fold more frequent in patients with AMD compared to control subjects, with the minor allele predicting susceptibility to disease. Pairwise linkage disequilibrium was observed between Tyr315Cys in the P2RX4 gene and Gly150Arg in the P2RX7 gene, and these two minor alleles formed a rare haplotype that was overrepresented in patients with AMD (n=17) compared with control subjects (n=3) (odds ratio 4.05, P=0.026). Expression of P2X7 (wild type or variant 150Arg) in HEK293 cells conferred robust phagocytosis toward latex beads, whereas coexpression of the P2X7 150Arg with P2X4 315Cys variants almost completely inhibited phagocytic capacity. Fresh human monocytes harboring this heterozygous 150Arg-315Cys haplotype showed 40% reduction in bead phagocytosis. In the primate eye, immunohistochemistry indicated that P2X7 and P2X4 receptors were coexpressed on microglia and macrophages, but neither receptor was seen on retinal pigment epithelial cells. These results demonstrate that a haplotype including two rare variants in P2RX7 and P2RX4 confers a functional interaction between these two variant receptors that impairs the normal scavenger function of macrophages and microglia. Failure of this P2X7-mediated phagocytic pathway may impair removal of subretinal deposits and predispose individuals toward AMD.

The expression of the neurotrophins and their receptors is essential for peripheral nervous system development and myelination. We have previously demonstrated that brain-derived neurotrophic factor (BDNF) exerts contrasting influences upon Schwann cell myelination in vitro - promoting myelination via neuronally expressed p75NTR, but inhibiting myelination via neuronally expressed TrkB. We have generated a small peptide called cyclo-dPAKKR that structurally mimics the region of BDNF that binds p75NTR. Here, we have investigated whether utilizing cyclo-dPAKKR to selectively target p75NTR is an approach that could exert a unified promyelinating response. Like BDNF, cyclo-dPAKKR promoted myelination of nerve growth factor-dependent neurons in vitro, an effect dependent on the neuronal expression of p75NTR. Importantly, cyclo-dPAKKR also significantly promoted the myelination of tropomyosin-related kinase receptor B-expressing neurons in vitro, whereas BDNF exerted a significant inhibitory effect. This indicated that while BDNF exerted a contrasting influence upon the myelination of distinct subsets of dorsal root ganglion (DRG) neurons in vitro, cyclo-dPAKKR uniformly promoted their myelination. Local injection of cyclo-dPAKKR adjacent to the developing sciatic nerve in vivo significantly enhanced myelin protein expression and significantly increased the number of myelinated axons. These results demonstrate that cyclo-dPAKKR promotes peripheral myelination in vitro and in vivo, suggesting it is a strategy worthy of further investigation for the treatment of peripheral demyelinating diseases.

Expression of A53T mutant human alpha-synuclein under the mouse prion promoter is among the most successful transgenic models of Parkinson's disease. Accumulation of A53T alpha-synuclein causes adult mice to develop severe motor impairment resulting in early death at 8-12 months of age. In younger, pre-symptomatic animals, altered motor activity and anxiety-like behaviors have also been reported. These behavioral changes, which precede severe neuropathology, may stem from non-pathological functions of alpha-synuclein, including modulation of monoamine neurotransmission. Our analysis over the adult life-span of motor activity, anxiety-like, and depressive-like behaviors identifies perturbations both before and after the onset of disease. Young A53T mice had increased distribution of the dopamine transporter (DAT) to the membrane that was associated with increased striatal re-uptake function. DAT function decreased with aging, and was associated with neurochemical alterations that included increased expression of beta-synuclein and gamma synuclein. Prior to normalization of dopamine uptake, transient activation of Tau kinases and hyperphosphorylation of Tau in the striatum were also observed. Aged A53T mice had reduced neuron counts in the substantia nigra pars compacta, yet striatal medium spiny neuron dendritic spine density was largely maintained. These findings highlight the involvement of the synuclein family of proteins and phosphorylation of Tau in the response to dopaminergic dysfunction of the nigrostriatal pathway.

The allostatic load index quantifies the cumulative multisystem physiological response to chronic everyday stress, and includes cardiovascular, metabolic and inflammatory measures. Despite its central role in the stress response, research of the effect of allostatic load on the ageing brain has been limited. We investigated the relation of mid-life allostatic load index and multifactorial predictors of stroke (Framingham stroke risk) and diabetes (metabolic syndrome) with voxelwise structural grey and white matter brain integrity measures in the ageing Whitehall II cohort (N = 349, mean age = 69.6 (SD 5.2) years, N (male) = 281 (80.5%), mean follow-up before scan = 21.4 (SD 0.82) years). Higher levels of all three markers were significantly associated with lower grey matter density. Only higher Framingham stroke risk was significantly associated with lower white matter integrity (low fractional anisotropy and high mean diffusivity). Our findings provide some empirical support for the concept of allostatic load, linking the effect of everyday stress on the body with features of the ageing human brain.

