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 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.

Mapping complex cell morphology in the grey matter with double diffusion encoding MR: A simulation study.

This paper investigates the impact of cell body (namely soma) size and branching of cellular projections on diffusion MR imaging (dMRI) and spectroscopy (dMRS) signals for both standard single diffusion encoding (SDE) and more advanced double diffusion encoding (DDE) measurements using numerical simulations. The aim is to investigate the ability of dMRI/dMRS to characterize the complex morphology of brain cells focusing on these two distinctive features of brain grey matter. To this end, we employ a recently developed computational framework to create three dimensional meshes of neuron-like structures for Monte Carlo simulations, using diffusion coefficients typical of water and brain metabolites. Modelling the cellular structure as realistically connected spherical soma and cylindrical cellular projections, we cover a wide range of combinations of sphere radii and branching order of cellular projections, characteristic of various grey matter cells. We assess the impact of spherical soma size and branching order on the b-value dependence of the SDE signal as well as the time dependence of the mean diffusivity (MD) and mean kurtosis (MK). Moreover, we also assess the impact of spherical soma size and branching order on the angular modulation of DDE signal at different mixing times, together with the mixing time dependence of the apparent microscopic anisotropy (µA), a promising contrast derived from DDE measurements. The SDE results show that spherical soma size has a measurable impact on both the b-value dependence of the SDE signal and the MD and MK diffusion time dependence for both water and metabolites. On the other hand, we show that branching order has little impact on either, especially for water. In contrast, the DDE results show that spherical soma size has a measurable impact on the DDE signal's angular modulation at short mixing times and the branching order of cellular projections significantly impacts the mixing time dependence of the DDE signal's angular modulation as well as of the derived µA, for both water and metabolites. Our results confirm that SDE based techniques may be sensitive to spherical soma size, and most importantly, show for the first time that DDE measurements may be more sensitive to the dendritic tree complexity (as parametrized by the branching order of cellular projections), paving the way for new ways of characterizing grey matter morphology, non-invasively using dMRS and potentially dMRI.

Alcohol metabolism contributes to brain histone acetylation.

Emerging evidence suggests that epigenetic regulation is dependent on metabolic state, and implicates specific metabolic factors in neural functions that drive behaviour1. In neurons, acetylation of histones relies on the metabolite acetyl-CoA, which is produced from acetate by chromatin-bound acetyl-CoA synthetase 2 (ACSS2)2. Notably, the breakdown of alcohol in the liver leads to a rapid increase in levels of blood acetate3, and alcohol is therefore a major source of acetate in the body. Histone acetylation in neurons may thus be under the influence of acetate that is derived from alcohol4, with potential effects on alcohol-induced gene expression in the brain, and on behaviour5. Here, using in vivo stable-isotope labelling in mice, we show that the metabolism of alcohol contributes to rapid acetylation of histones in the brain, and that this occurs in part through the direct deposition of acetyl groups that are derived from alcohol onto histones in an ACSS2-dependent manner. A similar direct deposition was observed when mice were injected with heavy-labelled acetate in vivo. In a pregnant mouse, exposure to labelled alcohol resulted in the incorporation of labelled acetyl groups into gestating fetal brains. In isolated primary hippocampal neurons ex vivo, extracellular acetate induced transcriptional programs related to learning and memory, which were sensitive to ACSS2 inhibition. We show that alcohol-related associative learning requires ACSS2 in vivo. These findings suggest that there is a direct link between alcohol metabolism and gene regulation, through the ACSS2-dependent acetylation of histones in the brain.

A generic framework for spatial quantitative risk assessments of infectious diseases: Lumpy skin disease case study.

The increase in availability of spatial data and the technological advances to handle such data allow for subsequent improvements in our ability to assess risk in a spatial setting. We provide a generic framework for quantitative risk assessments of disease introduction that capitalizes on these new data. It can be adopted across multiple spatial scales, for any pathogen, method of transmission or location. The framework incorporates the risk of initial infection in a previously uninfected location due to registered movement (e.g., trade) and unregistered movement (e.g., daily movements of wild animals). We discuss the steps of the framework and the data required to compute it. We then outline how this framework is applied for a single pathway using lumpy skin disease as a case study, a disease which had an outbreak in the Balkans in 2016. We calculate the risk of initial infection for the rest of Europe in 2016 due to trade. We perform the risk assessment on 3 spatial scales-countries, regions within countries and individual farms. We find that Croatia (assuming no vaccination occurred) has the highest mean probability of infection, with Italy, Hungary and Spain following. Including import detection of infected trade does reduce risk but this reduction is proportionally lower for countries with highest risk. The risk assessment results are consistent across the spatial scales, while in addition, at the finer spatial scales, it highlights specific areas or individual locations of countries on which to focus surveillance.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI.

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.

CPHLN recommendations for the laboratory detection of Shiga toxin-producing Escherichia coli (O157 and non-O157).

Shiga toxin-producing Escherichia coli (STEC) are important enteric pathogens responsible for sporadic cases and outbreaks of gastroenteritis. E.coli O157:H7/NM (STEC O157) are the most commonly known STEC serotypes but it is now increasingly apparent that non-O157 STEC serotypes have been underreported in the past because they were not part of routine screening in many front-line laboratories. The Canadian Public Health Laboratory Network (CPHLN) has identified the need for improved detection and surveillance of non-O157 STEC and has developed the following recommendations to assist in the decision-making process for clinical and reference microbiology laboratories. These recommendations should be followed to the best of a laboratory's abilities based on the availability of technology and resources. The CPHLN recommends that when screening for the agents of bacterial gastroenteritis from a stool sample, front-line laboratories use either a chromogenic agar culture or a culture-independent diagnostic test (CIDT). CIDT options include nucleic acid amplification tests (NAATs) to detect Shiga toxin genes or enzyme immunoassays (EIAs) to detect Shiga toxins. If either CIDT method is positive for possible STEC, laboratories must have a mechanism to culture and isolate STEC in order to support both provincial and national surveillance as well as outbreak investigations and response. These CPHLN recommendations should result in improved detection of STEC in patients presenting with diarrhea, especially when due to the non-O157 serotypes. These measures should enhance the overall quality of healthcare and food safety, and provide better protection of the public via improved surveillance and outbreak detection and response.

Interim laboratory testing guidance for the detection of non-tuberculous Mycobacterium (NTM) infections in post-operative patients exposed to heater-cooler units.

The advice contained in this document should be read in conjunction with relevant federal, provincial, territorial and local legislation, regulations, and policies. Recommended measures should not be regarded as rigid standards, but principles and recommendations to inform the development of guidance. This advice is based on currently available scientific evidence and adopts a precautionary approach where the evidence is lacking or inconclusive. It was approved for publication on December 5, 2016. It is subject to review and change as new information becomes available. The main changes to this version include additions to: Case load reported to date, Sarcoidosis-like disease as an Indicator, Whole Genome Sequencing effort, links to Provincial and Territorial Lab Services and Health Canada reporting.

Application of neurite orientation dispersion and density imaging (NODDI) to a tau pathology model of Alzheimer's disease.

Increased hyperphosphorylated tau and the formation of intracellular neurofibrillary tangles are associated with the loss of neurons and cognitive decline in Alzheimer's disease, and related neurodegenerative conditions. We applied two diffusion models, diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), to in vivo diffusion magnetic resonance images (dMRI) of a mouse model of human tauopathy (rTg4510) at 8.5months of age. In grey matter regions with the highest degree of tau burden, microstructural indices provided by both NODDI and DTI discriminated the rTg4510 (TG) animals from wild type (WT) controls; however only the neurite density index (NDI) (the volume fraction that comprises axons or dendrites) from the NODDI model correlated with the histological measurements of the levels of hyperphosphorylated tau protein. Reductions in diffusion directionality were observed when implementing both models in the white matter region of the corpus callosum, with lower fractional anisotropy (DTI) and higher orientation dispersion (NODDI) observed in the TG animals. In comparison to DTI, histological measures of tau pathology were more closely correlated with NODDI parameters in this region. This in vivo dMRI study demonstrates that NODDI identifies potential tissue sources contributing to DTI indices and NODDI may provide greater specificity to pathology in Alzheimer's disease.