Cannabis use is highly prevalent and often considered to be relatively harmless. Nonetheless, a subset of regular cannabis users may develop dependence, experiencing poorer quality of life and greater mental health problems relative to non-dependent users. The neuroanatomy characterizing cannabis use versus dependence is poorly understood. We aimed to delineate the contributing role of cannabis use and dependence on morphology of the hippocampus, one of the most consistently altered brain regions in cannabis users, in a large multi-site dataset aggregated across four research sites. We compared hippocampal volume and vertex-level hippocampal shape differences (1) between 121 non-using controls and 140 cannabis users; (2) between 106 controls, 50 non-dependent users and 70 dependent users; and (3) between a subset of 41 controls, 41 non-dependent users and 41 dependent users, matched on sample characteristics and cannabis use pattern (onset age and dosage). Cannabis users did not differ from controls in hippocampal volume or shape. However, cannabis-dependent users had significantly smaller right and left hippocampi relative to controls and non-dependent users, irrespective of cannabis dosage. Shape analysis indicated localized deflations in the superior-medial body of the hippocampus. Our findings support neuroscientific theories postulating dependence-specific neuroadaptations in cannabis users. Future efforts should uncover the neurobiological risk and liabilities separating dependent and non-dependent use of cannabis.

Artificial intelligence is one of the most exciting methodological shifts in our era. It holds the potential to transform healthcare as we know it, to a system where humans and machines work together to provide better treatment for our patients. It is now clear that cutting edge artificial intelligence models in conjunction with high-quality clinical data will lead to improved prognostic and diagnostic models in neurological disease, facilitating expert-level clinical decision tools across healthcare settings. Despite the clinical promise of artificial intelligence, machine and deep-learning algorithms are not a one-size-fits-all solution for all types of clinical data and questions. In this article, we provide an overview of the core concepts of artificial intelligence, particularly contemporary deep-learning methods, to give clinician and neuroscience researchers an appreciation of how artificial intelligence can be harnessed to support clinical decisions. We clarify and emphasize the data quality and the human expertise needed to build robust clinical artificial intelligence models in neurology. As artificial intelligence is a rapidly evolving field, we take the opportunity to iterate important ethical principles to guide the field of medicine is it moves into an artificial intelligence enhanced future.

With recent developments in MR acquisition at 7T, smaller brainstem structures such as the red nuclei, substantia nigra and subthalamic nuclei can be imaged with good contrast and resolution. These structures have important roles both in the study of the healthy brain and in diseases such as Parkinson's disease, but few methods have been described to automatically segment them. In this paper, we extend a method that we have previously proposed for segmentation of the striatum and globus pallidus to segment these deeper and smaller structures. We modify the method to allow more direct control over segmentation smoothness by using a Markov random field prior. We investigate segmentation performance in three age groups and show that the method produces consistent results that correspond well with manual segmentations. We perform a vertex-based analysis to identify changes with age in the shape of the structures and present results suggesting that the method may be at least as effective as manual delineation in capturing differences between subjects.

Accurate segmentation of the subcortical structures is frequently required in neuroimaging studies. Most existing methods use only a T1-weighted MRI volume to segment all supported structures and usually rely on a database of training data. We propose a new method that can use multiple image modalities simultaneously and a single reference segmentation for initialisation, without the need for a manually labelled training set. The method models intensity profiles in multiple images around the boundaries of the structure after nonlinear registration. It is trained using a set of unlabelled training data, which may be the same images that are to be segmented, and it can automatically infer the location of the physical boundary using user-specified priors. We show that the method produces high-quality segmentations of the striatum, which is clearly visible on T1-weighted scans, and the globus pallidus, which has poor contrast on such scans. The method compares favourably to existing methods, showing greater overlap with manual segmentations and better consistency.

BACKGROUND: Acute stroke management is a dynamic field. Treatment with recombinant tissue plasminogen activator is standard care in Australia, but there are no evidence-based practice guidelines about first out of bed activity (mobilization) after recombinant tissue plasminogen activator. AIMS: To identify factors influencing clinicians' decisions to delay or allow mobilization. METHODS: Case-crossover design. Using hypothetical case vignettes, we explored the factors that clinicians consider when deciding to first mobilize a patient after recombinant tissue plasminogen activator. Acute stroke physicians and nurses from Australian hospitals known to treat with recombinant tissue plasminogen activator participated. Information about hospital recombinant tissue plasminogen activator protocols and perceived benefits and harms of mobilization after recombinant tissue plasminogen activator were also captured. RESULTS: Fifty-four clinicians, 52% senior nurses, and 48% senior physicians from all states of Australia participated. Of the factors influencing decisions about mobilization after recombinant tissue plasminogen activator, neurological decline (0.29; confidence interval 0.12, 0.46; P = 0.001), neurological decline with symptomatic intracerebral hemorrhage (0.41; confidence interval 0.24, 0.59; P < 0.0001), infection of uncertain cause (0.32; confidence interval 0.14, 0.50; P = 0.001), severe chest infection (0.35; confidence interval 0.16, 0.53; P = 0.0004), severe stroke (0.29; confidence interval 0.12, 0.46; P = 0.001), drowsiness (0.47; confidence interval 0.29, 0.63; P < 0.0001), and confusion (0.31; confidence interval 0.15, 0.47; P = 0.0001) significantly influenced decisions. Falls risk was a common concern (85%). CONCLUSION: Growing interest in development of clear protocols that guide first mobilization after recombinant tissue plasminogen activator prompted this study. We have identified factors that may influence decisions about when to allow patients to mobilize after recombinant tissue plasminogen activator. These, combined with emerging evidence of risks and benefits of early mobilization, should help protocol development in the future.