Predicting outcome in clinically isolated syndrome using machine learning.

We aim to determine if machine learning techniques, such as support vector machines (SVMs), can predict the occurrence of a second clinical attack, which leads to the diagnosis of clinically-definite Multiple Sclerosis (CDMS) in patients with a clinically isolated syndrome (CIS), on the basis of single patient's lesion features and clinical/demographic characteristics. Seventy-four patients at onset of CIS were scanned and clinically reviewed after one and three years. CDMS was used as the gold standard against which SVM classification accuracy was tested. Radiological features related to lesional characteristics on conventional MRI were defined a priori and used in combination with clinical/demographic features in an SVM. Forward recursive feature elimination with 100 bootstraps and a leave-one-out cross-validation was used to find the most predictive feature combinations. 30 % and 44 % of patients developed CDMS within one and three years, respectively. The SVMs correctly predicted the presence (or the absence) of CDMS in 71.4 % of patients (sensitivity/specificity: 77 %/66 %) at 1 year, and in 68 % (60 %/76 %) at 3 years on average over all bootstraps. Combinations of features consistently gave a higher accuracy in predicting outcome than any single feature. Machine-learning-based classifications can be used to provide an "individualised" prediction of conversion to MS from subjects' baseline scans and clinical characteristics, with potential to be incorporated into routine clinical practice.

Epidemiological evaluation of spatiotemporal and genotypic clustering of Mycobacterium tuberculosis in Ontario, Canada.

BACKGROUND: In Canada, tuberculosis (TB) rates are at a historic low, with the remaining risk concentrated in a few vulnerable population subgroups. OBJECTIVES: To describe the epidemiology of TB in the Canadian province of Ontario and to characterise risk factors associated with transmission events, identified using genetic typing techniques. DESIGN: Retrospective analysis of 2186 culture-positive TB cases between August 2007 and December 2011. Temporal trends and risk of spatiotemporal and genotypic clustering were evaluated using Poisson and logistic regression models. RESULTS: Being in a spatiotemporal cluster was associated with Aboriginal status (odds ratio [OR] 3.63, 95% confidence interval [CI] 1.23-10.71). Cases in genotypic clusters were more likely to report homelessness as a risk factor (adjusted OR [aOR] 2.92, 95%CI 1.74-4.90) or be male (aOR 1.35, 95%CI 1.09-1.68), and were less likely to be aged ≥ 65 years (aOR 0.63, 95%CI 0.49-0.82), foreign-born (aOR 0.32, 95%CI 0.24-0.43) or Aboriginal (aOR 0.40, 95%CI 0.16-0.99). The Beijing lineage had an annual rate of increase of almost 10% (P = 0.047), and was associated with genotypic clustering (aOR 2.84, 95%CI 2.19-3.67). CONCLUSION: Genotypic data suggest that disease clusters are smaller, but far more common, than would be estimated using spatiotemporal clustering.

Effectiveness of simulated interventions in reducing the estimated prevalence of Salmonella in UK pig herds.

Salmonella spp are a major foodborne zoonotic cause of human illness. Consumption of pork products is believed to be a major source of human salmonellosis and Salmonella control throughout the food-chain is recommended. A number of on-farm interventions have been proposed, and some have been implemented in order to try to achieve Salmonella control. In this study we utilize previously developed models describing Salmonella dynamics to investigate the potential effects of a range of these on-farm interventions. As the models indicated that the number of bacteria shed in the faeces of an infectious animal was a key factor, interventions applied within a high-shedding scenario were also analysed. From simulation of the model, the probability of infection after Salmonella exposure was found to be a key driver of Salmonella transmission. The model also highlighted that minimising physiological stress can have a large effect but only when shedding levels are not excessive. When shedding was high, weekly cleaning and disinfection was not effective in Salmonella control. However it is possible that cleaning may have an effect if conducted more often. Furthermore, separating infectious animals, shedding bacteria at a high rate, from the rest of the population was found to be able to minimise the spread of Salmonella.

Semi-stochastic models for Salmonella infection within finishing pig units in the UK.

A multi-group semi-stochastic model is formulated to describe Salmonella dynamics on a pig herd within the UK and assess whether farm structure has any effect on the dynamics. The models include both direct transmission and indirect (via free-living infectious units in the environment and airborne infection). The basic reproduction number R0 is also investigated. The models estimate approximately 24.6% and 25.4% of pigs at slaughter weight will be infected with Salmonella within a slatted-floored and solid-floored unit respectively, which corresponds to values found in previous abattoir and farm studies, suggesting that the model has reasonable validity. Analysis of the models identified the shedding rate to be of particular importance in the control of Salmonella spread, a finding also evident in an increase in the R0 value.

A viable isolated tissue system: a tool for detailed MR measurements and controlled perturbation in physiologically stable tissue.

In vivo magnetic resonance imaging (MRI) assessment of neuronal tissue is prone to artifacts such as movement, pulsatile flow, and tissue susceptibility. Furthermore, stable in vivo scans of over 3 h are difficult to achieve, experimental design is therefore limited. Using isolated tissue maintained in a viable physiological state can mitigate many of these in vivo issues. This work describes the fabrication and validation of an MRI compatible viable isolated tissue maintenance chamber. Parameters measured from maintained rat optic nerves did not change significantly over 10 h: (i) mean axon radius [electron microscopy--0 h: 0.75±0.46; 5 h: 0.74±0.35; 10 h: 0.76±0.35 µm (P>>0.05, t-test], (ii) action potentials [grease-gap electrophysiology--4.89±0.16 mv, (P>>0.05, Pearson test], and (iii) diffusion tensor imaging parameters [fractional anisotropy: 0.86±0.02 (P>>0.05, Pearson test), mean diffusivity: 1.48E-06±9.74E-08 cm2/s, (P>>0.05, Pearson test)]. In addition, a thorough diffusion-weighted MR protocol demonstrated the comparable stability of viable isolated and chemically fixed rat optic nerve. This MRI compatible viable isolated tissue system allows researchers to probe neuronal physiology in a controlled environment by limiting in vivo artifacts and allowing extended MRI acquisitions.

Genotypic characterization of tuberculosis transmission within Toronto's under-housed population, 1997-2008.

Toronto has been the site of a recent extended tuberculosis (TB) outbreak in the homeless or under-housed population. Genotyping has identified a unique strain that continues to circulate within this population, with spread to individuals with no links to the shelter system, and anecdotally appears to progress rapidly from infection to active disease in some cases. The recent appearance and transmission of another unique strain was also identified, indicating that TB transmission continues to be a problem within the under-housed population. Enhanced surveillance utilizing molecular epidemiology is a useful tool to assist in TB control in vulnerable populations.

Correlation of thromboelastography with standard tests of anticoagulation in paediatric patients receiving extracorporeal life support.

UNLABELLED: Children requiring extracorporeal life support (ECLS) are at significant risk for thrombotic and haemorrhagic complications. Thromboelastography (TEG) is increasingly being used to assist in monitoring the coagulation status of critically ill patients. Its role in heparinised children receiving ECLS is unknown. METHODS: A retrospective review of TEG in 27 children (mean age 2 years and 8 months) receiving ECLS in a tertiary paediatric intensive care unit between December 2006 and April 2008. Paired TEG (kaolin and heparinase) analysis was performed on 171 occasions. On all occasions activated partial thromboplastin time (APTT) and platelet count were performed within 4 hours of the TEG (mean 6.5 minutes after TEG). On 158 occasions, the activated clotting time (ACT) was measured simultaneously with TEG. RESULTS: The TEG (kaolin) sample was not interpretable due to the heparin effect in 89 (52%) samples. There was a weak correlation between TEG (heparinase) variables and APTT, and between TEG and ACT with a stronger correlation between TEG (Maximum amplitude) and platelet count. CONCLUSION: TEG monitoring should always include paired samples in heparinised children on ECLS. In this heterogeneous population, weak, and moderate correlations exist between TEG and standard haematological tests. Prospective studies, with simultaneous sampling for TEG and conventional laboratory tests, must be performed in order to establish its absolute utility as a clinical tool in this population.

Defining Meyer's loop-temporal lobe resections, visual field deficits and diffusion tensor tractography.

Anterior temporal lobe resection is often complicated by superior quadrantic visual field deficits (VFDs). In some cases this can be severe enough to prohibit driving, even if a patient is free of seizures. These deficits are caused by damage to Meyer's loop of the optic radiation, which shows considerable heterogeneity in its anterior extent. This structure cannot be distinguished using clinical magnetic resonance imaging sequences. Diffusion tensor tractography is an advanced magnetic resonance imaging technique that enables the parcellation of white matter. Using seed voxels antero-lateral to the lateral geniculate nucleus, we applied this technique to 20 control subjects, and 21 postoperative patients. All patients had visual fields assessed with Goldmann perimetry at least three months after surgery. We measured the distance from the tip of Meyer's loop to the temporal pole and horn in all subjects. In addition, we measured the size of temporal lobe resection using postoperative T(1)-weighted images, and quantified VFDs. Nine patients suffered VFDs ranging from 22% to 87% of the contralateral superior quadrant. In patients, the range of distance from the tip of Meyer's loop to the temporal pole was 24-43 mm (mean 34 mm), and the range of distance from the tip of Meyer's loop to the temporal horn was -15 to +9 mm (mean 0 mm). In controls the range of distance from the tip of Meyer's loop to the temporal pole was 24-47 mm (mean 35 mm), and the range of distance from the tip of Meyer's loop to the temporal horn was -11 to +9 mm (mean 0 mm). Both quantitative and qualitative results were in accord with recent dissections of cadaveric brains, and analysis of postoperative VFDs and resection volumes. By applying a linear regression analysis we showed that both distance from the tip of Meyer's loop to the temporal pole and the size of resection were significant predictors of the postoperative VFDs. We conclude that there is considerable variation in the anterior extent of Meyer's loop. In view of this, diffusion tensor tractography of the optic radiation is a potentially useful method to assess an individual patient's risk of postoperative VFDs following anterior temporal lobe resection.

Tractography of the parahippocampal gyrus and material specific memory impairment in unilateral temporal lobe epilepsy.

INTRODUCTION: Temporal lobe epilepsy (TLE) is associated with disrupted memory function. The structural changes underlying this memory impairment have not been demonstrated previously with tractography. METHODS: We performed a tractography analysis of diffusion magnetic resonance imaging scans in 18 patients with unilateral TLE undergoing presurgical evaluation, and in 10 healthy controls. A seed region in the anterior parahippocampal gyrus was selected from which to trace the white matter connections of the medial temporal lobe. A correlation analysis was carried out between volume and mean fractional anisotropy (FA) of the connections, and pre-operative material specific memory performance. RESULTS: There was no significant difference between the left and right sided connections in controls. In the left TLE patients, the connected regions ipsilateral to the epileptogenic region were found to be significantly reduced in volume and mean FA compared with the contralateral region, and left-sided connections in control subjects. Significant correlations were found in left TLE patients between left and right FA, and verbal and non-verbal memory respectively. CONCLUSION: Tractography demonstrated the alteration of white matter pathways that may underlie impaired memory function in TLE. A detailed knowledge of the integrity of these connections may be useful in predicting memory decline in chronic temporal lobe epilepsy.

Imaging language pathways predicts postoperative naming deficits.

Naming difficulties are a well recognised, but difficult to predict, complication of anterior temporal lobe resection (ATLR) for refractory epilepsy. We used MR tractography preoperatively to demonstrate the structural connectivity of language areas in patients undergoing dominant hemisphere ATLR. Greater lateralisation of tracts to the dominant hemisphere was associated with greater decline in naming function. We suggest that this method has the potential to predict language deficits in patients undergoing ATLR.